The Changing Migrant Composition of Australia’s Population: Past, Present and Future (SpringerBriefs in Population Studies) 3030889386, 9783030889388

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SPRINGER BRIEFS IN POPULATION STUDIES

Tom Wilson · Jeromey Temple · Peter McDonald · Ariane Utomo · Bianca Brijnath

The Changing Migrant Composition of Australia’s Population Past, Present and Future 123

SpringerBriefs in Population Studies Advisory Editors Baha Abu-Laban, Edmonton, AB, Canada Mark Birkin, Leeds, UK Dudley L. Poston Jr., Department of Sociology, Texas A&M University, College Station, TX, USA John Stillwell, Leeds, UK Hans-Werner Wahl, Deutsches Zentrum für Alternsforschung (DZFA), Institut für Gerontologie, Universität Heidelberg, Heidelberg, Germany D. J. H. Deeg, VU University Medical Centre/LASA, Amsterdam, The Netherlands

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Tom Wilson · Jeromey Temple · Peter McDonald · Ariane Utomo · Bianca Brijnath

The Changing Migrant Composition of Australia’s Population Past, Present and Future

Tom Wilson Melbourne School of Population and Global Health The University of Melbourne Melbourne, VIC, Australia

Jeromey Temple Melbourne School of Population and Global Health The University of Melbourne Melbourne, VIC, Australia

Peter McDonald Melbourne School of Population and Global Health The University of Melbourne Melbourne, VIC, Australia

Ariane Utomo School of Geography, Earth and Atmospheric Sciences The University of Melbourne Melbourne, VIC, Australia

Bianca Brijnath Division of Social Gerontology National Ageing Research Institute Melbourne, VIC, Australia

ISSN 2211-3215 ISSN 2211-3223 (electronic) SpringerBriefs in Population Studies ISBN 978-3-030-88938-8 ISBN 978-3-030-88939-5 (eBook) https://doi.org/10.1007/978-3-030-88939-5 © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 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 Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Contents

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 4

2 International Migration and Australia’s Population . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

7 9

3 Projection Methods, Data and Assumptions . . . . . . . . . . . . . . . . . . . . . . . 3.1 The Projection Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Projection Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Input Data Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

11 11 14 19 22

4 The Future Demography of Australia’s Migrant Populations . . . . . . . 4.1 Pre-COVID Trends Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Global Talent Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Lower Immigration Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Higher Immigration Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 The Contribution of Migration to Projected Growth . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

23 23 32 34 36 38 43

5 Discussion and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45 48

6 Birthplace Population Profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Aggregate Population Profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.1 The Total Australian Population . . . . . . . . . . . . . . . . . . . . . . . 6.1.2 Australia-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.3 Overseas-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 ABS 2-Digit Category Birthplace Population Profiles . . . . . . . . . . . . 6.2.1 New Zealand-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.2 Melanesia-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.3 Micronesia-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.4 Polynesia-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

51 52 52 53 54 55 55 56 57 58

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6.2.5 UK-Born (Including Channel Islands and Isle of Man) . . . 59 6.2.6 Ireland-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 6.2.7 Western Europe-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 6.2.8 Northern Europe-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 6.2.9 Southern Europe-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 6.2.10 South Eastern Europe-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 6.2.11 Eastern Europe-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 6.2.12 North Africa-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 6.2.13 Middle East-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 6.2.14 Mainland South East Asia-Born . . . . . . . . . . . . . . . . . . . . . . . 68 6.2.15 Maritime South East Asia-Born . . . . . . . . . . . . . . . . . . . . . . . 69 6.2.16 Chinese Asia-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 6.2.17 Japan and Koreas-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 6.2.18 Southern Asia-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 6.2.19 Central Asia-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 6.2.20 North America-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 6.2.21 South America-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 6.2.22 Central America-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 6.2.23 Caribbean-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 6.2.24 Central and West Africa-Born . . . . . . . . . . . . . . . . . . . . . . . . 78 6.2.25 Southern and East Africa-Born . . . . . . . . . . . . . . . . . . . . . . . . 79 6.3 Individual Countries and Territories of Birth . . . . . . . . . . . . . . . . . . . . 80 6.3.1 England-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 6.3.2 China-Born (Excluding SARs and Taiwan) . . . . . . . . . . . . . 81 6.3.3 India-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 6.3.4 Philippines-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 6.3.5 Vietnam-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 6.3.6 Italy-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 6.3.7 South Africa-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 6.3.8 Malaysia-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 6.3.9 Scotland-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 6.3.10 Sri Lanka-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 6.3.11 Germany-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 6.3.12 Greece-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 6.3.13 South Korea-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 6.3.14 USA-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 6.3.15 Hong Kong-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 6.3.16 Lebanon-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 6.3.17 Indonesia-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 6.3.18 Netherlands-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 6.3.19 Iraq-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 6.3.20 Fiji-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 6.3.21 Thailand-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 6.3.22 Pakistan-Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

