China: The Great Transition: From Agrarian Economy to Technological Powerhouse 9819900506, 9789819900503

Citation preview

Bhabani Shankar Nayak   Editor

China: The Great Transition From Agrarian Economy to Technological Powerhouse

China: The Great Transition

Bhabani Shankar Nayak Editor

China: The Great Transition From Agrarian Economy to Technological Powerhouse

Editor Bhabani Shankar Nayak University for the Creative Arts Epsom, Surrey, UK

ISBN 978-981-99-0050-3 ISBN 978-981-99-0051-0 (eBook) https://doi.org/10.1007/978-981-99-0051-0 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

About This Book

The great transition of China from a subsistence agrarian economy to a technologically driven economic powerhouse reflects the skills and achievements of the hardworking Chinese people. The political commitment of the Chinese state and government is helping in leading the development trajectory of the country. The economic development in China is a product of political pursuit shaped by the Chinese people with unquestionable work ethics. China not only is the workshop of the world today but also works as the engine of global economic growth. The rapid transition of Chinese economy and its society is profoundly affecting the competitive capabilities of the capitalist economies. There are consistent attempts by the liberal and Western intellectuals, commentators and writers to undermine the Chinese politics and achievements of working people of China. The ideologically driven propaganda is a dangerous trap that hides viable alternatives from people. The volume celebrates all achievements and documents the challenges of combined and uneven developments in China. The Chinese state and government are trying to implement different policies and programmes to overcome different challenges in China during this transition processes.

v

Contents

1 Introduction: China—Challenges of the Great Transition . . . . . . . . . . Bhabani Shankar Nayak 2 Two Decades of Fiscal Decentralization and Regional Economic Growth in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Qiujia Wang and Bhabani Shankar Nayak 3 Regional Financial Development and Economic Growth in China: A Study of Guangdong–Hong Kong–Macao Greater Bay Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yuhao Luo and Bhabani Shankar Nayak 4 Impact of Financing on Investment in Chinese SMEs During Financial Crisis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jiang Mingte and Bhabani Shankar Nayak 5 Impact of the COVID-19 on Banks in China . . . . . . . . . . . . . . . . . . . . . . Boming Chen and Bhabani Shankar Nayak

1

9

39

61 87

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Liangyifang Peng and Bhabani Shankar Nayak

vii

Editor and Contributors

About the Editor Prof. Bhabani Shankar Nayak is a political economist and works as Professor of Business Management and Programme Director of Strategic Business and Management at the University for the Creative Arts, UK. His research interests consist of closely interrelated and mutually guiding programmes surrounding political economy of development, business, religion and capitalism. He is the author of Political Economy of Development and Business (2022), Creative Business Education (2022), Modern Corporate Strategies at Work (2022), China: The Bankable State (2021), Disenchanted India and Beyond (2020), Hindu Fundamentalism and the Spirit of Global Capitalism in India (2018) and Nationalising Crisis: The Political Economy of Public Policy in India (2007).

Contributors Boming Chen University of Glasgow, Glasgow, Scotland, UK Yuhao Luo Adam Smith Business School, University of Glasgow, Glasgow, Scotland, UK Jiang Mingte University of Glasgow, Glasgow, UK Bhabani Shankar Nayak Business School for the Creative Industries, University for the Creative Arts, Epsom, UK Liangyifang Peng University of Glasgow, Glasgow, Scotland, UK Qiujia Wang Adam Smith Business School, University of Glasgow, Glasgow, Scotland, UK

ix

Chapter 1

Introduction: China—Challenges of the Great Transition Bhabani Shankar Nayak

The great transition of China from a subsistence agrarian economy to a technologically driven economic powerhouse reflects the achievements of the hardworking Chinese people. China continues to grow as the second largest economy of the world from 2010 onwards. It is going to be the largest economy in the world by putting US economy behind. The Chinese GDP has increased of 1,500 times from 1952. The transformation of China and its economic growth is neither miraculous nor a product of market economy. The economic development in China is a product of political pursuit shaped by the Chinese people led by the Communist Party of China from 1921 onwards. China is not only the workshop of the world today but also works as the engine of global economic growth. The state led development in China paves the path of recovery and provides direction to the crisis ridden global economy. The rapid transition of Chinese economy and its society is profoundly affecting the competitive capabilities of the capitalist economies. There are consistent attempts by the liberal and western intellectuals, commentators and writers to undermine the Chinese politics and achievements of working people of China. The ideologically driven propaganda is a dangerous trap that hides viable alternatives from people. The phenomenal Chinese economic growth and development led to the significant fall of poverty in China. The World Bank (2022) study on “Four Decades of Poverty Reduction in China Drivers, Insights for the World, and the Way Ahead” shows that China lifted 800 million people out of poverty and contributed to three-quarters of the global reduction of extreme poverty. There were 250 million poor living in rural China in 1978 which has declined in a massive scale. There were more than 750 million (about two-thirds of the population) in China lived below international poverty line in 1990. The commitment and targeted approach of the Chinese government has led to the eradication of absolute poverty in China. There is remarkable growth of access and B. S. Nayak (B) Business School for the Creative Industries, University for the Creative Arts, 21 Ashley Rd, Epsom KT18 5BE, UK e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 B. S. Nayak (ed.), China: The Great Transition, https://doi.org/10.1007/978-981-99-0051-0_1

1

2

B. S. Nayak

availability of quality healthcare, education, livelihoods, social security and political stability in China. The massive investment in infrastructure, education, health and inclusive income stability programmes led to the rise of China. The unwavering commitment of Chinese government and state, determination of Chinese people and visionary leadership of the Communist Party of China have led this historic transition to a process of great leap forward. The prosperous transition in China continues to show features of combined and uneven development. China has largest billionaires, but many people still live and practice subsistence economy. Many Chinese do not have access to clean air, water, sanitation and dignified sources of livelihoods. Social, economic and political inequalities are hinderances to deepening of democratic and egalitarian development in China. The gender gap and widening gap between urban and rural China are twin serious challenges to progressive transformations in China. The Chinese state and government is trying to implement different policies and programmes to overcome these challenges. In spite of all achievements in fields of social and economic developments, poverty eradication, educational growth, improvements in health, communication and transportation, industrial and technological developments, China continues to face global ideological challenges from the erstwhile colonial countries. Chinese model of alternative economic development is a threat to the imperialist economic policies pursued by the Western European countries and America for centuries now. Therefore, the ideological campaign to undermine China and achievements of its hard working and skilled Chinese labour.

International Campaign to Undermine Chinese Path of Development The international debt trap is a product of colonial and neo-colonial plunders, imperialist hegemony and neoliberal economic policies imposed by developed countries on developing world. The Asian, African, Latin American and even the capitalist west is suffering from debt due to the dominance of Westphalian capitalist system that controls world economic and politics. However, the reactionary and capitalist ideologues, their mouthpiece mass media, writers, journalists, consultants, think tanks, leaders and their propaganda machines are on a relentless campaign to defame, delegitimise and diminish Chinese achievements. The core idea of this consorted antiChinese propaganda is to undermine the alternative development model pursued by China. During the 1990s, the G7 developed countries created a regime of free market economy led neo colonial economic policies under the leadership of the World Bank and IMF. These two institutions imposed structural adjustment, liberalisation, privatisation and globalisation policies on the countries which failed to repay the debt. These policies were tools of indirect control over natural resources, domestic consumer, labour and investment markets of the defaulter countries. The

1 Introduction: China—Challenges of the Great Transition

3

international debt trap is the mother of all economic crises in the developing countries which helps to maintain the economic and political hegemony of the developed countries in western Europe and US (Nayak, 2022a, b). The Chinese economic and political engagement in Asia, Africa and Latin America is challenging the debt dependence development model and questions the very foundation of western debt trap designed to exploit natural resources from the developing world. Debt is a political and economic tool of the western countries to control the politics and economic systems of the developing world and continue capitalist hegemony. China is a threat to such world order. From Chinese authoritarianism to Chinese debt trap campaigns are ideologically driven propaganda based on myths. There is absolutely no foundation to these campaigns. Falsehood is a norm for the survival of western hegemony over people and the planet. The Chinese ‘Debt Trap’ narratives are myth making propaganda. The idea of debt trap diplomacy is to undermine Beijing and its relationship with developing countries. In reality, China provides three different types of loans i.e., (i) interest free loan, (ii) long term loan for infrastructure with minimal interests and (iii) commercial loans. China even allows to restructure the terms of the existing loans based on changing economic conditions of the borrowing countries. China has never grabbed any assets of the any countries that borrowed from China. The acquisitions, investments and integrations are western business strategies in international trade, but China pursues these strategies with a difference when it comes to its lending patterns and policies for the developing countries (Nayak, 2022a). China is the one of the largest official creditors with a global presence, but it never puts conditions of structural adjustments, change of labour laws or liberalisation and privatisation of their economic systems while lending. The western propaganda machine never fails to portray integration and acquisitions as Chinese dominance and debt trap. Chinese economic engagement with the developing countries fundamentally challenges the western hegemony. Therefore, Beijing is branded as an authoritarian devil that intents to colonise and dominate the world. There is no iota of truth in it, but western ideologues look at themselves in prison of their own eyes. The colonial past is a mirror, where the colonisers plays their victim card to hide their past (Nayak, 2022a). The economic and political challenges faced by Asian, African and Latin American countries today are products of their colonial past and neo colonial present dominated by the United States and Western Europe. China is providing loans for infrastructure development by which the developing countries can recover from their western dependency to mobilise their own natural resources (Nayak, 2022a). The African, Asian and Latin American counties are not currently under substantial Chinese debt. In fact, the share of Chinese debt in comparison to total debt to GDP ratio is very minimal. So, it is time to debunk the unfounded narratives and propaganda around Chinese debt trap diplomacy. The expansion of Chinese economic and political engagement with developing countries help in reducing their dependency on western capital, which makes western powers uncomfortable and persistently spread lies against China. This is a diversionary strategy of the western leaders to hide their political and economic failures. Falsely outsourcing of all the blame on China is not

4

B. S. Nayak

going to hide failures of capitalism and so-called western democracy. The deepening of democracy depends on a debt free world economy. It can be facilitated by politics of unity, peace, solidarity and shared prosperity. The Chinese economy and politics based on peace, cooperation, development and socialism are four pillars of Chinese alternative for the world to pursue (Nayak, 2022a). The International Debt Statistics (2022) published by the World Bank has revealed that the external debt of 123 low- and middle-income countries have increased on average 5.6% to $8.7 trillion in 2020. It shows devastating impact of the pandemic on economy of the developing countries. The G20 creditors have designed a policy framework called the Debt Service Suspension Initiative (DSSI) as if the creditors are doing a charity for the poor living in the developing world. The international debt trap locks people and countries within an economic system where borrowing is normalised to service growing debt burden. Debt trap eats away income, wellbeing and livelihoods of people. Many poor commit suicides due to debt trap. Similarly, poor and developing countries sacrifice their economic independence and political sovereignty in decision making over their own people, resources and territories. The creditors force the debt trap countries to follow various policies that facilitates in realising the objectives of the developed creditor countries. It is a systematic strategy of develop countries to exploit the developing countries. Debt is a tool of control and exploitation. It helps to widen the gap between rich and poor, developed regions and under develop regions. The international debt crises and traps poverty, underdevelopment and inequalities are products of colonial politics and neo-colonial policies imposed on developing countries by the developed countries (Nayak, 2022b). There is a long-standing history of developed countries to occupy the territory and resources of the debt defaulter countries. For example, the French and Belgian soldiers had occupied the Ruhr; an area in North Rhine-Westphalia, Germany and access coal when the country failed to repay Versailles debts. During colonial period, countries in Asian, Africa and Americas were divided between European colonisers and European colonialism has established international debt trap in these continents. After the first World War, the United States Congress refused to cancel European debt. However, after the Second World War, the European countries have cancelled each other’s debt and came together during the Bretton Woods Conference to create an international financial system under the leadership of US. This conference led to the rise of Bretton Woods institutions and institutionalise international debt trap of the post-colonial developing countries (Nayak, 2022b). The international debt trap is resurfacing from 2020 onwards after the publication of “The Elements of the China Challenge” by the Policy Planning Staff, Office of the Secretary of State, United States. This unclassified Policy Planning Staff paper focuses on China’s “predatory development program and debt-trap diplomacy.” The paper also claims and highlights “Beijing’s authoritarian goals and hegemonic ambitions” It also argues that “the CCP has undertaken major infrastructure and investment projects, debt-trap diplomacy, and other predatory economic practices in every region of the world, the better to induce or compel sovereign nation-states, particularly their governing and business elites, to aid and abet China in the reshaping of world order. And the CCP has leveraged its integration into international organizations to infuse

1 Introduction: China—Challenges of the Great Transition

5

them with norms and standards rooted in the party’s authoritarianism”. These ideologically driven propaganda is far from truth. There is no factual foundation to such claims. It is part of a relentless anti-Chinese propaganda (Nayak, 2022b). The rise of China and its internationalism based on peace and development threatens the very foundation of debt driven international financial system led by western Europe and US. China is engaging with developing countries without putting any conditions and helps different countries in Asia and Africa to develop infrastructure to mobilise their own resources for their own economic development that is free from debt and western dependence. Such mutually beneficial engagement between developing countries and China threatens the very foundation of western hegemony. Therefore, China is portrayed as a devil by the so called western democratic world (Nayak, 2022b). In reality, the Chinese government is deepening its relationship with African continent by forgiving 23 interest-free loans for 17 African nations. The Chinese government has also cancelled more than $3.4 billion debt and restructured around $15 billion debt for the African countries between 2000 and 2019. Beijing is also renegotiating 26 other loans while refinancing around $15 billion of debt in Africa. Therefore, the Chinese debt trap is an ideologically motivated campaign to defame China and its alternative approach to international debt, bilateral, multilateral trade and infrastructure development programme. The western countries asks for structural adjustment to diminish welfare state and its infrastructure whereas China provides debt for infrastructural development for the rise of an economically independent state. China shows its commitment to mutual development when it comes to debt and investment whereas western countries impose conditions of investments that exploits people and their environment in the developing world (Nayak, 2022b). These two tales are central to understand and overcome debt driven capitalism and denounce western model of international economic system that destroys democracy for market, ruins people’s lives and livelihoods for profit and creates foundation for environmental disasters. The working poor across the world are victims of such a debt trap created by capitalism under the leadership of western states and governments. It is time to dismantle capitalism and its debt driven financial architectures for the sake of humanity, peace, prosperity and the planet. A debt driven western dominance based on capitalism is not an economic or political alternative. It has failed in different stages of history. The world does not need a unipolar, bipolar and multipolar world order led by United State, China, France, Britain, Germany, Russia and India. The world politics needs to focus on people, peace and planet based on egalitarian values of liberty, justice, fraternity and citizenship rights. A people and planet centric world order is the call of the day for a sustainable tomorrow (Nayak, 2022b).

Future of Chinese Transition The rapid transition of Chinese society, economy and culture is neither a developmental accident nor a miraculous economic growth. It is a product of mass movement of the working people in China led by the communist party. The political leadership

6

B. S. Nayak

and its commitment to the long-term development of Chinese people and their society led to the planned economic and political interventions in the form of public policies for the all-round wellbeing of Chinese society. The Eurocentric commentators and researchers theorise of Chinese models of authoritarian development path. Such a reductionist analysis hides the failures of Westphalian ideology and its state led capitalist development model under the dominance of market forces. Many Eurocentric and anti-Chinese researchers theorise ‘Chinese development’ as ‘Capitalism in Chinese character’. Such theorisation of Chinese development path is also distorted to justify the legitimacy of ‘failed neoliberal strategies of economic development’ to undermine the very foundation of Marxian political economy of development that guides Chinese economic planning based on Chinese resources, Chinese needs and Chinese desires. In 2015, the central committee of the Chinese Communist Party has clearly defined Chinese development path as “socialist political economy with Chinese characteristics.” There are eight major principles of “socialist political economy with Chinese characteristics”. These eight principles are based on sustainability led by science and technology, need based production to improve the livelihoods of the people, primacy of public ownership within National Property Rights, primacy of labor in the distribution of wealth, state led market, high speed development with performance, balanced development, openness with economic sovereignty (Enfu & Xiaoqin, 2017). These eight principles are pillars of Chinese development led by the ideals of peace and collective prosperity. In spite of idealist economic and development policies, the stark realities of inequality impedes Chinese development path. One third of all Chinese household assets are controlled by 1% of Chinese families like capitalist USA. The rise of inequality in China is a challenge but these principles are designed to address the growing disparities in China. These principles are used to overcome the dilemmas of dependency on the developed capitalist countries for capital and technology. The egalitarian economic growth for social development drives Chinese development policies to ensure public welfare over profit. In spite of significant achievements, the declining share of labour in GDP, growing privatisation of state-owned enterprises, rising income and property ownership, environmental crises, and rise of unproductive assets are some of the major challenges faced by the Chinese development path. The eight principles needs to be implemented in letter and spirit to address these issues. The sustainability and future growth of China depends on strengthening the eight principles of contemporary Chinese political economy of development (Enfu & Xiaoqin, 2017). This book is an evaluation of the great Chinese transition amidst all challenges. It evaluates strengths and limitations of the state led developments in China.

1 Introduction: China—Challenges of the Great Transition

7

References Enfu, C., & Xiaoqin, D. (2017, January). A theory of China’s ‘miracle’: Eight principles of contemporary Chinese political economy. Monthly Review, 68(8). Nayak, B. S. (2022a, August 28). International debt: A tale of two stories. South Asia Journal. Nayak, B. S. (2022b, August 27). Fables of Chinese debt trap. Counter Currents. Available at: https://countercurrents.org/2022/08/fables-of-chinese-debt-trap/ World Bank. (2022). Four decades of poverty reduction in China drivers, insights for the world, and the way ahead. International Bank for Reconstruction and Development/The World Bank.

Chapter 2

Two Decades of Fiscal Decentralization and Regional Economic Growth in China Qiujia Wang and Bhabani Shankar Nayak

Abstract The transition of Chinese economy started with the initiation of reforms and loosening of trade restrictions. This led to the fiscal decentralization which has played an important role in China’s economic development. The decentralization in China has been continuously improved and developed slowly based on social and economic needs of the Chinese society. In recent years, China’s economic growth rate has started to slow down. At this time, the problems of uneven regional development and untenable industrial layout in China have become increasingly serious. Differences in development between different regions and uneven resources distribution have also increased regional economic disparities. It is therefore important to study how to improve the fiscal decentralization system for China’s economic growth and the balanced development of regional economies. It argues that the state should establish a scientific and standardized fiscal decentralization system, change the single assessment system, and streamline administrative expenses to promote balanced development between regions.

Introduction In the past few years, the issue of fiscal decentralization, the remove of revenues and expenditures from central to local governments, has received attention from various countries. Fiscal decentralization, sometimes referred to as fiscal federalism, has the potential to improve public sector performance; there is also evidence suggesting that it can promote economic development and the World Bank has made it a major part of its governance reform agenda. However, other arguments suggest that fiscal decentralization, while improving the public sector’s economic efficiency, is not suitable for developing countries. Q. Wang Adam Smith Business School, University of Glasgow, Glasgow, Scotland, UK B. S. Nayak (B) Business School for the Creative Industries, University for the Creative Arts, 21 Ashley Rd, Epsom KT18 5BE, UK e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 B. S. Nayak (ed.), China: The Great Transition, https://doi.org/10.1007/978-981-99-0051-0_2

9

10

Q. Wang and B. S. Nayak

China’s economy has expanded quickly, and its economic system has continuously improved due to the fact that the country’s reform and opening up in 1978. Fiscal policy is an important basis for governing a country and is inseparable from economic development. Fiscal policy is an important aspect of reform, and it is constantly advancing. From the initial household contract responsibility system, followed by the reform of the fiscal system of tax sharing in 1994, revenue and expenditure were transferred from the central government to the local government. Governments of the provinces were given more power to implement measures to promote economic development. Such measures included strengthening infrastructure, introducing technology, attracting foreign companies to China, etc. Decentralization will reduce the budget of enterprises, which can improve the efficiency of enterprises and make the economy develop more sustainably. Fiscal policy is the most important macro policy tool in economic restructuring because of its role (Montinola et al., 1995). China’s unique fiscal decentralization reform has received much academic attention. Because China is a government-led country, fiscal decentralization significantly impacts China’s economic growth, and fiscal decentralization incentivizes local government action. As a result, an increasing number of economists are researching the theory, policy, and interrelationship of fiscal decentralization and economic development. Fiscal decentralization has a big influence on economic development and guides the direction of China’s reorganizations, especially in terms of economic policy. China needs to examine the relationship between fiscal policy and economic growth. This analysis intends to help in formulating the fiscal system, especially the ratio between the distribution of central and local finances. In the meantime, the local governments are more motivated by the move towards fiscal decentralization, thus promoting the swift development of the local market. When the economy is at an early development phase, the central government may need to allocate more funds to ensure the supply of national public goods. In contrast, when the economy is mature, increasing local government spending can help provide a greater variety of public goods to the local population and improve their welfare. This chapter discusses the impact of fiscal decentralization on economic development and the circumstances under which it can act as a catalyst or disincentive to make useful recommendations for reforming the fiscal system. There are many differences in geographical location and resource endowments, among other reasons, and the underlying conditions for economic growth objectively vary from region to region, with a cascading effect on the varying level of growth. Under a centralized fiscal system, local governments are largely executive agencies of the central government, with limited autonomy over local fiscal revenues and expenditures. An effective solution to this problem would be for the central government to rationalize the allocation of public resources through the institutionalization of fiscal decentralization, and there would be a more even distribution of public services across regions. By analyzing the mechanism and mechanism of fiscal decentralization on regional economic growth, this paper explores the factors and external conditions faced in economic development. It provides reference suggestions for achieving economic growth. At the same time, it also provides room for

2 Two Decades of Fiscal Decentralization and Regional Economic …

11

reflection on how the central government can provide appropriate fiscal transfers and other support systems and policies for different regions. There is no concrete conclusion on the relationship between fiscal decentralization and economic growth (Scott, 2009). Many economists have identified a high-quality hyperlink between them. They argue that fiscal decentralization can rationalize the responsibilities of the regional governments and enterprises. The local governments can be incentivized to improve economic efficiency. Fiscal decentralization also furthers economic development by rising the efficiency of local resource allocation as the local governments have more informational advantage in meeting local needs. Thanh and Canh (2020) examine data for Vietnam from 2006 to 2015. They discover that fiscal decentralization has a catalytic result on economic growth in Vietnamese provinces and that it is more effective in the areas with better public governance. In a learn about of fiscal reform in China from 2001 to 2011, the authors found that by transferring power from the prefecture degree to the county level, the governments could help construct public facilities in the area and the livelihood of the residents. Government officials would also benefit from economic growth, which will increase the motivation of officials, and could create an excellent competitive environment (Ma & Mao, 2018). Local officials’ personal and economic interests are coordinated to a certain extent, which better solves the local government officials’ incentive and assessment problems. Fiscal decentralization in India has also positively affected the country’s development and contributed to economic growth through increased investment and labor force. Fiscal decentralization is also an effective tool for economic development, and economic development leads to the development of education, which is significant for the country, according to the data analysis from 1990 to 2016 in South Asia (Sasana, 2019). In conclusion, fiscal decentralization performs a fundamental function in economic development in developing countries (Hanif & Gago-de Santos, 2017). Nevertheless, many scholars have also concluded that fiscal decentralization reforms can have negative effects. Decentralization reforms can trigger development imbalances between jurisdictions, local protectionism and, in more severe cases, unhealthy competition (Oates, 1999). Farida et al. (2021) analyses data for thirteen provinces in Indonesia from 2016 to 2019, and he finds that fiscal decentralization has not caused the economic increase and that inter-regional inequality has not improved. The local governments did not play an optimal role and did not use resources wisely, thus not allowing the economy to grow. The same is true in India. Although fiscal decentralization has been implemented for a long time, it is still low in most cities, and the economy has not developed (Ginting et al., 2019). Existing theoretical research also propose that the impact of fiscal decentralization on economic increase may have both positive and negative outcomes. A reasonable inference is that the connection between FD and monetary growth is now not inherently monotonic, and a non-linear relationship exists between the two. Economic growth and regional equity are traded off as a result of decentralization initiatives. The relationship between fiscal decentralization and economic growth is nonlinear, i.e., it takes a parabolic shape (Belkovicsová & Boór, 2021).

12

Q. Wang and B. S. Nayak

According to the analysis of the data of the single EU countries from 2005 to 2014, fiscal decentralization positively correlates in developing countries with lower economic development. In contrast, there is no positive correlation in developed countries. Therefore, fiscal decentralization does not apply to all countries (Slavinskait˙e, 2017). Akai’s (2007) theoretical study found an inverted U-shaped relationship. After examining panel records of 29 Chinese provinces from 1995 to 2014, Sun and Hao (2016) also concluded an inverted U-shaped relationship. Maliˇcká et al. (2017), after studying the cases of 26 EU countries, also found that fiscal decentralization has gone from promoting economic growth to inhibiting it. There is another argument that fiscal decentralization can boost economic increase in the lengthy run, however in the quick time, economic growth decline. Prudhomme (1995) argues that the state needs a sound system and transfer mechanisms under the same conditions. Otherwise, it may lead to a concentration of resources in one region, widening the fiscal gap between different regions. Under a centralized system, however, the central government can transfer resources from the developed regions to the lagging regions, which can reduce the regional disparity. Corruption is also a severe problem for the government. Corruption, as well as informal events, have a significant impact on economic growth, and corrupt practices can reduce economic growth and affect other activities in the region as a whole. Therefore, fiscal decentralization can only have the desired effect when the government has strict laws and regulations to prevent corruption. Fiscal decentralization increases the number of competing local governments and reduces the room for corrupt practices by government officials. Because everything is distributed into different regions, when problems arise, the responsible officials can be quickly identified, which cab increase local officials’ accountability and reduce corruption (Huynh & Tran, 2021). Hanif et al. (2020) analyzed panel data of 15 developing countries, and found that the positive effects of fiscal decentralization on economic growth can also be affected if a country does not have perfect regulations and sound institutions. Arif and Ahmad (2020) also analyzed 53 developed and developing countries and found that fiscal decentralization increases the likelihood of such behavior as corruption in government institutions has long been entrenched. Citizens have to pay bribes to access the public services they are supposed to have. In conclusion, a country needs an excellent competitive environment, low levels of government corruption, political stability, and a sound institutional structure. Other scholars have other arguments that link fiscal decentralization to the structure of government spending, where different degrees of decentralization affect the mix of fiscal spending and the structure of the supply of public goods, all of which can affect economic growth. In Martinez-Vazquez and McNab’s (2003) paper, it is argued that fiscal decentralization affects the display preferences for public goods. In places with higher fiscal decentralization, more government expenditure is allocated to the supply of private goods, which has the advantage of increasing the efficiency of public distribution.

2 Two Decades of Fiscal Decentralization and Regional Economic …

13

Since Keynesian theory focuses on short-run static equilibrium, he did not consider the issue of economic growth. In contrast, after the Second World War, when the western economies were doing well, scholars turned their attention from the problems of economic depression and mass unemployment to economic growth. Economic growth theories are divided into exogenous growth theories and endogenous growth theories. The Solow model is representative of exogenous growth theory (Mankiw et al., 1992). The Solow model’s main feature is the production function’s setting. With the savings and population growth rates exogenous, a general equilibrium economic model can be derived from the neoclassical production function (Barro, 1990). Its basic production function is Y = F(K, L), and the economic system is on a path of equilibrium growth when the capital stock per capita, k, remains constant. When k > 0 or k < 0, the capital-output ratio will change, and eventually, the economic system will converge to k = 0, and the economy will achieve continuous and stable growth. The model, therefore, explores the growth rate of aggregate output as determined by the exogenous population growth rate, n, given a constant per capita capital stock (Thiessen, 2003). However, this model ignores the impact of technological progress on economic equilibrium and is expressed only in the form of a Solow surplus. Later scholars of neoclassical theory recognized this shortcoming and patched it up with the exogenous nature of technological progress. However, this theory still has shortcomings in that the exogenous rate of technical progress entirely determines the long-run per capita growth rate theory. In the study, the effects of fiscal decentralization on the economy are usually treated as a residual part of the Solow model (Brueckner, 2006).

Theory of Endogenous Growth In the neoclassical growth model, factors such as savings rate, population growth, and technological progress are exogenously given, which is clearly at odds with real life. As savings rates, population growth, and technological advancement are related to human behavior. They can be adjusted through policy instruments. These three elements can therefore change over time, whereas the neoclassical model cannot consider these factors. The endogenous growth model is an endogenous growth model that considers the savings rate, technological progress, and human capital, overcoming the shortcomings of the original neoclassical model. One of the breakthroughs of the endogenous growth model is the relaxation of the assumption of diminishing marginal returns to capital. The main ways to eliminate this assumption are the theory of constant factor rewards (i.e., AK model), the dry school theory, human capital accumulation (Lucas model), and so on. The endogenous growth theory has not yet become a model accepted by most scholars due to the reality of economic performance, the complexity of theoretical research, and the different research focus. However, the endogenous growth model is a better explanation of the dynamics of economic growth.

14

Q. Wang and B. S. Nayak

Stages of Fiscal Decentralization Fiscal decentralization is the core of fiscal federalism, which originated in Tiebout’s ‘A Pure Theory of Local Fiscal Expenditures’, published in 1956. Later, it was supplemented, developed and improved by scholars, and gradually the first generation of fiscal decentralization theory was formed. The first-generation theory took the supply level of public goods as its study object and argued that local governments were more efficient and relevant in providing public goods to the residents of their jurisdictions than the central government. Therefore, the degree of fiscal decentralization should be expanded. Tiebout (1956) developed a competition model for local government public spending and assumed that government officials were a community of interests. Voters were free to move and respond to government services, and voters could move and select different jurisdictions according to their utility maximization principles. Furthermore, local governments are bound to improve the public goods they provide to retain and attract voters. The existence of this ‘voting with one’s feet’ mechanism will stimulate local governments to achieve Pareto optimal in the provision of public goods through differentiated competition. Subsequently, Oates (1972) proposed an optimal frontier theorem for decentralized public goods supply based on information asymmetry and political pressure by discussing the costs and benefits of decentralization. The centralized supply of public goods is more homogeneous but less efficient, while the decentralized supply is less homogeneous but more efficient. The central government’s collection of homogeneous public goods will lead to a mismatch between the supply and demand of public goods and efficiency losses since there is an information asymmetry between the supply and demand of public goods. At this point, the local governments are required to provide differentiated public goods according to the needs of their jurisdictions’ inhabitants to achieve efficiency improvement. The first generation of fiscal decentralization theory emphasizes the advancement of social welfare due to fiscal decentralization. However, in the course of the theoretical analysis, the risks of decentralization are not included in the study. In particular, if local governments have the concept of “upward accountability” rather than “downward accountability”, decentralization will cause contradiction between the supply of public goods by local governments and the needs of the public, which may distort the allocation of public resources (Buchanan, 1975). The economic decisions made by local governments may be at odds with the overall national policy, leading to economic turmoil; local governments may compete viciously to attract or retain voters, resulting in a waste of public resources and a loss of social welfare. The second generation of fiscal decentralization theory considers local governments as rational economic agents. They thinks that local governments may have a game between their own interests and the social needs. The study focus of this theory is the behavior pattern of governments. Qian and Weingast (1997) study the resource allocation function between central and provincial governments and argue that the division of labor and collaboration among governments is a true reflection of fiscal decentralization. Qian and Weingast (1997) point out that as rational economic

2 Two Decades of Fiscal Decentralization and Regional Economic …

15

agents, local governments have trade-offs between their utility and social needs in the provision of public services, which can lead to alienation of local government behaviour. With insufficient or inadequate constraints, local governments are prone to corrupt practices such as rent-seeking, leading to the inefficient or ineffective provision of public goods. In addition, fiscal decentralization can lead to opposition amongst nearby governments. When the competition is excessive, its growth effects often fail to offset its debilitating effects, and is not deductive to economic development. Local governments are accountable for their responsibilities when such competition becomes’ Market Protection’, and reinforce the hard budget constraints. The hard budget constraints mean that local governments may become an obstacle to financing local public goods, triggering improved fiscal arrangements by local governments (Montinola et al., 1995). The second-generation theory argues that fiscal decentralization leads to competition between governments for resources such as capital and talent. This competition facilitates the formation of constraints and incentives, which in turn can control local government intervention in the economy to a certain extent. Suppose a local government interferes excessively in the production decisions of enterprises in its jurisdiction while other regions adopt market-oriented competition strategies. In that case, it will put the enterprises in its jurisdiction at a competitive disadvantage, thus reducing fiscal revenue and damaging the allocation of factors in its authority. When there is too much incentive but not enough constraints, the public expenditure structure will be biased. Although local governments are most efficient in providing local public goods, there is also a risk that public goods are overused, misused and wasted by local governments, which will ultimately lead to the detriment of economic development.

Chinese Theory of Fiscal Decentralization Fu and Zhang explicitly introduced the concept of “Chinese fiscal decentralization” (2007). They point out that the core connotation of “Chinese fiscal decentralization” is the coexistence and vertical political management systems. It is different from the western fiscal decentralization system and has its unique characteristics. Firstly, “Chinese fiscal decentralization” is an “administrative unanimity” model of fiscal decentralization. In China’s fiscal reform, the central government plays a decisive role. The introduction of a series of major reform proposals has been an administrative consensus model of fiscal decentralization, which has also determined the pattern of budgetary decentralization in China (Qian & Weingast, 1997). Secondly, Chinese fiscal decentralization is an economic decentralization under the centralized political power. In Western countries, the appointment of officials is decided by the constituency’s voters through a “vote with the feet” mechanism, which can be described as “downward accountability”. In contrast, the central government decides the appointment of Chinese officials through personnel appointments and dismissals, which can be described as “upward accountability”; this “upward accountability” is a manifestation of political centralization. Therefore, Chinese

16

Q. Wang and B. S. Nayak

fiscal decentralization is a decentralized system that combines political centralization with economic decentralization. Under the Chinese fiscal decentralization system, local authorities officers are appointed and dismissed by using the central government, ensuing in a sturdy incentive for neighborhood governments to engage in “political tournaments”. In contrast, financial decentralization gives nearby governments a sure diploma of monetary autonomy, prompting them to seek to maximize their interests as rational monetary agents. The interaction between the two has greatly stimulated the development of local economies. Thirdly, the “Chinese style fiscal decentralization” reform process is a centrallyled “top-down” coercive institutional change. Due to the different political systems, the process of fiscal decentralization reform in Western countries is a “bottom-up” demand-induced institutional change. In contrast, in China, due to the single political system, local governments are dominated and controlled by the central government. The process of fiscal reform is a “bottom-up” coercive institutional change. This is also reflected in the successive tax-sharing reform policies. Local governments play games and compete within the established financial system to maximize their interests. Three two methods of measuring fiscal decentralization exist in the literature. The first one is the fiscal revenue decentralization indicator, or the ratio of local governments’ fiscal revenue to their central government’s fiscal spending for the current year. The second is the fiscal expenditure decentralization indicator, which measures how much each local government’s current-year budgets compare to those of the central government. However, this chapter adopts the fiscal revenue decentralization indicator. In addition to fiscal decentralization indicators, the economic growth dependent variable is another important indicator. There are two leading economic growth indicators in the existing literature: nominal GDP growth rate and real GDP growth rate. Since nominal GDP growth rates do not exclude the price factor, there is a risk that they are inaccurate measures of economic growth, so this paper adopts the real GDP growth rate. A large number of statistical yearbooks were collected, and the relevant data were collated, calculated and analyzed to ensure the rigour and authenticity of the results of the empirical analysis. Additionally, the relevant literature was applied to provide a theoretical basis to make the study more realistic. In this chapter, the thirty one provinces of China are divided into four regions, namely the East, Central, West, and Northeast. This chapter uses the Generalized method of moments for empirical analysis. As the relationship between the degree of fiscal decentralization and the level of economic development in the four regions is to be studied, relevant data from all provinces, municipalities, and autonomous regions in China must be found and analyzed. The growth rate of provincial GDP per capita from 2000 to 2020 was used as the explanatory variable. Fiscal revenue was used to measure the level of fiscal decentralization, taking into account the impact of factors such as the rate of change in fixed asset investment, the rate of change in population growth, and years of education per capita on economic growth. After that, we used panel data to analyze the relationship between fiscal decentralization and regional economic growth differences.

2 Two Decades of Fiscal Decentralization and Regional Economic …

17

China’s economy is in a phase of high growth. At present, China needs to develop new productivity factors while maintaining current productivity, making institutional reform a primary objective, stimulating social creativity on all fronts, and improving efficiency and product quality in conditions of sustainable development. Investigating how fiscal decentralization affects economic development incentives is therefore crucial. Moreover, there are still areas of improvement in China’s current fiscal decentralization system, and addressing these issues could lay a solid foundation for China’s fiscal system and contribute to the country’s economic development.