Chapter 1

Introduction

Abstract International migration plays a major role in shaping Australia’s demography, economy and society, and is often the subject of public and political debate. Yet surprisingly few studies have considered how the migrant composition of the population could change in future decades. This chapter introduces our study, which looks at the possible future population of Australia’s population in terms of its birthplace composition, and some of the implications of those changes. Keywords Population projections · Country of birth · International migration · Demographic transition · Australia Australia’s contemporary demography, society and economy owes a great deal to international migration. In 2020, an estimated 7.65 million residents, representing 30% of the population, were born outside Australia (Australian Bureau of Statistics, 2021). Over the decade of the 2010s, about half a million largely young, well-educated and healthy immigrants arrived on average every year, while a little more than half that number emigrated annually. Following international convention, immigration in Australian official statistics is defined as the movement of people to Australia for a year or more, while emigration is the movement of people away from Australia for a year or more. Australia experiences substantial net international migration gains, which—until the recent pandemic-related drop in international migration—averaged 216,000 per year during the 2010s (Australian Bureau of Statistics, 2020). International migration is regularly the subject of public debate, media commentary, and political decisions in Australia. Migration and population growth are commonly amongst the top issues of concern in the community (Essential Research, 2020). Each year the Australian Government announces the number of places available in the following year’s Migration Program (skilled worker and family permanent migration) and Humanitarian Program (refugee permanent migration) (Commonwealth of Australia, 2019). The Federal Government also monitors and regulates temporary immigration, which includes international students, working holidaymakers, and temporary workers. The current federal government has a Minister for Immigration, Citizenship, Migrant Services and Multicultural Affairs. Newspapers and television shows are keen on hosting debates about population and immigration. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 T. Wilson et al., The Changing Migrant Composition of Australia’s Population, SpringerBriefs in Population Studies, https://doi.org/10.1007/978-3-030-88939-5_1

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Researchers in Australia investigate a wide range of topics associated with international migration, including demographic trends and patterns (Raymer et al., 2018), labour force integration (De Alwis et al., 2019; Parr & Guo, 2005; Rajendran et al., 2020), the nexus between education, employment, and migration as in the case of international students (Robertson, 2011), education and employment outcomes of migrants (De Alwis et al., 2019), English language abilities (McDonald et al., 2019), fertility (Abbasi-Shavazi & McDonald, 2000, 2002), health and welfare (Brijnath et al., 2019; Khlat et al., 1992), and housing experiences (Easthope et al., 2017; Ting et al., 2018). It is surprising then that more attention has not been paid to Australia’s future demographic diversity in the context of high international migration flows. The Australian Bureau of Statistics (ABS) periodically prepares projections of Australia’s population overall, and specific projections of the Aboriginal and Torres Strait Islander population. However, it does not publish projections by birthplace or ethnic group. Prior to our research project, the most recent study on the future of Australia’s population origins was published about 20 years ago. Gibson et al. (2001) presented projections of Australia’s older population from culturally and linguistically diverse (CALD) backgrounds from 1996 to 2026 under the assumption of no international migration. Earlier work includes that of Price (1996) who prepared projections of Australia’s population by birthplace and “ethnic strength” from 1991 to 2025. In some other countries, national statistical offices or academic researchers periodically prepare projections of the birthplace and/or ethnic composition of their populations, including Dion et al. (2015) for Canada, Edmonston et al. (2002) for the US, Hollmann and Kingkade (2005) for the US, Lanzieri (2011) for countries of the European Union, Rallu (2017) for France, Statistics Canada (Morency et al., 2017), Statistics New Zealand (2017), Statistics Norway (2018) and the US Census Bureau (2018). Although the UK Office for National Statistics does not prepare ethnic group projections, the Greater London Authority does so on a regular basis for London (Greater London Authority (GLA), 2020), and academic researchers have created ethnic group population projections covering the whole UK (Coleman, 2010; Lomax et al., 2020; Rees et al., 2016). This Springer Brief looks ahead to see how international migration might shape Australia’s population composition over the coming decades. It presents projections of Australia’s resident population by country (or global region) of birth from 2016 to 2066, updating and extending work presented earlier (Wilson et al., 2020, 2021a, 2021b). We focus on birthplace rather than ethnic group for three reasons. First, ethnicity is partially a social construct, and difficult to objectively operationalise. Its meaning changes in response to migration, kinship patterns, and other social and cultural trends. All humans have an ethnicity, although those who belong to a majority ethnic group may not see themselves as being ‘ethnic.’12 Consequently, ethnicity may be self-identified, identified by others, and linked to specific behaviours with a particular ethnic group. Second, Australia has good quality and a long time series of demographic statistics on the birthplace of individuals and their parents but limited data on ethnicity (except for the Aboriginal and Torres Strait Islander population, and a census question on ancestry that is not clearly defined). Third, for many aspects of service provision, policy, and planning, country of birth is a useful