Fiscal Decentralization and Economic Growth There are many studies on the link between fiscal decentralization and economic growth, domestically and internationally. Most of the literature tends to be consistent in its results, namely, the increased decentralization leads to quicker local economic growth. However, a part of the literature holds the opposite view that fiscal decentralization can be detrimental to economic growth in some cases. The different conclusions reached by scholars may be due to various factors. On the one hand, it is possible that different periods have been chosen, with one part of the literature studying decentralization mainly before 2000 and the other part of the literature exploring it after 2000. Still another part of the literature examines the period in between. On the other hand, scholars may have studied different levels of data, with one part of the literature looking at national-level data and exploring FD in individual countries, and the other part using provincial or state-level data to analyze the relationship between FD and the economy. Oates (1972) argues that central governments have a geographical disadvantage over local governments regarding access to information, as they are farther away from the regions and do not have quick and direct access to information. On the other hand, local governments better understand local conditions. They can thus effectively avoid the problem of inefficient fiscal spending caused by information asymmetries so that they can, firstly, better meet the needs of residents, and secondly, provide public goods better suit to the local conditions, thus promoting rapid economic growth. Akai and Sakata (2002) focus on the relationship between FD and economic development in the US. Their regression analysis using the latest data from each US state shows that the US policy of budgetary decentralization has effectively promoted stable economic growth in the US. This is contrary to most previous literature that FD had hindered the US economy. Moreover, the authors argue that the findings of this paper are not influenced by history, culture and time, and can truly reflect the impact of FD on the US economy. Bird and Wallich (1993) argue that the greater the degree of fiscal decentralization, the faster the economic growth, which benefits the country as a whole. When the

18

Q. Wang and B. S. Nayak

central government devolves the power of revenue and disposal to the local governments, the efficiency of the local governments is raised, and, very importantly, the government budget deficit is reduced. Baskaran and Feld (2009) collected the panel data of 23 OECD countries from 1975 to 2001 for empirical analysis. Although the initial results of the research were that FD would lead to lower economic growth rates in these countries, these results became insignificant when robustness analysis was done. Therefore, the authors concluded that economic growth and FD in OECD countries are not correlated. However, there is evidence that central government control over the administration of taxes and fees promotes rapid economic growth. On the other hand, they also find that increased political freedom for local governments hinders economic growth. In sum, we need to distinguish between fiscal and political decentralization to better learn about the influence of decentralization on the economy. Baskaran and Feld (2013) continue to study the data from 1975 to 2008. In this paper, the authors change the fiscal decentralization degree indicators, not only using traditional research methods, but also using a new approach focusing on local tax freedom. Ultimately, the analysis results of each techniques exhibit that fiscal decentralization has a poor have an impact on monetary growth, however the consequences are greater sizeable with the tax freedom-based approach. Gemmell et al. (2013) studied the panel records of 23 OECD nations from 1972 to 2005, and regressed the data using expenditure and revenue as fiscal decentralization indicators. The results for budgetary expenditure as an indicator found that FD promotes slower economic growth, while the results for fiscal revenue as an indicator shows that FD promotes rapid economic growth. The research result of Oates (1972) is the same. Therefore, a country needs fiscal expenditure and revenue decentralization to coordinate to better help the national development. However, OECD countries have higher expenditure decentralization than revenue decentralization. So OECD countries need to reduce fiscal decentralization for their economies to grow rapidly. Rodden and Wibbels (2010) analyzed the relation between fiscal decentralization and economic cycles based on an empirical analysis of seven federal countries. While central government fiscal policy sometimes provides moderate protection against regional revenue shocks, pro-cyclical fiscal coverage amongst provincial governments can without difficulty override these stabilizing effects. Based on the cyclical nature of local government budgets in seven federal countries, their analysis found that own-account taxation typically exhibits a highly pro-cyclical dynamic. Contrary to the frequent sense, income sharing and switch structures are both pro-cyclical or do now not show off cyclical characteristics. Thus, the article argues that local governments also need to cope with potential economic shocks on their own. The current countercyclicality of fiscal policy provides a good warning to the world. The need for countercyclical fiscal policy today is unabated. More seriously, many countries have delegated much of their fiscal responsibilities to local governments, i.e. fiscal decentralization has reached a very high level. Rodden (2010) concludes that the characteristics of fiscal decentralization largely determine its impact on the scale of local government expenditure. Where local

2 Two Decades of Fiscal Decentralization and Regional Economic …

19

governments are dependent on public resources, fiscal decentralization expands the size of local government expenditure, and conversely curbs its expansion. In Xie et al. (1999) studied the fiscal decentralization in the US. The authors first installed an endogenous increase mannequin and confirmed how FD impacts the economy. When the model is combined with the actual situation in the US, the authors find that the share of state and local government spending in the US is the most consistent with the development of the US economy. Therefore, if the US increases the degree of fiscal decentralization, it will be detrimental to economic growth. Martinez-Vazquez and McNab (2006) not only examined the impact of fiscal decentralization on economic growth, but also the impact of fiscal decentralization on economic stability. The study results show that decentralization contributes to price stability in developed countries and is more pronounced in developing countries. Secondly, it is also demonstrated in the article that decentralization has a negative impact on economic development, but the negative impact may be attenuated, because fiscal decentralization promotes macroeconomic development, which can offset some negative effects. Lozano and Julio (2016) used quantitative evaluation to have a look at the have an effect on of the fiscal decentralization device on the regional economic system because the introduction of the political charter in Colombia in 1991. Their panel data regression analysis used AMG estimates, which allowed for the inclusion of more explanatory variables than traditional regression analysis. The conclusion is that decentralization has driven economic development in all regions of Colombia. Limi (2004) collected the data from fifty-one countries for an empirical study. The results show that, in theory, fiscal decentralization increases local government public goods provision and services to the population and promotes economic development. But in the analysis of the data of the early 1990s, fiscal decentralization did not promote economic growth. Thus, fiscal decentralization has performed an necessary position in the economic improvement of the countries due to the fact that the 1990s. Neyapti (2004) revisited the link between revenue decentralization, central bank independence and inflation levels on the basis of the previous literature. In distinction to the previously findings, revenue fiscal decentralization has a bad impact on inflation, i.e. inflation decreases as the degree of revenue fiscal decentralization increases. However, in the low inflation countries, even without considering the independence of central banks and the responsibilities of local governments, revenue fiscal decentralization still has a negative impact on inflation. Thornton (2007) argues that although the literature has shown a significant negative association between revenue decentralization and inflation, he believes these studies are inaccurate regarding revenue decentralization. In a regression analysis of the data of 19 OECD countries from 1980 to 2000, the author found no significant association between revenue fiscal decentralization and inflation. Basharan (2011) argues that there are significant problems with the existing literature on the relationship between revenue decentralization and inflation. One of these problems is the inaccurate selection of revenue decentralization indicators. Therefore, the authors used a reconstructed indicator of fiscal revenue decentralization, namely the fiscal revenue decentralization measure, and conducted a new study. The

20

Q. Wang and B. S. Nayak

new study results show a significant negative relationship between the degree of fiscal revenue decentralization and inflation, i.e. an increase in the degree of fiscal revenue decentralization is related with a limit in the rate of inflation instead. Prudhomme (1995) argues that unfettered fiscal decentralization leads to a attention of sources in a few areas and increases inequality between local governments. Huther and Shah (1998) argue that official corruption reduces the degree of fiscal decentralization. That is, when corruption among local government officials is serious, the central government will centralize its power to solve the problem. Thus the degree of fiscal decentralization will be reduced. Fiscal decentralization will constrain government behaviour and function as a check on the public sector. Buchanan (1975) proposed the Leviathan restraint hypothesis, in which he argues that fiscal decentralization has the effect of restraining the scale of government spending. An important impact of fiscal decentralization is that through the transfer of power to the local level, voters can exercise greater oversight over government spending, restraining local government spending and reducing unnecessary fiscal expenditure. This will reduce the number of social resources taken up by the government and increase the efficiency of their use. Secondly, fiscal decentralization can produce constraints on the behaviour of local officials. As decentralized local governments are closer to the electorate, voters will better monitor local officials, thus reducing the likelihood of corruption and promoting regional economic growth. Arikan (2004) used a model to illustrate that fiscal decentralization increases the number of competing local governments and leaves little room for corruption. The lower number of local governments makes them prone to corrupt practices. He also found through empirical tests that the higher the degree of fiscal decentralization, the less corruption. However, in some developing countries, the inadequacy of their political systems and legal systems limit the role of local residents in monitoring the government. Since corruption is entrenched in local government institutions and residents need to pay bribes to get admission to public offerings for which they have paid taxes, fiscal decentralization may also make bigger the possibility of rentseeking behaviour through local officers. Thus, the relationship between corruption caused by fiscal decentralization and economic growth needs further study. In terms of economic stability, Conyers (1990) finds that fiscal decentralization improves income distribution, stabilizes macroeconomic development, and increases public participation. Tanzi and Ter-Minassian (1995) argue that the degree of fiscal decentralization affects the design and implementation of macroeconomic policies. Mohanty and Zampolli (2009) conclude that government expenditure shocks under decentralization can lead to economic turbulence, using the data of 20 OECD countries from 1970 to 2008. Debrun and Kapoor (2010) used panel data of 49 countries from 1970 to 2006 and concluded that fiscal policy under decentralization contributes to economic stability mainly through automatic stabilizers. Melnyk et al. (2018) conclude that fiscal decentralization is one of the key factors affecting economic stability from the aspects of expenditure decentralization, revenue decentralization and revenue and expenditure decentralization. At the micro-level, Feltenstein and Iwata (2004) point out that fiscal decentralization can lead to inflation, which is detrimental to price stability. Martinez-Vazquez (2017) notes that the

2 Two Decades of Fiscal Decentralization and Regional Economic …

21

socio-economic outcomes associated with decentralization are uncertain but mostly positive and conducive to economic stability. Lago-Peñas et al. (2020) conclude that fiscal decentralization is conducive to financial stability using OECD data from 1995 to 2014. He also notes a positive relationship between the degree of fiscal decentralization and fiscal performance, but this relationship diminishes rapidly with increasing vertical fiscal imbalances. Csehi (2020) factors out the uncertainty in the have an impact on of fiscal decentralization on budgetary stability, which leads to a variation in the stringency of balanced price range guidelines throughout the vary of federal models. In the case of environmental pollution, most scholars argue that local governments under fiscal decentralization will relax environmental regulation standards, which is detrimental to the reduction of environmental pollutants. For example, Kunce and Shogren (2008) point out that the devolution of taxation powers and environmental regulation responsibilities can lead to low tax rates and slack ecological standards by local governments, leading to the internalization of pollutant emission rents, which is detrimental to pollutant reduction. Li (2020) concludes that fiscal decentralization has an asymmetric impact on environmental quality, using the data from Pakistan from 1984 to 2018. He shows that expenditure decentralization has an asymmetric effect on carbon emissions in Pakistan in the short and long term, while the positive impact of tax decentralization would reduce carbon emissions.

Fiscal Decentralization and Economic Growth in China Davoodi and Zou (1998) conducted a cross-country study of fiscal decentralization and collected panel data of 46 countries from 1970 to 1989. The chapter uses an endogenous growth model and concludes a negative association between fiscal decentralization and economic development. The higher the degree of state decentralization, the slower the economic growth rate. But this result was not found in developed countries. The study by Zhang and Zou (1998) also focused on quantitative analysis. They collected provincial panel data of China between 1978 and 1992, and after regression analysis, they found that from 1978 to 1992, the fiscal decentralization not only failed to achieve the expected effect, but also hindered the development of Chinese economy to some extent. Contrary to the findings of Zhang and Zou (1998), Lin and Liu (2000) found that further fiscal decentralization during the 1970s–1990s positively affected China’s economic growth. Similarly, a study by Qiao et al. (2008) refuted Davoodi and Zou (1998) and Zhang and Zou, arguing that fiscal decentralization policies helped to drive China’s economic growth between 1985 and 1998, but also led to uneven economic development among different regions in China. Jin and Zou (2005) used panel data of various provinces in China from 1972 to 1993 and 1994 to 1999. They found that there is no significant relationship between economic growth and expenditure decentralization in 1994–1999, but there is a very

22

Q. Wang and B. S. Nayak

sizable affiliation between economic growth and fiscal decentralization. Hanif’s study (2020) found that economic growth accelerates when local governments have more power over taxation. But how this mechanism exactly works is not very clear; it may be that increased taxation brings about a lot of public goods or that citizens increase output. In short, decentralization of fiscal spending promotes economic growth. In a study of China’s fiscal reforms from 2001 to 2011, the authors found that by shifting power from the prefecture-level to the county level, local governments could help construct public facilities and residents’ livelihoods. Government officials would also benefit from economic growth, thus increasing the motivation of the officials, which could create a good competitive environment (Ma & Mao, 2018). Ding (2008) examined the data from 1994 to 2003, and the authors found that there is a positive relationship. Using inter-provincial panel data from 1991 to 2015, Zhou Jiujun (2018) reached a conclusion that there is an inverted U-shaped relationship between fiscal decentralization and price stability. He noted that the effect of fiscal decentralization on the price level shifts from facilitating to inhibiting as the degree of decentralization increases. Ekaterina (2020) argues that Chinese-style fiscal decentralization’s fiscal incentives for local governments are key to achieving economic prosperity in China. Song et al. (2022) collected the data of 24 provinces from 2010 to 2018 and used empirical analysis to examine the relationship between fiscal decentralization on economic growth and poverty reduction. They find that fiscal decentralization has a catalytic effect on economic growth and a catalytic effect on poverty reduction. In conclusion, FD can help poverty governance in China before China can reduce the gap between the rich and the poor and achieve national economic development. Fiscal decentralization has been an important part of China’s economic restructuring over the past three decades. However, little research has been done on how decentralization in China affects the regional level. Chen and Groenewold (2013) developed a theoretical model and collected the data from China to solve it, and analyzed different types of impacts. The authors find that fiscal decentralization’s effects on the economy depend on fiscal policy and that distributional inequalities between regions are difficult to detect because of the overall good economic development. Jin et al. (2013) find that Guangdong is one of the most developed provinces in China, but that fiscal inequality within the province is high. They, therefore, collected the data on regional fiscal spending in China from 1999 to 2008. The results found that there were also problems with central government transfers to local governments. Fiscal decentralization reforms are therefore important and may slow down economic growth and hinder the development of small localities. Tang (2021) also examines the impact of fiscal decentralization on the development of small cities in China. The author examines the impact of escalating fiscal reforms on economic development. Among them, the effect is insignificant in the central and western regions. Zhang and Gong (2005) conclude that the tax sharing reform helps increase economic growth. This is more evident in economically developed regions, i.e. fiscal decentralization has brought about a higher positive impact in the eastern areas than in the central and western regions.

2 Two Decades of Fiscal Decentralization and Regional Economic …

23

The management of the environment is also part of promoting economic development as the global environment is deteriorating with the development of industries such as chemical industries and human damage to the environment. Cheng et al. (2021) used quarterly data from 2005 to 2018 in China to conclude that fiscal decentralization is a major factor influencing carbon emissions. He also points out that there is a need to further clarify government functions at all levels in energy conservation and emission reduction so that a clear distribution of power and responsibility can facilitate achieving carbon emission reduction and fiscal energy saving targets. However, some scholars have come to the opposite conclusion that fiscal decentralization reduces carbon emissions and improves environmental quality to a certain extent. Guo et al. (2020) studied the impact of budgetary decentralization on environmental pollution and economic growth. The results show that improving the environment in China can promote its economic development. Firstly, fiscal decentralization is not only an economic issue but also related to the national context and political system, and research methods and perspectives need to be multifaceted. Existing research requires a combination of empirical and normative analyses, China’s national conditions and international experience, and a link between historical experience and reality. The investigation results will have a positive, stimulating effect on economic development and the political system. Secondly, when studying fiscal decentralization in China, it is important to choose a theoretical model and indicator system appropriate to the actual situation in China. Traditional fiscal decentralization theories are based on criteria that do not exist in China, which is an economically decentralized and politically centralized country. Therefore, the decentralization effect of China’s tax reform cannot be explained by the decentralization theories of other countries. Thirdly, through literature review, we find that there is likely a curvilinear relationship between them, and an optimal degree of decentralization exists. Policy-makers should see the interaction between fiscal decentralization and economic growth, and make appropriate arrangements according to national conditions, rather than blindly decentralization. Local governments should be given a reasonable competition mechanism and incentive role under the background of decentralization. It is important not to confine their research on fiscal decentralization to decentralization itself; they also cast their eyes on issues such as the allocation of public resources, local government competition, official corruption, and financial system reform. Indirectly, they have linked fiscal decentralization to macroeconomic development. Finally, there are many studies on fiscal decentralization in China. Most of the literature is from different provinces of China, and there are few studies on the regional aspects of fiscal decentralization in China. But China is a large country, and other regions have developed differently. Although few mathematical studies have also been conducted from a regional perspective, most of them have analyzed the differences between the three areas of the East, Central, and West. However, this paper will explore the impact of fiscal decentralization on economic growth in four regions of China: East, Central, West, and Northeast.

24

Q. Wang and B. S. Nayak

Methods to Study the Impact of Fiscal Decentralization on Economic Development This section constructs a systematic and valid empirical model by using panel data at the provincial level in China, and the reasons for the choice of indicators are explained. In addition, the data for thirty one provinces in China are selected from the official Chinese data websites.

Time Span of the Data Fiscal decentralization in China mainly began with the 1994 tax-sharing reform, but national reforms are difficult to complete in a short period. The share of central fiscal expenditure in federal fiscal spending did not change much before and after the 1994 tax-sharing reform. Policy changes require some transition time, and it was not until 2000 that many of the problems of the tax split reform were resolved. Therefore, the paper selects the data from 2000 to 2020.

Division of Regions In this chapter, the data relating to thirty one provinces in mainland China are selected to reflect the socio-economic development of different regions of China. China’s economic areas are divided into four major parts: East, Central, West, and Northeast. The eastern region includes Beijing, Tianjin, Hebei, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong and Hainan. The central region includes Shanxi, Anhui, Jiangxi, Henan, Hubei, and Hunan. The Western Region includes Inner Mongolia, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Tibet, Shaanxi, Gansu, Qinghai, Ningxia, and Xinjiang. The Northeast region includes Liaoning, Jilin, and Heilongjiang.

Fiscal Decentralization Fiscal decentralization is only one of the many factors contributing to economic growth in China’s economic transition. Therefore, when conducting regression analysis based on the model, it is important to discuss the corresponding economic environment and select appropriate control variables to represent other factors affecting economic growth to improve the accuracy of the estimation and test the empirical findings’ stability. According to the previous research findings by Chinese and foreign scholars, different indicators have been found to measure fiscal decentralization. Liu’s (2000) study focused mainly on the budgetary allocation ratio between the central government and the local governments. For the first time, he used the fiscal allocation index

2 Two Decades of Fiscal Decentralization and Regional Economic …

25

proposed by Oates (1972), and the variables in the model were studied using the real tax rate, economic growth rate, and population growth as variables. Lin (2000), on the other hand, focused his study on the marginal cost approach, which means that the proportion of central and local fiscal revenues retained by local governments is used as the criterion for allocation. In Zhang and Gong’s study (2005), four decentralization indicators were designed, mainly considering China’s transfer payment system and off-budget revenues and expenditures. The results of this measurement more adequately examined China’s national and political development situation. Since fiscal decentralization in China is more a matter of devolution of government powers to local governments, this paper will use the share of local revenue in total revenue as an indicator for analysis.

Investment in Fixed Assets In reality, many factors affect economic growth. Traditional economic theory decomposes economic growth into three types of factors: capital stock, labor input, and technological factors, but these three factors do not fully cover the variables that affect economic growth (Davoodi & Zou, 1998). Many scholars also incorporate other elements into the model to examine the impact of different factors on economic development. In this paper, we will mainly investigate the effect of the degree of fiscal decentralization on economic growth. Therefore, the indicator of fiscal decentralization is preferred to be included in the model. Specifically, capital accumulation is an important factor influencing economic growth, directly reflecting the level of economic development. Therefore, this paper also includes the capital factor in the model. Theoretically, the capital stock, i.e., the existing fixed assets in the productive sector such as enterprises, should influence economic growth, but depreciation data is not easily available. So, in reality, the capital stock is not the sum of investment over the years minus depreciation over the years. The depreciation in the figures represents only physical depreciation; depreciation should also include intangible depreciation resulting from technological progress, so capital stock data is not available. Investment in fixed assets is the physical capital paid by an enterprise to acquire fixed assets in economic activity. It is an important indicator of economic growth due to its importance in an enterprise’s business activities. Investment in fixed assets can be specifically measured in absolute and relative terms. Some existing studies have used fixed asset investment growth rate as a proxy for the capital factor. In contrast, others have used the logarithm of fixed asset investment to indicate the impact of the capital factor on the economy.

Regional Economic Growth Rates GDP per capita, expressed in this paper as the ratio of a country’s GDP achieved in a given year to the country’s registered population for that year, is an important

26

Q. Wang and B. S. Nayak

tool for measuring the efficiency of a country’s economic growth. This indicator reflects the differences of the initial economic environment of different regions, and the degree to which a region’s initial economy is developed can significantly impact that region’s economic development. In addition, this paper introduces the empirical model with each region’s real growth rate per capita as the explanatory variable.

Years of Schooling Per Capita Years of education per capita in each region has been chosen as an indicator in this paper. Educational attainment also has an important impact on economic growth. China is a big country, and when there is a large amount of capital and talent available, the country will suffer from a widening gap in regional economic development and a structural imbalance in the industry, resulting in uneven regional economic growth as well as uneven educational development.

Description of the Data All local government work reports on the national data network specify the annual economic growth target, so the data used in this chapter is a panel of 31 provinces for the period 2000–2020, mainly obtained from the China Statistical Yearbook, the China Finance Yearbook, the China Financial Yearbook, provincial statistical yearbooks, provincial financial operation reports, and the website of the National Bureau of Statistics of the People’s Republic of China. The econometric analysis of all data was completed using Eviews 10.0 software, and descriptive statistics for key variables are shown in Table 2.1. Table 2.1 Summary of descriptive statistics results of various variables Variable name

Average value

Maximum value

Minimum value

Standard deviation

Observed number

GDP

0.0977

0.1960

−0.0540

0.0310

651

FD

0.4992

0.5475

0.4504

0.0349

651

RIA

0.1258

0.6593

−0.9974

0.2652

651

GRP

0.0290

8.9563

−0.9454

0.4171

651

YE

2.1252

2.5480

1.0981

0.1704

651

Notes GDP represents the economic growth rate of each region, FD is a proxy for fiscal decentralization. RIA is the rate of change in fixed asset investment in each region. GRP is the rate of change in population growth in each region. lnYE is the logarithmic value of years of schooling per capita in each region. From the statistical data of each variable in this table, there is no abnormal value. Therefore, there is no problem with the data of thirty-one provinces, which can be brought into the model

2 Two Decades of Fiscal Decentralization and Regional Economic …

27

Setting of the Benchmark Panel Model For dynamic panel models, the OLS estimates obtained in this case will be invalid due to the lagged terms of the explanatory variables on the right-hand side of the model, which are correlated with individual or random effects, i.e., their correlation with the error term as well. Therefore, this paper uses the Generalized method of moments proposed by Arellano and Bover (1995) and Blundell and Bond (1998), among others, for model estimation. GDPit = β0 + β1 GDPi (t−1) + β2 FDit + β3 controlit + λi + μit where controlit is a control variable, RIAit is the rate of change in fixed asset investment in region i in period t, GRPit is the rate of change in population growth in area i in period t, and lnYEit is the logarithm of years of education per capita in region i in period t. γi is an individual or random effect; μit is a random error term; and β0 is a constant term. China has implemented a tax-sharing reform, but there are many provinces in China. And with complex administrative relationships, there is no way for the state to complete the reform quickly. Therefore, this chapter chooses data for the period 2000–2020. This chapter uses the Systematic Generalised Method of Moments for model estimation. And the data from thirty-one provinces are collated for the subsequent empirical analysis. The data were obtained from the official website of China. No outliers were found in the results after data processing.

Regional Differences in the Impact of Fiscal Decentralization on Economic Growth In order to analyze regional differences, this section uses a panel data model to empirically examine the impact of fiscal decentralization on economic growth in four regions, i.e. East, Central, West, and Northeast regions. It also provides valid econometric evidence to support the previous economic theories based on the findings obtained and further analysis.

Panel Models Systematic GMM estimation is a standard approach to dynamic panel estimation as it effectively avoids endogeneity problems between variables and between variables and residuals. In practice, the consistency of the systematic GMM estimates depends on the validity of the choice of instrumental variables for the regression equation. Two hypothesis tests are usually required to test whether this condition is met: firstly, the

28

Q. Wang and B. S. Nayak

Sargan test on over-identification restrictions, which is mainly used to test the validity of the instrumental variables, and if the original hypothesis cannot be rejected, then the model is valid. The second is the AR(1) and AR(2) tests on the serial correlation of residuals. The original hypothesis is that the error terms are not serially correlated, which is similar to the Sargan test. If the original hypothesis cannot be rejected, then the model estimates are valid. The Wald test imposes different constraints on the other models to determine which model has better estimation effect (Table 2.2). For model (a), the results of the Sargan test show that there is no over-identification of instrumental variables in models (a), (b), (c), and (d). Applying the constraint that the coefficient on FD is 0 to model (a), the Wald test results show rejection at the 1% level, indicating that the model incorporating FD is set up correctly, which is consistent with the reality that fiscal decentralization affects economic growth. The coefficients of FD in models (a), (b), (c), and (d) are all negative and significant at the 1% level of significance, indicating that the effect of fiscal decentralization on economic growth is negative. By adding control variables to model (a), model (b), model (c), and model (d), in turn, the negative effect of FD is observed to be less and less. This indicates that although fiscal decentralization, in reality, has a negative Table 2.2 Summary of dynamic panel model estimation results Model form

Explained variables GDP Model (a)

Model (b)

Model (c)

Model (d)

GDP (−1)

0.8283*** (0.0082)

0.7336*** (0.0133)

0.7180*** (0.0184)

0.7567*** (0.0411)

FD

−0.2591*** (0.0061)

−0.2310*** (0.0089)

−0.2243*** (0.0097)

−0.0677*** (0.0226)

0.0359*** (0.0026)

0.0341*** (0.0032)

0.0306*** (0.0051)

0.3668*** (0.0608)

0.3694*** (0.0708)

RIA GRP

−0.1045*** (0.0119)

lnYE AR(1)

–

–

–

–

AR(2)

–

–

–

–

Sargan

30.3595

30.4701

30.5341

29.5377

Wald

0.8282 (0.0082)

0.7336 (0.0132)

0.7180 (0.0184)

0.7566 (0.0411)

Number of samples

589

589

589

589

Number of province

31

31

31

31

Notes *, **, *** denote significance at the 10%, 5%, and 1% significance levels, respectively; the null hypothesis for the AR(1) and AR(2) tests is that there is no first- and second-order serial autocorrelation of residuals in the model setting; the null hypothesis for the Sargan test is that there is no over-identification of instrumental variables in the model set

2 Two Decades of Fiscal Decentralization and Regional Economic …

29

effect on economic growth, this negative effect is gradually weakening in the real economy due to various influencing factors. For the logarithmic values of the control variables rate of change in fixed asset investment by region, rate of change in population growth by region, and years of schooling per capita by area, the results of model (a), model (b), model (c), and model (d) show that they are all significant at the 10% level. The rate of change in fixed asset investment and the rate of change in population growth in each region positively affect economic growth. In contrast, the value of years of education per capita in each area harms economic growth. China is a vast country with wide disparities in economic and social development of different regions. If the central government provides public services uniformly, it will be impossible to cater to the different needs of different regions and efficiently allocate resources. Since 1994, local governments have had a greater advantage in locational information than central ones. The decentralization of power has facilitated the local governments to tailor their fiscal spending activities to local conditions. This approach has been effective in meeting the heterogeneous needs of the local population, increasing the efficiency of resource allocation and thus reducing the disincentives to economic growth (Oates, 1999). This negative influence may be due to the incoordination with the stage of economic development at a certain time. For example, when fiscal decentralization was introduced during relatively rapid economic development, local governments retained limited financial resources and lacked the capital to undertake large investment projects. Moreover, fiscal decentralization segregates localities into polycentric interest groups. Local governments are bound to compete with each other to maximize their interests, and if this competition is vicious, it will also affect economic development. Under the Chinese-style decentralization system, local governments compete blindly for investment in pursuit of short-term benefits, making the use of funds less efficient. In addition, government investment is not invested through the market, which is not conducive to fair competition, and state-owned enterprises, collective enterprises, and large corporations are better placed to access these funds, further suppressing the development of small and medium-sized enterprises. In the long run, the regional economy will be stuck in a stalemate, which is not conducive to a steady increase in regional economic growth. The results of the empirical analysis show that the education level of each region’s population still has a dampening effect on economic growth. At the same time, the economic growth in areas with rapid educational growth has not been maintained at the same rate. In the case of the former, the rate of economic growth is inevitably dragged down by education. In the latter case, although it is reasonable for education to be moderately ahead of its time, it is also bound to be constrained by the speed of economic development if it is too far ahead. Education is an important factor in transforming the way the economy develops. Hence, it is vital to achieve a balanced development of education. Local governments need to reduce uneven development in education for the regional economic development gap to be reduced. Investment in fixed assets strongly correlates with economic growth, and investment in fixed assets can, to a certain extent, reflect the overall direction of a country’s

30

Q. Wang and B. S. Nayak

economic development. When the government continues to increase the proportion of fixed investment assets, enterprises receive more financial support, which further helps their development. Ultimately, this has a catalytic effect on China’s development.

Sub-regional Results To reflect the socio-economic development of different regions in China, the country’s economic regions have been divided into four major regions, namely, the East, Central, West and Northeast. Table 2.3 provides a summary of the estimated results for each region. Table 2.3 shows that the impact of FD on GDP is negative. This negative force is most pronounced in the eastern region, followed by the eastern, western central, and northeastern areas. The results show that this inhibiting effect of fiscal decentralization on economic growth is more pronounced in the more developed regions. Therefore, it is urgent to speed up the reform of the fiscal system, and a practical fiscal and tax systems in line with local characteristics according to the development status of different regions should be formulated as soon as possible. Table 2.3 Summary of dynamic panel model sub-regional estimation results Model form

Explained variables GDP East (e)

Central (f)

West (g)

North East (h)

GDP (−1)

0.5798*** (0.0559)

0.7461*** (0.0480)

0.7524*** (0.0390)

0.6079*** (0.0859)

FD

−0.2297*** (0.0388)

−0.1160*** (0.0.0708)

−0.1677*** (0.0289)

−0.0707*** (0.1172)

RIA

0.0443*** (0.0114)

0.0294* (0.0162)

0.0488*** (0.0083)

0.0343*** (0.0115)

GRP

0.2637*** (0.0945)

0.4018** (0.1617)

−0.0140 (0.0846)

−0.0832 (0.0523)

lnYE

−0.0248** (0.0103)

−0.0739** (0.0282)

−0.0093* (0.0049)

−0.0832 (0.0524)

Adjusted R-squared

0.8162

0.7543

0.8300

0.8687

F

172.3420 (0.0000)

70.0009 (0.0000)

228.6113 (0.0000)

71.4997 (0.0000)

Number of samples

200

120

240

60

Number of province

10

6

12

3

Notes *, **, *** denote significance at the 10%, 5%, and 1% significance levels, respectively; the null hypothesis of the AR(1) and AR(2) tests is that there is no first- and second-order serial autocorrelation of residuals in the model setting; the null hypothesis of the Sargan test is that there is no over-identification of instrumental variables in the model set

2 Two Decades of Fiscal Decentralization and Regional Economic …

31

For the logarithmic values of the control variables rate of change in fixed asset investment by region, rate of change in population growth by region, and years of education per capita by area, the results of models (e), (f), (g) and (h) show that the rate of change in fixed asset investment by region and pace of change in population growth by region has a positive effect on economic growth. In contrast, the logarithmic value of years of education per capita by region has a negative impact on economic growth, confirming the conclusion mentioned above that there is a inhibiting effect of the population’s education level by region on economic growth. As the leader of China’s economic development, the eastern region enjoys various advantageous conditions. Motivated by promotion mechanisms, the local governments took the lead in developing heavy industry. As a result, quantitative economic growth in the short term was achieved, resulting in the quantitative growth of the economy in the eastern part of China. In contrast, the quality of the economy failed to catch up in time. Because of the rapid development of the eastern region, the market mechanism is complete, and excessive government intervention is adverse to the smooth and healthy development of the regional economy. China has been pursuing the “Rise of Central China” strategy in recent years. Since the eastern region took the lead in development, China has increased its investment in the central area, continuously improving the market system in the central region, promoting the optimization and upgrading of the industrial structure in the central area, and striving to narrow the regional development gap. Although the effect of fiscal decentralization on the quality of economic growth in the west is negative, if the significance level is slightly relaxed, the western economic growth effect is also significant, indicating that China’s western development strategy has been effectively implemented. The natural environment in western China varies greatly, and regional development is highly uneven. The improvement of the degree of decentralization is conducive to the full play of the information advantages in the western region, thus better promoting the quality of economic development in the west. Moreover, compared with the eastern region, other regions are less developed, the level of marketization is lower, and the infrastructure and institutional environments need to be improved. The positive effects of appropriate local government intervention in the economies of their jurisdictions are more pronounced than that in the eastern region. GDP per capita, as a representative indicator of economic growth, remains significant for economic development in all regions, while it is the smallest in the fastest growing eastern area. The results indicate that a single driver of economic growth is unsustainable in the transition from high economic growth to high-quality economic development. Investment in fixed assets positively affects high economic development, which indicates that economic activities in the construction and acquisition of fixed assets can expand a region’s the production and construction capacity. But the increase in the number of years of schooling does not positively affect the economy. The table also shows that the central, and north-eastern regions have a

32

Q. Wang and B. S. Nayak

greater inhibiting effect than the east. This is because the relatively lagging regional development of the north-eastern and central areas cannot meet the personal development needs of all highly educated people. The mismatch between competencies and positions may become a shackle that hinders the effect of human capital, thus inhibiting the quality of economic development. The eastern coastal region is at the forefront of China’s reform and opening up. The economic and industrial structures are developing in a sound way, and institutional and technological innovations are balanced and advanced. Therefore, the eastern region has superior competitive advantages in modern economic development and is ahead of other areas in all aspects of economic growth. The western region is rich in natural resources such as minerals, land, and water energy with great potential for development. Still, it is constrained by the harsh climatic environment, poor facilities, and low-level industrial development. As a result, the western region lacks the capital, technology, and talent needed for economic growth and is still far behind other areas. The current national policy of supporting the development of the western region has not only helped to accelerate the economy of the part of the west itself, but also effectively bridged the relative gap with the developed areas, resulting in a positive trend of sustained economic development. As a major old industrial base and a major grain-producing region in China, the Northeast region has a solid economic foundation. Located at the center of the Northeast Asian economic circle, Northeast China has relatively obvious regional advantages in opening up, and also pays more attention to the effective use and protection of environmental resources. However, because of the failure to transform its modern economic development, the lack of innovative thinking and practical measures, the downward pressure on the economy continues to increase. The central region has broad market potential, the advantage of a regional location to the east and west. The benign construction of regional city clusters offers the possibility for further economic development. However, it is relatively short of resources, the ecological vulnerability caused by river basin pollution is obvious, and it lacks external location advantages for open economic development. The central and northeastern regions have their own obvious advantages and disadvantages. At the current stage, it is necessary to find an economic development model that suits the trend of the times and its own needs and effectively utilizes the national policy effects of the rise of the central region and the revitalization of the northeast to support the region’s development in a better and faster direction. The reform of the fiscal decentralization system has played a very important role in China’s economic transformation process. Following the tax-sharing reform, the share of fiscal revenue in GDP has increased nationwide. In contrast, the central government’s share of fiscal revenue has increased and the percentage of fiscal expenditure has decreased compared to that of local governments, i.e., the fiscal revenue controlled by local governments decreased while the fiscal expenditure matters borne by them increased.

2 Two Decades of Fiscal Decentralization and Regional Economic …

33

Fiscal decentralization has given local governments a certain degree of autonomy over their fiscal revenues and expenditures and thus a greater incentive to develop their economies. However, the incomplete and compromising nature of fiscal decentralization reforms and the single GDP assessment mechanism for local government officials under centralized political power has led to horizontal competition among local governments. In addition, due to differences in factor endowments and production environments between regions, the constant expansion of government fiscal revenues has laid the groundwork for uneven growth of regional economy. The above empirical results show that fiscal decentralization dampens economic growth and that tax reform does not promote rapid economic development. Fiscal decentralization has a dampening effect on economic growth in all regions of China. The Chinese government’s tax collection and management are heavily localized, creating artificial regional market segmentation and hindering the market mechanism’s efficient allocation of resources. Excessive competition between local governments has led to competition with the people for profits and hindered the development of the private sector economy, which, coupled with the expanding phenomenon of duplication, has created a certain degree of distortion in local economic development. Therefore, it is not advisable for China’s fiscal decentralization reform to continue to advance in-depth alone but rather to focus on standardizing and improving the existing institutional arrangements. For regions that are lagging in economic development, the phenomenon of tax protection by local governments is more serious. For performance considerations, local governments will turn more energy to chasing the high-speed growth of GDP blindly and have no time to care about public goods investment, infrastructure construction, environmental pollution control, etc. Due to the weak regional competition and insufficient investment, economic growth is inhibited. Fixed asset investment plays a catalytic role in economic growth. Local governments should further increase investment in regional infrastructure construction and education and strengthen investment attraction efforts and talent training strategies to accelerate the pace of regional economic development. Education should be popularized and strengthened in all regions. Education is often limited to what teachers teach you in school, but internships and on-the-job training are more important than school education if you want to improve your skills. Currently, China’s economic development requires not only an increase in the labour force but also the improvement of labour force quality. Since China’s reform and opening up, the economy has achieved a “leap-frog” style development and gradually transformed from an extensive economy to an intensive economy. The change of economic development mode is inseparable from human capital development. Human capital is the source of technological innovation, and the promotion of human capital is conducive to the optimization and upgrading of regional industrial structure, thus contributing to the sustainable and stable development of the economy.

34

Q. Wang and B. S. Nayak

Conclusion As demonstrated by the empirical results, fiscal decentralization negatively affects economic growth. However, given the existence of factors including central transfer payments, the results from simple measures should not be considered in isolation— the preliminary design of the fiscal decentralization system and the incomplete implementation process should also be evaluated. The effect of fiscal decentralization on regional economic growth is achieved through various matching fiscal systems. This decentralization should focus on in-depth regulation and reform of the relevant systems. Based on the above research and analysis, the following policy recommendations are proposed. After the 1994 tax-sharing reform, the basic framework of China’s fiscal policy was established; however, many problems remain. For example, when the policy was implemented, local governments did not follow the regulations to implement it. In addition, the state did not establish a unified and fair transfer payment system. Thus, China’s fiscal reform remains incomplete. China’s existing fiscal decentralization reforms have primarily focused on dividing fiscal revenues without a clear division of responsibilities for fiscal expenditures. However, fiscal decentralization is significantly lower than property expenditure decentralization in each region. Additionally, the division of power among the local governments is unclear: each region can claim the responsibility lies with other regions, making it impossible to identify the local government primarily accountable for the actual implementation. As China’s regions are not uniformly developed, the effects of fiscal decentralization differ for each region. As the differences in economic growth between China’s regions widen, the state must transfer funds to lagging regions to reduce the fiscal revenue gap between these areas and more developed regions. Achieving such a fiscal balance between regions is important to ensure the development of the lagging regions, which is essential for the coordinated growth of the national economy. Accordingly, it is not suitable for the central government to apply the same policy in all regions; instead, individual areas should be managed in a targeted manner according to each region’s characteristics. The state should improve relevant systems and increase its efforts to manage financial resources, as well as implement differentiated fiscal policies according to each region’s specific situation. The central government should transfer funds from developed regions to lagging regions to help public works in the less developed areas and reduce economic disparities between regions. In addition, a strict legal and regulatory system is required for transferring funds. By achieving these funding reforms, inter-regional disparities can be reduced. A significant issue in China is that the central government’s assessment criteria for local governments are GDP-based; however, these criteria also neglect aspects such as education, environment and employment in each region. Officials focus exclusively on short-term interests and ignore regional sustainable development. Excessive competition can also arise between local governments, who ‘grab’ resources for their own region, thereby leading to inefficient resource usage.

2 Two Decades of Fiscal Decentralization and Regional Economic …

35

Overall, the government should clarify its responsibilities and maintain good market order. Only by doing so can the government better provide public goods and services for the people. Thus, the state must establish better laws to monitor the government’s actions. Such government appraisal should not solely be judged from a single perspective; the state should also examine the governance capacity of local governments in a scientific, comprehensive and fair manner. In summary, the country must change the single GDP assessment mechanism and minimise excessive economic interference by local governments. These steps are essential to improve the government’s management capacity and better serve the people of China. China is a vast country with many administrative staff; as a result, China suffers from a disproportionately high level of day-to-day administrative overheads. This problem is mainly a result of the country’s primary focus on economic development and the concurrent slow pace of administrative reform. Administrative costs, especially in remote and backward areas, are excessive. Although the economy has improved in many areas, science, technology and education expenditure are insufficient, which harms local economic development and upgrading of industrial infrastructure. Accordingly, the government should improve the efficiency of administrative funding usage and strengthen its internal management. China’s central and western regions are dominated by production and processing industries, thus, the tax burdens in these areas are relatively heavy. Thus, it is necessary to further deepen the fiscal and taxation system reform towards consumptionbased VAT rather than production-based VAT. In addition, taxation system reform should be used to promote optimisation of the regional industrial layout and support key local industries through preferential taxation policies. First, local governments should provide preferential corporate income tax, preferential technological transformation equipment and preferential turnover tax to investors. Second, local governments should encourage enterprises to strengthen their technological research, including by issuing some preferential taxation policies to high-tech enterprises. Local governments should aim to encourage and attract talents to start businesses and join key employment sectors by providing preferential personal income tax conditions, as well as implementing personal income tax exemptions for the technical income of scientific researchers. In this way, the chapter introduces the concepts of fiscal decentralization and economic growth and their related theories. China is divided into four areas; eastern, western, central and north-eastern to analyse the impact of fiscal decentralization on regional economic development. The results of the empirical analysis found that fiscal decentralization did not promote economic development. Furthermore, it had a significant dampening effect on the developed regions in the east. The impact of years of education per capita on economic growth was negative in all regions. However, both the rate of change in fixed asset investment and the population growth rate positively affect economic growth. This negative impact of fiscal decentralization on economic growth may therefore be the result of a mismatch with the stage of economic development at a given time. For example, in periods of relatively rapid

36

Q. Wang and B. S. Nayak

economic development, following the introduction of fiscal decentralization, localities retained limited financial resources and lacked the capital to engage in large investment projects.

References Akai, N., & Sakata, M. (2002). Fiscal decentralization contributes to economic growth: Evidence from state-level cross-section data for the United States. Journal of Urban Economics, 52(1), 93–108. Arif, U., & Ahmad, E. (2020). A framework for analyzing the impact of fiscal decentralization on macroeconomic performance, governance and economic growth. Singapore Economic Review, 65(1), 3–39. Barro, R. J. (1990). Government spending in a simple model of endogenous growth. Journal of Political Economy, 98(5), 103–125. Baskaran, T., & Feld, L. P. (2013). Fiscal decentralization and economic growth in OECD countries: Is there a relationship? Public Finance Review, 41(4), 421–445. Belkovicsováa, D., & Boór, M. (2021). Kvantifikácia optimálnej miery fiškálnej decentralizácie v krajinách OECD. Politická Ekonomie, 69(5), 595–618. Brueckner, J. (2006). Fiscal federalism and economic growth. Journal of Public Economics, 90(10– 11), 2107–2120. Buchanan, J. M. (1975). The limits of liberty: Between anarchy and Leviathan. University of Chicago Press. Chen, A., & Groenewold, N. (2013). The national and regional effects of fiscal decentralisation in China. The Annals of Regional Science, 51(3), 731–760. Cheng, Y., Awan, U., Ahmad, S., & Tan, Z. (2021). How do technological innovation and fiscal decentralization affect the environment? A story of the fourth industrial revolution and sustainable growth. Technological Forecasting and Social Change, 162, 120398. Davoodi, H., & Zou, H. F. (1998). Fiscal decentralization and economic growth: A cross-country study. Journal of Urban Economics, 43(2), 244–257. Farida, N., Suman, A., & Sakti, R. K. (2021). Fiscal decentralization, economic growth and regional development inequality in eastern Indonesia. Journal of Indonesian Applied Economics, 9(2), 1–9. Gemmell, N., Kneller, R., & Sanz, I. (2013). Fiscal decentralization and economic growth: Spending versus revenue decentralization. Economic Inquiry, 51(4), 1915–1931. Ginting, A. M., Hamzah, M. Z., & Sofilda, E. (2019). The impact of fiscal decentralization on economic growth in Indonesia. Economic Journal of Emerging Markets, 11(2), 152–160. Guo, S., Wen, L., Wu, Y., Yue, X., & Fan, G. (2020). Fiscal decentralization and local environmental pollution in China. International Journal of Environmental Research and Public Health, 17(22), 8661. Hanif, I., & Gago-de Santos, P. (2017). Impact of fiscal decentralization on private savings in a developing country: Some empirical evidence for the case of Pakistan. Journal of South Asian Development, 12(3), 259–285. Hanif, I., Wallace, S., & Gago-de-Santos, P. (2020). Economic growth by means of fiscal decentralization: An empirical study for federal developing countries. SAGE Open, 10(4), 2158244020968088. Huynh, C. M., & Tran, H. N. (2021). Moderating effects of corruption and informality on the fiscal decentralization—Economic growth nexus: Insights from OECD countries. Annals of Public and Cooperative Economics, 92(2), 355–373. Jin, Y., Ling, L., Peng, H., & Song, P. (2013). Fiscal decentralization and horizontal fiscal inequality in China: New evidence from metropolitan areas. Chinese Economy, 46(3), 6–22.

2 Two Decades of Fiscal Decentralization and Regional Economic …

37

Lin, J. Y., & Liu, Z. (2000). Fiscal decentralization and economic growth in China. Economic Development and Cultural Change, 49(1), 1–21. Ma, G., & Mao, J. (2018). Fiscal decentralisation and local economic growth: Evidence from a fiscal reform in China. Fiscal Studies, 39(1), 159–187. Mankiw, N., Romer, D., & Weil, D. (1992). A contribution to the empirics of economic growth. Quarterly Journal of Economics, 107(2), 407–437. Maliˇcká, L., Šuliková, V., & Šoltés, M. (2017). Relationship between fiscal decentralization and ˇ economic growth in European Union countries and Slovakia. Ekonomický Casopis, 65(9), 856– 875. Martinez-Vazquez, J., & McNab, R. M. (2003). Fiscal decentralization and economic growth. World Development, 31(9), 1597–1616. Montinola, G., Qian, Y., & Weingast, B. R. (1995). Federalism, Chinese style: The political basis for economic success in China. World Politics, 48(1), 50–81. Neyapti, B. (2004). Fiscal decentralization, central bank independence and inflation: A panel investigation. Economics Letters, 82(2), 227–230. Oates, W. E. (1999). An essay on fiscal federalism. Journal of Economic Literature, 37(3), 1120– 1149. Prudhomme, R. (1995). The dangers of decentralization. World Bank Research Observer, 10, 201– 220. Qian, Y., & Weingast, B. R. (1997). Federalism as a commitment to reserving market incentives. Journal of Economic Perspectives, 11(4), 83–92. Qiao, B., Martinez-Vazquez, J., & Xu, Y. (2008). The tradeoff between growth and equity in decentralization policy: China’s experience. Journal of Development Economics, 86(1), 112–128. Rodden, J., & Wibbels, E. (2010). Fiscal decentralization and the business cycle: An empirical study of seven federations. Economics & Politics, 22(1), 37–67. Sasana, H. (2019). Fiscal decentralization and regional economic growth. Economics Development Analysis Journal, 8(1), 108–119. Scott, Z. (2009). Decentralization, local development and social cohesion: An analytical review. GSDRC Research Paper, 5, 1–22. Slavinskait˙e, N. (2017). Fiscal decentralization and economic growth in selected European countries. Journal of Business Economics and Management, 18(4), 745–757. Song, J., Geng, L., Fahad, S., & Liu, L. (2022). Fiscal decentralization and economic growth revisited: An empirical analysis of poverty governance. Environmental Science and Pollution Research, 29(19), 28020–28030. Tang, W. (2021). Decentralization and development of small cites: Evidence from county-to-city upgrading in China. China Economic Quarterly International, 1(3), 191–207. Thanh, S. D., & Canh, N. P. (2020). Fiscal decentralization and economic growth of Vietnamese provinces: The role of local public governance. Annals of Public and Cooperative Economics, 91(1), 119–149. Thiessen, U. (2003). Fiscal decentralization and economic growth in high income OECD countries. Fiscal Studies, 24(3), 237–274. Tiebout, C. M. (1956). A pure theory of local expenditures. Journal of Political Economy, 64(5), 416–424. Xie, D., Zou, H., & Davoodi, H. (1999). Fiscal decentralization and economic growth in the United States. Journal of Urban Economics, 45(2), 228–239.

Chapter 3

Regional Financial Development and Economic Growth in China: A Study of Guangdong–Hong Kong–Macao Greater Bay Area Yuhao Luo and Bhabani Shankar Nayak Abstract The construction of the Guangdong–Hong Kong–Macao Greater Bay Area has become one of China’s key development strategies, and it is particularly important to explore the relationship between financial development and economic growth in this region. This chapter analyses the economic status and financial development level of the Greater Bay Area. The research shows that the economic growth in the Greater Bay Area has no significant driving effect on financial development. The improvement of the level of financial development and the reorganization of the financial system have promoted the long-term impact of economic growth in the Greater Bay Area.

Introduction The construction of urban cluster economic bay area has been the focus of scholars around the world in the field of economic development. Studies show that about twothirds of the value of global economic activity comes from coastal economies. Therefore, the efficient and high-quality approaches to promote economic development is to construct the economic bay area made up of urban clusters. This chapter is based on the concept and measurement of economic growth and financial development proposed by previous literature, trying to find out the relationship between them in the Guangdong–Hong Kong–Macao Greater Bay Area. In this chapter, financial development is defined as a process in which the expansion of financial institutions and the change of financial structure improve the quality and efficiency of financial intermediary services. For economic growth, this paper uses per capita GDP to measure economic growth considering the impact of population. Y. Luo Adam Smith Business School, University of Glasgow, Glasgow, Scotland, UK B. S. Nayak (B) Business School for the Creative Industries, University for the Creative Arts, 21 Ashley Rd, Epsom KT18 5BE, UK e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 B. S. Nayak (ed.), China: The Great Transition, https://doi.org/10.1007/978-981-99-0051-0_3

39

40

Y. Luo and B. S. Nayak

There have been a large number of studies on economic and financial issues, but the results are not consistent, because the relationship between the two are different due to the economic situation and financial system in different regions. Three perspectives are considered to measure the financial development: financial development scale, intermediary efficiency and financial structure are used as measurement indicators to comprehensively measure the level of financial development in the Greater Bay Area, avoiding errors caused by single dimension indicators, which contributes to exploration of the impact of financial development on economic growth from multiple angles. The bay area is a new form of mega-city which promised to stimulate economic growth and technological innovation. Tokyo bay, San Francisco bay and New York City bay are known as the bay areas with the most economic aggregate and efficiency and in the world. In recent years, China has been constructing the fourth world-wide largest bay area in the Guangdong–Hong Kong–Macao Greater Bay Area (hereafter referred as Greater Bay Area). As the largest city cluster in China, the Greater Bay Area has the highest productivity, which is reflected in the fact that less than 1% of the national population creates more than 12% of the national GDP. Therefore, construction of the Greater Bay Area is a significant part in economic development of China. Worldwide popular and well-developed bay areas have successful development experiences. They attract talents, capital and enterprises from all over the world, and have been formed in a advanced development pattern of modern service industry as the leading factor, complementary multi-core industrial structures and diversity in industries. Advanced comprehensive financial service industry plays the key role of urban industrial development in worldwide bay areas and core city of these bay areas has gradually developed into international financial centers. These regions have formed a “financial plus” integrated service system and development pattern, such as the San Francisco Bay Area which are characterized by “financial plus technology”, formed the unique model of economic development. Given the experience from other bay areas, financial services should be essential part in the development planning of the Greater Bay Area. Finance services industry is driving force for economic development. It contributes to efficiency of capital allocation and maximum utilization of limited resources. Mature financial service industries can always be found in developed economic regions, which shows that financial service and economic development have been bound up with each other. Therefore, researching on financial scale, efficiency and structure problem in Greater Bay Area helps to understand the relationship between regional financial development and economic growth, promoting the development of economics and financial system in the Greater Bay Area. Although there are many studies on the relationship between financial and economic by scholars around the world, there are still insufficient researches on the newly formed Greater Bay Area.

3 Regional Financial Development and Economic Growth in China …

41

Financial Development and Economic Growth Since the twentieth century, the relationship between financial development and economic growth has been a hot research topic for scholars all over the world. The fruitful research results provide valuable experience for the follow-up research. Scholars have different views and opinions on the relationship between financial development and economic growth: some agree that finance promotes economy, some believe that there is no interaction between the two, while the other believe that financial development inhibits economic growth. Ammer et al. (2010) empirically analyzed panel data of the US and found that financial development has a positive impact on economic growth. Scholars like S. Ansart and V. Monvoisin (2017) have gained the same conclusion. Chinese scholar Zhou Li and Wang Ziming (2017) examined 23 years (1978–2000) panel data of different regions in China and use regression analysis method to explore the relationship between finance and economy in China. The research result shows that financial development strongly correlated with economic growth. He believes that promoting the development of financial industry contributes to the sustainable development of economy. Kuang Feihua (2007) analyzed and studied the relationship between financial development and economic growth in Guangdong by constructing a vector autoregressive model and proved that financial development significantly promote economy. M. Ibrahim and P. Alagidede (2018) used 34 years (1980–2014) panel data from 29 sub-Saharan African countries and found that while finance development promotes economic growth, it also increases risk and inflation. Huang and Lu (2021) collected and empirically analyzed the panel data of Jiangsu province in 30 years (1980–2010), and obtained the result that financial development in Jiangsu province significantly promoted the total economic growth in a long-term equilibrium. Moreover, detailed researches on finance were carried out by some scholars to study the relationship between finance and economy. Through empirical research, Bencivenga and Smith (1991) believed that financial intermediation can generally reduce the unnecessary capital mobility of society and thus promote economic growth. Levine and Zervos (1998) investigated and obtained panel data of 47 countries for 43 years (1976–1933), and reached relevant conclusions that confirmed the positive correlation between long-term economic growth and stock market development and bank development. Tan Ruyong (2000) empirically study capital market, financial intermediary and economic growth in China. His research result shows that the development of financial intermediary plays an obvious positive role in promoting economic growth in China, but he did not specify the relationship between development of stock market and economic growth. Rousseau and Wachtel (2000) made up for the research on how stock market affect economic growth. They use vector auto-regressive model to empirically analyze panel data of 47 countries from 1960 to 2001, and drew a conclusion that financial deepening is beneficial to the economic growth of a region. They also emphasized that development of traditional financial

42

Y. Luo and B. S. Nayak

intermediary and liquidity of stock market are important to the growth. C. Shen and C. Lee (2006) analyze how financial development affect real GDP per capita and discovered that stock market development promote economic growth, while banking industry and growth presents an inverse U-shape relationship. Jokipii and Monnin (2013) adopted panel data of 18 OECD countries and use VAR model to verify the relationship between the stability of the banking sector and the growth of the real economy. They concluded that there was indeed a positive correlation between the two, and that the instability of the banking sector would significantly affect the stability of the real economy. Bezemer et al. (2014) obtained and analyze panel data from 46 economics over a period of 21 years (1990–2011), demonstrating that expansion of financial market scale led to the development of credit flows system, which promoted economic growth. Bose and Kumar (2016) argue that the healthy development of the stock market is an important factor of economic growth, and financial development has a significant role in promoting economic growth.

Financial Development and Economic Growth Valickova et al. (2013) do not agree that financial development always contributes to economic growth by examining 67 studies and 1334 estimates about the relationship between finance and economy. They believe that only when financial development is matched with economy can it drive economic growth, otherwise the complexity of financial system may lead to financial crisis. Rioja and Valev (2004) examined a panel of 74 countries and found that the stimulating effect of financial development on economic growth may be varies with regard to the level of financial development of the country. Financial development can raise productivity in rich countries, while it can only promote economic growth by increasing capital accumulation in developing countries. C. Cheng et al. (2021) applied GMM method to analyze panel data of 72 counties from 2000 to 2015 and discovered that financial development does not contribute to economic growth in both developed and developing countries and the financial development even inhibit growth more significantly in high-income countries.

Economic Growth Contributes to Financial Development Ang and Mckibbin (2007) examined the time series data of Malaysia from 1960 to 2001 and found that although financial deepening promotes economy in the short term, output growth positively and unidirectionally affect financial development in a long period. Arestis and Demetriades (1997) also agree with this viewpoint. Yi Chen (2009) using data about economy and capital market in China over 15 years (1993–2007) and analyze the relationship between the two. The empirical evidence

3 Regional Financial Development and Economic Growth in China …

43

indicate that development of financial market do not have benefits to output growth in the short period, but macro-economic growth facilitates capital market to mature.

No Positive Impact of Financial Development on Economic Growth On the other hand, some scholars do not believe the existence of interaction between financial development and economic growth, and some even argue there is an inhibitory effect between the two. Data of nearly 100 countries in 15 years (1965– 1980) were used as research samples by Roubini and Martin (1992) to prove that there is a verifiable negative correlation between financial development and economic growth. K. Menyah et al. (2014) examine the panel data of 21 African countries and apply the panel bootstrapped approach to the Granger causality. They analyzed the relationship between financial development and economic growth and found that financial development did not significantly affect the growth. Li Ming (2017) made a quantitative analysis of the relationship between financial development and economic growth in Shandong Province, China, and found that there is no significant interaction between them.

Dual Causality Between Financial Development and Economic Growth However, some scholars do not believe that there is only a simple causal relationship between financial development and economic development. The study of Greenwood and Jovanovic (1990) made a conclusion that financial intermediation could create higher rates of return on capital, promoting investment and economic growth, while financial institutions would achieve scale expansion due to the growth, which results in a two-way relationship between financial intermediation and economic growth. Calderon and Lin Liu (2003) used the data of 109 countries and developed countries from 1960 to 1994 to build a vector autoregression model and Geweke causal decomposition test to analyze the causal relationship between financial development and economic growth. Through empirical research, result indicates that financial development and economic growth have bidirectional Granger causality. By examining panel data of 71 developed and developing countries over 44 years (1960–2004), C. Bangake and J. C. Eggoh (2011) also confirm the results of bidirectional Granger causality between the two. However, when considering the short-term causality, the financial development of low- and middle-income countries will not significantly stimulate economic growth in the short term, while the financial development of high-income countries will have a positive impact on economic growth.

44

Y. Luo and B. S. Nayak

Complex Relationship Between Financial Development and Economic Growth Finally, some scholars found that financial development does not always have a positive effect on economic growth, when financial development exceeds a certain threshold, it will not significantly promote economic growth. Fry (1997) collected and sorted out the panel data of 16 developing countries from 1970 to 1988, constructed a regression model for testing and analysis, and found the inverted U-shaped relationship between financial liberalization and economic growth. The same result was obtained by N. Samargandi et al. (2014). The panel threshold model was used by Xie Meilin (2018) to analyze the relationship between financial development and economic growth in China, she found that there was an inverted S-shape nonlinear relationship between them. Financial development promotes economic growth only when it falls between two specific thresholds, otherwise, it would have an inhibit effect. However, Sun and Zhang (2021) reached an almost opposite conclusion in their empirical study. They analyzed the inter-provincial panel data of China from 2011 to 2018 and found that the impact of financial development on economic growth presents a “U-shaped” relationship. When the level of financial development is low, financial repression will occur, hindering economic growth. With the continuous improvement of financial development level, financial development plays a role in promoting economic growth.

Theories of Financial Development Since the middle of the twentieth century, the theoretical research on financial development has become a hot topic of discussion among scholars around the world. From the financial structure theory by Goldsmith (1969) and the financial deepening theory by McKinnon and Shaw (1973) to the finance functional perspective by Merton and Bodie (1995), the research content has changed from solving the problem how developing countries can escape the economic growth trap through financial deepening, to solving the problem how to use financial function to accumulate capital and promote technological progress, so as to realize the purpose of facilitating economic growth. In essence, the theory of financial development is a study of what role the financial system plays in economic activities and what role it plays in influencing economic growth. The theory of financial structure was proposed by the economist Raymond W. Goldsmith (1969). In this book, Goldsmith explained all existing financial phenomena from three perspectives: financial instruments, financial institutions and financial structures. His theory of financial structure argues that the growth and development of financial system can be explained as the change of financial structure. Therefore, study the problem of financial development can be transformed into the

3 Regional Financial Development and Economic Growth in China …

45

study of how the financial structure changes, and in-depth study of a country’s financial structure can make a thorough understanding of the its financial development. This theory has a profound influence on the future research of financial development. In his book, Goldsmith compared and analysed the data of 35 countries over a hundred years, constructed a system to measure the financial development of a country, and put forward a very influential concept: Financial correlation ratio (FIR) which refers to the ratio of total financial value to total economic value in the same period. In his research, financial correlation ratio has a positive relationship with economic growth. Goldsmith proposed the theory of financial structure and pioneered the use of empirical methods to study the relationship between finance and economy, which has exerted a great influence on the theoretical study of financial development by later scholars and provided a theoretical reference for subsequent related studies. After the 1990s, the research on financial development mainly focuses on the study of which components of the financial system are the optimal financial structure. However, in the face of different economic and cultural environments in different regions, scholars from all over the world believe that only the financial structure that maximizes the region’s economic growth is the optimal financial structure for the region. Therefore, there are different viewpoints in the financial structure theory, and they can be divided into four main views: the bank-led financial structure theory, the market-led financial structure theory, the law-led financial structure theory and the financial service theory. The proponent of bank-dominated financial structure theory is Levine (1997, 2002). He believes that when banks occupy a dominant position in the financial system, they can more effectively raise savings, allocate capital and manage risks, which better promote economic growth. The promoters of the market-led theory are Greenwood and Smith (1997) and Allen and Gale (1999), who argue that the market is more willing than banks to provide financial support for high-risk innovation projects of enterprises, which can promote technical innovation and economic growth. Moreover, the information in mature markets is more transparent, which is conducive to the supervision of enterprises and the reduction of management risks. Western scholars generally believe that law plays a key role in the financial system, and different national laws will form different financial structures. LaPorta et al. study found that a country with sound financial regulations and strong contractual binding force has a more mature capital market; otherwise, the banks are more dominant. However, the research result of scholar Allen (2002) show that good legal constraints cannot promote the growth of enterprises, which is diametrically opposed to the law-led theory. He divided Chinese companies into two categories, one is Chinese government-controlled companies and exchange-listed companies, and the other is other private companies. His found that the legal treatment of such other private enterprises is not perfect, and there are some ‘gray areas’ that cannot be restrained by the law. Interestingly, these non-compliant companies grow and expand faster, which shows that law does not affect economic growth. Scholar Levine (2004), supporting the theory of financial services, believes that it is not necessary to argue whether the financial system is dominated by banks or the market, but to evaluate the positive impact of financial development on economic growth by considering the

46

Y. Luo and B. S. Nayak

financial system as a whole. How to improve the financial service function to serve the economy is the core of the theory. This theory provides a new perspective for the study of financial structure, marking that the study of financial structure theory has entered a new stage. The idea of financial repression was first introduced by Stanford economists McKinnon and Shaw (1973). They believe that slow financial development would have a restraining effect on economic activities. Through research and analysis of economic and financial conditions in developing countries, they found that the main reason for the slow economic development in developing countries is that too many restrictions by the authorities on financial services industry, resulting in the phenomenon of financial repression. These restrictions are mainly embodied in strict controls on bank loan interest rates, reserve ratio and exchange rate by means of government policies and regulations, causing the situation of the financial system lack of energy. As a result, market capital is hard to integrated and resources would be difficult to be allocated reasonably and make full use of, finally resulting in restriction of economic development and phenomenon of financial repression. Mckinnon and Shaw argue that developing world governments use monetary policy to impose strict caps on lending and deposit interest rates and set extremely high bank reserve requirements. In the presence of inflation, such a monetary policy would keep real interest rates low for a long time. As a result, very low interest rates represent very low deposit rates, and people are reluctant to deposit their idle money in the bank. At the same time, banks are also unable to rely on loan income to maintain the daily operations because of low interest rates. Although the very low loan interest rate stimulates enterprise loan investment, it will cause that banks have no incentive to effectively allocate funds to investment projects with high rate of return, which also forms a vicious circle of insufficient resource utilization and slow economic growth. Shaw and McKinnon believe that the government inhibits the development of the financial system through excessive intervention in financial activities. Therefore, they proposed the implementation of financial liberalization or financial deepening in response to financial repression effects. They oppose the excessive interference of the governing authorities in the financial system, and suggest that the governments of developing countries should release the control of financial instruments, financial policies, interest and exchange rates, and let the market adjust the supply–demand relationship of funds by itself. They believe that deregulation of finance can gradually improve the mechanism of the financial market, optimize the allocation of market resources, and promote financial development and economic growth to form a virtuous cycle. King and Levin (1993) are major contributors to the functional financial theory. They studied the impact of financial development on economic growth from the perspective of financial system function. They took both low-income and highincome countries as research objects, and the research results showed that the development of financial intermediation and capital market both promoted capital accumulation, which stimulated economic growth. The theory of financial function is consist of traditional financial theory and financial functional perspective.

3 Regional Financial Development and Economic Growth in China …

47

Traditional financial theory, also known as the financial institutional perspective, which is based on the development of financial institutions to analyze the financial system. Traditional financial theories believe that there is stability in the daily operations of various financial departments or organizations, as well as in the regulatory provisions of financial regulatory agencies and financial-related laws. Therefore, when the financial system encounters problems, it should be solved in accordance with the corresponding regulatory provisions. Although solving problems would reduce the efficiency of financial services, it is considered worthwhile. However, the traditional financial theory has a defect, that is, when there are changes in economic environment and basic techniques used by the financial system, there will be a lag in the supervision and regulation on the changes in the financial sectors, greatly reducing the efficiency of the financial system. To remedy this deficiency, functional perspective was proposed by R. Merton and Z. Bodie (1995). This theory mainly focuses on the role of financial institutions in different economic environments. It believes that the powerful resource allocation function of the financial system itself can remain stable even under the influence of the passage of time and changes in region. Therefore, financial institutions allocate economic resources based on stable financial functions, and at the same time innovate and compete in the process of development, which can improve the efficiency of financial functions. The detailed analysis of the impact of financial institutions on the economy can be summarized into the following three core functions: Firstly, the financial system provides consumers or investors in different countries and regions with payment channels when purchasing goods, services and assets, which is fast and convenient settlement method. Secondly, consumers or investors can improve the efficiency of managing financial assets and reduce investment risks through financial intermediaries and various types of financial instruments. Thirdly, the financial system establishes a distribution channel between the resource provider and the demander, and at the same time allows the aggregated resources to be allocated in an effective and reasonable manner, so as to maximize the use of limited resources in the market.

Performance of Economic Growth of the Greater Bay Area The Greater Bay Area is located in southeast China coastal harbour, from Hong Kong, Macao, and pan-pearl river delta nine cities to form. The economic aggregate of this region ranks the first in China, with a high concentration of talents, advanced science and technology, developed manufacturing industry and highly developed internationalization. As all indicators are on a national scale in a leading position, it became the key part in a country’s long-term development strategy. This chapter mainly uses the economic development data of the 11 cities mentioned above to analyze the economic development of the Guangdong–Hong Kong–Macao Greater Bay Area urban agglomeration from three aspects: economic aggregate and growth, industrial distribution and fixed asset investment.

48

Y. Luo and B. S. Nayak

Together with Tokyo, San Francisco and New York Bay Areas, the Guangdong– Hong Kong–Macao Greater Bay Area is one of the four largest economic bay areas in the world. Due to its large economic volume, high efficiency of economic activities, the concentration of professional talents and its unique geographical environment, it has become the choice for the construction of the Greater Bay Area in China. The total area of the Greater Bay Area is 55,901 square kilometres, and the permanent population of the Greater Bay Area has reached 70 million by the end of 2020. As shown in the Fig. 3.1, the GDP of the Greater Bay Area has grown rapidly over years, increasing by RMB 7816 billion over 17 years from 2309 billion in 2000 to 10,125 billion in 2017. Although the GDP growth rate slowed down under the influence of the financial crisis in 2008, the compound annual growth rate exceeded 9%, and the highest year-on-year growth rate reached 14% in 2010. In 2020, the GDP of the Greater Bay Area reached RMB 11.5955 trillion, accounting for 14.3% of the national total. As shown in Fig. 3.2, Shenzhen RMB 2767 billion, Guangzhou RMB 2501.9 billion and Hong Kong RMB 2297.2 billion are the first tier of urban agglomeration. Foshan RMB 1081.7 billion and Dongguan RMB 965 billion are the second tier; Huizhou RMB 422 billion, Zhuhai RMB 348 billion, Macao RMB 346 billion, Jiangmen RMB 320.2 billion, Zhongshan RMB 315.1 billion, Zhaoqing RMB 231.3 billion are the third tier. Compared to the world’s three largest bay area, with New York City and Tokyo as ‘a single core’ city drive bay area economy development characteristics, and the San Francisco Bay Area of the ‘two core cities’ lead the development of the regional characteristics, the Greater Bay Area is characterized by the development of a “multi-polar differentiation” and the “equalization”. As shown in Fig. 3.2, there 12000

16.00% 14.00%

10000

12.00% 8000

10.00%

6000

8.00% 6.00%

4000

4.00% 2000

2.00% 0.00%

0

GDP(

billion)

Growth Rate

Fig. 3.1 Total GDP and growth rate of the Greater Bay Area from 2000 to 2017 (Data source China’s Bureau of Statistics)

3 Regional Financial Development and Economic Growth in China … 3000 2500

49 7.00%

2767 2502 5.90%

6.00% 2297

5.00% 4.00%

2000 1500

2.80% 3.00%

3.00%

2.80%

2.20%

1.80% 0.60% 1082

1000

1.10%

1.00%

965

0.00% 422

500

2.00% 1.50%

-1.00%

-2.00% 348

346

-3.00%

320

315

231

-2.00% -3.00% -4.00%

0

GDP(billion)

Growth Rate

Fig. 3.2 Total GDP and growth rate of 11 cities in the Greater Bay Area in 2020 (Data source China’s Bureau of Statistics)

are significant differences in GDP among the three levels of the Greater Bay Area urban agglomeration. Among them, the backbone of the development of the Greater Bay Area are Guangzhou, Shenzhen and Hong Kong, accounting for 23.86%, 21.58% and 19.81% of the GDP of the Greater Bay Area urban agglomeration, which far exceeds the GDP of other cities. At the same time, the gap between the three cities is not large, highlighting the balance. In recent years, the industrial structure of the Guangdong–Hong Kong–Macao Greater Bay Area has been gradually improved, and some industries are in the stage of transformation and upgrading. In order to promote the construction of the Greater Bay Area, the successful experience from the other three largest bay area is worth learning from. Generally, successful economic development of a bay area usually starts from the port economy and industrial economy. After the stable development of the port and industrial system, the service economy will gradually form a scale. Then the innovative economy formed by high-tech industry will emerge and finally achieve the goal of comprehensively enhancing economic vitality. At present, the Greater Bay Area is transforming from a service economy to an innovative economy. Local departments should increase their support to the service industry, such as attaching great importance to technological innovation and talent cultivation and giving policy support to high-tech enterprises to promote the construction of innovative industries in the Greater Bay Area. From the analysis of the industrial structure of the Greater Bay Area, it can be seen that the service economy occupies a major part in the industrial structure, and the economic value created by it accounts for about two-thirds of the total value. As shown in Fig. 3.3, the three industries of the Greater Bay Area present an obvious

50 70.00%

Y. Luo and B. S. Nayak 62.70%

63.63%

63.89%

63.71%

64.33%

65.43%

66.07%

35.79%

34.89%

34.71%

34.91%

34.32%

33.23%

32.72%

1.51%

1.48%

1.40%

1.38%

1.35%

1.34%

1.21%

2011

2012

2013

2014

2015

2016

2017

60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% primary industry

secondary industry

tertiary industry

Fig. 3.3 Industry structure of the Greater Bay Area in 2017 (Data source China’s Bureau of Statistics)

structure of type ‘tertiary-secondary-primary’. The proportion of the service industry keeps rising, while the primary and secondary industry gradually decline. It can be predicted that the Greater Bay Area will put the tertiary industry in an absolute leading position in the future economy (refer to the development model of other bay areas), and develop towards an innovative economic model when the tertiary industry is highly developed. From the comparison of data between cities in Fig. 3.4, the service industry of Hong Kong and Macao is in an absolute leading position in economic activities. Guangzhou and Shenzhen take the service industry as the main pillar industry, but the primary and secondary industries also play an important role; Dongguan’s tertiary and secondary industries have a balanced development; Huizhou, Foshan, Zhongshan, Zhuhai and Zhaoqing’s economic model is given priority to secondary industry and the tertiary industry is slightly weaker. This situation is determined by the industrial positioning of cities in the Greater Bay Area: Hong Kong is a financial center, Shenzhen leads the country in scientific and technological research and development, Guangzhou has developed business and trade, and other cities mainly develop manufacturing industry. According to data of manufacturing industry distribution, the Greater Bay Area industrial manufacturing is upgrading and reform. As the Table 3.1 shown, the overall scale of high-tech manufacturing in four inland cities of the Greater Bay Area, Huizhou, Dongguan, Shenzhen, Zhuhai, expands rapidly in recent years through continuous investment, construction and development. Especially in Shenzhen and Dongguan, capital is increasingly focusing on high-tech industry. The scale of hightech industry in these two cities has been higher than other inland cities in the Greater Bay Area for a long time, with an increase rate of 10.9% and 16.6% respectively. According to the data in 2018, Shenzhen pays the most attention to the development

3 Regional Financial Development and Economic Growth in China …

51

100% 90% 36.4%

80% 57.4%

70% 60% 50%

92.7%

38.7% 52.1%

47.4%

42.8%

42.3%

65.2%

89.1%

40%

50.1% 56.6%

61.8%

30% 42.6%

20% 10% 0%

35.3%

6.3% 1.0%

9.8% 1.1%

0.0%

50.3%

47.5%

49.1%

55.3%

33.5% 1.3%

1.8%

Primary industry

0.4%

4.7%

Secondary industry

2.3%

8.1%

14.6% 2.4%

Tertiary industry

Fig. 3.4 The proportion of three industries in GDP of the Greater Bay Area cities in 2017 (Data source China’s Bureau of Statistics)

of high-tech manufacturing industry, with the output value of high-tech industry in the city accounting for more than two-thirds of the total industry, followed by Dongguan, Huizhou and Zhuhai, with the ratio reaching 40.4%, 38.9% and 29.3% respectively. According to Table 3.2, through Industry segmentation, the knowledge-andtechnology-intensive industrial system represented by Shenzhen, Dongguan and Table 3.1 Proportion of high-tech manufacturing added value in industrial added value of inland cities in the Greater Bay Area

Cities

Proportion in 2011 (%)

Proportion in 2018 (%)

Guangzhou

11.0

13.4

2.4

Shenzhen

56.8

67.3

10.5

5.8

8.1

2.3

Dongguan

28.9

38.9

10.0

Huizhou

36.1

40.4

4.3

Zhuhai

24.6

29.3

4.7 3.7

Foshan

Jiangmen

Growth (%)

5.6

9.3

Zhongshan

13.1

18.3

5.2

Zhaoqing

10.4

8.4

−2.0

Data source China’s Bureau of Statistics

52

Y. Luo and B. S. Nayak

Table 3.2 Distribution of main industries in inland cities of the Greater Bay Area Cities

Main industry

Guangzhou

Automobile manufacturing, electronics, information, petrochemicals

Shenzhen

Electronic information, software, new energy, new materials

Foshan

Textile clothing, food processing, furniture home appliances, building materials

Dongguan

Metal products, General and special equipment manufacturing

Huizhou

Electronic information, petrochemical industry

Zhuhai

Electronic information, biomedical machinery, manufacturing petrochemical, electricity energy

Jiangmen

Papermaking, equipment manufacturing

Zhongshan

Household appliances, Hardware

Zhaoqing

Food processing, chemical industry

Data source China’s Bureau of Statistics

Huizhou on the east bank of the Pearl River is gradually forming industrial clusters dominated by service and technology-driven industries such as finance, electronic information technology, bio-medicine, new materials and cultural innovation. Economic development model on pearl river west bank is mainly based on high and new technology industry which are concentrated in four cities Foshan, Zhongshan, Zhuhai and Jiangmen. However, it is undergoing industrial structure transformation, gradually building a modern industrial system, forming an industrial development model with information technology, new materials, new energy, medicine, biotechnology and other high-tech and advanced equipment manufacturing as the main economic driving force. Zhaoqing has a relatively weak industrial base, with food and chemical industries as the main industries, and is in urgent need of introducing technology-driven industries, such as new energy, materials, electronic technology and other industries. Compared with the fixed asset investment in Guangdong province, the fixed asset investment in the nine inland cities of the Greater Bay Area accounts for 73.15% of the total fixed asset investment in Guangdong province, with both of them rising steadily while the former has a larger growth rate. In 2019, the scale of fixed asset investment in inland cities of the Greater Bay Area reached RMB 2.87 trillion, a further increase compared with 2018, with an increase of RMB 315 billion, or 12.3%, over the previous year. By comparing the specific fixed asset investment of nine inland cities in The Greater Bay Area, it can be seen that the fixed asset investment is mainly concentrated in Guangzhou and Shenzhen, the two core cities, and the investment of these two cities accounts for nearly 50% of the total investment of inland cities in the Greater Bay Area. Compared with the data of recent five years, Shenzhen is the most likely place for fixed assets investment among inland cities in the Greater Bay Area, with an increase of RMB 405.731 billion in the five years, significantly exceeding the investment in other inland cities in the Greater Bay Area. In 2018, the investment in fixed assets

3 Regional Financial Development and Economic Growth in China …

53

in Shenzhen was about RMB 735.6 billion, surpassing Guangzhou for the first time and ranking first among the nine inland cities in the Greater Bay Area, accounting for more than a quarter of the total investment in 9 cities, reaching 25.6%. The fixed asset investment of Guangzhou is about RMB 692 billion, RMB 43.6 billion less than Shenzhen’s investment, accounting for 24.1% of the nine inland cities’ fixed asset investment. In terms of economic performance, the economic aggregate of the Greater Bay Area not only ranks the first in China, but also maintains a rapid growth in recent years. The total GDP of the three core cities, Guangzhou, Shenzhen and Hong Kong, account for nearly two-thirds of the total output value of the Greater Bay Area, which has formed the characteristics of “multi-polar differentiation” and “balanced” economic structure of the Greater Bay Area. From the perspective of industry distribution, the economy of the Greater Bay Area is dominated by the tertiary industry, which contributes nearly two-thirds of the total economic output value, and this value is still increasing year by year, while the proportion of the primary and secondary industries is gradually declining. The Greater Bay Area is undergoing industrial upgrading and reform, which is in the stage of transforming from the service economy to the innovation economy. Moreover, The industrial distribution of the Greater Bay Area is distinct. Hong Kong attaches importance to the financial industry; Shenzhen gives priority to the development of science and technology; Guangzhou is a paradise for trade; and other cities mainly develop manufacturing. With respect to fixed investment, inland cities in the Greater Bay Area have a highly centralized investment in fixed assets with a large amount and a fast growth rate. In 2019, the scale of fixed asset investment in inland cities in the Greater Bay Area reached RMB 2.87 trillion, up 12.3% year on year, highly concentrated in the two core cities of Guangzhou and Shenzhen, accounting for more than half of the total investment.

Financial Development of the Greater Bay Area Compared with western developed countries, China’s financial industry started late. The banking industry is in a dominant position in China’s financial market, while other sub industries such as securities and insurance are still in the initial stage of development. This chapter will first briefly explain the overall performance of the financial industry from the output value, employment population and number of institutions of the financial industry in the Greater Bay Area, and then specifically analyze the three major financial sub industries of banking, insurance and securities. The overall financial performance of the Greater Bay Area is introduced from three aspects, namely, the total output value of the financial industry, the number of financial employees and the number and scale of financial institutions. According to the statistical data of cities in the Greater Bay Area in recent years, the GDP of the financial industry reached RMB 1.04 trillion in 2017, while the GDP

54

Y. Luo and B. S. Nayak

of the financial industry was only RMB 19.373 billion in 2000 and RMB 461.607 billion in 2010. It can be seen that the overall size of the financial industry in the Greater Bay Area showed a rapid upward trend. In 2017, the GDP contribution rate of the financial industry in the Greater Bay Area reached 10.27%, and the financial industry has become a key part in the economic development of the Greater Bay Area. Hong Kong, Shenzhen and Guangzhou, the three core cities of the Greater Bay Area, are in the list of global financial center cities ranked by The Global Financial Centers Index (GFCI), jointly compiled by UK think tank Z/Yen Group and China (Shenzhen) Comprehensive Development Institute. In 2017, nearly 88% of the total output value of the financial industry in the Greater Bay Area came from Hong Kong, Guangzhou and Shenzhen, which shows that the financial industry in the Greater Bay Area is highly concentrated. The financial industry in Hong Kong, one of the three financial centers in the world, is the most mature in the development of the financial industry. The financial industry plays an extremely important role in Hong Kong’s economic system. In 2017, 38.3% of the total output value of the financial industry in the Greater Bay Area came from Hong Kong’s financial service industry, which reached RMB 398.32 billion. The added value of the financial industry in Guangzhou and Shenzhen both exceeded RMB 200 billion. Compared with the three core cities, the financial industry of other cities in the Greater Bay Area is still in its infancy. The output value of the financial industry represented by Dongguan, Foshan and Macao is close to RMB 50 billion, while the financial industry of the remaining five cities develops slowly with the total value of the financial industry less than RMB 30 billion. By the end of 2017, the total number of financial sector employees in the Greater Bay Area was 650,000, accounting for only 1.50% of the total employment, mainly concentrated in the three core cities of Hong Kong, Shenzhen and Guangzhou. Hong Kong is a world-class financial center with a highly developed financial industry. The number of financial employment in the city has reached 227,200, accounting for 7.5% of the total number of local employment and 34.95% of the total number of financial employment in the Greater Bay Area. The number of financial employment in Hong Kong alone is close to the total number of financial employment in the two core cities of Guangzhou and Shenzhen with the number 117,000 and 110,500 only accounting for 18%, 17% of the total employment in the Greater Bay Area. By the end of 2017, the total number of financial institutions in the Greater Bay Area was about 14,000. Hong Kong had the largest number of financial institutions (2891), accounting for 20.46% of the total number of financial institutions in the Greater Bay Area, followed by Guangzhou (2719), Shenzhen (1738), Foshan (1859) and Dongguan (1377). The balance of domestic and foreign currency deposits of financial institutions in the Greater Bay Area was about RMB 47.83 trillion, mainly concentrated in the three core cities of Hong Kong, Guangzhou and Shenzhen, which accounted for 82.10% of the total balance of deposits in the Greater Bay Area. Among them, the balance of domestic and foreign currency deposits of financial institutions in Hong Kong was about RMB 19.12 trillion, followed by Guangzhou RMB 8.55 trillion and Shenzhen RMB 11.60 trillion. By the end of 2016, there are 193 banking institutions in Hong Kong, among which 152 are licensed banks, 23 with restricted licenses and 18 deposit-taking companies.

3 Regional Financial Development and Economic Growth in China …

55

These 193 banking institutions operate more than 1289 local branches and 60 local representative offices of foreign banks, forming a huge business network. The total annual revenue of banking business and other income was RMB 377.639 billion, and the added value of the industry was RMB 270.2 billion. By the end of 2017, there are 29 banks in Macao with 210 head offices, branches and sub-branches, and the added value of the industry was 21.675 billion. There are 97 banking institutions in Guangzhou, including 8 representative offices, with total assets of RMB 6.41 trillion and annual profits of RMB 71.59 billion. The number of head offices and branches of banks in Shenzhen reached 2008, the total amount of financial assets reached RMB 8.38 trillion, and the annual profit reached RMB 114.635 billion. Total banking assets in the Guangdong–Hong Kong–Macao Greater Bay region was about RMB 45 trillion. By the end of 2016, there were 2638 insurance institutions in Hong Kong, and their business income and other income reached RMB 513.148 billion. In 2017, the original premium income of insurance institutions in Hong Kong reached RMB 489.172 billion, accounting for 55.46% of the premium income of the Greater Bay Area. At the end of 2016, the number of insurance companies in Macao increased to 23, with the original premium income of RMB 21.922 billion, accounting for only 2.49% of the premium income of the Greater Bay Area. In the same year, the number of legal person insurance institutions in Shenzhen increased to 25 with a total asset of RMB 3.61 trillion, and 72 insurance branches and various insurance operating institutions with a total asset of RMB 285.09 billion. In 2017, the annual original premium income of insurance institutions in Shenzhen was RMB 102.975 billion, accounting for 11.67% of the total premium income of the Greater Bay Area. In the same year, the number of insurance institutions in Guangzhou was 101, and the annual premium income was RMB 117.26 billion, accounting for 12.78% of the total premium income of the Greater Bay Area. In 2017, the insurance premium income of the Greater Bay Area was about RMB 840.4 billion, accounting for one quarter of the country’s total premium income. By the end of 2018, the number of listed companies on the Hong Kong Stock Exchange had reached 2315, 207 more than the previous year, and the market value of all listed companies had reached HK$ 29.91 trillion. Nearly half of the listed companies, with the number of 1146, came from the Mainland China, accounting for 67% of the total market value. Total turnover of the Hong Kong stock market for the year was HK$ 26.43 trillion, year-on-year growth rate was 21.71%. By the end of 2018, there were 2134 listed companies in Shenzhen Stock Exchange, and the market value of all listed companies reached RMB 16.54 trillion. The number of securities companies in Shenzhen was 22, and the total assets reached RMB 1.46 trillion, ranking the second in China after Shanghai, but the operating income and profit ranked the first in China, with the figure reaching RMB 54.858 billion and RMB 18.685 billion respectively. By the end of 2018, there were more than 100 listed companies in Guangzhou, and the market value of all listed companies reached RMB 2.25 trillion. There were 3 securities companies, 316 branches of securities companies, 7 futures companies and 4 securities management companies in Guangzhou, and the annual cumulative securities trading volume reached RMB 12.23 trillion. There

56

Y. Luo and B. S. Nayak

is no stock exchange in Macao, and residents generally trade securities through two financial intermediaries operated by banks and licensed securities brokers in Hong Kong. At the end of 2017, the market value of securities investment held by Macao residents reached 662.884 billion patacas. In the past decade, the overall scale of the financial industry in the Greater Bay Area has increased rapidly, mainly concentrated in the three core cities of Hong Kong, Guangzhou and Shenzhen. As the financial center of the Greater Bay Area, Hong Kong ranks first in terms of financial output value, employment number and number of financial institutions, followed by Shenzhen and Guangzhou, while the financial industry of other cities is relatively slow, which resulted in a high degree of financial agglomeration in the Greater Bay Area. The banking industry in the Greater Bay Area has a large scale. Shenzhen has the largest number of head offices and branches of banks, while Hong Kong ranks first in terms of the banking assets under management. The insurance industry in the Greater Bay Area ranks first in China, and its premium income accounts for a quarter of the total premium income of the country. The insurance industry in the Greater Bay Area is mainly concentrated in Hong Kong. The number of insurance institutions in Hong Kong far exceeds that in other cities, and the premium income accounts for half of the total premium income in the Greater Bay Area. The securities industry in the Greater Bay Area is concentrated in Hong Kong and Shenzhen. Although listed companies prefer to list on the Hong Kong Stock Exchange, whose total market capitalisation exceeds that of Shenzhen Stock Exchange, Shenzhen’s securities institutions rank first in terms of assets, revenues and profits.