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variable. It is closely associated with language and culture (Temple et al. 2021), which impacts on the provision of government and private sector services such as health care (Clarke & Isphording, 2017; Ji et al., 2019), health promotion (Kelaher et al., 1999; Taibi et al., 2019), aged care (Kendig & Russell, 1998; Radermacher et al., 2009; Warburton et al., 2009), family services (for example, family violence services, see Pruitt et al., 2017), and employment and settlement services (Colic-Peisker & Tilbury, 2006; Correa-Velez et al., 2015; Wulff & Dharmalingam, 2008). Projecting the birthplace composition of Australia’s population allows us to consider the long-run demographic development of the country. Over the last few decades Australia has exhibited many (but not all) features of the second demographic transition (Lesthaeghe, 2014), including below-replacement fertility, less marriage, more non-marital fertility, and net international migration gains, along with more individualism, greater gender equality, and a wider range of lifestyles. It has not, however, experienced natural decrease. Coleman (2006, p. 401) has argued that many western countries are experiencing a third demographic transition in which, “the ancestry of some national populations is being radically and permanently altered by high levels of immigration of persons from remote geographic origins or with distinctive ethnic and racial ancestry, in combination with persistent sub-replacement fertility and accelerated levels of emigration of the domestic population”. To a large degree a transition of this nature has been gradually occurring in Australia for many decades, but to a greater extent from the final years of the twentieth century. It has been facilitated by the removal of the racially-restrictive White Australia Policy in the 1970s (Jupp, 1995), a shift towards privileging skills in the selection of permanent migrants, and the introduction of temporary migration visas in the 1990s, which brought increasing numbers of temporary workers and a rapid rise in the number of international higher education students studying in Australia (Hugo, 2006), especially from China and India. These developments occurred in the context of broad-level global economic and political change. Czaika and de Haas (2014) conclude that global international migration patterns have become more geographically skewed in recent decades, with migrants from non-European countries moving to a smaller number of key immigration countries, including Australia. They suggest that migration trends and patterns have been affected by economic development (providing more people with the resources to emigrate), the lifting of emigration restrictions in the former communist bloc, the weakening of ties between former colonies and ruling countries, fewer racial restrictions on immigration, increasingly global labour markets, and improvements in technology. Historical migration developments are discussed further in the overview of Australia’s migration trends and population development in the following chapter. The data and assumptions used in our birthplace projections are then outlined in Chap. 3, while the results of the projection scenarios are presented in Chap. 4. The implications of the projections are discussed in Chap. 5, while Chap. 6 presents profiles of all 48 birthplace populations included in our modelling.