Financial Development and Economic Growth in the Greater Bay Area The construction of the Guangdong–Hong Kong–Macao Greater Bay Area has become one of the core goals of China’s long-term economic development plan in the future, and understanding the relationship between economic growth and financial development in the region has become a key part in the construction of the Greater Bay Area. By reading and learning previous scholars about the financial development and economic growth related theoretical basis and research results, this paper collects and processes related data and information of the Greater Bay Area, and current regional economic and financial development conditions are briefly summarized and analyzed. Economic data over 2000–2017 of the Greater Bay Area is selected for empirical analysis. Through a series of empirical analysis methods, this paper studies the relationship between economic growth and financial development in the Guangdong–Hong Kong–Macao Greater Bay Area, and draws the following conclusions. The Guangdong–Hong Kong–Macao Greater Bay Area urban agglomeration has significant regional advantages. The three core cities Guangzhou, Shenzhen and Hong Kong all have unique advantages, representing the most developed commerce center, technology center and finance center in China respectively. As the first region

3 Regional Financial Development and Economic Growth in China …

57

to implement reform and opening up, the economic aggregate of the Greater Bay Area ranks first in China. In 2020, the GDP of the Greater Bay Area is RMB 11,595.5 billion, accounting for 14.3% of the country. At the same time, the region is highly concentrated in talents, leading in science and technology, developed in manufacturing industry and highly internationalized. All indicators are in the leading position in the country, such as GDP, growth rate and efficiency. The Guangdong–Hong Kong–Macao Greater Bay Area has a particularly promising future. After being identified as a key national development strategic area, the Guangdong–Hong Kong–Macao Greater Bay Area is one of the core economic bay areas in the world, and will also be the largest urban cluster economic bay area with the strongest development potential in the world. The Guangdong–Hong Kong–Macao Greater Bay Area is undergoing transformation and upgrading of its economic model. Service economy is now the main driving force of the economic development pattern, but the focus on traditional manufacturing industry is shifting to high-tech manufacturing industry. The future development model of the Greater Bay Area has been determined to be an economic pattern driven by service economy and innovation economy. After the economic reform and systemic reform and the optimization of the industrial distribution, the Guangdong–Hong Kong–Macao Greater Bay Area learns economic development experience from three other core bay areas, Tokyo, New York and San Francisco Bay Area. In the near future, the Guangdong–Hong Kong–Macao Greater Bay Area will surpass the Yangtze River Delta and the Beijing-Tianjin-Hebei Economic zone to become China’s largest economic region. With the well-developed internationalization, large scale of economy and high efficiency, it is obvious that the Greater Bay Area will attract talents and professionals from all over the world, contributing to the development of the region. We believe that in the near future, the Guangdong–Hong Kong–Macao Greater Bay Area will become China’s business center, science and technology center and financial center. According to the successful development history of the three largest bay areas in the world, financial service has become one of the most important industries in the industrial chain of the bay area economic zone. The development path of the bay area economy shows that the financial service industry will develop together with the real industry to form the economic development pattern of “finance + ”. They respectively take the development system of “finance + technology” in the New York Bay Area, “finance + service” in the San Francisco Bay Area, and “finance + industry” in the Tokyo Bay Area as their unique characteristics. This shows that the financial industry has already become an indispensable part in the process of the construction and development in the bay areas. Based on the analysis and comparison of the industrial distribution and the financial service distribution structure of cities in the Greater Bay Area in recent years, it can be seen that the financial distribution is no longer highly concentrated in Hong Kong, but has gradually evolved into the financial distribution of three central cities in Hong Kong, Shenzhen and Guangzhou. Today, Hong Kong is still one of the international financial centers. Compared with other cities in the Greater Bay Area, Hong Kong has significant advantages in various financial subindustries, such as insurance and securities. With the advantages of stock exchange

58

Y. Luo and B. S. Nayak

and the special position in the country’s development strategy, Shenzhen has become the core area in the Greater Bay Area with a securities industry, second only to Hong Kong in scale. According to relevant development strategy documents, Guangzhou has set up a futures exchange and started building the financial zone in 2021, and the scale of futures trading and commercial banks in Guangzhou will be significantly improved, which is in line with the development planning objectives of the economic Bay Area, which has obvious promoting effect on the economic development and financial service efficiency of the Greater Bay Area.

Conclusions The analysis of the economic and financial indicators of the Guangdong–Hong Kong– Macao Greater Bay Area show that the economic growth has no significant impact on the promotion of the financial system. Although there is a weak impact in the long run, the impact has an obvious lag effect. On the other hand, the results of empirical analysis point out that the improvement of the two indicators of regional financial development scale and financial structure is helpful to promote the economic growth of the Greater Bay Area, while the indicator of financial intermediation efficiency does not have a significant driving effect on economic development. In general, economic development cannot promote the development of finance, while expanding the scale of finance and enhancing the dominant position of the banking industry to adjust the financial structure can support and promote the economic growth of the Greater Bay Area. It is clear that financial development is one of the important strategic goals of the development of the Greater Bay Area urban agglomeration, and financial development is an important factor to promote economic growth. The Guangdong–Hong Kong–Macao Greater Bay Area has become one of the regions with the largest economic scale and the fastest economic growth rate in China after experiencing the initiation, promotion and on-the-spot construction of the Party Central Committee and national leading institutions. Through empirical research and analysis, this paper puts forward the following suggestions for the development and construction of the Guangdong–Hong Kong–Macao Greater Bay Area. For the construction of the Greater Bay Area, the country should be on the policy support to promote the financial services industry development. Based on Hong Kong, Guangzhou and Shenzhen “one super and two strong” financial industry distribution pattern, government should vigorously develop the capital market and construct multi-level financial centers to promote the financial services industry development of other cities in the region. We also need to learn the successful experience from other three largest bay area, to improve the financial service structure and establish a development model featuring “finance + industry”, forming a virtuous cycle where Industrial development and financial demand facilitate mutually, which is of great strategic significance to the industrial upgrading of the Greater Bay Area today.

3 Regional Financial Development and Economic Growth in China …

59

It is important to push reform for the optimization of the financial system under the command of the state. A financial structure supported by diversified financial services should be formed, with the banking industry as the leading force and the development of financial markets such as insurance and securities being emphasized, which will help to optimize the market capital allocation, improve the enterprise’s financing structure, optimize utility of the limited resources. This can promote industrial reform and upgrading of the Greater Bay Area in the present and future.

References Allen, F., & Gale, D. (1999). Comparing financial systems. MIT Press. Ammer, J., Vega, C., & Wongswan, J. (2010). International transmission of US monetary policy shocks: Evidence from stock prices. Journal of Money, Credit and Banking, 42, 179–198. Ang, J., & McKibbin, W. (2007). Financial liberalization, financial sector development and growth: Evidence from Malaysia. Journal of Development Economics, 84(1), 215–233. Ansart, S., & Monvoisin, V. (2017). The new monetary and financial initiatives: Finance regaining its position as servant of the economy. Research in international Business and Finance, 39, 750–760. Arestis, P., & Demetriades, P. (1997). Financial development and economic growth: Assessing the evidence. The Economic Journal, 107(442), 783–799. Bangake, C., & Eggoh, J. (2011). Further evidence on finance-growth causality: A panel data analysis. Economic Systems, 35(2), 176–188. Bencivenga, V. R., & Smith, B. D. (1991). Financial intermediation and endogenous growth. Review of Economic Studies, 58, 195–209. Bezemer, D. J., Grydaki, M., & Zhang, L. (2014). Is financial development bad for growth? University of Groningen, Faculty of Economics and Business. Bose, S., & Kumar A. (2016). Growth of finance, real estate and business services: Explorations in an inter-sectoral framework (Working Papers 16/162). National Institute of Public Finance and Policy. Calderón, C., & Liu, L. (2003). The direction of causality between financial development and economic growth. Journal of Development Economics, 72(1), 321–334. Chen, Y. (2009). An empirical study on the relationship between stock market and economic growth in China. Economic Journal, 4(4), 28–30. Cheng, C., Chien, M., & Lee, C. (2021). ICT diffusion, financial development, and economic growth: An international cross-country analysis. Economic Modelling, 94, 662–671. Fry, M. J. (1997). In favour of financial liberalisation. The Economic Journal, 107(442), 754–770. Goldsmith, R. (1969). Financial structure and development. Yale University Press. Greenwood, J., & Jovanovic, B. (1990). Financial development, growth, and the distribution of income. Journal of Political Economy, 98(5, Part 1), 1076–1107. Greenwood, J., & Smith, B. D. (1997, January). Financial markets in development, and the development of financial markets. Journal of Economic Dynamics and Control, 21(1), 145–181. Huang, J., & Lu, J. (2021). Research on the effect of regional financial development on regional economic growth based on an empirical analysis of Jiangsu province. Baidu Scholar, 2012–2, 22–25. Ibrahim, M., & Alagidede, P. (2018). Effect of financial development on economic growth in sub-Saharan Africa. Journal of Policy Modelling, 40(6), 1104–1125. Jokipii, T., & Monnin, P. (2013). The impact of banking sector stability on the real economy. Journal of International Money and Finance, 32, 1–16. King, R., & Levine, R. (1993). Finance and growth: Schumpeter may be right. Quarterly Journal of Economics, 108(3), 717–738.

60

Y. Luo and B. S. Nayak

Kuang, F. (2007). Relationship between financial development and economic growth in Guangdong province. Jinan University. Levine, R. (1997). Financial development and economic growth: Views and agenda. Journal of Economic Literature, 35, 688–726. Levine, R. (2002). Bank-based or market-based financial systems which is better. Journal of Financial Intermediation, 11, 398–428. Levine, R. (2004). Finance and growth: A survey of the theoretical and empirical literature [R]. Tinbergen Institute Discussion Papers No. 04-039/2. Levine, R., & Zervos, S. (1998). Stock markets, banks, and economic growth. American Economic Review, 88, 537–558. Li, M. (2017). Empirical analysis of financial development and economic growth in Shandong Province, China, based on time series VAR analysis. Finance and Economics, 98–101. Menyah, K., Nazlioglu, S., & Wolde-Rufael, Y. (2014). Financial development, trade openness and economic growth in African countries: New insights from a panel causality approach. Economic Modelling, 37, 386–394. Merton, R. C., & Bodie, Z. (1995). A conceptual framework for analyzing the financial system, the global financial system: A functional perspective. Harvard Business School Press. Rioja, F., & Valev, N. (2004, January). Finance and the sources of growth at various stages of economic development. Economic Inquiry, 42(1), 127–140. Available at SSRN: https://ssrn.com/ abstract=906211 Roubini, N., & Sala-i-Martin, X. (1992). Financial repression and economic growth. Journal of Development Economics, 39(1), 5–30. Rousseau, P., & Wachtel, P. (2000). Equity markets and growth: Cross-country evidence on timing and outcomes, 1980–1995. Journal of Banking & Finance, 24(12), 1933–1957. Samargandi, N., Fidrmuc, J., & Ghosh, S. (2014). Financial development and economic growth in an oil-rich economy: The case of Saudi Arabia. Economic Modelling, 43, 267–278. Shen, C., & Lee, C. (2006). Same financial development yet different economic growth: Why? Journal of Money, Credit, and Banking, 38(7), 1907–1944. Sun, Z., & Zhang, J. (2021). Financial technology, financial development and economic growth. Finance and Accounting Monthly, 4, 8. Tan, R. (2000). The theory of financial development and financial development of China. China Economic Publishing House. Valickova, P., Havranek, T., & Horvath, R. (2013). Financial development and economic growth: A meta-analysis. SSRN Electronic Journal. Xie, M. (2018). Research on the relationship between financial development and real economy growth under threshold effect. Modern Business Journal, 1, 63–64. Zhou, L., & Wang, Z. (2017). Empirical research on the roles of financial services clustering to regional economic growth. Guanghua School of Management, Peking University.

Chapter 4

Impact of Financing on Investment in Chinese SMEs During Financial Crisis Jiang Mingte and Bhabani Shankar Nayak

Abstract Small and medium-sized enterprises’ financing and investment issues have always been crucial in the economic growth and development. This chapter aims to examine the investment and financing decisions of SMEs in China between 2005 and 2015. Therefore, this chapter selected 4868 companies as samples from the CSMAR database for the study. In order to study the changes in investment of SMEs in China during the crisis and the impact of different financing channels (internal financing and external financing) on their investment, this study establishes two specific models to test these two hypotheses. The research shows that the financial crisis reduces investment in SMEs in China. At the same time, the investment decision of Chinese SMEs relies more on external finance (bank loans) than internal finance during the crisis. Finally, based on the data results, this chapter proposes some policy optimization suggestions for government and financial institutions like banks, which can help Chinese SMEs better cope with potential future crises.

Introduction The financial crisis of 2008 had a considerable impact on the world’s financial system, with particular attention being paid to the impact on corporate financing and investment decisions. SMEs are the backbone of the country’s economic development and an essential source of innovative employment and economic growth, so the financing and investment of SMEs in the financial crisis deserve attention (Zubair et al., 2020). The financing methods of enterprises are generally divided into two types: internal financing and external financing. Internal financing is biased towards operating income, while external financing sources are generally new equity and borrowings

J. Mingte University of Glasgow, Glasgow, UK B. S. Nayak (B) Business School for the Creative Industries, University for the Creative Arts, 21 Ashley Rd, Epsom KT18 5BE, UK e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 B. S. Nayak (ed.), China: The Great Transition, https://doi.org/10.1007/978-981-99-0051-0_4

61

62

J. Mingte and B. S. Nayak

from financial intermediaries such as banks (Yang et al., 2009). Different companies will choose the most optimized financing method through evaluation. However, the 2008 financial crisis prompted banks to implement tight lending policies, which made it more difficult for companies to raise money. Besides, large listed companies often have conditions such as “too big to fail,” good loan records, and others. So they can receive government subsidies and bank leniency during crises. Conversely, banks are unwilling to provide SMEs loans during the crisis. On the one hand, information asymmetry is easy to cause adverse selection and moral hazards, and other problems. On the other hand, SMEs often have problems such as incomplete information disclosure and incomplete credit records, thus increasing the risk of banks providing credit. China is in a period of rapid economic development, but the difficulty of financing small and medium-sized enterprises is a “bottleneck” that restricts their development. It is also an unavoidable problem in the current coordinated development of the economy (Liu, 2009). The global financial crisis of 2008 had a severe negative impact on China’s economy. According to the National Bureau of Statistics, China’s GDP growth has declined sharply recently, from 11.9% in 2007 to 6.1% in 2009. At the same time, the development of SMEs in China is also in trouble. Not only are export-oriented SMEs forced to reduce production in the face of shrinking international markets, but some entrepreneurs distrust investment markets and thus withdraw their funds. In addition, China SMEs do not have the strength to withstand market turbulence by themselves. For example, the new SMEs are in the development stage. They do not have a robust technical level and rigorous enterprise management, which lead to their passive situation in a crisis. In recent years, the outbreak of COVID-19 has had a significant impact on the world’s economy, and the development of SMEs in China has been negatively affected. Therefore, the research about the investment and financing of Chinese SMEs during the 2008 economic crisis is essential. Its analysis results can effectively help the Chinese government’s policy formulation in the face of financial turmoil during COVID-19. Therefore, it is necessary to study Chinese SMEs’ financing and investment decisions during the financial crisis. Several empirical studies confirm the impact of financing on investments. Rousseau and Kim (2008) studied the investment behavior of South Korea’s manufacturing industry before and after the 1997 financial crisis, and research concludes that the Q-theory supports companies to invest more when there is an opportunity for growth able growth opportunities for growth. It is consistent with our assumption that the financial crisis will reduce corporate investment. Because during the crisis, the Great Depression in the economy led to a shortage of bank credit supply, creating financing difficulties. The negative impact of the financial crisis on small and medium-sized enterprises is noticeable. The supply chains are paralyzed by the financial crisis, which led to a sharp decline in demand. According to Lema et al. (2022), the financial crisis caused financial flow problems that prevented SMEs from carrying out their investment plans. This situation is evident in some young export-oriented companies; these SMEs will reduce investment behavior during the crisis because lacking sufficient funds to address issues such as operations and sales. Kahle and Stulz (2013) argue that

4 Impact of Financing on Investment in Chinese SMEs During Financial …

63

although the decrease in the supply of bank credit during the crisis has had a specific impact on corporate investment, it cannot have a decisive impact on the investment behavior of some enterprises with many financing means. Compared with large, listed companies, the financing problem in the crisis has a more significant impact on small and medium-sized private enterprises. A study from Akiyoshi and Kobayashi (2010) of the productivity of Japanese firms during the financial crisis from 1997 to 1998 showed that an increase in financial frictions reduced firm productivity. In other words, a decrease in bank lending coincided with a decrease in corporate investment. Through the model of Chen and Hsu (2005), small companies face a higher risk premium because they have lower collateral to enter the credit market. Thus it concludes that SMEs will face a tremendous shock in the financial crisis of sudden credit tightening. The theory of investment asymmetry proposed by Kasahara (2008) explains that differences in financing constraints affect the degree of investment. His research of 24,184 companies in the UK confirmed a U-shaped relationship between corporate investment and cash flow, which means there is no monotony between investment and cash. At the same time, as external financial constraints increase, so does the sensitivity of investments to cash flows. In other words, his research resembles our hypothesis that during the financial crisis, fewer loans provided by banks increased external financial constraints, and corporate investments were more inclined toward internal financing. According to Wang (2010), in the context of uncertain market prospects, internal financing has a cost advantage, which can avoid adverse selection and moral hazards to a certain extent. That is, he believes that internal financing has more advantages than external financing in an environment of market turmoil caused by the financial crisis. Similarly, by studying a company’s shift from NASDAQ to the New York Stock Exchange, Yang et al. (2009) confirmed that companies become less dependent on internal financing as their visibility and liquidity increase. Simply put, the yang et al. study argues that large public companies can benefit from low external financing costs, while small and medium-sized companies still favor internal financing. Financing options are widely recognized as the most challenging issue facing SMEs. Pecking theory shows that the preferred financing order of a company is internal financing, debt, and equity (Agliardi et al., 2016). It believes that SMEs prefer internal financing to avoid the additional costs caused by information asymmetry and agency problems to a certain extent. Fazzari, Hubbard, and Petersen (1987) argued that some companies’ ability to raise external financing would be limited when they do not have sufficient access to the capital markets. It results in their investment behavior becoming more dependent on the raising of internal funds. It contradicts the hypothesis that SMEs’ investments are more sensitive to cash flow. However, Berger and Udell (1998) argued that the financing methods of SMEs are not limited. On the one hand, internal funding is provided by internal family and friends. On the other hand, angel investment and private placement have to some extent, compensated for the limitations of SMEs’ inability to enter the PR market for financing. Therefore, the study argues that the financing methods of SMEs depend to some extent on the choices of entrepreneurs, which is inconsistent with the statement that SMEs’ investments are biased towards internal financing.

64

J. Mingte and B. S. Nayak

According to Nguyen et al. (2015), borrowing from banks remains the primary means of financing SMEs when banks reduce their lending to SMEs during a crisis. First, during the financial crisis period, economic turmoil led to increased difficulty in internal financing, and many entrepreneurs reduced their internal financing strategies to avoid risks. Second, even if banks are not willing to take the risk of lending to SMEs. However, some of the government’s coercive policies have forced it to fund SMEs. In this way, the share of external financing will likely remain a large part of SMEs’ investment. According to Yang (2022), private equity and venture capital will make China’s SMEs face more financial risks in the crisis and are more likely to go bankrupt in the crisis. However, in the financial turmoil caused by COVID-19 in 2022, private equity and venture capital have played a positive role for SMEs. There are two reasons; the first is that enterprises consciously strengthen risk control and avoid high-risk investment behavior. Second, the government has developed an effective regulatory system to promote the stability of financial markets. In the studies of Liu (2009), SMEs in China has been growing at relatively high rates, but there was a reversal in 2007. In order to control the inflation caused by the financial crisis, the central government has taken measures such as raising deposit interest rates and reserve requirement ratios, thereby increasing the operating costs of SMEs. With the advent of the global financial crisis, the international financial market has shown a tightening trend, which has led to great difficulties for China’s exportoriented SMEs. In addition, due to the sluggish domestic demand, it is difficult for export-oriented SMEs to turn to the domestic market. In order to solve the difficulties caused by the crisis, the Chinese government began to implement an active fiscal policy in 2008 to strengthen investment in SMEs. On the issue of credit, the China Banking Regulatory Commission (CBRC) asked banks to strengthen special services for SMEs to ensure an increase in their credit levels. However, due to the poor resilience of SMEs, banks are still reluctant to lend to SMEs in the absence of substantial government guarantees. Therefore, financing is still the main problem for Chinese SMEs, influencing their investment and business. Zhao (2009) argues that financing difficulties are an important issue for Chinese SMEs during the crisis. He mentioned in his study of international trade during the financial crisis of Chinese SMEs that SMEs will face more difficult credit conditions because of their small-scale, poor anti-risk ability, and low credit level, and thus have to reduce production and investment behavior. In the works of Liu et al. (2022), the impact of the financial crisis on the investment and financing of SMEs has always been there, whether it is the financial crisis of 2008 or the financial turmoil caused by COVID-19 in 2020. However, the government’s policy support is vital in helping SMEs in their financing difficulties. On the one hand, the financially specific fund can greatly meet the financing needs of SMEs during a crisis. On the other hand, a loose lending policy can make it easier for SMEs to lending to banks, such as lower requirements for collateral.

4 Impact of Financing on Investment in Chinese SMEs During Financial …

65

Investment and Financing of SMEs This chapter is an in-depth literature review of financing and investment. At first, there will be some literature review about the capital structure and SMEs’ financing preferences. Then, this chapter will show some financing sources (external finance and internal finance) for SMEs, especially in China. The third part is a conceptual framework for financing SMEs in China, and the last is a literature review on the investment of Chinese SMEs. According to OECD (2004), businesses with fewer than 250 employees and an annual turnover of fewer than 50 million euros are defined as SMEs. Ninety-five percent of businesses in the world today are SMEs. However, no one can doubt that SMEs are an essential factor in economic development, especially in developing countries like China; SMEs have the potential to bring about transformational change and are the driving force for economic growth. However, according to Beck (2007), although SMEs play a considerable role in the country’s economic activities, their development is constrained by difficulties in obtaining funds. The development of SMEs requires investment, which is reflected in various fields such as technological upgrading, market development, and asset acquisition. However, the source of funds for investment is inseparable from financing decisions. Therefore, it is necessary to study the capital structure and financing decisions of SMEs, which can help companies strategically plan financing behaviors. The concept of leverage involves a company’s lending and investment behavior, which requires that the income generated by the investment is greater than the cost of the loan. Due to the uncertainty and risk of investment, SMEs may face debt pressure, such as interest. Literature shows that lack of capital is a major problem for SME development (Beck, 2007). Therefore, SMEs’ investment and financing framework deserve in-depth study. At first, this part will conduct an in-depth theoretical analysis of the capital structure of SMEs. Then, it will discuss the financing preference of SMEs. In particular, by examining the funding sources available to SMEs during the financial crisis, it is possible to measure the influence of financing on investment clearly. In the third part, a conceptual framework will build to improve the lending infrastructure and optimize the capital structure of companies. Finally, this study provides an in-depth literature review of SMEs’ investments. Importantly, each section will discuss the specifics of SMEs in China.

Capital Structure and Financing Preferences of SMEs Profitability, age, size, and growth are defined as the main factors affecting the capital structure of SMEs. According to Abor (2005), companies with poor profitability are more inclined to short-term financing, and their leverage ratio and financing ability are negatively correlated. However, most SMEs in developing countries rely more

66

J. Mingte and B. S. Nayak

on short-term debt. Therefore, financial institutions are reluctant to provide capital to SMEs due to the volatility of risk, especially during a financial crisis. In addition, another reason for the lack of long-term loans by SMEs is their lack of collateral, and they do not have valuable collateral to secure long-term mortgages (Abor & Biekpe, 2009). Besides, SMEs themselves will reduce their preference for external funding to a certain extent because of their profitability constraints and their risk-averse nature (Daskalakis & Psillaki, 2008). Debt overstock is a major problem for investment and financing. Therefore, SMEs like to reduce debt to avoid conflicts between owner-manager-lender. At the same time, emerging enterprises will find it difficult to get loans from external financial institutions due to a lack of credibility and other problems, so they rely more on internal financing (Abor & Biekpe, 2009). From the structural point of view, it can be concluded that the short-term debt of SMEs is negatively related to the age of the company. Compared with large listed companies, they have less information asymmetry and can raise funds more easily by issuing stocks. Therefore, it can be concluded that leverage and firm size are negatively related (Abor & Biekpe, 2009). According to the research on the determinants of the capital structure of most SMEs, the pecking order theory is more in line with the financing preferences of SMEs, that is, the order of internal funds-debt-equity. For SMEs, managers have high control and ownership of enterprises, so the financing decisions of SMEs are largely decided by managers and owners. According to the model of Auken (2005), both the manager’s experience and growth preference will have an impact on the capital structure, thus affecting the financing preference of SMEs. In this way, managers will reduce debt financing for fear of the risk of bankruptcy, and the capital structure of SMEs and risk-prone will also lead to their aversion to external financing. Based on the above theoretical discussion of capital structure, large listed companies are more inclined to trade-off theory because their large enough experience scale and information symmetry can guarantee the stability between their debt cost and income. However, SMEs and other emerging economies are more suitable for pecking theory. However, due to the above specific factors, such as the influence of managers’ decision-making and family problems, the capital structure of SMEs will become difficult to describe. Therefore, the next part will do a more literature review to discuss the source of financing for SMEs in detail. The financing difficulties of SMEs exist in many countries around the world, but they are particularly prominent in China. First, China’s immature capital market has led to a lack of regional markets for SMEs, making it difficult for SMEs to finance through the capital markets. Second, China SMEs have a much smaller amount of bond financing than large listed companies due to problems such as scale and cash flow. According to statistics, a large listed company raised up to 66.8 billion yuan in 2008, which is the sum of 70 SMEs (He, 2012). In addition, China’s four major stateowned commercial banks are not mature. In order to avoid financial risk, they targeted their main customers at large public companies, creating credit difficulties for SMEs. Lacking good credit ratings and third-party guarantees, SMEs have difficulty getting long-term loans from financial institutions such as banks.

4 Impact of Financing on Investment in Chinese SMEs During Financial …

67

Source of Financing for SMEs Financing is a critical factor in the development of SMEs, so it is crucial to study the ways in which companies obtain capital. However, SMEs are subject to various restrictions in their financing. For example, financial institutions such as banks will hinder the financing of SMEs due to problems such as information mismatch and financial reputation. First, seeking bank loans is the most common way for SMEs to finance themselves (Norton, 2003). However, despite the Basel II norms requiring banks to reduce their requirements for lending to SMEs, the risks posed by information asymmetry still led to reluctance by most banks. In addition, collateral plays an important role in the long-term relationship between banks and SMEs, and high-value collateral can facilitate banks to provide long-term low-interest loans to SMEs (Petersen & Rajan, 1994). Therefore, borrowers need to maintain a good relationship with banks so that they are willing to lend because they can assess the quality of borrowers. However, this is not good news for SMEs. First, most SMEs do not have high-value collateral to seek long-term relationships with banks. Second, the severe impact of the financial crisis could lead to SMEs going bankrupt and being unable to repay their debts, so banks were reluctant to take the risk of lending. In addition, the financial markets in some developing countries are underdeveloped, and theories such as the pecking order have also demonstrated the difficulty of lending from banks in the early days of emerging companies. Therefore, it can conclude that emerging small and medium-sized enterprises are difficult to obtain financing through formal channels. In this way, some SMEs in developing countries will choose to obtain funding sources through equity financing (Mac Bhaird & Lucey, 2011). However, this approach is still difficult because emerging companies do not have enough performance to attract investors. Simply put, emerging SMEs cannot provide long-term sales earnings information to convince investors that they are worth investing in. It is consistent with the restrictions on borrowing funds from banks because emerging SMEs cannot prove their profitability and growth potential. However, this is a paradoxical question. Small and medium-sized enterprises cannot make better profits because they lack funds to invest in development. And due to SMEs do not have sound profit proof, financial institutions are reluctant to issue loans to them, thus forming a vicious circle. In this way, the government’s policy support for small and medium-sized companies in the embryonic stage is particularly important. Conversely, informal financing also has certain advantages, such as not requiring loan collateral. According to Beck et al. (2008), informal sources make SMEs the primary source of external financing, which is also in line with the order of pecking theory. Generally, there are two ways of informal external financing for SMEs: one is funds provided by people such as family members or friends, which is called love capital; the other one is “angel investment” by the business investor, which depends on investors’ approval of the development potential of the companies (Gudov, 2013). Therefore, informal financing is a relatively cheap and convenient financing option

68

J. Mingte and B. S. Nayak

for SMEs. Besides, some SMEs will also use owner financing, subsidized financing, and sweat equity to get through the start-up period to optimize resource use when there is insufficient financial support. However, due to the lack of regulation, informal investments also increase the uncertainty and riskiness of the market. At the same time, social financing is also becoming more and more important in the way SMEs are funded, that is, to obtain financial benefits through social networks (Carey & Flynn, 2005). Promising industries raise funds for specific projects through social electronic platforms, which has an important effect on early-stage SMEs. At the same time, social financing relies more on trust than formal financing channels, which will be a competitive advantage for SMEs. Also, according to Carlos (2011), social capital may become an intangible relationship asset for SMEs, providing companies with new information resources in a volatile business environment. As for Chinese SMEs, there are two sources of internal financing: retained profits financing and depreciation financing. On the one hand, the financing of retained profits is to directly convert profits into investments, which avoids the risks caused by cash expenditures and ensures debt capacity. On the other hand, depreciation financing of fixed assets is also a form of internal financing, which aims to obtain capital through the difference between depreciation and opportunity cost. As for external financing, direct financing includes bond financing, equity financing, and public funds. Bond financing is a way for an enterprise to raise funds from investors by issuing bonds and promising to repay the principal and interest within a certain period. Also, equity financing aims to bring in the capital by bringing in new shareholders. At last, public funds are a prevalent financing method for SMEs in China, mainly including commercial credit and private loans. According to the above, this kind of informal loan can avoid the restrictions required for many bank loans and reduce the cost of loans. Indirect external financing includes bank financing and financing by financial institutions. A common formal financing channel for bank financing, SMEs are difficult to obtain large amounts of bank financing due to factors such as the size and creditworthiness of SMEs in China. In addition, some leasing institutions and pawn loans can help to finance SMEs; although the cost of non-bank institution loans is high, the process is more straightforward and more convenient and can meet the short-term capital needs of SMEs (Jiang et al., 2014). According to Wu et al. (2008), the financial needs of China SMEs are cyclical and phased. In the early days, SMEs in China mostly raised funds through personal savings and the support of relatives and friends. Then, the funding needs of SMEs increase rapidly during the growth phase and require external financing from banks or financial institutions. However, during the financial crisis, the financing preference of SMEs did not have specific research analysis results before, which is worth studying.

4 Impact of Financing on Investment in Chinese SMEs During Financial …

69

Conceptual Frameworks for Financing of SMEs As mentioned above, the financing of SMEs is an important but under studied area (Wu et al., 2008). Owing to the financing options for SMEs vary with size and age, so a good conceptual framework can provide favorable guidance for SMEs’ financing options. In general, the financing of SMEs is affected by various factors. First, the complexity of the company’s capital structure makes it difficult to make financing decisions. For example, the characteristics of the company or the preferences of managers can affect financing decisions. Second, the balance between the demand and supply of funds by SMEs depends on the macro environment to some extent, such as monetary factors or political factors. Therefore, due to this study discusses the financing process during the period of the financial crisis. SMEs will face a worse financing environment, which results in more complicated financing decisions. So, the conceptual framework for financing SMEs requires the following points. One is to describe the capital structure of SMEs and their financial structure. Second, the framework needs to understand the financing sources of SMEs and the reasons for financing difficulties. In this way, the financing preferences of SMEs can be accurately determined, thereby providing guidance for managers to improve capital structure and optimize loan infrastructure. In China, there are certain restrictions on the financing framework and capital structure of small and medium-sized private enterprises. The first is the immature capital market and the restrictions on external financing of SMEs by the stock market. The second is the immature banking industry, which mostly provides loans to large companies in order to avoid risks, thus ignoring SMEs. Third, the small number of credit guarantee institutions in China makes it difficult to guarantee long-term loans to SMEs, while banks do not recognize private credit guarantees. Finally, public funding as a conduit for SMEs to finance is not formally regulated and is not recognized by the Chinese government (Jiang et al., 2014). Therefore, in order to promote the stable development of SMEs, China’s capital structure needs to be optimized. Not only the development of capital markets and banking is needed, but also the government must guide and regulate public investment and credit guarantees. As Liu (2009) said, local governments can establish guarantee funds for SMEs’ loans and implement policies that incentivize banks to lend to SMEs, such as tax reductions. With the help of the Chinese government, China’s SMEs have developed rapidly and played an engine for the Chinese economy. However, underdeveloped financial markets allocate most of their financial resources to large state-owned enterprises rather than innovative SMEs. This discrimination in resource allocation makes it more difficult for SMEs to finance. For example, in 2004, SMEs accounted for 50% of GDP with access to 10% of bank loans (Wu et al., 2008). It can be seen from here that the financing dilemma of SMEs is always present, which is rooted in the pecking theory and China’s underdeveloped financial markets. There is no doubt that this situation will be even more difficult during the financial crisis. According to Cousin (2007), national policies have also played a large role in influencing the financing of SMEs. Because of the government’s preference for large

70

J. Mingte and B. S. Nayak

state-owned enterprises, banks are more willing to fund state-owned enterprises that are inefficient and even have non-performing loans. Because even if they go bankrupt, failed state-owned enterprises can receive financial assistance from the government. However, this unfair market and political environment for SMEs has led to SMEs’ financing woes in China. Especially during the financial crisis, large state-owned enterprises (SOEs) received most of the bank’s funds because they were “too big to fail.” At the same time, SMEs became more difficult due to the lack of policy support for financing. The relationship between SMEs and banks is also a major factor in the financing difficulties of SMEs. First, banks lack a specialized agency to approve SMEs’ borrowings, so they cannot approve the credit and integrity of SMEs’ information. Second, since SMEs are in the embryonic stages of development, they lack enough fixed assets as collateral to go to lend. In this way, the lack of assets limits the ability of SMEs to guarantee loans (Zhang, 2006). Therefore, the Chinese government needs to promote the establishment of a guaranteed system for small and medium-sized enterprises, and an independent strategic policy governance system has greatly promoted the development of SMEs. According to Yao and Yang (2022), the main reason for the restrictions on financing SMEs in China is the old operating model under the traditional financial system. Digital finance can use big data to compensate for information asymmetry under the support of emerging technologies, thereby breaking through the constraints of traditional markets and promoting the financing of Chinese SMEs. In short, digital finance has a certain role in reducing the financing constraints of SMEs in China. Relying on advanced digital technologies, digital finance can facilitate financing by reducing information asymmetry when it comes to credit approvals for SMEs. In this way, Government support for the development of digital technologies is also crucial to addressing the financing problem of SMEs in China.

Investment in SMEs SMEs seek technological innovation and job creation by investing in expanding their businesses (Luo et al., 2016). However, the limitation of funds often makes them have to give up valuable investments, thus losing opportunities. Based on data from 1557 high-investment and low-investment SMEs, a positive correlation between cash flow and SME investment was concluded. In addition, debt stimulates investment in SMEs but limits low investment in SMEs. In addition, the deterioration of the macro environment and the expansion of firm size are inversely correlated with investment in SMEs, while an increase in the age of firms will promote investment (Serrasqueiro, 2017). Therefore, it can conclude that the size, cash flow, age, and macro environment all affect the investment of SMEs. Further, the financial crisis can be used as an independent variable, while factors such as the age of the company, the size of the company, and cash flow can be used as control variables to study the impact of the financial crisis on SMEs’ investment in the data model of the fourth part.

4 Impact of Financing on Investment in Chinese SMEs During Financial …

71

In China, the global economic crisis has led to deflation worldwide, so the import and export of Chinese companies have been on a downward trend since 2008, which has hit SMEs even harder (Liu, 2009). Insufficient market demand was a huge problem for SMEs during the financial crisis (Li, 2005). According to the research, the number of orders from SMEs has dropped by 20–30% since 2009, and many orders have been suspended or canceled. Besides, the annual sales volume of Chinese SMEs has also dropped by 17–22%. Due to the shrinking demand in foreign markets, SMEs, which are mainly based on foreign trade exports, have chosen to reduce production or reduce product lines to avoid risks. In addition, according to Chen (2009), as of the second half of 2008, about 67,000 Chinese SMEs had stopped production, and the number of unemployed people had also fallen sharply (5%). Therefore, investment in SMEs in China during the financial crisis was reduced for the following reasons. First, macroeconomic conditions are harsh under the global economic crisis. Second, due to shrinking market demand, SMEs have chosen methods to reduce the scale of production or even reduce the production line, thereby reducing cash flow. In addition, issues such as layoffs will also reduce the company’s size, which will affect investment. In conclusion, this part does an in-depth literature review about the capital structure and financing preferences, source of finance, and conceptual framework for financing and investment of SMEs. In detail, scholars have different perspectives on the investment and financing of SMEs during the crisis. First, most scholars support a negative correlation between investment and crisis, which means SMEs will reduce investment during the financial crisis. During the financial crisis, the harsh financial environment invested Chinese declined significantly. Second, some argue that banks will reduce their lending to SMEs during the crisis, which makes SMEs’ investments more dependent on internal funding. However, another group of scholars argues that some favorable policies from the government and the principle of risk aversion within companies have led to external financing remaining the primary source of funding for SMEs’ investments. Therefore, accurate data studying about investment and financing of Chinese SMEs in the financial crisis under the specific economic system and national conditions is essential.

Methods to Study Financing of SMEs It makes two specific analytical regression models which correspond to the two hypotheses of this chapter. At first, there is a standard investment model to examine the investment of SMEs in China during the crisis. This section quantifies the dependent variables (investment) and control variables (cash flow, age, and size). The second model is modified based on the standard investment model, which aims to compare external and internal financing for the investment of Chinese SMEs during a financial crisis. According to Yang et al. (2009), a company’s conversion upgrade will reduce its cash flow sensitivity and less reliance on internal financing. Banks use information

72

J. Mingte and B. S. Nayak

such as the financial statements of large companies as a way to assess their ability to repay loans. As a result, large companies take cash flow as an advantage and are able to reduce the restrictions on borrowing fund from banks. In addition, by increasing the scale of listing of enterprises, the companies win more popularity and reputation. In this way, their difficulty with external financing will also be reduced. On the contrary, SMEs are more inclined to rely on internal financing because of the difficulty of external financing. Badertscher et al. (2013) have concluded that SMEs are more likely to receive more positive external influences from listed companies in industries with better information quality, thereby enhancing their investment flexibility. According to the summary of the literature review, the first hypothesis is as follows; H1: Chinese SMEs will decline due to low investment during the financial crisis. According to Zubair et al. (2020), this chapter can use a simple investment model to investigate hypothesis 1 as following: Investment tit = α + β1 Crisis + β2 PostCrisis + β3 Cashflowit + β4 Sizeit + β5 Ageit + εit In this model, i and t represent individual companies and years, respectively. This study divides the study time into three periods: pre-crisis, crisis, and postcrisis. Because the impact of the financial crisis is long-lasting, its impact on SMEs financing and Investment will not be limited to 2008–2009, so this study sets the 2008–2012 period as a crisis affected by the financial crisis. Therefore, the crisis is a virtual independent variable that is 1 when the time is in the period 2008–2012; otherwise, it is 0. On this basis, the model analyzes the regression coefficients β 1 and β 2 to study the differences and significance of enterprises before and after the crisis. (Zubair et al., 2020). According to the research, there are several ways to measure Investment. The first is the sum of tangible and intangible fixed assets divided by the total assets at the beginning of the year (Akbar et al., 2013). However, this way of measuring Investment is mostly applicable to large public companies because SMEs in China rarely disclose information about intangible fixed assets, which results in difficulties in data collection. Secondly, Firth et al. (2012) proposed to measure Investment by dividing the sum of fixed assets plus depreciation by total assets at the beginning of the year so that the collection of intangible asset data could be omitted. Besides, Asker et al. (2015) also measured Investment as dividing the sum of annual change of tangible fixed assets with depreciation by the total assets at the beginning of the year. This chapter uses change in tangible fixed assets plus depreciation over beginning-of-year total assets to measure Investment. Based on the literature review, cash flow, company size, and age all affect SMEs’ investments (Abor, 2005, Kasahara, 2008). Since hypothesis 1 aims to study the impact of the financial crisis on SME investment in China, these factors affecting Investment will be defined as the control variable. Duchin et al. (2010) proposed to measure the cash flow of SMEs by dividing the sum of operating income at the beginning of the year and depreciation by total assets. Besides, the size of a company

4 Impact of Financing on Investment in Chinese SMEs During Financial …

73

is one of the most important parts of the control variable, which the natural logarithm of total assets can describe. Finally, age is the number of years of business. In order to study the impact of changes in internal and external financing of SMEs in China on Investment during the financial crisis, Hypothesis 2 is following: H2: Chinese SMEs became more dependent on internal financing than external financing during financial crisis. Since this hypothesis is still take investment as dependent variable, this study only needs to make appropriate adjustments to the investment regression model 1. In order to analyze the interactive correlation, the model 2 will make adjustment based on the model from Zubair et al. (2020): Investmentit = α + β1 Crisis + β2 Internalfinanceit + β3 Externalfinanceit + β4 Internalfinanceit ∗ Crisis + β5 Externalfinanceit ∗ Crisis + β6 Size + β7 Age + β8 Cashflow + εit This model aims to test the different effects of internal finance and external finance on the investment of Chinese SMEs during a financial crisis. β 4 and β 5 are two coefficients to respond to the result of the regression model about internal finance and external finance, respectively. According to Guariglia (2008), internal financing can be quantified as the sum of after-tax income and the depreciation of total assets at the beginning of the year. At the same time, the change in bank debt over total assets at the beginning of the year can measure the external financing of Chinses SMEs (Nguyen et al., 2015). In this model, size, age, and cash flow also are defined as control variables. However, one point to emphasize is that the dummy variable crisis here also was 1 between 2008 and 2012, and the rest of the time was 0. In conclusion, Chapter 3 provides a standard investment model to examine if Chinese SMEs will decline their investment during the financial crisis. Then, there will be a more complex model to compare the impact of different financing channels on the investment of Chinses SMEs between 2005–2015.

Analysis of the Chinese SMEs This section provides a descriptive statistics table for the main variables of the whole sample and a descriptive statistics table for variables by period. At last, there will be a correlation analysis result table to show the correlation between each variable. This study selects all A-share small and medium-sized listed companies from 2005 to 2015, namely small and medium-sized board companies, ChiNext companies, and science and technology innovation board companies, as the initial research samples. And then, this study uses annual data of these companies for research. At the same time, in order to ensure scientific and accurate research results, this study also screens the initial study sample according to the following conditions:

74

J. Mingte and B. S. Nayak

(1) Exclude samples from the financial industry. The data sample in this study is from listed companies on the SME Board because listed companies are easily subject to the legal constraints of governments in the financial sector, such as market access and business development. As a result, the accounting treatment of these companies differs from those of other industries. In this way, in order to ensure the consistency of the research results, the previous literature has excluded such companies from the initial study sample, so this study also eliminates the sample of the financial industry. (2) Remove samples of ST, SST, *ST, and PT classes. Under normal circumstances, there will be obvious problems with the operating conditions of listed companies marked as ST, SST, *ST, and PT by the exchange, so these companies are likely to would forge false financial statements to avoid being delisted. Therefore, aiming to reduce the bias that the research results may influence, this study excludes such abnormal study samples. (3) Samples with missing and outlier values for related variables are excluded. After a series of filters based on the above conditions, this study finally obtained the non-balanced panel data composed of 4846 observations. The sample size was large, which ensured the credibility of the research conclusions of this study.

Data Source The data used in this study are from the CSMAR database. Prior to the start of the empirical analysis, this study manages all continuous variables at the enterprise level below 1% and above 99% annually by Winsorize. It can contribute to mitigate the possible effect of outliers on regression outcomes. At the same time, in order to eliminate the possible aggregation characteristics of the sample data, this study also adjusts the enterprise-level cluster adjustment for the standard error of the regression coefficient. The analysis and processing of data is mainly done by the software Stata 16.0.

Summary Statistics To get a preliminary understanding of the characteristics of variables, this section describes in detail the sample size, mean, standard deviation, minimum, median, and maximum values of each variable. According to Table 4.1, the mean of investment is 0. 0738, and the median is 0.0452. According to internal and external financing, this table shows that the mean of internal finance is 0.0847, which is more than twice external finance (0.0415). Even more, the median of internal finance is 0.0762, which is much more than 0.0088 for external finance.

4 Impact of Financing on Investment in Chinese SMEs During Financial …

75

Table 4.1 Descriptive statistics of the main variables of the whole sample SD

MIN

Investment

4846

N

MEAN 0.0738

0.0876

−0.0914

MEDIAN 0.0452

MAX 0.4915

Pre_Crisis

4846

0.0173

0.1305

0.0000

0.0000

1.0000

Crisis

4846

0.3731

0.4837

0.0000

0.0000

1.0000

Post_Crisis

4846

0.6096

0.4879

0.0000

1.0000

1.0000

CashFlow

4846

0.7580

0.4805

0.1082

0.6479

5.7730

InternalFinance

4846

0.0847

0.0630

−0.1202

0.0762

0.4687

ExternalFinance

4846

0.0415

0.0995

−0.2275

0.0088

0.7299

Size

4846

21.4111

0.8112

19.4076

21.3227

24.1350

Age

4846

12.6749

4.6356

2.6795

12.2836

27.6110

The above is a descriptive analysis of a total sample of 4846 Chinese SMEs, in which the data of each variable are within a reasonable range. Then, this study makes a specific descriptive analysis of various indicators over different periods in Table 4.2. Table 4.2 is a more specifical descriptive analysis result that divides the variables (investment, internal finance, external finance, cash flow, Size, and age) into three periods: pre-crisis, crisis, and post-crisis. For the control variables, cash flow significantly declined during the crisis, which fell from 1.0544 to 0.8222 between 2005 and 2012. It can be explained that the crisis led to a challenging business environment, so the operating income for the Chinese declined. Besides, the Mean number Size does not show noticeable change, but its median number significantly declined from 2005–2015. According to the mean number in Table 4.2, the investment profile of SMEs showed a continuous downward trend during 2005–2015, from 0.1157 to 0.0675. Among them, the proportion of Chinses SMEs’ investment decreased by about 0.0336 from pre-crisis to the crisis. In contrast, the investment decreased by 0.0146 from the crisis to the post-crisis period, which shows the decline was significantly reduced. In this way, it can prove that the financial crisis did have a long-term negative impact on the investment situation of Chinese SMEs. However, this negative impact was gradually relieved after the crisis, according to hypothesis 1. As for internal finance and external finance, Table 4.2 shows that the proportion of internal financing in China SMEs has always been about twice that of external financing. For example, the mean of Internal finance before a crisis is 0.1221, higher than external finance (0.0623). During the crisis, the proportion of internal finance is 0.0925, which is about twice as much as external finance (0.0446). Even after the crisis (2012–2015), the mean of internal finance is 0.0788, but external finance is just 0.0390. In this way, it can conclude that Chinses SMEs rely more on internal finance for investment during the financial crisis, which accords with hypothesis 2 to some extent. However, the decline in internal financing during the crisis is also more significant than the decline in external financing, so this study requires further correlation regression analysis. This simple descriptive model does not fully confirm

0.0313

20.5524

6.9301

0.0623

8.2749

Age

0.0971

20.6478

0.1221

InternalFinance

0.7734

0.0853

Size

1.0544

CashFlow

ExternalFinance

0.1157

Investment

10.9938

21.2254

0.0446

0.0925

0.8222

0.0821

10.4849

21.1245

0.0098

0.0826

0.6990

0.0526

Median

Mean

Mean

Median

Crisis (2008–2012)

Pre-Crisis (2005–2007)

Table 4.2 Descriptive statistics for variables by time period

13.8289

21.5465

0.0390

0.0788

0.7103

0.0675

Mean

13.4274

21.4654

0.0076

0.0715

0.6169

0.0402

Median

Post-Crisis (2013–2015)

2.7189***

−0.0056* 2.8351***

−4.9831**

−0.0177

−0.0137***

−33.6861***

−4.0363**

−0.0296***

−0.1119***

−0.0146***

0.3210***

−3.1892*

−0.2322***

Mean

−453.5788***

−134.2282***

−0.8025

−37.1057***

−40.0730***

−26.9947***

Median

Difference: Post-Crisis—Crisis

−33.6861***

−11.2121***

−0.0336***

0.5776***

Median

Mean

Difference: Crisis—Pre-Crisis

76 J. Mingte and B. S. Nayak

4 Impact of Financing on Investment in Chinese SMEs During Financial …

77

the extent to which Chinese SMEs rely on different financing channels, the regression analysis is necessary.

Correlation Analysis The previous section has conducted a descriptive statistical analysis of the sample data and found that the data used in this study has a certain degree of rigor and rationality. As for correlation analysis, on the one hand, the degree of correlation between variables is preliminarily judged. On the other hand, there is an obvious multicollinearity problem between variables. This section uses Pearson coefficients to test the correlation of each variable, and the test results are shown in Table 4.3, where the lower left corner is the test results of Pearson correlation coefficients. Table 4.3 shows a correlation between internal and external financing and investment, which are 0.1630 and 0.3244 at a 1% level. In this way, it can conclude that the investment of SMEs relies more on bank debt than internal financing. Besides, the correlation between crisis and internal finance is 0.0961 at a 1% level, while external finance correlates with the crisis at 0.0239 at a 10% significant level. It can show that the correlation between the financial crisis and internal financing is far more significant than external financing. Since there is a negative correlation between the crisis and financing, the crisis will reduce the financing level of SMEs. In this way, the destructive impact of the crisis on the internal financing of SMEs in China is far more significant than that of internal financing, which means Chinese SMEs should use more bank debt as investment funds. Besides, Table 4.3 also shows the low correlation between internal and external finance at 0.0796, which has little interactivity impact. From the correlation analysis results, Growth, the correlation between independent variables such as business age and cash flow is not high. Moreover, the absolute value of the correlation coefficient of the variables used in this study does not exceed 0.75, which shows that there is no multicollinearity problem between the variables, and the empirical regression model in this study is reliable. In conclusion, the descriptive and correlation analysis results prove hypothesis 1 to some extent, which is that the financial crisis will reduce the investment of Chinese SMEs. However, as for hypothesis 2, the descriptive analysis result shows that internal financing plays a significant role in Chinese SMEs’ investment. In contrast, the correlation between external financing and investment proves a high correlation. Therefore, hypothesis 2 needs a more detailed regression analysis to verify.

Findings of the Study The following three tables examine the impact of the financial crisis on investment of the influence of different financing channels on the investment of Chinese SMEs. The

−0.1025***

−0.1660***

0.0819***

0.0789***

0.0730***

0.1206***

Cash flow

−0.1261***

−0.0569***

Age

0.3111***

−0.0275*

0.1621***

0.2834*** 0.1512***

−0.1163*** −0.0311** 0.2085***

1.0000

Cash flow

−0.1241***

1.0000

Post_crisis

−0.0603***

0.0462***

0.0796***

1.0000

Internal finance

Notes *,**,*** means at the significance levels of 10%, 5%, and 1%, respectively (two-tailed test)

−0.2798***

−0.1766***

−0.1250***

0.0413***

Size

0.0961*** 0.0239*

0.0278*

0.1640***

0.3244***

Internal finance

0.1031***

−0.9639***

1.0000

Crisis

External finance

Crisis

−0.0893***

1.0000

Pre_crisis

Post_crisis

1.0000

0.0635***

Investment

Pre_crisis

Investment

Table 4.3 Correlation analysis results between variables

−0.0210

0.1550***

1.0000

External finance

0.0447***

1.0000

Size

1.0000

Age

78 J. Mingte and B. S. Nayak

4 Impact of Financing on Investment in Chinese SMEs During Financial …

79

study begins by examining whether SMEs in China have reduced their investment because of the financial crisis. Table 4.4 shows a fundamental linear regression to the independent variable of the financial crisis and three enterprise-level control variables (cash flow, size, and age). Table 4.4 is the result of the primary effect regression of the financial crisis on SME investment in China. It shows crisis has harmed Chinses SMEs’ investment, which resulted in a 4.49 percentage point decline. Also, Cash flow positively affects investment and is significant at the 1% level (5.88%). Besides, the natural logarithm of SMEs’ total assets will also have a positive impact on investment (4.99%), which is significant at the 1% level. However, Age can have a negative impact on a company’s investments, but it is not significant. Overall, investment in SMEs in China declined negatively during the financial crisis, which supports hypothesis 1. This finding is in line with that of Liu (2009), who examined the impacts of the global financial crisis on Chinese SMEs. In addition, these results also show that SMEs with high cash flow and larger scales take on more investments and are significant in F-statistics. Next, this study examines Hypothesis 2, which aims to examine the differences in the impact of external and internal financing on SME investment in China during the crisis. Therefore, this study performed a regression analysis on Model 2, and the results are shown in Table 4.5. According to the data in Table 4.5, internal financing positively impacts SMEs’ investments and is significant at the 5 percent level (12.01%). In contrast, the positive impact of external financing on investment in SMEs in China is much greater than that Table 4.4 Main effects regression results

(1) Investment Crisis

−0.0448 (−0.31)

CashFlow

0.0588*** (5.82)

Size

0.0499*** (8.38)

Age

−0.0142 (−0.59)

_cons

−0.8734*** (−4.48)

Firm

Yes

Year

Yes

N

4846

R2 Adj.

0.106 R2

0.100

Notes *,**,*** means at the significance levels of 10%, 5%, and 1%, respectively (two-tailed test).The brackets are the t-test values that have been cluster-adjusted at the enterprise level

80

J. Mingte and B. S. Nayak

Table 4.5 Regulatory effect regression results

(1) Investment Crisis

−0.1488 (−1.13)

InternalFinance

0.1201** (2.13)

ExternalFinance

0.2096*** (8.14)

InternalFinance_Crisis

0.0000 (0.00)

ExternalFinance_Crisis

−0.0088 (−0.21)

CashFlow

0.0269*** (2.77)

Size

0.0326*** (6.18)

Age

0.0077 (0.36)

_cons

−0.6885*** (−3.95)

Firm

Yes

Year

Yes

N

4846

R2

0.157

Adj. R2

0.152

Notes *,**,*** means at the significance levels of 10%, 5%, and 1%, respectively (two-tailed test).The brackets are the t-test values that have been cluster-adjusted at the enterprise level

of internal financing, which is significant at the 1 percent level (20.96%). Besides, cash flow has a 2.67% positive effect on investment at a 1% significant level, and Size has a positive impact (3.26%) and is significant at the 1% level. Therefore, it shows that Chinese SMEs rely more on external finance than internal finance for investment during the Financial Crisis. The test result refuses hypothesis 2. As for the interaction items, the coefficient of the interaction term Internal Finance’ Crisis is positive, which means Internal Finance weakens the negative influence of Crisis on investment of Chinese SMEs. Also, Internal Finance plays a negativeoriented regulatory role, but this regulatory effect is not apparent. Differently, the coefficient of the interaction term External Finance’ Crisis is negative, which means External Finance will strengthen the negative effect of Crisis on Investment, and External Finance plays a positive regulatory role. However, this regulatory effect is also not noticeable.

4 Impact of Financing on Investment in Chinese SMEs During Financial …

81

In order to examine the magnitude of the impact of internal and external financing on SME investment in China, this study further makes a separate return to the three periods: pre-crisis, Crisis, and post-crisis, and the results are shown in Table 4.6. According to the data in Table 4.6, there is always a positive correlation between internal and external financing and investment: both internal and external financing increase as investment increases, and vice versa. Before the crisis, investments by SMEs in China relied more on external financing (0.2292 vs 0.1526). However, both internal and external finance declined during the crisis, which is 0.0509 and 0.0856, respectively. Furthermore, in the aftermath of the crisis, both external and internal financing picked up significantly; internal finance reached 0.0927, and external finance up to 0.2056. In addition, by comparing the T-value of the impact of internal financing and external financing on investment in various periods, it can also be seen that external financing is at a high significance level. Therefore, as can be seen from regression models from various periods, Chinese SMEs are more dependent on external financing in every period, including during the financial crisis, which is contrary to hypothesis 2. Besides, the relationship between some control variables and investment is also worth noting. For example, the age of a company is not related to investment in pre-crisis and post-crisis. In contrast, during a financial crisis, the age of a company is positively correlated with its investment (0.0256). In addition, the impact of cash flow on investments increased during the financial crisis, reaching 0.0598 at a 1% significant level, which is more than twice as much as the pre-crisis period (0.0232). Table 4.6 Regression results over different time periods Pre-Crisis (2005–2007)

Crisis (2008–2012)

Post-Crisis (2013–2015)

Investment

Investment

Investment

InternalFinance

0.1526 (0.49)

0.0509 (0.62)

0.0927 (1.28)

ExternalFinance

0.2992 (1.56)

0.0856** (2.19)

0.2056*** (7.34)

CashFlow

0.0232 (0.41)

0.0598*** (4.37)

0.0353* (1.88)

Size

0.1179 (1.25)

0.0623*** (4.71)

0.0435*** (4.01)

Age

−0.1021*** (−2.85)

0.0256 (1.05)

−0.2981 (−1.42)

_cons

−1.5350 (−0.88)

−1.4225*** (−4.37)

2.8239 (1.05)

Firm

Yes

Yes

Yes

Year

Yes

Yes

Yes

N

84

1808

2954

R2

0.325

0.151

0.155

0.282

0.140

0.150

Adj.

R2

82

J. Mingte and B. S. Nayak

All in all, the regression results of these data show a positive correlation between internal financing and external financing and investment. However, China SMEs have always relied more on external financing than internal financing, which is inconsistent with hypothesis 2. Due to the instability caused by the financial crisis, Chinese SMEs may avoid turbulence by avoiding the risks posed by internal financing and obtaining external financing from policy support such as financial subsidies from the Chinese government, which is reasonable. Besides, a series of measures by the Chinese government to support SMEs’ external financing cannot be ignored. According to Wen’s (2009) government work report, the Chinese government has implemented a proactive monetary policy and significantly increased the supply of credit. According to statistics, the new credit in the first quarter of 2009 alone reached 4.58 trillion yuan, more than three times that of the same period in 2008. In this way, some government subsidies and incentives for banks to lend have made it easier for Chinese SMEs to lending during the crisis, thus securing external financing.

Conclusions The financial crisis of 2008 had a lasting negative impact on economies around the world. As an important driver of economic development, the investment and financing of small and medium-sized private enterprises during the crisis has received significant attention from the government and the industry. However, as SMEs lack good credit and performance guarantees, their borrowing restrictions on banks will also increase. Especially during the financial crisis, banks were reluctant to supply credit loans to SMEs to avoid the risk of some companies being unable to repay their loans. Therefore, this study aims to examine the influence of the financial crisis on SME investment and compare the impact of different financing methods on investments. As a developing country with a rapidly developing economy, China’s SMEs are also in a tough situation in the face of the financial crisis. Therefore, this study collected 4868 Chinese small and medium-sized listed companies as a sample in the CSMAR database to study their investment and financing from 2005–2015. Firstly, this study examines whether Chinese SMEs have reduced their investment during the financial crisis. In this section, the size of the investment is measured in terms of change in tangible fixed assets plus depreciation over beginning-of-year total assets. According to the descriptive analysis results of the different time periods, there was a marked decline in investment in SMEs in China in the years following the financial boom (2008–2012). The investment rate fell from 11.57% to 8.67% during the crisis, which is consistent with hypothesis 1. Besides, regression analysis results that take firm size, cash flow, and age as control variables also prove the significant negative impact of the crisis on SME investment in China (−4.48%). Secondly, this study examines the impact of SME financing types (internal finance and external finance) on investment in China during the crisis. The results show that there is a positive correlation between financing and investment. During the financial crisis, both internal and external financing of SMEs in China declined significantly,

4 Impact of Financing on Investment in Chinese SMEs During Financial …

83

which led to a decline in investment to some extent. However, according to the results of the multi-period regression, China SMEs have always relied more on external financing than internal financing, including during the financial crisis, which is contrary to hypothesis 2. The result shows that even though banks reduced their supply of loans to SMEs to avoid risk during the financial crisis, bank loans also are the main source of funding for SME investment in China. It is partly due to the Chinese government’s spending on SME development and a series of policies that estimate banks’ lending to SMEs, thus guaranteeing the possibility of external financing during the crisis. On the contrary, some internal sources of financing are more likely to reduce investment because of their difficulty in bearing the risks posed by the financial crisis. For example, as it is discussed above, retained profit financing and depreciation financing are the two most important financing methods for SMEs in China at present. However, the commercial difficulties caused by the financial crisis had a significant negative impact on the profits of SMEs, which led to a further devastating impact on internal financing. In this way, entrepreneurs will reduce internal financing to avoid financial risks. All in all, external financing (bank loans) has always been one of the most important financing methods for SMEs in China, which played a significant role in the investment of SMEs during the financial crisis. Therefore, policymakers should pay more attention to and improve the bank’s loan supply policy to private enterprises, such as stipulating minimum supply standards, guarantor system, etc., so as to mitigate the negative impact of the financial crisis on China’s SMEs investment decisions. Take the Chinese government’s support policy for SMEs in China during the 2008 economic crisis as an example. First, the China Banking Regulatory Commission (CBRC) requires five major banks to establish dedicated service outlets for loans to small businesses, ensuring that their credit growth is not lower than average. Secondly, the government provides funds to guarantee the credit of small and medium-sized enterprises, which not only improves the guarantee system but also protects the credit supply risk of banks. This study concludes with some recommendations for ways to deal with the financial crisis in the future. The first point is the mandatory requirements of the policy for banks to supply credit loans to SMEs or the preferential incentive policies for banks who are willing to lend to SMEs. For example, reducing the imposition of business tax on financial institutions that actively provide loans to SMEs. Secondly, the guarantor institution always remains important. In this way, local governments all around China can organize the establishment of guaranteed institutions, and the government can provide funds for guarantees, thereby reducing the market instability caused by the crisis. In addition, it is also important to establish a special section responsible for SME financing in order to achieve integrated services and thus improve the efficiency of approval. Also, the government needs to pay attention to the expansion and development of SME financing channels in China. For example, the government should promote the improvement of the area of the SME sector of the stock exchange and encourage all sectors of society to invest in innovative SMEs, such as the SMEs Development Fund. In this way, SMEs will have more channels to raise capital to avoid the risk of bankruptcy during financial crises or difficulties. However, the

84

J. Mingte and B. S. Nayak

government’s support for SMEs cannot be unlimited, as excessive help may affect the autonomy and creativity of Chinese SMEs. In this way, the government can impose appropriate loan requirements and terms on SMEs. For example, the government could require banks to provide different percentages of loans based on the number of patents owned by SMEs. Finally, focusing on the financial crisis caused by COVID-19 in 2020, the Chinese government has launched several fiscal policies to facilitate the financing of SMEs. First, the government asked state-owned banks to lower the interest rate on SME loans to reduce their financing cost. For example, the Chinese Bank provided SMEs with ¥3 trillion as credit liquidity. In addition, the CBRC also put forward a requirement for the proportion of state-owned bank credit in 2020 to increase by 30% year-onyear. Besides, banks have reduced the requirements for SME loan collateral, which has reduced their financing difficulties to a certain extent (Liu et al., 2022). It can be seen from these measures that the Chinese government has further strengthened its policy support for SME financing in China on the basis of the 2008 financial crisis.

References Abor, J. (2005). The effect of capital structure on profitability: An empirical analysis of listed firms in Ghana. The Journal of Risk Finance, 6, 438–445. https://doi.org/10.1108/15265940510633505 Abor, J., & Biekpe, N. (2009). How do we explain the capital structure of SMEs in sub-Saharan Africa? Evidence from Ghana. Journal of Economic Studies, 36, 83–97. https://doi.org/10.1108/ 01443580910923812 Agliardi, E., Agliardi, R., & Spanjers, W. (2016). Corporate financing decisions under ambiguity: Pecking order and liquidity policy implications. Journal of Business Research, 69, 6012–6020. https://doi.org/10.1016/j.jbusres.2016.05.016 Akbar, S., Rehman, S., & Ormrod, P. (2013). The impact of recent financial shocks on the financing and investment policies of UK private firms. International Review of Financial Analysis, 26, 59–70. https://doi.org/10.1016/j.irfa.2012.05.004 Akiyoshi, F., & Kobayashi, K. (2010). Banking crisis and productivity of borrowing firms: Evidence from Japan. Japan and the World Economy, 22, 141–150. https://doi.org/10.1016/j.japwor.2010. 03.001 Auken, H. V. (2005). Differences in the usage of bootstrap financing among technology-based versus nontechnology-based firms. Journal of Small Business Management, 43, 93–103. https:// doi.org/10.1111/j.1540-627X.2004.00127.x Beck, T. (2007). Financing constraints of SMEs in developing countries: Evidence, determinants and solutions, 35. Beck, T., Demirgüç-Kunt, A., & Maksimovic, V. (2008). Financing patterns around the world: Are small firms different? Journal of Financial Economics, 89, 467–487. https://doi.org/10.1016/j.jfi neco.2007.10.005 Berger, A. N., & Udell, G. (1998). The economics of small business finance: The roles of private equity and debt markets in the financial growth cycle. Journal of Banking & Finance, 22, 613–673. https://doi.org/10.1016/S0378-4266(98)00038-7 Carey, D., & Flynn, A. (2005). Is bank finance the Achilles’ heel of Irish SMEs? Journal of European Industrial Training, 29, 712–729. https://doi.org/10.1108/03090590510629849 Carlos, M. J. (2011). Social capital and dynamic capabilities in international performance of SMEs. Journal of Strategy and Management, 4, 404–421. https://doi.org/10.1108/17554251111181034

4 Impact of Financing on Investment in Chinese SMEs During Financial …

85

Chen, H.-J., & Hsu, H.-T. (2005). The role of firm size in controlling output decline during the Asian financial crisis. Journal of Economic development, 30(2), 103. Cousin, V. (2007) Banking in China, Palgrave Macmillan Studies in Banking and Financial Institutions. Palgrave Macmillan. Available at: https://ideas.repec.org/b/pal/pmsbfi/978-0-230-595842.html. Accessed 14 August 2022. Daskalakis, N., & Psillaki, M. (2008). Do country or firm factors explain capital structure? Evidence from SMEs in France and Greece. Applied Financial Economics, 18, 87–97. https://doi.org/10. 1080/09603100601018864 Duchin, R., Ozbas, O., & Sensoy, B. A. (2010). Costly external finance, corporate investment, and the subprime mortgage credit crisis. Journal of Financial Economics, 97, 418–435. The 2007–2008 financial crisis: Lessons from corporate finance. https://doi.org/10.1016/j.jfineco.2009.12.008 Fazzari, S., Hubbard, R. G., & Petersen, B. C. (1987). Financing constraints and corporate investment (Working Paper No. 2387). National Bureau of Economic Research. https://doi.org/10. 3386/w2387 Firth, M., Malatesta, P. H., Xin, Q., & Xu, L. (2012). Corporate investment, government control, and financing channels: Evidence from China’s Listed Companies. Journal of Corporate Finance, 18(3), 433–450. https://doi.org/10.1016/j.jcorpfin.2012.01.004. García-Pérez-de-Lema, D., Madrid-Guijarro, A., & Duréndez, A. (2022). Operating, financial and investment impacts of Covid-19 in SMEs: Public policy demands to sustainable recovery considering the economic sector moderating effect. International Journal of Disaster Risk Reduction, 75, 102951. https://doi.org/10.1016/j.ijdrr.2022.102951 Guariglia, A. (2008). Internal financial constraints, external financial constraints, and investment choice: Evidence from a panel of UK firms. Journal of Banking & Finance, 32(9), 1795–1809. https://doi.org/10.1016/j.jbankfin.2007.12.008 Gudov, A. (2013). Combining formal and informal financial sources: Russian early entrepreneurs’ and established firms’ structure of external financing. Journal of Chinese Entrepreneurship, 5(1), 39–60. https://doi.org/10.1108/17561391311297879 He, F. F. (2012). SME external financing difficulties and solutions. Corporation Research, 251–252. Jiang, J., Li, Z., & Lin, C. (2014). Financing difficulties of SMEs from its financing sources in China. Journal of Service Science and Management, 7(3), 196–200. https://doi.org/10.4236/jssm.2014. 73016 Kahle, K. M., & Stulz, R. M. (2013). Access to capital, investment, and the financial crisis. Journal of Financial Economics, 110(2), 280–299. https://doi.org/10.1016/j.jfineco.2013.02.014 Kasahara, T. (2008). Severity of financing constraints and firms’ investments. Review of Financial Economics, 17(2), 112–129. https://doi.org/10.1016/j.rfe.2007.02.009 Li, D. (2005). Review of SMEs’ international cooperation in Southern SuZhou. Business Modernization, 451, 33–35. Liu, X. (2009). Impacts of the global financial crisis on small and medium enterprises in the People’s Republic of China. https://doi.org/10.2139/ssrn.1627967 Liu, Y., Zhang, Y., Fang, H., & Chen, X. (2022). SMEs’ line of credit under the COVID-19: Evidence from China. Small Business Economics, 58(2), 807–828. https://doi.org/10.1007/s11 187-021-00474-9 Luo, P., Wang, H., & Yang, Z. (2016). Investment and financing for SMEs with a partial guarantee and jump risk. European Journal of Operational Research, 249, 1161–1168. https://doi.org/10. 1016/j.ejor.2015.09.032 Mac an Bhaird, C., & Lucey, B. (2011). An empirical investigation of the financial growth lifecycle. Journal of Small Business and Enterprise Development, 18, 715–731. https://doi.org/10.1108/ 14626001111179767 Norton, A. (2003). Basel 2-SMEs 0 Another tricky hurdle for business? Credit Management (pp. 40– 41). Nguyen, T., Nguyen, H.G. (Lily), & Yin, X. (2015). Corporate governance and corporate financing and investment during the 2007–2008 financial crisis. Financial Management, 44, 115–146. https://doi.org/10.1111/fima.12071

86

J. Mingte and B. S. Nayak

Petersen, M. A., & Rajan, R. G. (1994). The benefits of lending relationships: Evidence from small business data. The Journal of Finance, 49, 3–37. https://doi.org/10.1111/j.1540-6261.1994.tb0 4418.x Rousseau, P. L., & Kim, J. H. (2008). A flight to Q? Firm investment and financing in Korea before and after the 1997 financial crisis. Journal of Banking & Finance, 32(7), 1416–1429. https://doi. org/10.1016/j.jbankfin.2007.11.013 Serrasqueiro, Z. (2017). Investment determinants: High-investment versus low-investment Portuguese SMEs. Investment Analysts Journal, 46, 1–16. https://doi.org/10.1080/10293523. 2016.1246148 Wang, D.H.-M. (2010). Corporate investment, financing, and dividend policies in the high-tech industry. Journal of Business Research, 63(5), 486–489. https://doi.org/10.1016/j.jbusres.2009. 04.006 Wen, J. B. (2009). Full text: Report on the work of the government. Available at: http://www.npc. gov.cn/englishnpc/c2762/200903/4b76ad6093f44ded8ce92fbc7b134f16.shtml Wu, J., Song, J., & Zeng, C. (2008). An empirical evidence of small business financing in China. Management Research News, 31, 959–975. https://doi.org/10.1108/01409170810920666 Yang, C.-C., Baker, H. K., Chou, L. C., & Lu, B. W. (2009). Does switching from NASDAQ to the NYSE affect investment–cash flow sensitivity?. Journal of Business Research, 62(10), 1007–1012. https://doi.org/10.1016/j.jbusres.2008.05.006 Yang, S. (2022). Are private equity and venture capital helping small and medium-sized enterprises during the COVID-19 pandemic? Evidence from China. Economic Analysis and Policy, 76, 1–14. https://doi.org/10.1016/j.eap.2022.07.007 Yao, L., & Yang, X. (2022). Can digital finance boost SME innovation by easing financing constraints: Evidence from Chinese GEM-listed companies. PLoS One, 17(3), e0264647. https:// doi.org/10.1371/journal.pone.0264647 Zhang, D. (2006, January 18). ABC Bank to restructure by end of ’06. China Daily. Zhao, Y. (2009). Research on the approaches of the participation of China’s SMEs in international trade under financial crisis. International Journal of Business and Management, 5(1), 69. https:// doi.org/10.5539/ijbm.v5n1p69 Zubair, S., Kabir, R., & Huang, X. (2020). Does the financial crisis change the effect of financing on investment? Evidence from private SMEs. Journal of Business Research, 110, 456–463. https:// doi.org/10.1016/j.jbusres.2020.01.063

Chapter 5

Impact of the COVID-19 on Banks in China Boming Chen and Bhabani Shankar Nayak

Abstract This chapter analyses the impact of the new coronavirus on the profitability of banks in China. It argues that the new coronavirus had a significant impact on banks’ return on capital and non-performing loan ratios, but not on capital adequacy ratios. This proves that although the COVID-19 outbreak has led to a severe economic decline, the banking sector as a whole is still manageable through policy changes and the control of the outbreak.

Introduction The rapid spread of the COVID-19 led pandemic had significant impact on the lives of people and economic development worldwide. The manufacturing sector was halted in large numbers and the service and entertainment sectors were severely affected. Travel restrictions as a result of the pandemic have led to a sharp decline in tourism and social consumption and increased downward pressure on the economy. Banks are the mainstay of the modern financial industry as well as the functioning pivot of the national economy. With the highest share of financial institutions, the banking sector is an important force in driving the development of the social economy and assumes the social responsibility of providing basic financial services as well as promoting healthy economic development. This new corona-virus has made asset quality management difficult for commercial banks, precisely because the widespread spread of the virus has had to prompt governments to carry out mandatory regional blockades, businesses to temporarily suspend operations, etc. This has left individuals or businesses without a source of income, but costs for businesses have continued to rise. So, banks and their customers are also under enormous pressure. B. Chen University of Glasgow, Glasgow, Scotland, UK B. S. Nayak (B) Business School for the Creative Industries, University for the Creative Arts, 21 Ashley Rd, Epsom KT18 5BE, UK e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 B. S. Nayak (ed.), China: The Great Transition, https://doi.org/10.1007/978-981-99-0051-0_5

87

88

B. Chen and B. S. Nayak

As a result, the new coronavirus has created a serious downturn in the economies of various countries, business conditions have gradually declined, the liquidity cycle has been extended and the credit risk for businesses has increased significantly, naturally increasing the possibility of businesses and individuals defaulting on their debts because they are unable to repay their obligations. This affects the non-performing loan rates of commercial banks, making the NPL rate higher. As the pandemic began to strike in the US, UK, France and other Western countries, leading to a serious blow to capital markets, cross-border investment and industrial chains, and bringing a considerable impact to world trade, this made the economic operation of international commercial banks difficult, with operating pressures and external risks rising rapidly; business growth was slow, profitability levels plummeted, loss provisions increased significantly and low-profit banking institutions fell into huge economic crisis. In order to face these risks, banks in the Chinese banking system, as well as worldwide, should immediately make strategic adaptations to make the best possible solutions to prevent a banking crisis, in the present and in anticipation of a future with the pandemic. With a focus on China’s top-growing banks, the research effectively analyses government policy changes and commercial banks’ risk protection in the face of the unexpected crisis since the start of the new corona-virus outbreak. In the immediate period leading up to the virus outbreak, the commercial banks in China went into a shutdown period, as the government temporarily restricted people’s travel, disrupting the normal economic development and further increasing the financial burden on the commercial banks by reducing their profits significantly. This study chapter analyses in detail the different aspects of the performance of the impact of the COVID-19 on Chinese banks from different perspectives and suggests timely solutions for banks. Emphasis would be placed on determining the trend of interest rate movements of commercial banks by finding out the revenue capacity, net profit, etc. Comparison of banks in China over different periods to collect information on fluctuations in bank lending rates. It is also possible to determine whether the operations of banks have been affected by the new coronavirus by comparing the capital adequacy ratios of banks in different parts of the world. The risk of transmission of the COVID-19 outbreak was confirmed as “high” and meeting the criteria for an international public health emergency (World Health Organization, 2020) through an outbreak meeting convened by the World Health Organization on 30 January 2020. On 28 February, it was announced that the global risk and risk level for corona-virus transmission had been raised to “very high” (WHO, 2020). On 30 March, it was announced that the new corona-virus disease had collapsed health systems in many countries and that significant human and material resources would be needed to stabilize the health care system, thus declaring that the new corona-virus pneumonia virus pandemic had spread widely around the world (Ghebreyesus, 2020). Recent information released by the World Health Organization indicates that the spread of the New Corona-virus is likely to be more difficult in the second year than in the first. It is clear from this that the impact of the epidemic would be long term and complex.

5 Impact of the COVID-19 on Banks in China

89

According to China Daily, GDP growth in the US fell by 4.8% in the first quarter of 2020, and the unemployment rate in April was the highest since the Great Depression at 14.7%. In April, the unemployment rate reached its highest level since the Great Depression at 14.7% and 44 million people have filed for unemployment benefits since mid-March; the impact of the epidemic on the UK, Spain, Italy, France and other countries is undoubtedly a heavy shock to the already weak economy of the Euro-zone. The European Central Bank predicts that real GDP in the Euro-zone will fall by 8.7% in 2020 (Peng, 2022); Japan’s economy was in a sustained slump before the epidemic and the epidemic is a serious blow to the Japanese economy, which will be in recession to a greater extent than other developed economies and the recovery process will be more difficult. According to Statistics Bureau data on China’s GDP (Li & Hou, 2022), GDP growth reached 11.0% year-on-year in the first quarter of 2003 during the SARS epidemic and then fell to 10.0% when China was in the midst of rapid economic development following its accession to the WTO, while China’s economic development has slowed significantly during the COVID-19, with 2019’s GDP growth of 6.1% year-on-year and a lower GDP of 6.8% year-on-year in the first quarter of 2020 due to the impact of the pandemic. If the spread of the new corona-virus are not controlled in time, the IMF’s forecast for the global economy in 2022 declines (Ma & Yu, 2022). Specifically, global economic growth is expected to decline to 3.6% in 2022, down from 6.1% in 2021. Among the developed economies, GDP growth is expected to fall to 3.7% in the US from 5.7% in 2021, 2.8% in the Euro-zone from 5.3% in 2021, 3.7% in the UK from 7.4% in 2021, and 2.4% in Japan from 1.6% in 2021. Among the emerging market economies, China’s GDP growth is expected to fall to 4.4% from 8.1% in 2021 and India’s GDP growth is expected to fall to 8.2% from 8.9% in 2021 (IMF, 2022). Despite this, the epidemic did not only affect the decline in GDP of individual countries, but also the volatility of global financial markets. As volatility soared, market liquidity deteriorated significantly, including in the US Treasury market, which is traditionally seen as deeper, and this in turn led to sudden movements in asset prices. In order to maintain the stability of the international financial system and sustain the world economy, central banks around the world began to propose new policy approaches to prevent significant economic declines. First, according to a report provided by the IMF (Danninger et al., 2022), central banks in half of the countries in developing markets and low-income countries as well have reduced their policy rates. The impact of the rate reductions would be strengthened by direction from central banks on the forward path of monetary policy and an enhanced asset acquisition program. Second, additional liquidity has been provided by central banks to the financial market, for example through public market operations. Thirdly, some central banks have accepted to reinforce the availability of USD liquidity by means of exchange line facilities. Finally, IMF reports describe central banks as having restarted schemes that they used during the financial crisis globally and introduced a new series of broad-based schemes, which have included buying higher-risk assets such as corporate bonds (Adrian & Natalucci, 2022). Through effectively stepping in as the ‘buyer of last resort’ for these securities markets and assisting in keeping pressure on the rising

90

B. Chen and B. S. Nayak

cost of credit in check, governments are making sure that families and companies in particular are continuing to have available credit at acceptable prices. Therefore, for fiscal policy as seen in KPMG (2022), various countries have actively introduced a series of fiscal support policies including tax cuts, investment and refinancing to boost their economies. As reported by Chen and Huang (2022) The United States: The US Treasury will launch an economic stimulus package of approximately US$1 trillion, which may include: US$500 billion to US$550 billion for tax cuts; US$200 billion to US$300 billion to support small and micro enterprises; and US$50 billion to US$100 billion to support aviation companies and related industries. In addition, the US government may have US$250 billion to distribute directly to the general public in the America. According to Yang (2022) the UK: The UK Finance Ministry has proposed a £30 billion economic stimulus package, with measures such as partial tax exemptions for small businesses and lowering the threshold for claiming sick pay. Of this, £7 billion will be used to provide help for businesses and individuals, £5 billion for the NHS and other public services to combat the pandemic, while another £18 billion is to be used for some other additional stimulus measures. For China, the country where the outbreak of the new corona-virus first began to spread, the impact was most significant. As announced by the Chinese Ministry of Finance, the Chinese government has decided to increase the policy hedge to perform the key role of stabilizing the economy in three different ways, creatively setting up a direct fiscal funding mechanism to effectively respond to the shock of the pandemic. Firstly, the Chinese government has raised the deficit rate to over 3.6%, which further strengthens fiscal macro-control (Liu, 2020). The benefits of raising the deficit rate are, on the one hand, to clearly release positive signals, stabilize and boost market confidence; on the other hand, to actively hedge against the impact of revenue reduction and expenditure increase caused by the new corona-virus, enhance the central fiscal macro-control, and make an important and special contribution to effectively respond to the influences of the new corona-virus, protect market players, preserve employment and people’s livelihood, and promote the economy to achieve resumed growth relatively quickly. Secondly, the scale of investment by the Chinese government was expanded to steady the fundamentals of the economy. The Chinese government issued RMB 1 trillion in special treasury bonds to fight the pandemic (Song, 2022), for local public health and other infrastructure construction and expenditure related to fighting the pandemic, to speed up the remediation of outstanding shortcomings exposed by the pandemic and to protect the expenditure needs of China’s pandemic prevention and control. Thirdly, the ADB Briefing Report reported over RMB 2.3 trillion in new tax cuts and fee reductions during the high virus period in 2020, effectively helping to ease the difficulties of enterprises. The Chinese government issued and implemented seven consecutive batches of 28 tax and fee reduction policies in the face of relatively difficult fiscal balances. The advantages of this are the granting of property tax and urban land use tax hardship relief to enterprises in industries more affected by the pandemic; measures to support enterprises in resuming work and production, such as improving tax rebates for exports, exempting port construction fees for imported and exported goods, halving

5 Impact of the COVID-19 on Banks in China

91

the levy on the ship oil pollution damage compensation fund and other policies to support stable foreign trade, as well as introducing tax policies to expand auto consumption; specifically focusing on helping small and medium-sized enterprises in areas with high levels of new corona-virus outbreaks. For monetary policy, central banks around the world have announced interest rate cuts and other accommodating monetary policies to increase liquidity and provide effective support for the financial system. For example, according to China Development Network (Zhang & Zhao, 2022), the US Federal Reserve directly lowered the target range of the federal funds rate to 0%~0.25% through two emergency interest rate cuts of 50 basis points and 100 basis points respectively on 3 and 16 March and launched a US$700 billion quantitative easing program to support the financial markets. In addition, the Federal Reserve announced the establishment of the Commercial Paper Financing Facility (CPFF) to support household and business credit, a tool that the Fed has once again restarted after the 2008 financial crisis. The Treasury Department will also provide US$10 billion in credit protection to the Fed from the Treasury Exchange Stabilization Fund (ESF) and approved the establishment of the Money Market Mutual Fund Liquidity Facility. As reported by China Economic Network (Jiang, 2022), the Bank of England raised interest rates by 25 basis points at its February and March rate meetings respectively, resulting in a rapid increase in the benchmark interest rate from 0.25% to 1%. During the February rate hike, four members of the Bank of England’s Monetary Policy Committee called for a 50 basis point hike instead of 25 basis points, so the GBP quickly adjusted upwards once the news of the hike came out (He, 2022); during the March rate hike, the same 25 basis points were raised, but one of the nine members did not support the hike and the GBP quickly dived. The CEIC (2022) database shows that in China, the Central Bank of China is also injecting liquidity into the market by adjusting the reserve ratio. From January to May, the reserve requirement ratio was cut three times from 10.4% to a five-year low of 9.4%. Based on central bank data, a total of 1.75 trillion yuan of base money was injected, providing long-term liquidity support to the market. It is worth noting that the reserve ratio for small and medium-sized depository institutions was cut by 0.5% twice in April and May to provide credit support to small and medium-sized enterprises. Such a series of adjustments were aimed at fulfilling the dual functions of monetary policy tools, both aggregate and structural, maintaining a reasonable abundance of liquidity, enhancing the stability of aggregate credit growth, promoting a further decline in real lending rates at a lower level, improving the funding structure of financial institutions, enhancing long-term stable sources of funding for financial institutions, strengthening the capacity to allocate funds and increasing support for the real economy. At present, most small and medium-sized enterprises (SMEs) have to face an abrupt break in their financial chains, which may hinder their normal operations or even result in bankruptcy, due to the impact of COVID-19. However, Chinese banks have implemented lax lending policies for some SMEs in order to encourage their business to develop steadily down the road, but once the working capital of these