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References Abbasi-Shavazi, M. J., & McDonald, P. (2000). Fertility and multiculturalism: Immigrant fertility in Australia, 1977–1991. International Migration Review, 34(1), 215–242. https://doi.org/10.1177/ 019791830003400109 Abbasi-Shavazi, M. J., & McDonald, P. (2002). A comparison of fertility patterns of European immigrants in Australia with those in the countries of origin. Genus, 58(1), 53–76. Australian Bureau of Statistics. (2020). Australian demographic statistics, September 2019. Catalogue Number 3101.0. https://www.abs.gov.au/ausstats/[email protected]/mf/3101.0. Accessed on March 26, 2020. Australian Bureau of Statistics. (2021). Migration, Australia. https://www.abs.gov.au/statistics/peo ple/population/migration-australia/2019-20#data-download Brijnath, B., Antoniades, J., & Temple, J. (2019). Psychological distress among migrant groups in Australia: Results from the 2015 National Health Survey. Social Psychiatry and Psychiatric Epidemiology. https://doi.org/10.1007/s00127-019-01782-y Clarke, A., & Isphording, I. E. (2017). Language barriers and immigrant health. Health Economics, 26(6), 765–778. https://doi.org/10.1002/hec.3358 Coleman, D. (2006). Immigration and ethnic change in low-fertility countries: A third demographic transition. Population and Development Review, 32(3), 401–446. https://doi.org/10.1111/j.17284457.2006.00131.x Coleman, D. (2010). Projections of the ethnic minority populations of the United Kingdom 2006– 2056. Population and Development Review, 36(3), 441–486. https://doi.org/10.1111/j.1728-4457. 2010.00342.x Colic-Peisker, V., & Tilbury, F. (2006). Employment niches for recent refugees: segmented labour market in twenty-first century Australia. Journal of Refugee Studies, 19(2), 203–229.https://doi. org/10.1093/jrs/fej016 Commonwealth of Australia. (2019). Budget strategy and outlook budget paper No. 1 2019-20. https://budget.gov.au/2019-20/content/bp1/download/bp1.pdf Correa-Velez, I., Barnett, A. G., & Gifford, S. (2015). Working for a better life: Longitudinal evidence on the predictors of employment among recently arrived refugee migrant men living in Australia. International Migration, 53(2), 321–337. https://doi.org/10.1111/imig.12099 Czaika, M., & de Haas, H. (2014). The globalization of migration: Has the world become more migratory? International Migration Review, 48(2), 283–323. https://doi.org/10.1111/imre.12095 De Alwis, S., Parr, N., & Guo, F. (2019). The education-occupation (Mis)match of Asia-born immigrants in Australia. Population Research and Policy Review, 39(3), 519–548. https://doi. org/10.1007/s11113-019-09548-9 Dion, P., Caron-Malenfant, É., Grondin, C., & Grenier, D. (2015). Long-term contribution of immigration to population renewal in Canada: A Simulation. Population and Development Review, 41(1), 109–126. https://doi.org/10.1111/j.1728-4457.2015.00028.x Easthope, H., Stone, W., & Cheshire, L. (2017). The decline of ‘advantageous disadvantage’ in gateway suburbs in Australia: The challenge of private housing market settlement for newly arrived migrants. Urban Studies, 55(9), 1904–1923. https://doi.org/10.1177/0042098017700791 Edmonston, B., Lee, S. M., & Passel, J. S. (2002). Recent trends in intermarriage and immigration and their effects on the future racial composition of the US population. In J. Perlmann & M. C. Waters (Eds.), The new race question: How the census counts multiracial individuals (pp. 227– 255). Russell Sage. Essential Research (2020). Essential report: Most important issues. https://essentialvision.com.au/ most-important-issues-4 Gibson, D., Braun, P., Benham, C., & Mason, F. (2001). Projections of older immigrants. People from culturally and linguistically diverse backgrounds, 1996–2026, Australia. Australian Institute of Health and Welfare. https://www.ecald.com/assets/Resources/Projections-of-Older-Immigrants. pdf

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Greater London Authority (GLA). (2020). Ethnic group population projections. https://data.london. gov.uk/dataset/ethnic-group-population-projections. Hollmann, F. W., & Kingcade, W. (2005). Impact of racial and ethnic exogamy and international migration on forecast population distributions for the United States in 2030. Results of a macro-simulation. In 25th International Population Conference of the International Union for the Scientific Study of Population, Tours, 2005. Hugo, G. (2006). Globalization and changes in Australian international migration. Journal of Population Research, 23(2), 107–134. https://doi.org/10.1007/BF03031812 Ji, M., Taibi, M., & Crezee, I. H. (2019). Multicultural health translation, interpreting and communication. Routledge. Jupp, J. (1995). From ‘white Australia’ to ‘part of Asia’: Recent shifts in Australian immigration policy towards the region. International Migration Review, 29(1), 207–228. https://doi.org/10. 1177/019791839502900109 Kelaher, M., Williams, G., & Manderson, L. (1999). Towards evidence-based health promotion and service provision for new migrants to Australia. Ethnicity & Health, 4(4), 305–313. https://doi. org/10.1080/13557859998074 Kendig, H., & Russell, H. (1998). Aging, ethnicity and health policy in Australia. Health systems & aging in selected pacific rim countries: cultural diversity & change (pp. 19–420. Khlat, M., Vail, A., Parkin, M., & Green, A. (1992). Mortality from melanoma in migrants to Australia: Variation by age at arrival and duration of stay. American Journal of Epidemiology, 135(10), 1103–1113. https://doi.org/10.1093/oxfordjournals.aje.a116210 Lanzieri, G. (2011). Fewer, older and multicultural?: Projections of the EU populations by foreign/national background: Publications Office of the European Union Luxembourg. Lesthaeghe, R. (2014). The second demographic transition: A concise overview of its development. Proceedings of the National Academy of Sciences, 111(51), 18112–18115. https://doi.org/10. 1073/pnas.1420441111 Lomax, N., Wohland, P., Rees, P., & Norman, P. (2020). The impacts of international migration on the UK’s ethnic populations. Journal of Ethnic and Migration Studies, 46(1), 177–199. https:// doi.org/10.1080/1369183X.2019.1577726 McDonald, P., Moyle, H., & Temple, J. (2019). English proficiency in Australia, 1981 to 2016. Australian Journal of Social Issues, 54(2), 112–134. https://doi.org/10.1002/ajs4.67 Morency, J.-D., Malenfant, É. C., & MacIsaac, S. (2017). Immigration and diversity: Population projections for Canada and its regions, 2011 to 2036. Catalogue No. 91–551-X: Statistics Canada. https://www150.statcan.gc.ca/n1/pub/91-551-x/91-551-x2017001-eng.htm Parr, N., & Guo, F. (2005). Occupational concentration and mobility of Asian immigrants in Australia. Asian and Pacific Migration Journal, 14(3), 351–380. https://doi.org/10.1177/011719 680501400305 Price, C. (1996). Immigration and ethnicity. Commonwealth Department of Immigration and Multicultural Affairs. Pruitt, L., Hamilton, G., Heydon, G., & Spark, C. (2017). Abbott’s ‘budget crisis’, CALD women’s loss? Service providers explore the impact of funding cuts. Australian Journal of Political Science, 52(3), 335–350. https://doi.org/10.1080/10361146.2017.1332157 Radermacher, H., Feldman, S., & Browning, C. (2009). Mainstream versus ethno-specific community aged care services: It’s not an ‘either or.’ Australasian Journal on Ageing, 28(2), 58–63. https://doi.org/10.1111/j.1741-6612.2008.00342.x Rajendran, D., Ng, E. S., Sears, G., & Ayub, N. (2020). Determinants of migrant career success: A study of recent skilled migrants in Australia. International Migration, 58(2), 30–51. https://doi. org/10.1111/imig.12586 Rallu, J.-L. (2017). Projections of older immigrants in France, 2008–2028. Population, Space and Place, 23(5), e2012. https://doi.org/10.1002/psp.2012 Raymer, J., Shi, Y., Guan, Q., Baffour, B., & Wilson, T. (2018). The sources and diversity of immigrant population change in Australia, 1981–2011. Demography, 55(5), 1777–1802. https:// doi.org/10.1007/s13524-018-0704-5