92

B. Chen and B. S. Nayak

enterprises becomes problematic or irremediable, the credit risk of the banks would be further expanded, inflicting huge losses on the banks. According to the financial results released by the major UK banks (Wang, 2020), HSBC reported a net profit of only US$4.3 billion in the first half of 2020, down 65% year-on-year, and Barclays reported a net profit of £1.3 billion in the first half of the year, substantially lower than the £3 billion reported a year earlier. In the same period Chinese commercial banks experienced a precipitous fall in commercial banking profits in the second quarter of 2020, a fall that was 9.45% faster than the same period in 2019 (Sun et al., 2022). This shows that commercial banks around the world suffered different sizes of hits to their economies after the initial impact of the outbreak, and that different types of commercial banks have significantly different profitability, financial provisioning capacity and resilience to risk, and demonstrate different net profits. In China, there are seven main types of banks: central banks, policy banks, stateowned commercial banks, joint-stock commercial banks, urban commercial banks, rural credit cooperatives and rural commercial banks. From the data released by the Chinese government for the first three quarters of 2020 (Pang, 2020), the net profit growth rate of large commercial banks in China declined by 8.5%, shareholding commercial banks by 7.34% and rural commercial banks by 11.6%, but the net profit of private and foreign commercial banks grew against the trend in the second quarter, mainly because of their relatively small size volume. However, on the whole, the major commercial banks experienced a significant but declining net profit. The decrease in commercial bank profits was caused by a combination of many factors (KPMG, 2022). The first point is that, after being forced to operate temporarily as a result of the pandemic, commercial banks’ business outlets were shut down directly and all offline business ceased. This has led to commercial banks in the service of the real economy to restore the development and their own business process is greatly restricted, the volume of business sharply reduced, customers are afraid of the risk of infection and consequently less to go to the business office for business, which would be facing a reduction in profit sources, while staff wages, daily operating expenses and other fixed costs have not been reduced. On the contrary, the measures taken to prevent the proliferation of the epidemic require new staff, increased disinfection, etc. but raise new expenses for epidemic prevention projects. These invariably increased the various financial burdens on commercial banks in general. The second point is the rapid decline in asset quality of banks. Under the impact of the pandemic, credit risk pressures have multiplied, and small and medium-sized banks are facing difficulties. According to the PWC report (PWC, 2022), this predicament is attributed to the fact that banks’ customers are affected by the pandemic prevention and control, while Chinese banks’ customers are mainly divided into three categories: individuals, legal entities and governments. The specific impact manifested itself in the loss of jobs for individuals, the suspension of work and business for legal entities, suspension of government projects and the inability to complete them on time, all of which ultimately resulted in a backlog of funds, sluggish flows, the inability to recover commercial bank loans on time and a rising number of non-performing loans. These effects directly block the customer’s source of funds and significantly decrease their ability to repay the loan on time, which extends to

5 Impact of the COVID-19 on Banks in China

93

problems with the recovery of commercial bank loans. If a bank’s customers fail to repay their loans on time or go insolvent, the bank’s stock of assets becomes non-performing, which in turn significantly drives up the level of non-performing assets of the bank. According to the research, the global commercial disposal of nonperforming assets has increased significantly compared to previous years, reflecting that the scale of non-performing assets is expanding globally. The new coronavirus has affected most industries to varying degrees, particularly the banking sector, which has affected almost all offline business and has seen a massive reduction in offline bank branches. In China’s banking sector, for example, the large number of offline branches is a major feature of China’s banking sector, especially large commercial banks. As the main channel and venue for banking services, offline branches are an important reflection of banks’ competitiveness (Wang, 2022). By increasing the number of branches, banks are able to attract and serve customers, achieve scale expansion and increase their market share. However, it is also important to see that offline branches are the most high-cost, difficult to manage and risk-concentrated service channels for banks. The number of branches of China’s six largest state-owned banks are all down from the end of 2019–2021, according to data from the banks’ annual reports (Yin, 2022), with a combined reduction of over 2,000 domestic establishments in 2 years, a 1.7% drop. This can be seen to have undoubtedly dealt a considerable blow to the Chinese banking sector. But with almost the entire industry being affected by the new coronavirus, the digital sector is instead growing rapidly. During COVID-19, some traditional banks tried to provide a package of services including credit, financing, settlement, treasury and supply chain finance to corporate customers through telecommuting, while also opening up a green channel for online loans. Payment data for 2019–2020 released by the People’s Bank of China showed that the number of online banking transactions by Chinese banking financial institutions reached 163.784 billion in 2019, up 7.42% year-on-year, with a transaction value of RMB 1657.75 trillion; the number of mobile banking transactions reached 121.451 billion, with a transaction value of The number of mobile banking transactions reached 121,451 million, with a transaction value of RMB 335.63 trillion, representing a year-on-year increase of 38.88%. The industrywide off-counter rate was 89.77%, with several state-owned banks and shareholding banks having a counter transaction replacement rate of over 90%. Data given by China Securities shows that 123.220 billion mobile payments were made in China in 2020, amounting to 432.16 trillion RMB, an increase of 21.48% and 24.50% yearon-year respectively. It is evident that as the social environment continues to change, people are more inclined to engage in online consumption activities, and this rising trend presents a good opportunity for banks under the influence of the COVID-19 to transform to digitization. This research takes into account the different factors that the epidemic would affect the operation of Chinese banks, such as profitability factors, size factors, asset quality factors, funding factors, capital adequacy factors and bank valuation factors. The main objective is to investigate the profitability of the top-ranked banks in China, as profitability is a measure of the profitability and profitability of a commercial bank over a certain period of time, which is the basis for the survival and development

94

B. Chen and B. S. Nayak

of a commercial bank and is an indicator of great interest to all parties. Profitability ratios are also commonly used in financial analysis and are divided into gross margin, profitability, return on assets, return on capital and return on equity. An example of the top 5 banks in China is used to develop the analysis, collect and collate information. Finally, this information has been used to make some recommendations that could improve the development of Chinese banks.

History of the Chinese Banking System The traditional business development model for banks is that banking profits come mainly from branch deposits and loans in China. China’s banking system is vital to the operation of the Chinese economy and is the primary channel for distributing savings to investment opportunities. With the expansion of the Chinese economy over the last decade, Chinese banks now appear in the ranking of the world’s largest banks because of the rapid growth of banking activity in China. Between 2010 and 2020, China’s banking system expands significantly in size, with the number of branches expanding to a phenomenal 400,000. According to the most recent World Bank ranking, the top 5 banks in China are Industrial and Commercial Bank of China (ICBC), China Construction Bank (CCB), Agricultural Bank of China (ABC), Bank of China (BOC) and Bank of Communications (BCOM). The Chinese government owns a majority shareholding in these banks and combined they account for half of the assets of the Chinese banking system. The China Banking Regulatory Commission, in an effort to improve the efficiency of China’s banking sector, announced in 2018 that small banks would be allowed to open branches across the country (Guiso et al., 2004). This initiative has broken the monopoly of state-owned banks in China and has resulted in a significant growth in the Chinese banking sector as a whole, as well as a dramatic increase in financial standards. The development of China’s banking industry has broadly gone through three periods: the period of exploring the construction of a banking system in line with China’s national conditions, the period of building a socialist banking system with Chinese characteristics and the construction of a modern banking system in China (Xi, 2017). In 1948, the Central Government of China decided to merge the North China Bank, the North Sea Bank and the Northwest Peasant Bank to form the People’s Bank of China, marking the first step in the construction of a new Chinese banking system. During the period from 1949 to 1978, although the banking sector encountered many difficulties in development, there was a dramatic increase in the level of banking business. The balance of deposits in the banking sector increased rapidly from RMB 2.645 billion to RMB 115.501 billion, and the balance of loans increased from RMB 864 million to RMB 189.042 billion (Su, 2007). The development of the bank’s business has strongly supported the growth of various sectors of the national economy. The second step was China’s decision to shift work focus to modernization in 1978, which not only marked the beginning of China’s economic reform, but also

5 Impact of the COVID-19 on Banks in China

95

the modernization of the Chinese banking system. Firstly, a banking system was established with the People’s Bank of China as the central bank and the four major state-owned banks, namely, ICBC, Agricultural Bank, China National Bank and China Construction Bank, as specialized banks. Secondly, the Agricultural Bank of China was re-established to support the development of agriculture; the Bank of China was re-established to meet the needs of the country’s opening up to the outside world and the development of international financial services; and the China Construction Bank was re-established to promote business related to urban capital investment. In January 1984, the State Council decided to establish the Industrial and Commercial Bank of China (Qing, 2008). The Industrial and Commercial Bank of China (ICBC) took over the commercial and industrial credit and savings business previously handled by the People’s Bank of China, and subsequently the People’s Bank of China (PBOC), which became a financial institution exclusively responsible for performing central banking functions and supervising various financial activities. In 1986, the first joint-stock commercial bank was established in China, the Bank of Communications (Niu, 2015), which signified the continuous exploration of the market in China’s banking sector. This period allowed for the speedy expansion of China’s banking sector, both in terms of institutional improvements and the increase in institutions, as well as in terms of the expansion of the scope of business and the increase in content. Although this phase led to an increasingly commercialized banking sector in China, the uncertainty of bank performance and lending left many Chinese companies in a loss-making position at the end of the 1990s. The majority of Chinese banks’ loans were taken up by state-owned enterprises, which continued to finance their activities by means of creditworthy bank credits, but these enterprises were ultimately unable to repay these loans (Lardy, 1999). The sharp increase in non-performing bank loans contributed to the equity market and property market prosperity in China in the early 1990s and the ensuing economic depression. The sudden increase in infrastructure investment allowed for a sharp increase in money and credit allocation, causing inflation to occur in China in 1984 (Hu, 2022). In response, the People’s Bank of China introduced a macro policy of tightening the money supply, gaining experience for China’s macro control thereafter. In order to further strengthen banking supervision, the People’s Bank of China has introduced a series of systems to improve banking supervision in the light of the development of the banking sector and the economic and financial situation. For example, in 1987(Luo & Wang, 2022), the People’s Bank of China introduced a cost rate, a comprehensive expense ratio and an insurance working capital ratio for professional banks, as well as the autonomy of business operations and the establishment of internal structures. These measures prompted the transition of the internal management mechanism of specialized banks from an administrative institution to an entrepreneurial system, facilitating their functioning in accordance with the principles of “self-management, self-financing, self-risk bearing and self-development”. The final step was from 1992 to 2017, when the Chinese banking system moved from a stage of market-oriented reform to a stage of globalization and reform. In December 2001, China formally joined the World Trade Organization, which provided a transitional period for opening up the banking sector to the outside world.

96

B. Chen and B. S. Nayak

As a result, accelerating the globalization of the banking system became an inevitable choice. China’s banking sector began to enter a high growth period and a series of measures were implemented, such as the stock reform and listing of state-owned commercial banks; actively supporting the development of small and medium-sized enterprises and improving credit; accelerating the innovation of financial products; strengthening the supervision of the banking sector and expanding the financial opening to the outside world.

Impact of COVID-19 on the Chinese Banking Sector Since COVID-19 began spreading widely around the world, the virus has had varying degrees of impact on economies in different parts of the world. The implications of COVID-19 for the Chinese banking sector could be divided into three areas: shortterm, long-term and systemic risk. In China, the impact of the new coronavirus led to some cities having to be temporarily locked down, which also caused a sharp rise in unemployment and a rapid economic decline in a short period of time. The short-term impact on China’s banking sector included the closure and semiclosure of all industries, including banks, in areas severely affected by the pandemic, with the exception of basic public health care and the food industry, which resulted in the suspension of all offline bank branches and the cessation of all offline banking operations. The outbreak of the COVID-19 is somewhat similar to the global economic crisis of 2008, and a synthesis of the previous literature on systemic risk in banking could lead to a possible breakdown of the banking system in China or even globally if timely measures are not taken to remedy the situation (Adrian & Brunnermeier, 2016). The impact of the new coronavirus has been responsible for the closure of offline bank branches, a significant reduction in banks’ operating income and a rapid decline in net interest rates. Because the incomes of businesses and residents were greatly reduced by the impact of the pandemic, this also caused the number of bank deposits to fall dramatically in the short term, and thus the cost of bank debt to keep increasing. Restrictions on people’s travel directly reduced the number of short-term bank loans, which also had a direct impact on the decline in lending rates for banks. The data shows that on 20 February 2020 the one year LPR and the five year LPR were 4.05% and 4.75% respectively, down 10BP and 5BP respectively from the previous month (Dong, 2022). In March of the same year because of the fall and rebound in interest rates, which resulted in a significant fall in credit rates. The government would expect a downward adjustment in LPR in April of the same year. In the long term, COVID-19 broke out in China in January 2020 and started spreading globally from February. This not only had a significant impact on the world economy, but also plunged global financial markets into instability. Business development in the Chinese banking sector has long been characterized by an overreliance on collateral at the expense of in-depth analysis of customer qualification profiles. Although the business is diverse, the industry could also be affected by the

5 Impact of the COVID-19 on Banks in China

97

new corona-virus, the stagnation of sales in the property sector and the tightening of financing channels (Deloitte, 2022). At a time when the banking sector is facing a shock to businesses in the sector, a decline in performance and a sustained deterioration in the quality of bank lending assets. Central banks and financial regulators have had to introduce new policies to prevent the collapse of corporate and personal assets, which could further cause economic crises. The specific operations include: on 3 February 2020, the Central Bank conducted a RMB 1.2 trillion reverse repurchase operation and lowered the 7-day and 14-day reverse repurchase rates by 10 basis points; on 17 February 2020, the Central Bank conducted a RMB 200 billion medium-term lending facility (MLF) operation and a RMB 100 billion 7-day reverse repurchase operation, and lowered the MLF rate by 10 basis points. The 1 year and 5 year LPR released on 20 February 2020 were also cut by 10 and 5 basis points respectively (An, 2020). These operations have to some extent relieved the liquidity pressure faced by the banking sector, ensuring a certain amount of financial market liquidity and steadying the volatility of money market interest rates. Over the long term, the pandemic has brought about a structural impact on the microscopic subjects of the social economy, as well as a certain impact on the industrial chain, the supply chain and the transformation of the entity economy. The adjustment in the growth of the banking sector would cause a shift in funding demand, as the banking sector would face adjustments in the asset structure and funding allocation. Reasons from the monetary policy, the Central Bank will continue to guide to reduce the cost of financing for the real economy, while the Central Bank will also release long-term stable funds by way of downgrading and lowering interest rates. The banking sector will have sufficient funds to facilitate the recovery of the real economy in the aftermath of the epidemic, thus benefiting the long-term entity economy (Carletti et al., 2022). From the fiscal policy side, the government would advance tax and fee reduction, and promote active fiscal policies such as special bonds to support the entity economy and maintain stable growth of the entity economy. In the end, in terms of the systemic risk of the new corona-virus affecting China’s banking sector, a large proportion of bank lending is taken up by corporate loans. This is because the higher the proportion of third sector credit influenced by the pandemic, the higher is the exposure of banks to risk. The blockade of areas precisely because of the epidemic has significantly affected the transport sector, postal services and some of the commercial and retail sectors (Ozili & Arun, 2020). As a result, these enterprises account for a large proportion of bank loans. During the pandemic there is a high risk of bankruptcy due to the inability to operate normally. These enterprises happen to be the main clients of rural commercial banks, therefore the banking sector is under great pressure in terms of economic systemic risk. However, in comparison to corporate loans, business in personal loans is much less affected by the pandemic (Chen et al., 2020). But for families and industries that work regularly there are difficulties in operating. In conclusion, the large and powerful banks are significantly less affected by the pandemic than the small and medium-sized banks, but the reduction in income of the small and medium-sized banks could affect the functioning of the large banks.

98

B. Chen and B. S. Nayak

Methodological Framework of the Study The study follows the methodological traditions outlined by Apuke (2017), supporting or rejecting existing theories can also be a part of a research process. Leedy and Ormrod (2001) evaluated that collection and evaluation of data to understand and analyze different events is also an integral part of the research studies. Williams (2011) illustrated how collection of reliable information and carrying out data analysis can be determinant to the overall success of a research process. This is the reason why, as explained by Apuke (2017), a quantitative research method is adopted by researchers as it takes account of a comprehensive data collection and analysis. Usage of numerical information and introducing statistical/math models can be significant in ensuring reliability and validity of information. The explanation of a phenomenon and clarifying problems can be easily and effectively carried out with the help of statistical data analysis (Aliaga & Gunderson, 2002). Hence, the process of data collection that can help in accepting or refuting claims can be effectively carried out through quantitative methods which have been adopted in course of this research.

Study Variables The study takes account of a regression-based analysis. One of the first steps that a researcher needs to undertake in such research include finalizing study variables. In this case, the following shall make the variables:

Dependent Variables In the regression model undertaken for the study, ROA (Return on Assets) is the dependent variable in this study. ROA refers to the measure of profitability of a company compared with the total assets (Petersen & Schoeman, 2008). Since the study has taken account of information of ten Chinese banks, this variable shall be critical in measuring profitability and carrying out comparative analysis. The formula to calculate ROA has been shown as follows: Return on Assets (ROA) =

Net Income Total Assets

With a higher ROA, the overall efficiency of a company is demonstrated. Ichsan et al. (2021) explain that ROA is one of the ratios that demonstrate both profitability and efficiency of a business. Hence, depiction and assessment of a firm’s asset utilization and profitability can both be determined through this ratio. Independent Variables: This research has taken account of four independent variables namely: CAR (Capital Adequacy Ratio), NPL (Non-Performing Loan), LDR

5 Impact of the COVID-19 on Banks in China

99

(Loan to Deposit Ratio) and ER (Efficiency Ratio). All these ratios have been calculated based on the information provided by the banks in the annual reports. The description of the independent variables has been provided as follows: . Capital Adequacy Ratio: As explained by Fatima (2014) CAR can be defined as a measure through which a bank’s risk weighted capital exposure is evaluated. It helps in measuring the availability of available capital of the bank and has been used to protect the stability of the global financial systems and secure creditors and investors. There is a need for using this measure as part of the study due to the topic of research. Recession and slowdown in economy caused by Covid-19 impacts overall profitability of banks and results in losses for the bank as borrowers are not able to repay loans. Hence, management of capital ratios can protect a bank against possible defaults. A higher CAR demonstrates efficiency and profitability of the banks (Bitar et al., 2018). This has been calculated by taking account of the following ratio: CAR =

Tier 1 Capital + Tier 2 Capital Risk Weighted Assets

In regards to the above formula used for the calculation of CAR, Fatima (2014) explains that Tier I capital has the ability to absorb a reasonable number of losses without having the need for the bank to cease operations and trading. Tier 2 capital refers to the ability of the bank to absorb any losses in case of liquidation proceedings. However, there are a few limitations of using CAR as an indicator of the bank’s profitability and efficiency. One of the critical limitations of CAR is the fact that it does not take account of expected losses during bank runs and financial crisis which can have an impact on the capital and cost of capital (Fatima, 2014). . Non-Performing Loan: In simple words, loans are assets in the financial statements of a bank. The borrowers are debtors who avail loans for different purposes. These borrowers avail loan and repay them with interest which is the most critical aspect of a bank’s cash flow and profitability. However, when a borrower defaults repayment of interest or loan in a given time line, such loan becomes non-performing (Messai & Jouini, 2013). As explained by Sharma, in the banking industry, a loan can be deemed as non-performing in circumstances where no interest or principal is repaid for a period of 90 days. As further underlined by Ari et al. (2021), the overall impact of Covid-19 on macroeconomic situations results in increasing total non-performing loans and impact the financial performance of the lender. In the context of Chinese banks, this could be one of the critical determinants to find out whether the overall profitability and financial position of the banks has been influenced by the pandemic. This has been calculated by taking account of the following formula: NPL =

Nonperforming Loan Total Loan

100

B. Chen and B. S. Nayak

A higher ratio is not preferred because it refers to a higher proportion of nonperforming loans as compared to total loans forwarded by the bank. Hence, for demonstrating profitability and efficiency of the bank, the NPL ratio should be low (Messai & Jouini, 2013).

Data Collection The sample collected for carrying out quantitative data analysis include ten five Chinese banks. The data considers 12 quarters starting from the last quarter of 2019 to the first quarter of 2022. Therefore, data was collected for a sample of 50 bank quarters. It has been decided to consider the last quarter of 2019 as the pre-Covid period and the period when the outbreak is just beginning, the four quarters of 2020 are described as the peak COVID-19 outbreak period, and the four quarters of 2021 and the first quarter of 2022 are described as the declining COVID-19 outbreak period. The research, therefore, focuses on the year 2020 when the impact of Covid-19 was rather the most drastic. All the ratios have been calculated after analyzing the official numbers posted by the ten Chinese commercial banks.

Models In order to carry out a quantitative analysis of the data, regression models have been used and implemented in this research. Furthermore, a number of tests for ensuring reliability and validity of the data used in the research have been also considered. The models used in the study are as follows.

Multiple Linear Regression and OLS Method In regard to finance and econometric studies, usage of multiple regression and OLS method can be determined as the most-utilized tools. The best aspect about using these methods is their simplicity and how the tools can help in estimating relationship between dependent and independent variables (Schmidheiny, 2021). As per multiple linear regression technique, different explanatory variables (as described in the previous part of the research) can be used to predict the outcome of the dependent variable. The formula for the OLS regression model is: y = β0 + β1 x + u x is the explanatory variable, y is the explanatory variable, u is the error term.

5 Impact of the COVID-19 on Banks in China

101

To test the hypothesis in this research, OLS method has been implemented to analyses the impact of the pandemic on the performance of Chinese banks.

Context of the Study In regard to finalizing the methods for data collection and analysis in this study, there were a wide range of consideration and debates. There are primarily two kinds of data collection methods: primary and secondary data. In this case, the decision to use secondary data has been undertaken by taking account of the hypothesis and evaluating that information collected directly from sources through interviews, surveys, and other sources shall not help in moving the study in the right directly. Hence, a decision to use secondary data was undertaken. There was also an issue in regards to the mismatch of the type of data as the information available (of the banks) was not in daily and monthly periods but only in quarters and annual forms. Since a comparative analysis and regression assessment with the number of Covid19 cases was to be carried out, it was decided that the quarterly information for a period of four years for five Chinese banks. The comparison with the number of Covid-19 cases during the period was also carried out by using the same period of time. Furthermore, usage of a quantitative data analysis seems the only correct option in the given circumstances after taking account of different aspects such as the research question and hypothesis. The advantage of using quantitative data is the fact that it helps in providing a clear statistical information based on which a decision can be placed (Johnson, 2002). It was critical to make a separate and standalone model for study based on regression. Rather than the mere usage of descriptive statistics, it was important to take account of statistical model to come up with better conclusions. The methodological choices made in this study was based on the depth of research topic and questions. For testing hypothesis, it is critical that a decisionmaker should take account of a quantitative research method which has been considered in this case along with a detailed description of data collection and analysis methods.

Analysis and Findings This section describes in detail the results of applying the OLS model to work out the impact of COVID-19 on the different profitability of the bank. The second section presents the tables that emerged from the application of the model and provides a brief analysis. Then the results of the overall data are analyzed and summarized.

102

B. Chen and B. S. Nayak

Analysis of Data Results During the COVID-19 outbreak in China, the local government decided to adopt a lock-down policy, restricting people’s travel to curb the spread of the virus, allowing only essential retail shops such as pharmacies and supermarkets to be open, while all other social interaction was banned. This policy dealt a direct blow to the consumer market in the infected areas and disrupted society and economic activities in China. Therefore, when using the OLS model to analyses the data, the social consumption growth rate (SCGR) was used as an indicator to quantify the impact of the new coronavirus, with the social consumption growth rate as the independent variable and the banks’ return on assets, non-performing loan ratio and capital adequacy ratio as the dependent variables in separate regression analyses. So X in the following formula for each bank is the social consumption growth rate and Y is the corresponding ROA, NPL and CAR for each bank.

Analytic Models The following tables are derived from the data calculated by the OLS model.

ICBC (Industrial and Commercial Bank of China) According to the use of model OLS to calculate the social consumption growth rate on the ROA of ICBC regression results are shown in Table 5.1, ROA = −2.15646SCGR + 1.00862, from the table can be seen SCGR coefficient p-value is 0.00701, this number to be less than 10% indicates that this coefficient is significant, so it is concluded that when the social consumption growth rate is increasing by 1%, the return on assets increases by −3.38959. As can be seen, the SCGR has an impact on the ROA of ICBC, with the bank receiving less and less profit when the pandemic outbreak becomes more and more aggressive. The results of the regression of social consumption growth rate on the NPL of ICBC based on the use of the model OLS are shown in Table 5.2, NPL = 2.17689SCGR + 1.49734, from the table it can be seen that the p-value of the SCGR coefficient is 0.09498, when this number to be less than 10% means that this coefficient is significant, so it is concluded that when the social consumption growth rate rises by 1%, the return on assets rises by 2.17689. This shows that the growth rate of social consumption has an impact on the non-performing loans of ICBC, and also means that the greater the impact of the new corona-virus, the more it can lead to a prolonged regional blockade, leaving households or businesses at risk of bankruptcy or collapse unable to repay their loans. Thus having to borrow from banks, putting considerable pressure on banks around the world.

5 Impact of the COVID-19 on Banks in China

103

Table 5.1 The ROA of ICBC Regression statistics Multiple R

0.78608

R2

0.61792

Adjusted R2

0.57016

Standard error

0.02819 10

Observations ANOVA DF

SS

MS

F

Significance F

Regression

1

0.01028

0.01028

12.93845

0.00701

Residual

8

0.00636

0.00079

9

0.01665

Total

Coefficients Intercept SCGR

Standard error

t Stat

P-value

1.00862

0.00897

112.39354

4.388E-14

−2.15646

0.59951

−3.59700

0.00701

Table 5.2 The NPL of ICBC Regression statistics Multiple R

0.55620

R2

0.30936

Adjusted R2

0.22303 0.05408

Standard error

10

Observations ANOVA Regression

DF

SS

MS

F

Significance F

1

0.01048

0.01048

3.58353

0.09498

0.00292

Residual

8

0.02341

Total

9

0.03389

Coefficients

Standard error

t Stat

Intercept

1.49734

0.01721

86.98681

SCGR

2.17689

1.14995

1.89302

P-value 3.403E-13 0.09498

Table 5.3 gives the results of the regression of the social consumption growth rate on the CAR of ICBC based on the use of the model OLS, CAR = −4.55257SCGR + 17.03664. As can be seen from the table, the coefficient of SCGR has a p-value of 0.77961 which is a much higher than 10%. This indicates that this coefficient is insignificant, thus evidencing that SCGR has no effect on the CAR of ICBC.

104

B. Chen and B. S. Nayak

Table 5.3 The CAR of ICBC Regression statistics 0.10179

Multiple R R2

0.01036 −0.11334

Adjusted R2

0.73988

Standard error

10

Observations ANOVA DF

SS

MS

F

Significance F

0.08376

0.77961

Regression

1

0.04585

0.04585

Residual

8

4.37943

0.54742

9

4.42529

Total

Coefficients

Standard error

t Stat

P-value

Intercept

17.03664

0.23545

72.35481

1.48E-12

SCGR

−4.55257

15.73007

−0.28941

0.77961

CCB (Chinese Construction Bank) According to the results of the ROA regression of social consumption growth rate on CCB using model OLS is shown in Table 5.4, ROA = −3.38959SCGR + 1.09969, from the table it can be seen that the p-value of SCGR coefficient is 0.00713, this number is less than 10% which means that this coefficient is significant, so it is concluded that when the social consumption growth rate will increase by 1%, the return on assets will increase by −3.38959. It can be seen from the data that during the height of the COVID-19, the return on assets of the banks showed negative growth, indicating that the disease was severe enough to prevent normal activities in the infected areas and prevent people from going out to buy essential goods, resulting in a drop in the total retail sales of consumer goods and a consequent drop in the growth rate of social consumption. The results of the regression of social consumption growth rate on NPL of CCB based on the use of model OLS are shown in Table 5.5, NPL = 1.98380SCGR + 1.48666, when the coefficient p-value of SCGR is less than 10%, it means that this coefficient is significant. From the Table 5.4 it is clear that the p-value of SCGR coefficient is 0.09964, which is less than 10%. It can be concluded that this coefficient is significant and that when the rate of growth of social consumption improves by 1%, the rate of return on assets improves by 1.98380. As a conclusion, the SCGR has an effect on the NPL of the ICBC.

5 Impact of the COVID-19 on Banks in China

105

Table 5.4 The ROA of CCB Regression statistics Multiple R

0.78509

R2

0.61637

Adjusted R2

0.56842

Standard error

0.56842 10

Observations ANOVA DF

SS

MS

F

Significance F

Regression

1

0.02541

0.02541

12.85365

0.00713

Residual

8

0.01582

0.00197

9

0.04123

Total

Coefficients Intercept SCGR

Standard error

t Stat

P-value

1.09969

0.01415

77.70539

8.385E-13

−3.38959

0.94544

−3.58519

0.00713

Table 5.5 The NPL of CCB Regression statistics Multiple R

0.54983

R2

0.30232

Adjusted R2

0.21511 0.05011

Standard error

10

Observations ANOVA Regression

DF

SS

MS

F

Significance F

1

0.00870

0.00870

3.46663

0.09964

0.00251

Residual

8

0.02009

Total

9

0.02880

Coefficients

Standard error

t Stat

Intercept

1.48666

0.01594

93.21435

SCGR

1.98380

1.06547

1.86188

P-value 1.958E-13 0.09964

Calculation results for the regression of the social consumption growth rate on the CAR of the CCB based on the use of the model OLS are given in Table 5.6, CAR = −9.48338SCGR + 17.14493. From the table it can be seen that the coefficient of SCGR has a p-value of 0.36871 which is well above 10%. In this regard, this shows that this coefficient is insignificant, thereby certifying that the SCGR has no effect on the CAR of the CCB.

106

B. Chen and B. S. Nayak

Table 5.6 The CAR of CCB Regression statistics 0.31916

Multiple R R2

0.10186 −0.01041

Adjusted R2

0.46828

Standard error

10

Observations ANOVA DF

SS

MS

F

Significance F

0.90735

0.36871

Regression

1

0.19897

0.19897

Residual

8

1.75431

0.21928

9

1.95329

Total

Coefficients

Standard error

t Stat

P-value

Intercept

17.14493

0.14902

115.04667

3.641E-14

SCGR

−9.48338

9.95578

−0.95255

0.36871

BOC (Bank of China) The resulting ROA regression of social consumption growth rate on BOC based on the use of model OLS is depicted in Table 5.7, ROA = −1.02928SCGR + 0.90572, from the table it can be seen that the p-value of the coefficient of SCGR is 0.09776, which is less than 10%. This indicates that this coefficient is significant. It can be concluded that when the growth rate of social consumption increases by 1%, the return on assets increases by −1.02928, proving that SCGR has an impact on the NPL of the BOC. The NPL regression results of social consumption growth rate on BOC based on the use of model OLS are in Table 5.8, NPL = 0.83618SCGR + 1.36359. From the table, it is clear that the p-value of the coefficient of SCGR is 0.60499, which is much greater than 10%. This proves that SCGR has no effect on the NPL of Bank of China. A regression of the social consumption growth rate on the CAR of the BOC based on the use of the model OLS is provided in Table 5.9 with CAR = 2.95741SCGR + 15.87003. From the graph, it can be seen that the p-value of the coefficient of SCGR is 0.77891 that is a lot higher than 10%. This indicates that this coefficient is insignificant, resulting in evidence that SCGR has no effect on the CAR of BOC.

ABC (Agricultural Bank of China) Based on the results of the ROA regression of social consumption growth rate on ABC using the model OLS as presented in Table 5.10, ROA = −2.91834SCGR + 0.90190, the p-value of the coefficient of SCGR is 0.00301 which is smaller

5 Impact of the COVID-19 on Banks in China

107

Table 5.7 The ROA of BOC Regression statistics Multiple R

0.50365

R2

0.25366

Adjusted R2

0.16037

Standard error

0.02936 10

Observations ANOVA DF

SS

MS

F

Significance F

2.71907

0.09776

Regression

1

0.00234

0.00234

Residual

8

0.00689

0.00086

9

0.00924

Total

Coefficients Intercept SCGR

Standard error

t Stat

P-value

0.90572

0.00934

96.93672

1.432E-13

−1.02928

0.62420

−1.64896

0.09776

Table 5.8 The NPL of BOC Regression statistics Multiple R

0.18697

R2

0.03495 −0.08567

Adjusted R2

0.07306

Standard error

10

Observations ANOVA Regression

DF

SS

MS

F

Significance F

1

0.00154

0.00154

0.28980

0.60499

0.00533

Residual

8

0.04270

Total

9

0.04425

Coefficients

Standard error

t Stat

Intercept

1.36359

0.83618

58.64734

SCGR

0.83618

1.55328

0.53833

P-value 7.935E-12 0.60499

than 10% as evident from the table. This shows that this coefficient is significant. The conclusion can be reached that when the growth rate of social consumption grows by 1%, the return on assets grows by −2.91834, which demonstrates that SCGR has an influence on the NPL of the Agricultural Bank of China.

108

B. Chen and B. S. Nayak

Table 5.9 The CAR of BOC Regression statistics 0.10213

Multiple R R2

0.01043 −0.11326

Adjusted R2

0.47902

Standard error

10

Observations ANOVA DF

SS

MS

F

Significance F

0.08432

0.77891

Regression

1

0.01935

0.01935

Residual

8

1.83567

0.22946

9

1.85505

Total

Coefficients Intercept SCGR

Standard error

t Stat

15.87003

0.15244

104.10445

2.95741

10.18409

0.29039

P-value 8.096E-14 0.77891

Table 5.10 The ROA of ABC Regression statistics Multiple R

0.82911

R2

0.68743

Adjusted R2

0.64836 0.03272

Standard error

10

Observations ANOVA DF

SS

MS

F

Significance F

Regression

1

0.01884

0.01884

17.59471

0.00301

Residual

8

0.00856

0.00107

Total

9

0.02741

Coefficients Intercept SCGR

Standard error

t Stat

P-value

0.90190

0.01041

86.60196

3.526E-13

−2.91834

0.69573

−4.19460

0.00301

On the basis of using model OLS to figure out the result of NPL regression of social consumption growth rate on ABC is shown in Table 5.11, ROA = 1.90398SCGR + 1.46880, the p-value of the coefficient of SCGR is 0.00964 as seen from the table, is less than 10%. This means that this coefficient is significant. It follows that when the growth rate of social consumption goes up by 1%, the return on assets goes up by 1.90398, evidencing that SCGR has an effect on the NPL of the Agricultural Bank of China.

5 Impact of the COVID-19 on Banks in China

109

Table 5.11 The NPL of ABC Regression statistics Multiple R

0.52444

R2

0.27504

Adjusted R2

0.18442

Standard error

0.05140 10

Observations ANOVA DF

SS

MS

F

Significance F

3.03517

0.00964

Regression

1

0.00802

0.00802

Residual

8

0.02113

0.00264

9

0.02916

Total

Coefficients

Standard error

t Stat

Intercept

1.46880

0.01635

89.78552

SCGR

1.90398

1.09287

1.74217

P-value 2.642E-13 0.00964

Table 5.12 The CAR of ABC Regression statistics Multiple R

0.14649

R2

0.02146 −0.10085

Adjusted R2

0.39674

Standard error

10

Observations ANOVA Regression

DF

SS

MS

F

Significance F

1

0.02761

0.02761

0.17545

0.68632

0.15740

Residual

8

1.25927

Total

9

1.28689

Coefficients Intercept SCGR

Standard error

t Stat

16.53306

0.12626

130.94409

3.53315

8.43492

0.41887

P-value 1.293E-14 0.68632

According to Table 5.12 gives the regression results of the CAR of the BOC based on the social consumption growth rate using the model OLS, CAR = 3.53315SCGR + 16.53306. It can be seen from the table that the p-value of the coefficient of SCGR is 0.68632 which is considerably higher than 10%. This indicates that this coefficient is insignificant, which demonstrates that SCGR has no effect on the CAR of BOC.

110

B. Chen and B. S. Nayak

Table 5.13 The ROA of BCOM Regression statistics Multiple R

0.77083

R2

0.59417

Adjusted R2

0.54345

Standard error

0.03095 10

Observations ANOVA DF

SS

MS

F

Significance F

Regression

1

0.01122

0.01122

11.71316

0.00905

Residual

8

0.00766

0.00095

9

0.01889

Total

Coefficients Intercept SCGR

Standard error

t Stat

P-value

0.78278

0.00985

79.46053

7.014E-13

−2.25237

0.65811

−3.42244

0.00905

BOCM (Bank of Communications) The results of the ROA regression of social consumption growth rate on BCOM based on the use of model OLS are shown in Table 5.13, ROA = −2.25237SCGR + 0.78278, the p-value of the coefficient of SCGR is 0.00905 from the table, is less than 10%. This shows that this coefficient is significant. Thus it can be derived that when the growth rate of social consumption increases by 1%, the return on assets will increase by −2.25237, which proves that SCGR has an impact on BCOM of Agricultural Bank of China. The results of the regression of the social consumption growth rate on the NPL of BCOM based on the use of the model OLS are given in Table 5.14, NPL = 1.32271SCGR + 1.58977. From the table it can be seen that the p-value of the coefficient of SCGR is 0.45865, which is much higher than 10%. This indicates that this coefficient is insignificant, thus demonstrating that SCGR has no effect on the NPL of BCOM. The result of the regression of the social consumption growth rate on the CAR of BCOM which is based on the use of the model OLS is given in Table 5.15, CAR = 9.18588SCGR + 14.98956. It is evident from the table that the coefficient of SCGR has a p-value of 0.41089 which is much higher than 10%. This indicates that this coefficient is insignificant, thereby supporting that SCGR has no effect on the CAR of BCOM. The OLS model calculations provide quantitative results on the impact of the new corona-virus on the profitability of the top 5 banks in China. The research data indicates that the profitability of the top 5 banks in China is affected to varying degrees, most significantly in the return on assets and non-performing loan ratios of

5 Impact of the COVID-19 on Banks in China

111

Table 5.14 The NPL of BCOM Regression statistics 0.26538

Multiple R R2

0.07042 −0.04576

Adjusted R2

0.07991

Standard error

10

Observations ANOVA DF

SS

MS

F

Significance F

0.60612

0.45865

Regression

1

0.00387

0.00387

Residual

8

0.05108

0.00638

9

0.05496

Total

Coefficients

Standard error

t Stat

Intercept

1.58977

0.02543

62.51212

SCGR

1.32271

1.69897

0.77853

P-value 4.767E-12 0.45865

Table 5.15 The CAR of BCOM Regression statistics Multiple R

0.29325

R2

0.08599 −0.02825

Adjusted R2

0.49801

Standard error

10

Observations ANOVA Regression

DF

SS

MS

F

Significance F

1

0.18668

0.18668

0.75269

0.41089

0.24802

Residual

8

0.18668

Total

9

2.17085

Coefficients Intercept SCGR

Standard error

t Stat

14.98956

0.15848

94.57852

9.18588

10.58791

0.86758

P-value 1.743E-13 0.41089

the banks, between the start of the new corona-virus transmission outbreak in China in late 2019 and 2022. This is because during the period 2019–2020 when the virus spreads, the shutdown policy will directly affect the supply side of labor production, with lower capital utilization and weaker investment by manufacturers, while on the other hand, the shock to social consumption demand will lead to lower investment, employment and wages as well as higher prices.

112

B. Chen and B. S. Nayak

And with the above data it can be concluded that the new corona-virus is insignificant to the capital adequacy of the top 5 banks in China. Therefore, it can be assumed that in the “Global 1000 Banks” report by The Banker (Macknight, 2022), ICBC, China Construction Bank, Agricultural Bank of China and Bank of China occupy the top 4 positions in the global list, and 11 Chinese banks are among the top 25 in the world, indicating that these 5 Chinese banks are fully capable of withstanding the COVID-19 transmission risk.