6

1 Introduction

Rees, P., Wohland, P., & Norman, P. (2016). The United Kingdom’s multi-ethnic future: How fast is it arriving? In J. Lombard, E. Stern, & G. Clarke (Ed.), Applied spatial modelling and planning. Routledge. Robertson, S. (2011). Cash cows, backdoor migrants, or activist citizens? International students, citizenship, and rights in Australia. Ethnic and Racial Studies, 34(12), 2192–2211. https://doi. org/10.1080/01419870.2011.558590 Stastistics Norway. (2018). Norway’s 2018 population projections. Reports 2018/22. https://www. ssb.no/en/befolkning/artikler-og-publikasjoner/norways-2018-population-projections Statistics New Zealand. (2017). National ethnic population projections: 2013(base)– 2038 (update). https://www.stats.govt.nz/information-releases/national-ethnic-population-projec tions-2013base2038-update Taibi, M., Liamputtong, P., & Polonsky, M. (2019). Impact of translated health information on CALD older people’s health literacy. In M. Ji, M. Taibi, & I. H. M. Crezee (Eds.), Multicultural health translation, interpreting and communication. Routledge. Temple, J., Wilson, T., Brijnath, B., Utomo, A., & McDonald, P. (2021). English language proficiency among older migrants in Australia, 2016–2046. Journal of International Migration and Integration. https://doi.org/10.1007/s12134-021-00836-y Ting, C. Y. P., Newton, P. W., & Stone, W. (2018). Chinese migration, consumption, and housing in twenty-first century Australia. Geographical Research, 56(4), 421–433. https://doi.org/10.1111/ 1745-5871.12316 United States Census Bureau. (2018). 2017 national population projections tables: Main series. 2017 National population projections tables. Projections for the United States: 2017–2060. https:// www.census.gov/data/tables/2017/demo/popproj/2017-summary-tables.html Warburton, J., Bartlett, H., & Rao, V. (2009). Ageing and cultural diversity: Policy and practice issues. Australian Social Work, 62(2), 168–185. https://doi.org/10.1080/03124070902748886 Wilson, T., McDonald, P., Temple, J., Brijnath, B., & Utomo, A. (2020). Past and projected growth of Australia’s older migrant populations. Genus, 76(20). https://doi.org/10.1186/s41118-020-000 91-6 Wilson, T., Temple, J., Brijnath, B., McDonald, P., & Utomo, A. (2021a). Projections of older European migrant populations in Australia, 2016–56. Journal of Population Ageing. https://doi. org/10.1007/s12062-020-09319-x Wilson, T., Temple, J., Brijnath, B., Utomo, A., & McDonald, P. (2021b). The ageing of Asian migrant populations in Australia: projections and implications for aged care services. Asian Population Studies. https://doi.org/10.1080/17441730.2021.1953689. Wulff, M., & Dharmalingam, A. (2008). Retaining skilled migrants in regional Australia: The role of social connectedness. Journal of International Migration and Integration/revue De L’integration Et De La Migration Internationale, 9(2), 147–160. https://doi.org/10.1007/s12134-008-0049-9