Conclusions This research explores the impact of the new coronavirus on the Chinese banking industry by developing an OLS model. As an example, the return on assets, nonperforming loans and capital adequacy ratio of the top 5 banks (ICBC, BOC, ABC, BCOM, CCB) in China are influenced by the new coronavirus. The specific period of the research is divided into from 2019, when the new coronavirus starts to spread from China, to 2020, when the new coronavirus breaks out worldwide, to the first quarter of this year 2022. From the calculated data, it can be obtained that the new coronavirus has a significant impact on the return on assets of all five banks. This is because in order to limit the outbreak of the new coronavirus, each infected region had to adopt a policy of city closures to reduce transmission, shutdowns in industry, disruptions in transport, etc., and most companies’ production and operations were in difficulty, and in China, the main source of banking profits was for corporate financial services. In China, the main profit source of banking business is financial services to companies. Therefore, the return on assets of banks received a relatively strong shock under the impact of the new coronavirus. For the impact of the new coronavirus on banks’ NPL ratios, the data showed that the COVID-19 had a significant effect on the NPL ratios of ICBC, CCB and ABC, while it had no effect on the NPL ratios of two banks, BOC and BCOM. The reason for the lack of effect on BOC and BCOM could be due to the small sample size, or some unknown factors could have affected the NPL data for BOC and BCOM, resulting in the NPL data for BOC and BCOM being inconsistent with the other three banks. However, the main significant impact was due to the COVID-19, which severely affected most sectors such as banking, retail, transport and tourism. Among others, the small and medium-sized businesses, restaurants and retail may need the most help to reduce costs, ease debt obligations, maintain working capital and stabilize supply chains. As most of these sectors were forced to close during the COVID-19, their revenues were almost negative and they had to face bankruptcy. While take away services have helped some large restaurants save some of their daily expenses, human resource costs and heavy back office work are still affecting this sector extremely hard. Businesses, consumer households are already facing financial challenges with millions of people who are currently experiencing the reality of unemployment. Although some of these consumers will receive relief in the form of unemployment insurance, in most cases this will not be adequate to cover basic

5 Impact of the COVID-19 on Banks in China

113

living costs and mortgages. Many borrowers will be unable to recover financially and resume mortgage repayments at the end of the forbearance scheme, creating problems for the functioning of the Chinese banking system. Therefore, Chinese banks can prepare for an increase in lending by preventing an increase in lending, by hedging risks, and accelerating the clearing of non-performing loans, possibly by offering to ask bank staff to help businesses or consumers to set up repayment plans, modifications or liquidations. These measures will mitigate the impact of the new coronavirus on the banking sector generally to a certain extent. Finally the data shows that the new corona-virus has no significant impact on the capital adequacy ratio of the top five banks in China. The reason for this would probably be that the capital adequacy ratio is a reflection of the extent to which a commercial bank can absorb losses with equity before the assets of depositors and creditors are lost. Therefore, according to the above sources, four of the five banks are among the top four banks in the world, demonstrating that the Chinese banks researched had sufficient capital adequacy to withstand the risk of economic downturn in the event of a new corona-virus outbreak. In the event of a short outbreak, the impact on the profitability, asset quality and business operations of small and medium-sized banks is more negative, affecting their capital adequacy levels to some extent, but the impact on the Chinese banking sector as a whole is not significant. In summary, the new coronavirus has had a significant impact on the global banking industry, specifically in terms of affecting bank customers generally in traditional industries (manufacturing, wholesale and retail, etc.), as well as small and medium-sized customers (small and medium-sized enterprises, individual entrepreneurs), where the pandemic has had a more dramatic negative impact. The overdue rate and probability of default of loans of small and medium-sized banks may increase to a certain extent, and the credit risk pressure on the asset side of small and medium-sized banks may further enhance. Although in the short-term outbreak, the new coronavirus will have a negative impact on the scale of operation, asset quality, profitability and capital adequacy of small and medium-sized banks due to their poor foundation and high operating pressure. Furthermore, the more time that the epidemic lasts, the more banks are affected and the more unstable the whole banking system is. However, for the strong banks, their own ability to withstand risks is better, which can be helped by the government’s timely adjustment of monetary and fiscal policies as well as the adjustment of the banking sector’s asset structure. Overall, the adverse impact of the new coronavirus on the global banking industry is of a phased nature. In the future, after the new coronavirus is under control, the economy will stabilize rapidly, and the global banking industry will experience faster development. For the development of the new coronavirus affecting the global banking sector, a few suggestions are made in relation to the data to facilitate a rapid recovery and increase bank profitability. The first suggestion is: improve risk management capabilities. Firstly, the new coronavirus poses many challenges to the global economy and banking operations. The global banking industry should enhance the level of risk management, maintain a high level of capital adequacy and liquidity, increase risk identification ability,

114

B. Chen and B. S. Nayak

and establish an isolation and rescue mechanism among banks to avoid the spread of systemic risks. Focus on protecting businesses affected by the short-term impact under the pandemic to help economic recovery. Secondly, focus on lending to specific sectors. For example, cash flows in sectors such as tourism, transportation, wholesale and retail, and accommodation and catering remain at high risk. Therefore, the banking industry needs to make proper risk identification when classifying business and create differentiated credit solutions to meet the requirements of particular industries. Finally, actively explore ways to dispose of non-performing loans. In the face of the pressure on asset quality brought about by the new coronavirus, the banking industry has the ability to use financial technology to quickly identify risky assets and have a clear understanding of the risk exposure of non-performing loans. Non-performing loans are flexibly disposed of through bulk transfers, debt swaps, debt-to-equity swaps or by seeking government policy support. The second suggestion is: to further increase investment in emerging sectors. Covid-19 has affected traditional industries, resulting in a greater impact on traditional business in the banking sector, but also creating investment opportunities in emerging sectors. Against the backdrop of the new crown epidemic, working and living at home has become the norm, which has led to the rise of industries such as unmanned delivery, “cloud office”, “cloud education” and smart cities. The banking industry has to take advantage of these new industries and invest more in these new sectors to meet the financial requirements of customers. It is important for banks to strengthen their business structure and mitigate the impact of the economic downturn on their profitability. A final suggestion: deepen the transformation of your business model. The new coronavirus has dramatically changed people’s lives and work patterns, placing new demands on the banking industry’s service model. Since the outbreak of the new coronavirus, “non-contact” service models such as mobile banking and internet banking had a significant contribution to make. These online office and service models provide efficiency without compromising service requirements. In the post-outbreak period, the banking industry has to aggressively develop online products to take advantage of telecommuting and online services to reduce labor costs and business operation costs. The global banking industry is advised to capitalize on the trend of digital transformation, use financial technologies such as block-chain, cloud computing and big data to upgrade online payment systems as well as transform business models to meet the new lifestyle and consumption of consumers under the new coronavirus.

References Adrian, T., & Brunnermeier, M. (2016). CoVaR. American Economic Review, 106(7), 1705–1741. Adrian, T., & Natalucci, F. (2022). COVID-19 crisis threatens financial stability. [Online] imf.org. Available at: https://www.imf.org/zh/News/Articles/2020/04/14/blog-gfsr-covid-19-cri sis-poses-threat-to-financial-stability. Accessed 6 July 2022.

5 Impact of the COVID-19 on Banks in China

115

Aliaga, M., & Gunderson, B. (2002). Interactive statistics (3rd ed.). Sage. An, Y. (2020). Impact of the COVID-19 on China’s banking sector, recommendations and M&A outlook. [Online] Sohu.com. Available at: https://www.sohu.com/a/379721258_676545. Accessed 11 July 2022. Apuke, O. D. (2017). Quantitative research methods: A synopsis approach. Kuwait Chapter of Arabian Journal of Business and Management Review, 6(11), 40–47. Ari, A., Chen, S., & Ratnovski, L. (2021). The dynamics of non-performing loans during banking crises: A new database with post-COVID-19 implications. Journal of Banking & Finance, 133. Bitar, M., Pukthuanthong, K., & Walker, T. (2018). The effect of capital ratios on the risk, efficiency and profitability of banks: Evidence from OECD countries. Journal of International Financial Markets, Institutions and Money, 53, 227–262. Carletti, E., Claessens, S., Fatás, A., & Vives, X. (2022). The bank business model in the postCovid-19 world. VOX, CEPR Policy Portal. [Online] Voxeu.org. Available at: https://voxeu.org/ article/bank-business-model-post-covid-19-world. Accessed 24 July 2022. CEIC. (2022). A review of China’s monetary policy in 2020 under the impact of the epidemic. [Online] Info.ceicdata.com. Available at: https://info.ceicdata.com/zh-cn/chinas-monetary-pol icy-amid-the-pandemic_jan21. Accessed 8 July 2022. Chen, H., Qian, W., & Wen, Q. (2020). The impact of the COVID-19 pandemic on consumption: Learning from high frequency transaction data. SSRN Electronic Journal. Chen, Z., & Huang, J. (2022). US fiscal policy and reflections in the face of the epidemic shock. [Online] Zgcznet.com. Available at: https://www.zgcznet.com/zdct/202203/20220314/j_2022 031409573100016469796766208635.html. Accessed 5 July 2022. Danninger, S., Kang, K., & Poirson, H. (2022). Emerging economies must prepare for a tightening of Fed monetary policy. [Online] imf.org. Available at: https://www.imf.org/zh/News/Articles/ 2022/01/10/blog-emerging-economies-must-prepare-for-fed-policy-tightening. Accessed 9 July 2022. Deloitte. (2022). The impact of a new Corona virus on the financial operations of the Chinese property industry. [Online] www2.deloitte.com. Available at: https://www2.deloitte.com/con tent/dam/Deloitte/cn/Documents/real-estate/deloitte-cn-re-covid-19-real-estate-operations-cap ital-report-zh-200515.pdf. Accessed 26 July 2022. Dong, F. (2022). LPR variety data centre-oriental wealth. [Online] Data.eastmoney.com. Available at: https://data.eastmoney.com/cjsj/globalRateLPR.html. Accessed 10 July 2022. Fatima, N. (2014). Capital adequacy: A financial soundness indicator for banks. Global Journal of Finance and Management, 6(8), 771–776. Ghebreyesus, T. A. (2020). WHO Director-General’s opening remarks at the media briefing on COVID-19—30 March 2020. [Online] who.int. Available at: https://www.who.int/director-gen eral/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid19---30-march-2020. Accessed 26 July 2022. Guiso, L., Sapienza, P., & Zingales, L. (2004). Does local financial development matter? The Quarterly Journal of Economics, 119(3), 929–969. He, L. (2022). After 50 bps hike: Bank of England warns of recession, truss in power may make rate hikes more “violent”. [Online] Sohu.com. Available at: https://www.sohu.com/a/574786335_121 255906. Accessed 9 July 2022. Hu, Y. (2022). Inflation overview and outlook. [Online] Pdf.dfcfw.com. Available at: https:// pdf.dfcfw.com/pdf/H3_AP202105121491224021_1.pdf?1620815825000.pdf. Accessed 26 July 2022. Ichsan, R., Suparmin, S., Yusuf, M., Ismal, R., & Sitompul, S. (2021). Determinant of Sharia Bank’s financial performance during the Covid-19 pandemic. Budapest International Research and Critics Institute (BIRCI-Journal): Humanities and Social Sciences, 4, 298–309. IMF. (2022). World economic outlook October 2021. [Online] imf.org. Available at: https:// www.imf.org/zh/Publications/WEO/Issues/2021/10/12/world-economic-outlook-october-2021. Accessed 7 August 2022.

116

B. Chen and B. S. Nayak

Jiang, H. (2022). Sterling exchange rate to maintain high volatility under weak market. [Online] M.ce.cn. Available at: http://m.ce.cn/bwzg/202205/18/t20220518_37592002.shtml. Accessed 8 July 2022 Johnson, R. (2002). Research methods: A good introduction to basic quantitative research. Contemporary Psychology, 47(1), 54–56. KPMG. (2022). Reflections on how commercial banks can respond under the epidemic. [Online] assets.kpmg. Available at: https://assets.kpmg/content/dam/kpmg/cn/pdf/zh/2020/05/how-com mercial-banks-respond-to-epidemic.pdf. Accessed 10 July 2022. Lardy, N. (1999). Strengthening the banking system in China. Basel, Switzerland: Bank for International Settlements, Monetary and Economic Department, pp. 17–40. Leedy, P., & Ormrod, J. (2001). Practical research: Planning and design (7th ed.). Pearson. Li, L., & Hou, F. (2022). Economic analysis of animal production in China. [Online] Cyxb.magtech.com.cn. Available at: http://cyxb.magtech.com.cn/EN/Y2016/V25/I1/230. Accessed 1 August 2022. Liu, C. (2020). The macroeconomic impact of the COVID-19. Statistics and Application, 9(5), 862–869. Luo, Y., & Wang, G. (2022). Financial development in the centenary of the communist party of China. [Online] M.aisixiang.com. Available at: https://m.aisixiang.com/data/131564-2.html. Accessed 24 July 2022. Ma, S., & Yu, M. (2022). Yicai report: China’s economy under the impact of the epidemic: “Protecting market players” remains a top priority. [Online] Yicai.com. Available at: https://www. yicai.com/news/101409933.html. Accessed 9 July 2022. Macknight, J. (2022). China Press release: The banker’s world bank 1000 rankings 2022: China’s banking sector outpaces US in tier 1 growth (simplified Chinese). [Online] Thebanker.com. Available at: https://www.thebanker.com/Top-1000-World-Banks/China-Press-Release-2022-1000Simplified-Chinese. Accessed 3 August 2022. Messai, A. S., & Jouini, F. (2013). Micro and macro determinants of non-performing loans. International Journal of Economics and Financial Issues. Niu, X. (2015). History of bank of communications. The Commercial Press. Ozili, P., & Arun, T. (2020). Spillover of COVID-19: Impact on the global economy. SSRN Electronic Journal. Pang, B. (2020). Data on key regulatory indicators for the banking and insurance sector in the third quarter of 2020. [Online] www.gov.cn. Available at: http://www.gov.cn/xinwen/2020-11/13/con tent_5561279.htm. Accessed 1 August 2022. Peng, D. (2022). European Central Bank ramps up QE in response to epidemic shock, expects Eurozone recession of 8.7% this year. [Online] Finance.sina.com.cn. Available at: https://finance.sina. com.cn/roll/2020-06-05/doc-iircuyvi6798284.shtml. Accessed 12 July 2022. Petersen, M. A., & Schoeman, D. I. (2008). Modeling of banking profit via return on assets and return-on-equity. Proceedings of the World Congress on Engineering. PWC. (2022). Strengthening the foundations for epidemic preparedness and response. [Online] pecan.com. Available at: https://www.pwccn.com/zh/banking/banking-newsletter-2020-half.pdf. Accessed 12 July 2022. Qing, J. (2008). History of the industrial and commercial bank of China. China Financial Press. Schmidheiny, K. (2021). The multiple linear regression model. Short Guides to Microeconomics. Song, Y. (2022). China issued a special national bond of 1 trillion yuan to fight against epidemics, directly reaching the grassroots level in cities and counties, directly benefiting enterprises and people. [Online] Gov.cn. Available at: http://www.gov.cn/xinwen/2020-05/22/content_5514005. htm. Accessed 10 July 2022. Su, N. (2007). China financial statistics (1949–2005). University of Michigan. China Financial Press. Sun, T., Huang, X., Wen, H., Yang, L., & Meng, H. (2022). China financial stability report 2020. [Online] Gov.cn. Available at: http://www.gov.cn/xinwen/2020-11/07/5558567/files/d7ba5445e 5204c83b37e3f5e07140638.pdf. Accessed 11 July 2022.

5 Impact of the COVID-19 on Banks in China

117

Wang, H. (2020). UK banking sector hit by double whammy of epidemic and European Union exit. [Online] www.xinhuanet.com. Available at: http://www.xinhuanet.com/world/2020-08/11/ c_1126353305.htm. Accessed 27 June 2022. Wang, L. (2022). Financial technology learning report: Where do offline bank branches go from here? [Online] Fmba.pbcsf.tsinghua.edu.cn. Available at: http://fmba.pbcsf.tsinghua.edu. cn/index.php?m=content&c=index&a=show&catid=60&id=2351. Accessed 13 July 2022. WHO. (2020). WHO Director-General’s opening remarks at the media briefing on COVID-19—28 February 2020. [Online] www.who.int. Available at: https://www.who.int/director-general/spe eches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---28february-2020. Accessed 26 Jun. 2022. Williams, C. (2011). Research methods. Journal of Business and Economics Research, 5(3). World Health Organization. (2020). Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel Corona-virus (2019nCov). [Online] www.who.int. Available at: https://www.who.int/news/item/30-01-2020-statem ent-on-the-second-meeting-of-the-international-health-regulations-(2005)-emergency-commit tee-regarding-the-outbreak-of-novel-coronavirus-(2019-ncov). Accessed 25 July 2022. Xi, J. (2017). A collection of important documents from the 19th Party Congress. The People’s Press. Yin, A. (2022). Changes in the number of national bank branches since the COVID-19. [Online] Bajiahao.baidu.com. Available at: https://baijiahao.baidu.com/s?id=1736497316350831170&wfr= spider&for=pc. Accessed 7 July 2022. Zhang, P., & Zhao, S. (2022). High inflation in the United States is the inevitable product of excessive stimulus and structural imbalance. [Online] Ndrc.gov.cn. Available at: https://www.ndrc.gov.cn/ wsdwhfz/202206/t20220629_1329214.html?code=&state=123. Accessed 10 July 2022.

Chapter 6

Chinese Female Athletes and the Expansion of Business in Wuhan Province Liangyifang Peng and Bhabani Shankar Nayak

Abstract In recent years, there has been an increased concern about the business value of female athletes. China is gradually embracing Western sporting principles because the sporting environment in Western countries is largely liberalised and commercial competitions are more developed. However, in China, research into the business value of female athletes is still in its infancy. The issues affecting the commercial worth of female athletes and the approaches to support female empowerment and the growth of the business value of female athletes in China are therefore examined in the study. The chapter outlines the impacts of Chinese female athletes on the expansion of business value, using Chinese female athletes as an example and including the elements that contribute to the disparities between the Chinese and Western athletic systems.

Introduction The struggle of women for equal rights has spanned over two centuries. The flawed selection mechanism for female athletes and women’s sporting events receives less attention from the sports industry, and female athletes may positively affect the business value. China’s national sports system has resulted in a lack of reasonably mature selection procedures for sports players compared to developed Western nations. Men’s and women’s domestic sports events differ in terms of quantity and standardisation. China must concentrate on establishing the social media image of female athletes in light of its own reality and the characteristics of its own athlete training system in order to strengthen the reputation of female athletes in international competition and

L. Peng University of Glasgow, Glasgow, Scotland, UK B. S. Nayak (B) Business School for the Creative Industries, University for the Creative Arts, 21 Ashley Rd, Epsom KT18 5BE, UK e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 B. S. Nayak (ed.), China: The Great Transition, https://doi.org/10.1007/978-981-99-0051-0_6

119

120

L. Peng and B. S. Nayak

boost their business value, and finally enhance awareness of the effects of female athletes on the growth of business value. Sport is a somewhat unique industry in that the athletes’ income is determined and paid not only by the sporting club or organisation to which they belong but also in various other ways, including advertising endorsement fees. A high business value is an intrinsic part of the income of great athletes, in addition to their individual achievements. There is no female athlete in the top 10 of the Forbes list (Forbes the top 50 highest-paid athletes in the world 2021), and only two female athletes are in the top 50. Chinese female athletes face tough competition from foreign female athletes. As a result of this competitiveness, Chinese female athletes are becoming more wellknown in a variety of sporting tournaments, and their business value is rising. Still, every athlete strives to enhance their personal performance and level of competition. Consequently, the effect of Chinese female athletes on the expansion of their business value is a topic worthy of investigation. The development of a sports athlete’s business value is correlated with the attainment of personal value, and Chinese female athletes continue to lag behind their international counterparts in terms of visibility and overall income. Therefore, the purpose of this study is to provide countermeasures and recommendations, particularly on how to increase the business value of Chinese female athletes, and to investigate how Chinese female athletes can contribute to the growth of business value, which is related to the sustainable and healthy operation of the sports industry and the advancement of gender equality. Many studies have analysed the origins of the disparity between the business value of male and female athletes and provided remedies to improve the commercial situation of female athletes. In football matches, one of the most commercialised sports in the world, for instance, the bonuses and awards for male football matches are significantly greater than those for female football matches. Some football unions have announced initiatives to promote the business value of the female game, including the provision of grants to encourage social capital investment. Their effectiveness, however, remains much lower to that of the male game. Gendered decisions continue to influence sports performance between female and male athletes (Thibault et al., 2010). Even in Norway, where the gender is relatively equal, youth girls and boys hold different ambitions about whether to become professional athletes when they grow up (Eriksen, 2021). Connell (2008) finds a strong link between the characteristics such as competitiveness and masculinity, which may have a depressing effect on other factors like feminine and female. Koivula (1995) discovered that there are people who hold a traditional belief that some sports like American football and weight lifting are considered masculine, while some sports like gymnastics and ice skating are seen as feminine. In China, gender segregation in jobs remains, and this inequality plays a significant role in identifying the gap in income between female workers and male workers (Summerfield et al., 2011). Under the historical background, China’s female athletes, not only on behalf of themselves but also in the image of China, play an integral role in winning the glory for the nation (Brownell, 2005). Xu et al. (2019) find that this phenomenon gradually influences and builds a

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province

121

gender perception of female athletes in Chinese people, which is a different sports aesthetic compared with western countries. Exploring sports athletes’ business value is a typical behavioural economics phenomenon. Sports data can explore individual and group behaviours. The commercialisation of an event is highly related to the professional staff (Clausen et al., 2018). They established a theory that the complexity of the composition of staff and highly commercialisation could encourage the sports unions to participate in more social media events. Once a link is formed with social media, these unions and organisations are exposed to higher platforms to develop sports communication, create brand recognition and lead to more social capital investment. There are some previous studies on identifying the business value of athletes. Wolfe et al. (2005) present that sports have the potential to make value in the business environment. Woratschek et al. (2014) proposed a conceptual framework that the business value can be analysed between the relationship between sports items and the audience. However, there is still a lack the investigation between sports and commercialisation. Jalonen et al. (2018) argued that the business value is not the value exchange but the co-creation. For the market influence, the scale of the market, especially on how the sports teams draw attention from fans, affects the income of athletes directly (Scully, 1989). However, it is controversial that sports clubs are willing to make a sustainable and long-term relationship with sports fans. Still, these fans are unwilling to let their enthusiasm for the clubs be considered commercial and irrational actions (Abosag et al., 2012). Some research showed that the personal performance of athletes is a double-edged sword in influencing the emotions of the audience. Abosag et al. (2012) argued that the audience would react emotionally and rationally to the sports competitions. Hence, it is difficult to measure whether personal performance is a reasonable factor in measuring the business value of athletes. The business value of athletes can be related to the support from fans for their favourite athletes. Popularity and performance also play a significant role for athletes and influence the public. Positive brand associations could be used to shape stable brand equity. Ohanian (1991) investigated the impact of famous people endorsement by establishing a model for athletes to build their own brands (Ohanian, 1990). Then Erdogan (1999) refined this model by considering the sports athletes as an independent brand. Later Braunstein and Zhang (2005) creatively used this model to combine the power of stars and sports athletes. The personal images of athletes also could be transferred to athlete brand images, which are sports performance, attractive appearance and replicable ways of joining sports (Arai et al., 2013). The match between the athletes and brands is described in detail by Craft et al. (2008) that consumers are encouraged to make unique choices led by brands, brand identification system is a successful way to affect the perception of consumers. Moreover, a link between athletes and brands is created to achieve a win–win goal. More income for athletes could be brought by effective branding. Meanwhile, the highly match between the athletes and brand could, in turn, increase the value of the brands. This view is also agreed by Yoshida and Gordon (2012) that the positive relationship between customers and sports teams can influence brand equity and consumer behaviours as

122

L. Peng and B. S. Nayak

well. According to the theory of Cortsen (2013), sports brands could be described as emotional capital; Guenzi and Nocco (2006) report that brand equity is an integral form of shaping the character of a consumer-based sports team to affect the behaviours of consumers. Some football clubs in England founded charitable foundations to conduct their corporate social responsibility (Anagnostopoulos & Shilbury, 2013). This responsibility must be essential to managing the sports club strategies (Blumrodt et al., 2013). Smith and Westerbeek (2007) analyse that social responsibility and social value played a significant role in improving the positive health conditions, the social interactions between citizens, the different cultural communications among countries and the attractions of sports to young people, etc. Therefore, sports could become a vital tool of social value (Smith & Westerbeek, 2007) and responsibility to have long-term positive effects on society (Anagnostopoulos & Shilbury, 2013). Kauppi et al. (2013) discuss that unpredictable factors in sports influence the sports operation externally. Relying heavily on the audience of sports competitions, it is essential to make strategies to satisfy the audience on different live streaming platforms, like the public audio, online webpage watching, and mobile apps (Kauppi et al., 2013). Therefore, the professional and commercial sports operations could shrink the gap between predictable situations and these unpredictable influences the reality (Bamford et al., 2018). Borland (2016) examines the similar theory that the sports union can be considered as the leading producer of a sports event, and the audience cannot create the productive value of sports events (Stabell & Fjeldsted, 1998). There lacks a cognition to describe the core work of sports unions and the essence of sports management (Woratschek et al., 2014). However, there are some researchers who hold different views of the composition to the value of sports athletes. Ferrand et al. (2012) evaluate a similar theory about the main participants of the business value of athletes and the value that sports organisations and firms can create. Moreover, the power of sports fans can not be neglected. These organisations and firms could provide a platform for sports fans, the audience and all the stakeholders from sports to create value for athletes together. As for the role of female athletes in sports media and advertising, some studies illustrate that most female athletes always outline their appearance and feminine character (Kim et al., 2006). However, Kane and Maxwell (2011) find that when there is a lack of a match between sports items and the gender of athletes, physical attractiveness could be unuseful, and consumers will increase their interest in the competitions again when the female athletes express the professional ability during the games. Liu and Brock (2011) find that in China, female athletes played better than male athletes in sports such as volleyball, diving, football, etc. However, consumers still pay more attention to the appearance of female sports endorsements still rather than their level of competition. After reviewing previous literature, we know that every sports item could provide a platform for athletes to become self-branding images and gradually improve their business values. Meanwhile, increasing the business value could, in turn, enhance the power of attracting and influencing more consumers. Moreover, these factors could be used to analyse the business value of female athletes in different ways.

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province

123

This feminist theory in sports is important to develop an economic framework for analysing how gender affects consumer decision-making in order to shed light on the problem of gender prejudice in sports. The difference in physical attributes and functions between male and female athletes has led to gender segregation in their training patterns. As a result, many individuals believe that female athletes are at a disadvantage in their respective sports, and this biased perception prevents female athletes from receiving the respect they deserve. In an effort to reduce gender discrimination in sports, feminism in sports has focused research on whether team sports and training should be separated by gender. Several previous research methods examined the factors that affect the business value of female athletes by collecting quantitative data on their annual wage, age, number of sponsorships, etc. Humphreys (2000) established a human capital earnings model to estimate the salary gap between male and female professional coaches, whereas Clement (2013) compared the financial rewards for professional male and female athletes and found that female athletes continue to face potential inequalities in terms of endorsement and advertising fee compared to male athletes. Ohanian (1990) created a scale to measure the celebrity’s personal performance, trustworthiness, and attractiveness regarding endorsement. Additionally, qualitative methodologies were employed to examine the changes in the business worth of female athletes. Scraton and Flintoff (2013) conclude the liberal, radical, and socialist views of sports feminism. Bayle et al. (2018) utilise the qualitative comparative technique to investigate the commercialisation affecting factors by interviewing sixteen firms. Marie and Jennifer (2009) conducted a poll of 340 college students and discovered that several sports had been given gender-biased names, which may hinder the development of some sports. Xu et al. (2019) investigated the relationship between sports and gender perception by surveying 423 individuals on 16 sports and concluded that the goal of gender norms is not to categorise sports as male or female. Using qualitative methodologies, the study explores the business value of Wuhan’s female athletes, including changes in consumer psychology, and analyse the influence of female athletes on the growth of business value in Wuhan. Considering that most sports are not widely commercialised and that the economic potential of female sports players has only just begun to exist, it is currently impossible to get complete industry statistics from public sources for quantitative research. In order to get secondary data and information from a few official and professional websites, this article primarily uses public data collection and analysis methods. Before using the data for the qualitative research for this thesis, these methods are used to verify the legitimacy of the data. The secondary data collected in this research paper are mainly from the following sources: The business value ranking is mainly based on Forbes (www.forbes.com), which has been tracking the annual revenue of athletes, the value of commercial brands and other data on the commercial value of sports since 1990; The official website of the sports organizations such as The International Olympic Committee

124

L. Peng and B. S. Nayak

(https://olympics.com/en/), International Federation of Association Football (https:// www.fifa.com), International Tennis Federation (https://www.itftennis.com/en/), Women’s Tennis Association (https://www.wtatennis.com); The official website of big sports events such as The National Basketball Association (https://www. nba.com/), The Union of European Football Associations (https://www.uefa.com/), The Wimbledon Championships (https://www.wimbledon.com), and The Australian Open (https://ausopen.com/); The official website for General Administration of Sport of China (https://www.sport.gov.cn/). In order to provide supporting documentation for future research on the expansion of the commercial value of female athletes, the main implications of using the open data collection and analysis method in this study include first obtaining statistics on the development and history of the sports industry to which the subject of the study belongs. The second step is to comprehend the research patterns and outcomes of others in order to give suggestions and strategies for conducting the individual study. Despite reviewing a large amount of material for this research, the overall research focus is case studies and qualitative analysis, which lacks strategic thinking. As a result, this research has a wider scope and focuses on the growth of the sports business and the empowerment of economic value. Thirdly, considering potential strategies to raise the commercial value of female athletes and offering context for the research’s conclusions. On the one hand, this research’s use of open data collection and analysis techniques has several strengths, including the potential to investigate subjects that are not widely accessible, the relative transparency of publicly available information, the relative veracity of reliable media sources, the simplicity and low cost of gathering publicly available information, and the relative trustworthiness of the outcomes of analysis based on such information. The limitations of this approach, on the other hand, include the collection of public information, which is based mainly on media reports, which have a degree of information bias and tendentious presentation, the lack of sufficient data in public information makes it challenging to provide quantitative data analysis as a basis for research, the public information has a degree of sampling bias and the sample is not representative enough, and the classification and comparison.

Female Athletes and Business Value Sport is a complicated social and cultural phenomenon as well as a human activity. Many people believe that the scope and depth of sports development have been a key barometer of a nation’s and society’s advancement. The political, economic, and cultural aspects of society’s operation are all strongly related to and continually influenced by the sports industry. In response to the commercialisation of sport at the time, Pierre de Coubertin proposed the “revival of the Olympic movement” in 1892. He suggested that the games be run in the spirit of “solidarity, friendship, and peace” in order to get rid of the murky and undesirable tendencies that were present in the sports world. The path to hell is paved with good intentions. Thus the IOC

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province

125

is committed to advancing the Olympic Movement following the tenets of “noncommercialization, non-professionalism, and non-politicization.” Many competitions, including the Olympic Games, are no longer financially viable due to the lack of commercial activity. The 1988 Seoul Olympics allowed some tennis professionals to compete in the Olympics, establishing a new chapter in the history of professional participation in the Olympics. The three Summer Olympics that the IOC lost from 1972 to 1980 prompted reform and the promotion of commercialisation. The USA men’s basketball team, dubbed the Dream Team, won the championship in a rout, greatly expanding the NBA’s global impact. From a practical perspective, only high-level athletic tournaments have drawn more spectators and sponsors, even though amateur athletes’ participation can undoubtedly inspire more people to take up sports. The 1984 Olympics in Los Angeles’ Uberos organisation restored the Olympics’ financial viability, and successive iterations of the Games have provided enormous economic advantages to numerous host nations. According to research by renowned investment firm Goldman Sachs Securities, a successful Beijing bid would boost China’s economic growth rate by 0.3% a year from 2002 to 2008 (Goldman Sachs 2002). The expense of hosting the football World Cup, which is currently the most significant single event in history, is enormous. However, the countries still actively bidding do so because of the World Cup’s considerable influence on employment and economic growth. The 2018 FIFA World Cup’s total economic impact on Russia from 2013 to 2018 has been estimated at 952 billion rubles (about $14.5 billion), or nearly 1% (TASS 2018) of the country’s annual GDP, according to the Russian news agency TASS. As a result, the economy serves as the foundation for the growth of the sport, and the development of the sport is inextricably linked to the material base that the economy provides in the form of human, financial, and material resources. At the same time, the expansion of sports consumption also supports the economy. According to statistics, the sports industry in the UK supports at least 360,000 employees annually (Statista Research Department, 2021) and is worth £6.85 billion (about US$102 billion) on average. The UK government spends five times this much on sports. However, the market needs to be carefully developed if the sports sector is promoted and its business value maximised. The development and improvement of top athletes’ business value are most emblematic of the sports industry. Breakthrough victories by their athletes in international competitions will effectively boost national self-esteem and self-confidence for some nations whose sports were not previously of a high standard, and these athletes will then become national calling cards that will be supported by numerous commercial endorsements from their countries. For instance, Yuzuru Hanyu, the twotime Winter Olympics men’s singles skating champion, has endorsements from all Japanese companies aside from P&G, and even P&G’s advertisements are targeted at the Japanese market. Liu Xiang, a breakthrough athlete in Chinese men’s athletics, has endorsements from primarily Chinese companies. Beginning with an analysis of the factors affecting athletes’ business value, this chapter will compare how the value of female athletes develops in China and other nations, trace the development of two representative female athletes in Wuhan,

126

L. Peng and B. S. Nayak

Hubei Province, China, who have gradually increased their business value, and offer recommendations for cultivating and enhancing the value of female athletes in China.

Business Value of International Female Athletes The ten highest-paid female athletes in the world in 2021 were listed in Forbes magazine’s ranking of female athletes’ earnings in January 2022. These athletes’ earnings comprised base salaries, performance bonuses, award bonuses, allowances, and money earned off the field from endorsements, licencing, manufacturing and spinoff souvenir sales, as well as base salaries, performance bonuses, and allowances. Naomi Osaka, a Japanese tennis player, topped the list with annual earnings of $57.3 million (Forbes, 2022), setting a new record for the highest annual earnings of a female athlete. Forbes provides a summary of the present state of business value. Firstly, total revenue increased, but the rise was somewhat concentrated, with advertising and endorsements dominating the revenue composition: In 2021, the top ten highest-paid female athletes in the world received a combined pre-tax income of $167 million, a 23% increase over the previous year, with the majority of the growth coming from Naomi Osaka and Serena Jameka Williams, the two highest-profile players. Of Naomi Osaka’s $57.3 million in revenue, $2.3 million in tournament prize money, or 4%; however, her commercial battlefield of advertising endorsements has been richly rewarded, adding more than ten endorsement brands in 2021 alone; Serena Williams’ $45.9 million in revenue, with $900,000 in tournament revenue and $45 million in off-court revenue from advertising endorsements (Forbes, 2022). Moreover, non-tennis sports seek a breakthrough; the number of players shortlisted in sports other than tennis increased dramatically in 2021. In 2019, the top 10 highest-paid female athletes were all tennis players. Still, in 2021, there is a 50/50 split between tennis and non-tennis athletes, with Simone Arianne Biles and Candace Parker making the Forbes list of female athletes. Furthermore, the uniqueness of athletic performance and the dissemination of the “celebrity effect” can lead to the effective realisation of the core competitiveness of the business value of female athletes, with Naomi Osaka relying on the sustained market buzz brought about by her excellent performance in her prime years, with four Grand Slams in her career so far and being the first Asian player in history to be ranked No. 1 in the world in singles. In contrast, Williams is still ranked No. 1 in the world in singles. Female athletes lack compensation, treatment of facilities, and media attention due to gender-specific factors. Still, the number and amount of sponsors for female athletes’ events have steadily increased in recent years, and television ratings for female sports are gradually rising. At the same time, online communication has also provided more channels for female athletes to receive information. Sports with a high degree of professionalism must break the inequality between male and female athletes by creating a more open and de-labelled competitive environment, allowing female athletes to have their own strengths to conquer audiences and sponsors, and

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province

127

gaining more and broader opportunities to increase their business value, thereby eliminating the enormous income gap.

Factors Influencing the Business Value of Sports Athletes By analysing the laws of sports industry development, there are six main factors influencing the business value of sports players as follows.

Marketisation and Commercialization of Sports Even though the Olympic motto of “Faster, Higher, Stronger, Together” guides modern sport, the history of athletic events demonstrates that fans enjoy intense competition. Football, tennis, rugby, basketball, golf, Formula One, and other top commercial sports are all extremely adrenaline-pumping, except for golf, which is less intense, according to Forbes. The World Cup, Europa League, UEFA Champions League, and the five main soccer competitions (Premier League, La Liga, Ligue 1, Serie A, and Bundesliga) are worth over $100 billion (Statista Research Department, 2022), more than any other sport, according to Forbes, making men’s football by far the most significant sport in the world. With a salary of $130 million annually (Forbes, 2022), Lionel Messi will be the highest-paid athlete in 2021. However, the top 50 in terms of revenue are divided between 18 athletes in basketball, 14 in rugby, 5 in football, 3 in boxing, golf, and tennis, 2 in motor racing, and 1 in baseball and mixed martial arts (Forbes, 2022). The fact that every basketball player is from the NBA and every American football player is from NFL demonstrates how far ahead the US is in terms of the commercialisation of sports. Even if the ordinary NBA player laments that their income is increasing far more slowly than that of the superstars, Nathen Chen, the winner of the men’s figure skating competition at the Beijing Winter Olympics, will make over $5 million this year (Nora, 2022). The vast majority of sports have a significant gender gap, except for tennis, which is relatively small. For example, in football, where France won the 2018 World Cup in Russia and received $38 million in prize money (FIFA Council, 2018), the U.S. women’s soccer team only received $4 million in 2019 despite winning two FIFA Women’s World Cups. The U.S. Soccer Federation declared equal pay for the men’s and women’s national soccer teams in May 2022. The US women’s soccer team has a solid track record and consistently outperforms the US men’s soccer team in terms of commercial sponsorship and endorsements. Serena Williams, who has always worked to advance gender equality, must acknowledge that “The tennis programme has come a long way in encouraging gender equality among participants. We must uphold equality while working to achieve it further. The next step is to extend this equity to all sports and to encourage more female athletes to participate in other

128

L. Peng and B. S. Nayak

sports.” Many critics contend that because this is a commercial event, ticket and sponsorship sales for men’s and women’s matches in the same sport are different, and complete equality could have an adverse effect on temporary and ticket sales and, thus, the natural development of the event. However, the commercialisation of women’s tournaments in many sports began later than it did for men. For instance, the first men’s World Cup was held in 1930, whereas the first women’s World Cup was hosted 61 years later, in 1991, and the WNBA was even founded in 1996. On the other hand, women’s singles competitions began at The Wimbledon Open in 1884, which encouraged women’s tennis to become more commercialised than other women’s sports. Women’s commercial sports competitions started later than men’s, requiring time for the market and audience to grow. Both the event’s organisers and competitors had to put in more effort. The most significant component in the business value of the athlete is, therefore, the robust market for the sport itself, the large audience, and the high level of commercialisation of sport in the location where the sport is played. Tim Duncan, the renowned NBA power player, was a former US junior swimming champion, as was Philip John Neville, a former England left-back and a member of Manchester United’s 92 Golden Generation. In addition to their enthusiasm for basketball and football, they also have practical concerns for their own growth.

Match Between Athletes and Business Value of the Project Even for the most popular sports things, there are notable disparities between products and even between players with varied duties for the same item. This is because the core business values of various sports vary. The best way for a player to increase their business value is if they align with the sport’s primary business value. A significant chunk of football players’ accessories is jerseys. After a transfer, the news of jersey sales and the share of sales is discussed in the media, regardless of whether the player is Lionel Messi or Cristiano Ronaldo dos Santos Aveiro. According to incomplete data, the average footballer’s shirt sales are almost the same, except for superstars like Lionel Messi, Cristiano Ronaldo dos Santos Aveiro, and Neymar da Silva Santos Junior. A star’s typical footwear endorsement price, or even a combination of endorsement fees, is not very expensive, unlike basketball, where a player’s shoe endorsement has traditionally served as a symbol of their economic value and as the subject of media attention. LeBron James, for instance, signed a lifetime contract with Nike worth $1 billion after receiving a seven-year, $90 million contract from the brand when he joined the NBA in 2003. Meanwhile, athletes like Kevin Durant and Stephen Curry have shoe deals worth an average of more than $20 million annually. Numerous everyday celebrities have millions of endorsement deals with sneakers. It is commonly known that centres don’t sell shoes; Joel Embiid, who claimed to be the centre with the most significant amount of sneaker endorsement at the time, never disclosed the exact number, while

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province

129

Karl Malone, a well-known centre in the early years, couldn’t even secure a sneaker sponsor. Additionally, basketball and football were initially marketed toward the general public in terms of commercial endorsements. In addition to athletic goods, the brands that players promoted were mostly consumer items like beer, milk, and cell phones. Tennis, however, has long had an “aristocratic image,” with players sponsoring a variety of high-end companies, such as Mercedes Benz, Land Rover, Aston Martin, Rolex, TAG Heuer, and so forth. As a result, an athlete’s business value will swiftly rise if they fit well with the sport’s primary business value.

Individual Sports Performance of Athletes Despite all the off-field elements, sports are primarily still about performance. Sports are about getting higher, quicker, and stronger. When an athlete achieves a breakthrough achievement, they are not only given event-related awards, but their popularity also skyrockets, resulting in brand sponsorships, endorsements, and a spike in sales of ancillary goods. A devoted fan base and a sustained market following can be acquired if a high level of competitiveness is maintained for a considerable time. The Lionel Messi and Cristiano Ronaldo team has dominated men’s international football for nearly the past fifteen years. They have also long held the top spot in the footballers’ earnings rankings. In addition to being the best earners in men’s tennis, Roger Federer, Novak Djokovic, and Rafael Nadal have dominated the world of men’s tennis for the past twenty years.

Individual Sports Characters of Athletes The level of athletic competition, however, virtually invariably determines an athlete’s economic value for the majority of sports. But there are some exceptions, such as in women’s tennis, where Maria Sharapova, who has topped the global list of female athletes’ earnings for 11 years straight, is still far from Serena Williams’ 23 Grand Slam singles titles in terms of her record, with five Grand Slam wins, except that her status as the media’s chosen “most beautiful female athlete,” her business value is more prominent in the context of luxury brands such as perfume, jewellery, and watches that she wears, which are more expensive. By winning the junior girls’ singles at the Wimbledon Tennis Championships, Eugenie Bouchard automatically made her way into the top 10 female athletes’ earners of the year list for her attractiveness. Brands choose spokespersons based on a variety of factors, including the spokesperson’s physical attributes as well as how well their personalities mesh with

130

L. Peng and B. S. Nayak

the brand’s corporate culture. Roger Federer has maintained his lead in terms of business value despite having a worse record than Rafael Nadal and Novak Djokovic over the past three years. This is probably because he is not only excellent on the court but also a gentleman off it, taking care of his family, loving his country, and serving the public. It was sometimes said that American newspaper tycoon William Randolph Hearst could influence the outcome of the US presidential election by exerting media control. Yet, he was powerless to champion his gorgeous lover Marion Davies. The audience for movie actors is a tremendously nuanced phenomenon that is still incomprehensible to reason. Athletes also require audience support, and many athletes, particularly in some individual sports, are not as commercially viable due to a lack of public appeal. For instance, Michelle Wingshan Kwan, who retired more than ten years ago without having won a Winter Olympics gold, is far more well-liked than Nathen Chen, the men mentioned above’s figure skating winner from the Beijing Winter Olympics, who is also of Chinese origin. A similar issue affects Mark Selby; despite being the world’s best snooker player, the crowd still prefers Ronnie O’Sullivan’s playing style, according to online fan comments.

Channels of the Business Value Expression Business value is mainly expressed in annual salary or competition bonuses as well as endorsement and sponsorship payments over the course of a career for athletes because performance and personal image are significant variables in assessing business worth compared to athletes in similar sports. With the advancement of technology, several well-known athletes have begun to experiment with their own brands, venture into unrelated industries, or make profitable investments. The most famous example is Michael Jordan, whose career annual salary totals less than 100 million dollars when the only absolute value is taken into account. However, Jordan is more successful due to his collaboration with Nike, which resulted in the development of the AIR JORDAN sub-brand. According to estimates from the American media, as of 2020, Jordan has generated a staggering $1.3 billion in revenue alone just from Jordan’s and Nike’s cooperation. Numerous sportsmen on the Forbes list have businesses outside of sports, including Tom Brady, the quarterback of the New England Patriots, Maria Sharapova, and Cristiano Ronaldo, who has his own brand called “CR7.” The “TB12” brand is exclusive to Tom Brady. Success has also been achieved by other sportsmen who have transitioned into other professions due to their unique talents, such as Dwayne Johnson, a well-known professional wrestler who later became an actor and producer and the highest-paid actor in the world in 2020.

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province

131

Special Impacts Sports athletes’ nationality and ground-breaking achievements in their sport are two further unique factors that have a bearing on their business value. Naomi Osaka, a Japanese tennis player, was once ranked first among female athletes by Forbes. She was not particularly competitive as an American-born Haitian-Japanese mix with the Williams sisters in front of her and Cori Gauff in her rear. However, choosing to represent Japan would have made history for Japan and gained more endorsements. She later obtained sponsorships from several wellknown companies, including Tonex, Shiseido, Nissan, and LV. Eileen Gu, who is of mixed Chinese and American ancestry, decided to represent China at the Winter Olympics in Beijing and also garnered much support. Like George Weah, who became a Liberian icon after winning the 1995 Golden Ball, FIFA World Footballer of the Year, and African Footballer of the Year, other well-known athletes who entered politics due to their fame also found great success. After leaving politics, he was elected Pakistan’s Prime Minister. Because of their particular experience, they are also more commercially useful after retirement than the normal athlete.

Role of Female Athletes in the Expansion of Business Value Increasing numbers of female athletes are utilising social media to develop a stronger personal brand image and engage with consumers (Geurin, 2017). Through selflove, self-disclosure, and self-empowerment, the female athlete’s identity becomes apparent (Toffoletti & Thorpe, 2018). This strategy increases the visibility of female athletes to counter the marketing and promotion dominance of male athletes (Antunovic & Hardin, 2012).

Female Athletes in Social Media and Advertising The worldwide interest in women’s sports is growing substantially. Numerous professional athletes use social media to promote their own brands by highlighting their personal life, training regimes, product endorsements, and advertising (Li et al., 2020). The growth of mobile clients has transformed mobile phones and computers into a second screen in addition to the television (Billings & Ruihley, 2013), hence boosting the interaction between fans and athletes, coaches and clubs (Naraine & Parent, 2016). However, the most recent study by Cooky et al. (2015) revealed that just 3.2% of sports news is dominated by female athletes, and only 2% of ESPN’s total airtime is devoted to female sporting events. More than four-fifths of sports coverage on

132

L. Peng and B. S. Nayak

television concentrated on male athletes and men’s sports, whereas less than ten percent focused on female athletes and women’s sports, according to research by Lumby et al. (2009). New coverage indicates that female athletes are still underrepresented in sports (Cooky et al., 2013). This pattern is even more apparent in contrast between Olympic and non-Olympic years when the share of women-led sports coverage significantly increases (Litchfield & Osborne, 2015). Coche (2017) utilised quantitative analysis to evaluate how athletes structured their Twitter profiles. Female athletes prefer to share professional photographs rather than action images. At the Rio Olympics, 70% of tweets about male competitors displayed their individual sporting pictures, but just 40% of tweets about female athletes did so. For female athletes, showcasing their image in award ceremonies, media interviews, and team pictures was more important than presenting their sporting image. Female athletes were portrayed as passive participants in sports. Twitter has introduced the concept of interaction and sharing to traditional sporting events (John & Stuth, 2013). However, most research still focuses on analysing the profiles and personal brands of female athletes (Guerin, 2017), with little attention paid to whether female athletes receive equal coverage on Twitter compared to male athletes. Examining if Twitter’s coverage of female athletes has removed gender prejudice is worthwhile (Sainz de Baranda, 2010). The survey reveals that Instagram users have a greater engagement rate than Facebook users, with an average engagement rate of 0.15% on Facebook posts compared to 2.4% on Instagram (Feehan, 2019). Instagram is becoming the primary platform for fan engagement with players and clubs (Instagram, 2018). Moreover, Instagram’s stories feature makes the platform more accessible to young people, and this new kind of promotion has the potential to improve athletes’ brand awareness (Li et al., 2020). Smith and Sanderson (2014) contradict previous research, which indicated that female athletes outnumbered male players in sports photographs and that the majority of pictures of female athletes did not feature off-field and non-sports stances. Female athletes typically use Instagram to highlight their personal hobbies and lives, rarely focusing on competitive photographs. They strive to generate a social effect with their supporters and control their individual sporting displays. Therefore, professional teams must strategically utilise the platform to enhance the athlete’s personal brand (Anagnostopoulos et al., 2018). The concept of the sports-media-commercial complex was introduced by Messner (2003), where sports became one of the mediums for promoting consumer goods (Messner et al., 2000), and the London 2012 Olympic Games were the first time that every country’s delegation included at least one female athlete, while the percentage of female athletes in this edition reached almost 45% (Brennan, 2012). Female athletes are increasingly in the public eye, and the number of professional female athletes and their performances are setting records repeatedly. However, female athletes receive far less media coverage than their male counterparts (Bishop, 2003), as female athletes are still considered an irrelevant part of many media platforms and the sports media is one of the tools to maintain male privilege (Cooky et al., 2013). The achievements of female athletes should not be disregarded, and they are one of the mediators that influence sport-viewing behaviour (Entman, 1993). However,

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province

133

in terms of how female athletes are marketed and promoted, the majority of people believe that the most effective method to do so is through something other than their professional sport (Kane, 2013), such as their appearance and identity outside of that of an athlete. This positioning disregards the individual accomplishments of female athletes and diminishes their sporting prestige in the minds of viewers (Fink, 2015). The existence of this negative cycle does not contribute to the growth of the business value of female athletes. To transform female athletes and women’s sports, more professional sports managers should be recruited. Women’s sports leagues should be established in this sports media business complex to break the traditional marketing approach that emphasises promoting the physical appearance of female athletes. Despite the fact that the number of female athletes and women’s events are reaching new heights and that they are achieving incredible results, there is still a need to raise awareness of this inequality in sporting events and to construct a sports media business complex that belongs to female athletes (Fink, 2015). Meier and Saavedra (2009) proposed that developing female athletes as role models can motivate more women to participate in sports. When women can become key players in athletics, as well as in all aspects of life, there is more hope for women to attain equal status, as their outstanding accomplishments transcend gender boundaries (Meier, 2015). Female sports growth is hindered by the absence of female athletes’ presence in the media and female employee representation in sports marketing organisations (Mills, 2010). Therefore, the increased exposure of female athletes and the growing number of women in senior executive positions in sports organisations have contributed to the eradication of gender inequity and helped women realise their full potential (Meier, 2015).

Female Athletes in China in Social Media and Advertising Xu and Kreshel (2021) suggested that China should mould female athletes differently using social media. It is difficult for sportsmen and women in China’s state-run sports system to pursue their ideal sports careers. Li Na, a former national system-trained tennis star who went abroad to train, compete, and accomplish exceptional success at her own expense, has a more realistic image on social media than the archetypal Chinese athlete who does nothing but train. In this phase, she can better realise her identity as an athlete and an ordinary person. Female athletes under the state-run sports system and those under the individual system promote their personal brand image differently. Athletes under the state-run sports system do not have a professional marketing team to promote their personal brand image (Xu & Kreshel, 2021), so it is difficult for fans to discover the unique qualities of female athletes under this system. This has unquestionably increased the distance between spectators and athletes, which has impeded the development of Chinese female athletes.

134

L. Peng and B. S. Nayak

In China, successful athletes are elevated to the status of national heroes, and female athletes appear to be accorded greater respect than their male counterparts (Dong et al., 2007). In China’s traditionally strong sports, such as volleyball, diving, and table tennis, female competitors have also outperformed male athletes (Liu & Brock, 2011). Therefore, it is beneficial to assess the effects of female athletes in China, particularly the endorsements they receive (Liu et al., 2007). The development of Wuhan’s sports sector is centred on the establishment of an internet+ platform, with the introduction of digitalisation in stadiums facilitating more public engagement in sporting events. In addition, Wuhan has produced notable female athletes in a variety of sports, including Li Na in tennis, Fu Mingxia in diving, and Chen Jing in table tennis. This provides Wuhan with an advantage in marketing and promoting female athletes by blending the city’s character with the personalities of the athletes to increase their economic value (Dong, 2011). Male athletes and men’s sports continue to dominate media coverage of sports today. There should be an equitable allocation of sports media goals, and female athletes’ accomplishments should not be marginalised. In addition, the media should evaluate the focus on female athletes as compared to male athletes. The focus is still on their looks and body image rather than their athletic performance (Trolan, 2013), which can hinder the career growth of female athletes in the future.

Chinese Female Athletes and Business Value As an integral part of the commercial activities of the sports industry, the primary characteristics of the business value of female athletes are, firstly, the basis of the business value of female athletes is the athletes’ leading performance, i.e. the “head effect,” but the primary determining factor is the popularity of the sport itself and the market popularity of the athletes’ personal image IP. The optimal mix of these three variables can continuously raise the value of the athlete’s intangible assets while also ensuring the expansion of the market and the success rate of the deal. Moreover, the stage of the business value of female athletes, the cycle of the business value of female athletes, exhibits a degree of volatility, and the business value of female athletes is not precisely positively connected with the athletic level curve. The business value of female athletes is volatile, and their business value and the curve of their athletic level are not precisely positively correlated; their business value may fluctuate significantly at different stages of their athletic level, particularly when they reach the pinnacle of their sports. Thirdly, due to the unique physiological characteristics and social obligations of women, female athletes’ business value may not only be applied to the traditional sports manufacturing industry chain but also modern service industry market sectors like parenting and children’s intellectual development due to the increasing rigid demand of the livelihood consumer market, despite some risky and fluctuating factors.

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province

135

Chinese female athletes have an advantage in numerous sports and consistently hold the top spots in the world rankings in the three major sports diving, badminton, and table tennis. Most of China’s female athletes have competed for their nation in various sporting competitions under the national sports system. Tennis player Li Na from Wuhan represented her nation individually in 2011 by winning the women’s singles title at the French Open. This was her second podium result of the year after placing second at the Australian Open. Her victory was a significant advancement for women’s tennis in Asia and aided the growth of the game in China. Major brands have flocked to her as a result of her victory, and her individual business value has reached a peak. In this regard, Her solo competitions have become a calling card for tennis in China. Li Na’s success has also played a significant role in her decision to leave the national sports system and compete on her own, in addition to her superb form and superior technical abilities. Li Na, a famous and representative female tennis player in Wuhan, Hubei Province, China, is analysed in the research that follows to discuss the factors that led to the development of her market worth throughout the most illustrious ten years of her career’s golden era (2010–2020). In addition, using a comparative analysis of the disparities between China and other nations in the commercial value of female athletes and propose strategies for increasing the business value of female athletes in China through the development of the legal and management systems, the training of professional sports agents and intermediaries, the innovation of market operation strategies, and the development of world-class female athletes. This research also revealed ways to deal with the rise in female athletes’ business worth in China.

Formation of Li Na’s Business Value Outstanding Performance in a Competition Acts as the Initial Foundation for Business Value Li Na began playing tennis when she was six years old and became a professional when she was seventeen. She has finished second in 12 world-class tennis tournaments and won nine of them over the course of her career. She ended Western athletes’ long-standing dominance of women’s tennis by placing second in the 2014 World Women’s Singles Rankings. Her victory at the French Open presented a significant chance for her to raise her market worth, and her outstanding performances have made her a sought-after commodity by numerous businesses as a result of her appearances in significant tennis tournament finals. Li Na has been picked as a spokeswoman by well-known brands such As Nike, Mercedes Benz, and Rolex to improve their brand exposure while also providing her with gear for the competition. Li Na signed ten sponsorship contracts this year and earned US$23 million.

136

L. Peng and B. S. Nayak

A Positive Personal Brand Contributes to a Higher Business Value Li Na is adored by fans both at home and abroad and has consistently given off a positive impression of being cheerful, healthy, frank, and hilarious with a great sense of humour. Her excellent personal image fits well with the corporate culture of many businesses, and image building is key to getting business endorsements. Li Na’s tenacity in the face of difficulty, her spirit of challenge, her desire to triumph, and her perseverance in pursuing it are in line with the corporate spirit promoted by Taikang Life, and this has grown to be an extremely significant factor in how much Taikang Life values her. She won her first Grand Slam title in a tennis tournament where Europe and the United States are so strong. One of the main motivations for Taikang Life’s interest in Li Na is due to this. Her positive and healthy image and pursuit of quality of life perfectly match Kunlun Mountain Mineral Water’s commitment to promoting the idea of “drinking good water to improve the quality of life.” With Li Na’s endorsement, these brands have undoubtedly gained significantly. They are now more likely to satisfy consumers’ psychological requirements, get recognition, and win favour, boosting product sales and increasing income, improving the brand’s reputation. She officially retired from tennis in September 2014 after reaching the peak of her professional tennis career, but her passion for the sport and her contribution as a role model for influencing, guiding, and inspiring the younger generation to endure. In fact, She became the 60th member of the Laureus World Sports Institute in June 2016, the first Asian player to be inducted into the Hall of Fame in 2019, and the ambassador of the China Tennis Tournament in August 2020.

The Expert Business Value Operation Team Has Assisted the Value Enhancement Li Na’s accomplishments and reputation alone are insufficient to draw in as many prestigious sponsors, and her commercial team has a vital role to play in increasing her commercialisation. Li Na’s marketing staff has always been extremely picky and demanding regarding the businesses she supports. They will visit the brand and choose based on its operational profile and social rating before signing a contract. She has a win-win relationship with the brands she supports because those brands have a great reputation and have been around for a while. Li Na joined IMG in 2009 and has been playing worry-free ever since. Given that other tennis stars, including Federer, Rafael Nadal, and Maria Sharapova, have signed with IMG, it is clear that IMG has a comprehensive structure in place to increase her economic value. She was one of the most remarkable women’s tennis players of all time, and because of her influence on the sport and the growth of tennis, she has a very high market value.

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province

137

The Market in China Li Na has the support of both domestic and foreign brands thanks to the Chinese market, which obviously enhances her market worth. Nevertheless, since Djokovic is from Serbia, a small, war-torn nation with an insufficient domestic market, and has recently been ignored internationally by the European and American powers as a result of the Russian-Ukrainian conflict, many high-end sponsors are put off. Djokovic is one of the top four men’s tennis players and the former world number one. He has both achievements and an appealing image. The Chinese nationality of Li Na, which has incredible financial potential for her, has been compared to Novak Djokovic’s uncle as something to be jealous of her Chinese nationality has a big market. International brands hope to enter the Chinese market through Li Na, who is China’s calling card and a national icon with countless fans willing to pay for her endorsement. Domestic brands can capture the domestic market by signing her and at the same time go global through Li Na’s influence internationally. According to the viewing figures, a record 116 million people watched the French Open Final in China, which would be unfathomable in any other nation. Her path towards professionalism and commercialisation has been made strong and powerful by the enormous market in China that serves as a firm foundation for her commercial value. Li Na has established herself as a favourite of many prestigious advertisers. She has leveraged tennis’ enormous popularity and the sizable market that Chinese nationality represents to acquire massive economic value.

National Sports System and the Growth of Athletes’ Business Value Li Na, Peng Shuai, Yan Zi, and Zheng Jie signed solo agreements with China’s National Tennis Management Centre at the end of 2008, authorising them to train, compete, hire their own coaching staff, make their own plans, and self-financing. However, they were forced to allocate a part of their personal income to China’s National Tennis Management Centre. To represent their nation at the Olympic Games, Asian Games, and Confederations Cup, players who represented themselves must be available at the national team’s discretion. Players will have more freedom under the solo model in terms of competition and prize money, emphasising their individual growth and effectively embracing the “individual” model of tennis. Additionally, it means that the players will be subject to a level of pressure never before experienced, both from the external financial pressure and from their personal capacity to adjust to the change from the national system to the personal pattern of professionalism. Regarding the national sports system, it can be concluded as a gathering of theoretical viewpoints, directives, policies, measures, and development strategies put

138

L. Peng and B. S. Nayak

into place by our government to foster competitive tennis, raise the technical proficiency and overall competitive strength of our athletes on the international arena, and achieve the strategic objective of Olympic glory. The selection of physically exceptional and highly talented athletes and the use of a systematic and scientific training model to build a group of outstanding athletes is more constrained than the personal pattern when relying on the nation’s human, financial, and material resources. The personal pattern is consistent with our national circumstances and the outcome of reform and innovation inside the national sports system. Li Na shocked everyone by winning the French Open in 2011 and the Australian Open just 13 months after beginning the solo era. Due to Li Na’s success, the tennis community considered that their personal pattern had produced results that the national system had not been able to. Additionally, the personal pattern allowed athletes to choose to compete on their own based on their athletic condition and gave them the freedom to modify their training regimens and even switch coaches. The solo model follows this trend, maximising athletes’ potential and enabling them to perform at their best. Tennis is highly professional, market-oriented, and globalised. After Li Na won the French Open, there was a never-before-seen debate about the national and personal systems. Some even advocated for the national sports system to be abolished, claiming it impeded the growth of tennis in China while wasting much money on unproductive endeavours. In reality, China’s tennis management system has reformed in recent years. As a result, Li Na has emerged as the nation’s first golden flower, and the national sports system has been opened up to allow athletes to prosper. The national sports system, which emerged from a planned economy, is no longer able to oversee the national sport in the face of modern sport. Sports have become significantly professionalised and commercialised due to sports globalisation, which has wreaked havoc on the domestic national sports system. But it’s also important to note that Li Na would not be the player she is today without the early growth of the national sports system. The national system guaranteed the early training of the athletes, and the athletes’ years of training and experience laid the groundwork for Li Na’s current success. The national system has reached a point where innovation is required, and the activity must abide by the rules of tennis played internationally and fit into the global trend. The success of Li Na is not just about herself. It is also about how well the national tennis system has adapted to modern times and the global tennis craze. The personal pattern is a creative innovation, but it doesn’t undercut the national sports system; rather, it enhances it in a way that is consistent with our national circumstances. To develop and innovate is a good model for the development of the sport, and it is worthwhile to learn from the successful experience of the single flight of tennis based on the national conditions of the country.

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province

139

Business Value of Chinese Female Athletes In essence, the business value of athletes is created by converting the element of investment in human sporting skills into a measurable manifestation of value via commercial operation and bearing. In a market economy, the athlete is not only the opponent in the arena but also the centre of professional sport. All economic operations in the sports business and sports market are tightly centred on the athlete as the centre. The object of athlete business value refers to the socialised individuals in sporting business relationships, i.e. the athletes. In the interaction of the interdependence and needs of the subject and object of the athletes’ business value, through the embodiment of commercial activities, it is possible to meet the needs of all parties, thereby promoting the development of the sports economy and ultimately forming the athletes’ business value.

Current Status of the Business Value of China’s Female Athletes As Chinese competitive sports continue to develop, athletes’ business worth is becoming more apparent due to economic growth and business penetration into sports activities. Female athletes’ business value is currently experiencing favourable market development chances. Others have a cross-border profile and personal image tag. Now, the primary sources of business value gains for female athletes include athlete intangible asset creation, signing fees and additional income from the transfer process, event prize money, cultural, intellectual property, advertising endorsements, and sports sponsorship. At this juncture, professional sport and commercial development can be harmonised. For instance, Li Na, Asia’s first Grand Slam women’s singles champion, has worked extensively with luxury brands such as Mercedes Benz and Rolex to address the demand for a pioneering spokesperson in her vertical to highlight the brand’s professional image. After the ceremony, Yang Qian and her hairbands and nail art rapidly dominated the trending requests, and sales of the yellow duck headgear on Taobao increased 42-fold. For the nation, Olympic champions are the embodiment of heroes. Regardless of the group or class, they are affirmed from the heart, which is a type of spiritual trust and support for the sense of national glory. This will motivate ordinary consumers to pay attention to and support the Olympic champions’ “same model” and be willing to purchase the products they endorse. The development of the business value of Chinese women’s sport is in its infancy. The current scenario is primarily as follows. Initially, in China’s sports management system, most sports and athletes, both men and women, are still administratively managed and face the problem of aligning the traditional management system with the market economy, especially the identity and property rights attributes of athletes undergone substantial identity transformation. Specifically, the identification of ownership and the structural diversity of the

140

L. Peng and B. S. Nayak

distribution method have been affected by the identity and property rights of athletes. In China, there has been no coordinated management body for athletes’ participation in commercial activities, and each sports centre has independently formulated nonuniform standard management rules, resulting in fragmented management, numerous rules, varying standards, a lack of development awareness, and lengthy decisionmaking processes, which has prevented the establishment of effective management boundaries. Existing sports management departments lack the economic understanding and commercial development expertise to identify and resolve potential risks and issues that may arise during the process of business value realisation. In addition, some significant research and endeavours are also being carried out progressively as the commercialisation of sports progresses. The China Volleyball Association made an official announcement in August 2022, designating the China Sports Communication Group, a division of the China Sports Industry Group, as the team’s only business development organisation. Secondly, on 4 June 2022, a new amendment to the Sports Law of the People’s Republic of China was enacted. This is the first comprehensive and systematic revision after nearly 27 years since the promulgation and implementation of the Sports Law in 1995. In response to the new situation, era, and requirements, the revision of the Sports Law has resolved major fundamental, systemic, and overall problems in the field of sports from a legal standpoint. Still, in competitive sports, these problems have not been resolved. In the chapter, the business development behaviour and business value realisation of athletes have not yet been unified, agreed upon and systematically regulated; consequently, in the practice of business value development of athletes, there are still some relatively prominent legal issues to be resolved, such as the property rights and ownership attributes in the commercial use of athletes’ personality marks, which leads to disputes over the distribution of the prizing. Thirdly, With the active guidance of macro policies, the active exploration of market players, and the continuous cultivation and stimulation of consumer demand, which all support the synergistic development of the sports industry with economic and social benefits, China’s sports industry is projected to reach 5 trillion Yuan in 2025. The rapid rise of the sports business is an inevitable consequence of the resurgence of consumer demand, and it is becoming a major force in China’s economic transformation and upgrading. During the development of the sports industry, Chinese female athletes have achieved a certain level of influence in society through their own efforts and the demonstration of their competitive achievements. However, this influence must be transformed in the capital and industrial markets, and it must receive more attention and investment from the capital and be effectively integrated with other industries through a variety of channels in order to reflect the maximum commercial potential. Integration of the sports business will be strongly influenced by policy support and capital promotion to meet market demand. Moreover, the growth of the business value of Chinese female athletes is still in a “free” state, with a high degree of arbitrariness and variability, the sports intermediary market, the promotion of sports brokers’ agents, and the standardised operation behaviour are relatively poor. Although there has been some market exploration, the national unified development model for women’s teams such as diving, table tennis,

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province

141

and volleyball remains the primary model, complemented by the independent market development model exemplified by Li Na and Eileen Gu. On the one hand, Zheng Qinwen has registered as an athlete with the Wuhan Tennis Centre and will receive financing from the Wuhan Sports Bureau for the next four years to ensure her and her team’s normal functioning and to hire high-calibre coaches. The Wuhan Sports Bureau will pay a specific amount of funds to her and her team over the next four years to assure their regular operation and provide complete assistance in terms of recruiting high-calibre coaches, scientific research, medical rehabilitation, and other logistical support. With the rapid development of big data, rehabilitation medicine, and other industries, as well as the internationalisation of overseas interoperability, the athletes’ sports life cycle is extended through scientific protection, thereby enhancing athletic performance and laying the groundwork for the sustainable development of their business value. In women’s sports such as swimming, skiing, aerial skills, and speed skating, the “overseas training, competition instead of training” training model has been implemented, whereas, in volleyball and tennis, extensive data analysis and sports rehabilitation training have been implemented to optimise the athletes’ performance. In the direction of digital transformation, with 5G communication, artificial intelligence, and other cutting-edge technologies thriving, on the one hand, the combination of satellite live technology, big data algorithms, and Internet communication channels effectively increases the supply capacity of the sports industry. On the other hand, digital technology has broken through the traditional form of the sports consumption market, with intelligent sports and home fitness services conspicuously emerging. Shangtang Technology, the world’s premier artificial intelligence software firm, debuted its first home consumer artificial intelligence robot, the “SenseRobot” AI chess robot, in August 2022. Olympic gold medalist Guo Jingjing served as the company’s chief experience officer. Olympic champion Guo Jingjing is the Chief Experience Officer for the artificial intelligence chess robot.

Strategies to Enhance the Business Value of Chinese Female Athletes Enhancing the economic value of Chinese female sports should not only satisfy the current requirements of the localised management system but also draw from the successful experience of foreign female athletes in increasing their commercial worth. The following techniques are offered in light of the obstacles and market risks encountered by Chinese female athletes in the current process of boosting their business value. 1. Accelerate the legalisation of sports, introduce laws and regulations for the commercialisation of female athletes as soon as possible from a more open and integrated perspective, both to regulate uniform requirements and to form differentiated management rules based on the characteristics of sports, to establish

142

2.

3.

4.

5.

6.

7.

L. Peng and B. S. Nayak

a legal protection mechanism for athletes’ rights and interests, and to provide professional protection for intangible assets. Make use of social media and big data technological innovation to obtain and accumulate data on the overall development of the sports industry and its sub-sectors that transcend geographical boundaries and project margins, and conduct scientific analysis from multi-dimensional perspectives such as competitive performance, participating audiences, the degree of market operation, and development trends in order to provide precise data support for policy formulation and strategic development. Continue constructing a unified management platform for athletes’ commercial activities, encourage the emergence of sports star agents, and establish sports intermediaries with international perspectives and resource integration capabilities to emphasise the value-driven nature of professional sports services. Continue building exceptional female athletes with rapid growth in athletic performance and influence, Using the growth path of young athletes like Eileen Gu and Zheng Qinwen as a model, breaking the niche of sports, attracting capital participation through the creation of internationally renowned sports intellectual properties, and showcasing the athletic talent of various female athletes and the power of media communication expansion. Further, incorporate parts of the market-oriented operation and attempt to harness the flow economy to maintain a positive personal image on social media, so transcending the commercial constraints that were initially confined to the sports field. In addition to demonstrating their value in competitive sports, female athletes can use their strong affinity and easy access to audiences to create greater personal value in the areas of commercial endorsement, mother-and-child market, youth mentoring, sports promotion, variety shows, etc. To expand the growth space of female athletes after retirement, they can take on the social roles of professional managers, technical officials, coaches or referees, volunteer workers, etc., so as to realise the transformation and upgrading of their careers and maintain the long-term interest of the commercial market in them. Explore the new development model of online and offline integration in the “postepidemic period” of the sports industry, integrate sports resources, reconstruct the business model of the sports industry market, drive the sustainable development of the industry with the release of consumer potential, and offer additional chances for female athletes to increase their business value.

Conclusion In conclusion, the factors influencing the growth of female athletes’ business value is a subject at the intersection of sports economics and gendered based behavioural economics. One of the most effective ways to promote the development of the entire sports industry is to effectively increase the business value of competitive sports, which has only recently been commercialised. Once more, the development

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province

143

of China’s sports industry needs to overcome the constraints of the management system, increase industrial capital investment, bolster economic momentum and lay out the entire life cycle of sports industries. Last but not least, with the prevalence of the digital economy, sports stars have unique “fan economies” from the perspective of commercial operation, and the expansion of female athletes’ business value can be diversified through channels like online media, social media platforms, and live streaming, and these new channels are also becoming more popular. Research on behavioural economics is quite fascinating. It took more than a century for women to fight for their political rights, beginning with Mary Wollstonecraft’s 1792 essay “A Defence of Women’s Rights: A Critique of Political and Moral Questions” and ending with the British Parliament passing the Representation of the People Act in 1918, which granted women the right to vote with certain restrictions. Only a few female athletes have cracked within the top 50 in the thirty years since the Forbes athlete earnings list was published. It is within this context, the government needs to drive the market forces by which Chinese female athletes and the operating teams behind them can overcome the commercial management structure to boost their business value and advance women’s emancipation through sports.

References Abosag, I., Roper, S., & Hind, D. (2012). Examining the relationship between brand emotion and brand extension among supporters of professional football clubs. European Journal of Marketing, 46(9), 1233–1251. Anagnostopoulos, C., Parganas, P., Chadwick, S., & Fenton, A. (2018). Branding in pictures: Using Instagram as a brand management tool in professional team sport organisations. European Sport Management Quarterly, 18(4), 413–438. Anagnostopoulos, C., & Shilbury, D. (2013). Implementing corporate social responsibility in English football. Sport, Business and Management: An International Journal, 3(4), 268–284. Antunovic, D., & Hardin, M. (2012). Activism in women’s sports blogs: Fandom and feminist potential. International Journal of Sport Communication, 5(3), 305–322. Arai, A., Ko, Y. J., & Kaplanidou, K. (2013). Athlete brand image: Scale development and model test. European Sport Management Quarterly, 13(4), 383–403. Bamford, D., Hannibal, C., Kauppi, K., & Dehe, B. (2018). Sports operations management: Examining the relationship between environmental uncertainty and quality management orientation. European Sport Management Quarterly, 18(5), 563–582. Billings, A., & Ruihley, B. (2013). The fantasy sport industry: Games within games. Routledge. Bishop, R. (2003). Missing in action. Journal of Sport and Social Issues, 27(2), 184–194. Blumrodt, J., Desbordes, M., & Bodin, D. (2013). Professional football clubs and corporate social responsibility. Sport, Business and Management: An International Journal, 3(3), 205–225. Braunstein, J., & Zhang, J. (2005). Dimensions of athletic star power associated with Generation Y sports consumption. International Journal of Sports Marketing and Sponsorship. Brennan, C. (2012). Finally. It’s all about the women at London Olympics. Available at: http://usatoday30.usatoday.com/sports/story/2012-07-25/London-Olympics-Brennanwomen/56488526/1. Accessed 14 July 2022. Brownell, S. (2005). Challenged America: China and America—Women and sport, past, present and future. The International Journal of the History of Sport, 22(6), 1173–1193.

144

L. Peng and B. S. Nayak

Catharine, L., Caple, H., & Greenwood, K. (2009). Towards a level playing field: Sport and gender in Australian media. Australian Sports Commission. Clausen, J., Bayle, E., Giauque, D., Ruoranen, K., Lang, G., Schlesinger, T., Klenk, C., & Nagel, S. (2018). International sport federations’ commercialisation: A qualitative comparative analysis. European Sport Management Quarterly, 18(3), 373–392. Clement, A. (2013). Professional female athletes: Financial opportunities. Journal of Physical Education, Recreation & Dance, 58(3), 37–40. Coche, R. (2017). How athletes frame themselves on social media: An analysis of Twitter profiles. Journal of Sports Media, 12(1), 89–112. Connell, R. (2008). Masculinity construction and sports in boys’ education: A framework for thinking about the issue. Sport, Education and Society, 13(2), 131–145. Cooky, C., Messner, M. A., & Hextrum, R. H. (2013). Women play sport, but not on TV. Communication & Sport, 1(3), 203–230. Cooky, C., Messner, M. A., & Musto, M. (2015). It’s dude time! Communication & Sport, 3(3), 261–287. Cortsen, K. (2013). Annika Sörenstam—A hybrid personal sports brand. Sport, Business and Management: An International Journal, 3(1), 37–62. Craft, B., Mayo, N., & Chan, P. (2008). Why branding can increase a professional athlete’s value: A rationale for designer engagement (PhD Diss.). The Ohio State University. Dong, J., Zhang, R., & Wang, D. (2007). Studies of women, culture, and sport. Beijing Sport University Press. Dong, Q. (2011). Research on the co-branding strategy of sports event and host city. In 2011 International Conference on Management and Service Science. Dumitrescu, L., & Budac, C. (2008). The business value. Management & Marketing, 6(1), 83–88. Entman, R. M. (1993). Framing: Toward clarification of a fractured paradigm. Journal of Communication, 43(4), 51–58. Erdogan, B. Z. (1999). Celebrity endorsement: A literature review. Journal of Marketing Management, 15(4), 291–314. Eriksen, I. M. (2021). “Teens’ dreams of becoming professional athletes: The gender gap in youths” sports ambitions’. Sport in Society. Available at: https://doi.org/10.1080/17430437.2021.189 1044. Accessed 19 June 2022. Feehan, B. (2019). 2019 social media industry benchmark report, Rival IQ. Available at: https:// www.rivaliq.com/blog/2019-social-media-benchmark-report/. Accessed 14 July 2022. Fenghua, Y. (2021). ‘“Internet+” city sports stadium service platform design and application. In 2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP). Ferrand, A., Chappelet, J.-L., & Seguin, B. (2012). Olympic marketing. Routledge. Available at: https://www.taylorfrancis.com/books/mono/10.4324/9780203132067/olympic-market ing-alain-ferrand-jean-loup-chappelet-benoit-seguin. Accessed 19 June 2022. Fink, J. S. (2015). Female athletes, women’s sport, and the sport media commercial complex: Have we really “come a long way, baby”? Sport Management Review, 18(3), 331–342. Forbes. (2022). The world’s 10 highest-paid athletes 2022 [Online]. Available at: https://www.for bes.com/sites/brettknight/2022/05/11/the-worlds-10-highest-paid-athletes-2022/. Accessed 16 July 2022. Geurin, A. N. (2017). Elite female athletes’ perceptions of new media use relating to their careers: A qualitative analysis. Journal of Sport Management, 31(4), 345–359. Guenzi, P., & Nocco, M. (2006). The launch of new brands by professional soccer teams: The case of U.S. Lecce - Salento 12. International Journal of Sports Marketing and Sponsorship, 7(3), 99–114. Humphreys, B. (2000). Equal pay on the hardwood: The earnings gap between male and female NCAA Division I basketball coaches. Journal of Sports Economics. Available at: https://doi.org/ 10.1177/152700250000100306. Accessed 14 July 2022.

6 Chinese Female Athletes and the Expansion of Business in Wuhan Province

145

Instagram. (2018). Scrolling, swiping, and scoring: Key moments in sports on Instagram. Instagram. Available at: https://business.instagram.com/blog/key-moments-in-sports-on-instagram. Accessed 14 July 2022. Jalonen, H., Tuominen, S., Ryömä, A., Haltia, J., Nenonen, J., & Kuikka, A. (2018). How does value creation manifest itself in the nexus of sport and business? A systematic literature review. Open Journal of Business and Management, 6(1), 103–138. Joan, M., & Stuth, K. (2013). Social media and the second screen. Marketing Insights, 25(1), 18–19. Kane, M. J. (2013). The better sportswomen get, the more the media ignore them. Communication & Sport, 1(3), 231–236. Kauppi, K., Moxham, C., & Bamford, D. (2013). Should we try out for the major leagues? A call for research in sport operations management. International Journal of Operations & Production Management. Kim, E., Walkosz, B. J., & Iverson, J. (2006). USA Today’s coverage of the top women golfers, 1998–2001. Howard Journal of Communications, 17(4), 307–321. Li, B., Scott, O. K. M., Naraine, M., & Ruihley, B. J. (2020). Tell me a story: Exploring elite female athletes’ self-presentation via an analysis of Instagram Stories. Journal of Interactive Advertising, 21(2), 1–37. Litchfield, C., & Osborne, J. (2015). Women in the sports pages: A brief insight into Olympic and non-Olympic years in Australia. The International Journal of Sport and Society, 4(4), 45–56. Liu, T., & Brock, J. L. (2011). Selecting a female athlete endorser in China: The effect of attractiveness, match-up, and consumer gender difference. European Journal of Marketing, 45(7), 1214–1235. Marie, H., & Jennifer, D. G. (2009). The influence of gender-role socialization, media use and sports participation on perceptions of gender-appropriate sports. Journal of Sport Behavior, 32(2), 207–226. Meier, M. (2015). The value of female sporting role models. Sport in Society, 18(8), 968–982. Meier, M., & Saavedra, M. (2009). Esther Phiri and the Moutawakel effect in Zambia: An analysis of the use of female role models in sport-for-development. Sport in Society, 12(9), 1158–1176. Messner, M. A., Dunbar, M., & Hunt, D. (2000). The televised sports manhood formula. Journal of Sport and Social Issues, 24(4), 380–394. Mills, L. (2010). The corporatization of women’s football in South Africa: A case study of the Sasol sponsorship and its transformative potential. In J. Shehu (Ed.), Gender, sport and development in Africa: Cross cultural perspectives on patterns of representation and marginalization (pp. 125– 134). CODESRIA. Naraine, M. L., & Parent, M. M. (2016). Illuminating centralized users in the social media ego network of two national sport organizations. Journal of Sport Management, 30(6), 689–701. Nora. (2022). Nathan Chen Net Worth 2022: Biography salary assets cars [Online]. Available at: https://caknowledge.com/nathan-chen-net-worth/. Accessed 14 August 2022. Ohanian, R. (1990). Construction and validation of a scale to measure celebrity endorsers, perceived expertise, trustworthiness, and attractiveness. Journal of Advertising, 19(3), 39–52. Roobina, O. (1991). The impact of celebrity spokespersons perceived image on consumers intention to purchase. Journal of Advertising Research, 31(1), 46–54. Sainz de Baranda Andújar, C. (2010). Mujeres y deporte en los medios de comunicación. Estudio de la prensa deportiva española (1979–2010). Universidad Carlos III Press. Scully, W. (1989). The business of major league baseball. Journal of Sport and Social Issues, 13(2), 131–132. Smith, T., & Westerbeek, M. (2007). Sport as a vehicle for deploying corporate social responsibility. Journal of Corporate Citizenship, 2007(25), 43–54. Stabell, C. B., & Fjeldstad, Ø.D. (1998). Configuring value for competitive advantage: On chains, shops, and networks. Strategic Management Journal, 19(1), 413–437. Statista. (2021). Number of employees in the sport industry in the United Kingdom (UK) from 2011 to 2018 [Online]. Available at: https://www.statista.com/statistics/608423/united-kingdom-spo rts-industry-number-of-employees. Accessed 16 August 2022.

146

L. Peng and B. S. Nayak

Statista. (2022). Revenue of the biggest (Big Five) European soccer leagues from 1996/97 to 2021/22 [Online]. Available at: https://www.statista.com/statistics/261218/big-five-european-soccer-lea gues-revenue/. Accessed 16 August 2022. Summerfield, G., Dong, X., Aslanbeigui, N., & Hu, J. (2011). Wage differentials, occupational segregation, and gendered creativity perceptions in the Chinese science and technology sector: Beijing and Wuhan. Eastern Economic Journal, 37(2), 178–196. Available at: https://www.jstor. org/stable/41239561. Accessed 19 June 2022. Thibault, V., Guillaume, M., Berthelot, G., Helou, E., Schaal, K., Quinquis, L., Nassif, H., Tafflet, M., Escolano, S., Hermine, O., & Toussaint, F. (2010). Women and men in sport performance: The gender gap has not evolved since 1983. Journal of Sports Science & Medicine, 9(2), 214–223. Tingchi Liu, M., & Brock, J. L. (2011). Selecting a female athlete endorser in China. European Journal of Marketing, 45(7/8), 1214–1235. Tingchi Liu, M., Huang, Y., & Minghua, J. (2007). Relations among attractiveness of endorsers, match-up, and purchase intention in sport marketing in China. Journal of Consumer Marketing, 24(6), 358–365. Toffoletti, K., & Thorpe, H. (2018). ‘Female athletes’ self-representation on social media: A feminist analysis of neoliberal marketing strategies in “economies of visibility.” Feminism & Psychology, 28(1), 11–31. Trolan, E. J. (2013). The impact of the media on gender inequality within sport. Procedia - Social and Behavioral Sciences, 91(1), 215–227. Wolfe, A., Weick, E., Usher, M., Terborg, R., Poppo, L., Murrell, J., Dukerich, M., Core, C., Dickson, E., & Jourdan, S. (2005). Sport and organizational studies. Journal of Management Inquiry, 14(2), 182–210. Woratschek, H., Horbel, C., & Popp, B. (2014). The sport value framework—A new fundamental logic for analyses in sport management. European Sport Management Quarterly, 14(1), 6–24. Xu, Q., Fan, M., & Brown, A. (2019). Men’s sports or women’s sports?: Gender norms, sports participation, and media consumption as predictors of sports gender typing in China. Communication & Sport, 9(2). Available at: https://doi.org/10.1177/2167479519860209. Accessed 19 June 2022. Xu, Q., & Kreshel, P. J. (2021). State versus professional: A case study of how Chinese new media construct elite female athletes. International Journal of Sport Communication, 14(1), 131–150. Yoshida, M., & Gordon, B. (2012). Who is more influenced by customer equity drivers? A moderator analysis in a professional soccer context. Sport Management Review, 15(4), 389–403.