Chapter 2

International Migration and Australia’s Population

Abstract This chapter presents a brief overview of past international migration trends and policies, and their effect on the growth and diversity of Australia’s population. It covers the post-World War Two migration schemes, the dismantling of the White Australia Policy, and the increasing diversity of migrant origins. Keywords International migration · Australia · Historical demography Prior to the arrival of the British settlers, Australia and its surrounding islands were inhabited by numerous Aboriginal and Torres Strait Islander peoples—the Indigenous owners and first sovereign nations of the continent (see Taylor et al., 2021; The Uluru Statement, 2017). At Federation in 1901, the six British colonies—New South Wales, Victoria, Queensland, Tasmania, South Australia, and Western Australia— united to form and collectively govern the Commonwealth of Australia. At this time, less than five per cent of the Australian population had its origins outside of Australia and the British Isles. Such patterns in the origins of settlers continued for decades after Federation; only two per cent of the population had origins outside of Australia, New Zealand and the British Isles by 1947 (Price, 1987). This level of Britishness was the result of deliberate policy to maintain close ties to the colonial home country. The Second World War became a turning point in Australia’s contemporary population history. Post-war population projections indicated that Australia’s population would rise from 7.7 million in 1950 to 8.0 million by the year 2000 (McDonald & Kippen, 2000). Such a scenario was considered unacceptable by the post-war reconstructionists. As a group, they wielded considerable policy power at the time, and they equated the prospect of a small population to a small economy. With the potential of ending up as a small economy, Australia would be in a vulnerable position in the increasingly precarious political and economic constellations of the world. In August 1945, Arthur Calwell, the first Minister for Immigration in the Australian Parliament, prepared a policy paper on immigration. This became the foundation of what was deemed as Australia’s successful post-war migration scheme (Markus et al., 2009). It became apparent immediately that immigration from the British Isles alone could not provide the required volume of immigration. In the early years of the post-war period, the refugee camps in Europe became a key source of immigrants to Australia. Making the most of this ready source, the volume of © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 T. Wilson et al., The Changing Migrant Composition of Australia’s Population, SpringerBriefs in Population Studies, https://doi.org/10.1007/978-3-030-88939-5_2

7

8 Table 2.1 Persons born in regions of Europe, 1947, 1961 and 1971, Australia

2 International Migration and Australia’s Population Region of Europe

1947

1961

1971

British Isles

543,000

758,000

1,089,000

Northern Europe

32,000

259,000

272,000

Eastern Europe

24,000

228,000

309,000

Southern Europe

53,000

361,000

541,000

Source Price (1987: 8–9)

immigration from Eastern and Western Europe to Australia reached new records. Subsequently, large numbers of migrants from Southern Europe began to arrive to meet the rising demands for work in manufacturing and construction during 1950s and 1960s. By 1971, the composition of the population in Australia had become more diverse (Table 2.1). In the 1949–1971 period, the flows of migrants coming in from the British Isles continued to be significant. But, at the same time, there was a rise in the numbers of arrivals of migrants from various European origins. Italy, Yugoslavia, Greece, Germany and the Netherlands were ranked as major source countries in this cohort of arrivals. The arrivals of one million people from these parts of Europe irrevocably altered the fabric of society in Australia. The White Australia Policy remained in effect during this period. Arguably, the greater diversity brought by these European migrants had altered the character of Australia in a gradual manner that could have been perceived as less threatening to earlier cohorts of British settlers. Concurrently, compared to what had been the case during pre-World War II period, official attention in Australia had now shifted towards focusing more on the politics of Asia. There were several factors behind this shift. The first was Australia’s World War II involvement and experience in the Asia-Pacific region. The second—and the more important reason—was the birth of post-colonial states in this region. It soon became apparent that the White Australia Policy was an embarrassment. This was particularly the case as Australia attempted to build diplomatic and economic relations with its neighbouring Asian countries, who were highly cognisant of Australia’s restrictive migration policy. In 1972, the Whitlam Labour Government fully abolished the White Australia Policy (McDonald, 2019). In the 1970s and 1980s, large numbers of refuges from Vietnam and Lebanon arrived in Australia. Their arrivals served to test the country’s fresh commitment to a non-white Australia. By 1996, the one million people born in an Asian country represented 5.5% of the Australian population (McDonald, 2019). This percentage has been growing ever since; for example, in 2016, the proportion of the Australian population born in Asia had risen to 13.4%. In effect, by 2016, Asian-born populations had now made up almost half of the overseas-born population in Australia. There had also been a relatively large flow of refugees from East Africa and migrants from Southern Africa (Table 2.2). Thus, over the past 100 years, migration to Australia has been characterised by waves of arrivals from different countries of the world, in different periods of time, and under varying socio-economic conditions both within

2 International Migration and Australia’s Population Table 2.2 Persons born in regions of the world, 1971 and 2016, Australia

9

Region

1971

2016

British Isles

1,089,000

1,284,000

Other Europea

1,122,000

1,157,000

West and Central Asia

46,000

297,000

South Asia

45,000

796,000

East Asia

30,000

853,000

Southeast Asia

33,000

973,000

Africa

62,000

435,000

USA and Canada

43,000

156,000

Latin America and Caribbean

13,000

149,000

Pacific

16,000

166,000

New Zealand

80,000

607,000

Total overseas

2,579,000

6,873,000

Australia

10,177,000

17,254,000

a Includes

Turkey (40,000 in 2016) Source Price (1987) (1971); ABS 2017 (2016)

Australia and in the countries of origin. The 2016 age distributions by countries of birth reflect these past waves.

References Markus, A. B., Jupp, J., & McDonald, P. (2009). Australia’s immigration revolution. Allen & Unwin. McDonald, P. (2019). Migration to Australia: From Asian exclusion to Asian predominance. Revue Européenne Des Migrations Internationales, 35(1), 87–105. McDonald, P., & Kippen, R. (2000). Australia’s population in 2000: The way we are and the ways we might have been. People and Place, 8(3), 10–17. Price, C. (1987). Immigration and ethnic origin. In W. Vamplew (Ed.), Australians: Historical statistics (pp. 2–22). Sydney: Fairfax, Smye and Weldon. https://socialsciences.org.au/library/ historical-statistics-chapter-1/ Taylor, A., Wilson, T., Temple, J., Kelaher, M., & Eades, S. (2021). The future growth and spatial shift of Australia’s Aboriginal and Torres Strait Islander population, 2016–2051. Population, Space and Place, 27(4), e2401. https://doi.org/10.1002/psp.2401 The Uluru Statement. (2017). Uluru statement from the heart. https://ulurustatement.org/

Chapter 3

Projection Methods, Data and Assumptions

Abstract This chapter describes the population projection modelling, including details of the birthplace-specific cohort-component model, the birthplace categories chosen, input data estimation, adjustment and smoothing, and projection assumptions. It summarises the main features of the four main projection scenarios, which are Pre-COVID Trends (assuming a return to the migration trends just prior to the pandemic), Global Talent (assuming immigration is more influenced by the global geography well-educated younger adults), as well as Lower Immigration and Higher Immigration policy scenarios. Keywords Cohort-component model · Population projections · Australia · Projection scenarios

3.1 The Projection Model Projections of Australia’s resident population by birthplace, sex and single years of age from 2016 to 2066 were prepared using a purpose-built cohort-component model incorporating multiple birthplace groups. The main difference with a standard cohort-component model (Wilson & Rees, 2021) is that all babies born in Australia to overseas-born mothers, by definition, form part of the Australia-born population. The model was designed using a movement accounts population accounting framework (Rees, 1984) and consists of just one scale of projections comprising the individual birthplace groups (i.e., there is no separate national scale projection to which the birthplace projections are constrained). The model was operationalised in an Excel/VBA program which can handle between 2 and 50 birthplace populations and projections for up to 50 years ahead. The model projects the population forward one year at a time. There are three main steps. First, the population of all cohorts in the population at the start of each projection interval are projected using a cohort population accounting equation. The population of a cohort at time t + 1 is the population of that cohort at time t minus deaths occurring to that cohort over the year plus immigration and minus emigration during the year, i.e.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 T. Wilson et al., The Changing Migrant Composition of Australia’s Population, SpringerBriefs in Population Studies, https://doi.org/10.1007/978-3-030-88939-5_3

11

12

3 Projection Methods, Data and Assumptions i i i i i Ps,a+1 + Is,a→a+1 − E s,a→a+1 (t + 1) = Ps,a (t) − Ds,a→a+1

(3.1)

in which: P i s t t +1 a a →a+1 D I E

population birthplace sex a point in time one year beyond time t age group the period-cohort aged a at time t and aged a + 1 at time t + 1 deaths immigration emigration.

Time labels have been omitted from deaths, immigration and emigration in the equation above to reduce clutter; the reference period for all these flows is the one year interval from t to t + 1. The projected number of deaths and emigrations are calculated by multiplying death and emigration rates, respectively, by the population-at-risk of death and emigration. The population at risk is approximated by the mean of the start- and end-of-interval populations. For example, the number of deaths is projected as i i = ds,a→a+1 Ds,a→a+1

 1 i i P (t) + Ps,a+1 (t + 1) 2 s,a

(3.2)

in which d = the death rate. Including the end-of-interval populations on the right-hand side of this equation is not problematic because an iterative calculation scheme is employed which updates the end-of-interval populations in successive iterations until convergence is achieved (Rees, 1984). This approach was chosen over the classic (non-iterative) matrix algebra approach (Keyfitz & Caswell, 2005) because it produces the projected demographic components of change directly, offers flexibility in setting projection assumptions, and is simple to program. Preliminary emigration projections were produced by multiplying emigration rates by the population at risk: i i = es,a→a+1 E s,a→a+1

 1 i i Ps,a (t) + Ps,a+1 (t + 1) 2

(3.3)

in which e = the emigration rate. Preliminary immigration projections consist of immigration numbers by sex and period-cohort specified as projection assumptions. Immigration numbers, rather than rates, are used because immigration is more influenced by policy in Australia than the population at risk in the rest of the world. Adjustments are then made to produce final

3.1 The Projection Model

13

immigration and emigration projections which differ according to which projection scenario is being produced. The adjustment methods are described in the next section on projection scenarios. In the second step, the number of babies born during the projection interval is projected. The number of births by age group of women is projected by multiplying national age-specific fertility rates by national female age-specific populations at risk. This step of the projection calculations is not birthplace-specific because all birthplace populations who give birth in Australia have Australia-born babies: B

Aus

  1   ba P f,a (t) + P f,a (t + 1) = 2 a

(3.4)

in which: B Aus b f

births Australia-born age-specific fertility rate female.

The advantage of this approach of using national-scale fertility is that data requirements are kept modest; the disadvantage is that changes in the birthplace composition of the population cannot influence overall national fertility. Births are split into males and females using an assumed sex ratio at birth, which is defined as the number of male babies born per 100 female babies. The number of female babies is calculated as: B Aus = B Aus f

100 (S R B + 100)

(3.5)

in which S R B = sex ratio at birth. The number of male babies is found as: BmAus = B Aus

SRB (S R B + 100)

(3.6)

in which m = males. In the third step, babies born during the projection interval are projected to become the population aged 0 at the end of the interval. The equation differs between the Australia-born and overseas-born populations. For the Australia-born, the population aged 0 at time t + 1 is the number of births born during the projection interval minus deaths, plus immigration and minus emigration: Aus Aus Aus Aus + Is,b→0 − E s,b→0 Ps,0 (t + 1) = BsAus − Ds,b→0

(3.7)

14

3 Projection Methods, Data and Assumptions

in which b → 0 = the cohort born during the projection interval and aged 0 at time t + 1. For overseas-born populations there cannot be, by definition, any Australia-born births to overseas-born populations. The projected population aged 0 is therefore immigration minus deaths minus emigration: i i i i − Ds,b→0 − E s,b→0 Ps,0 (t + 1) = Is,b→0

(3.8)

Finally, the end-of-interval populations become the start-of-interval populations for the next projection interval. The highest open-ended age group population is the sum of the two oldest projected cohort populations: i i i Ps,105+ (t + 1) = Ps,105 (t + 1) + Ps,106+ (t + 1)

(3.9)

We produced projections for a total of 48 individual countries and global regions of birth but to keep the analysis manageable we mostly focus on the 26 countries and global regions in the ABS classification of birthplaces (Australian Bureau of Statistics, 2016). These consist of Australia, individual countries with large and long-standing immigration flows to Australia (such as New Zealand, the UK, and Ireland) along with regional groupings of countries (such as Polynesia, Northern Europe, and the Middle East). The full list, and the constituent countries in each grouping, is shown in Table 3.1.

3.2 Projection Scenarios Migration is the most volatile and difficult-to-forecast variable of the three demographic processes of fertility, mortality and migration, and it is the most important demographic variable in projections of birthplace-specific populations. Alternative projections were created in which only the immigration assumptions were varied. Four scenarios containing alternative futures for immigration were formulated, and they are: (i)

(ii) (iii) (iv)

a Pre-COVID Trends scenario in which the migration trends and patterns of the 2011–16 base period return after several years of disruption from COVID19, a Global Talent scenario which sees the origins of migrants increasingly drawn from the growing well-educated populations in emerging economies, a Higher Immigration scenario in which the Australian Government promotes a high population growth policy, and a Lower Immigration scenario in which the Government tightens immigration controls and reduces the number of available visas.

Table 3.2 defines the migration assumptions in the scenarios. In all four scenarios actual international migration estimates for the period 2016–17 to 2019–20 are used,

3.2 Projection Scenarios

15

Table 3.1 The ABS 2-digit birthplace classification ABS code Country/region of birth

Constituent countries/territories

11

Australia

Australia

12

New Zealand

New Zealand

13

Melanesia

New Caledonia, Papua New Guinea, Solomon Islands, Vanuatu

14

Micronesia

Guam, Kiribati, Marshall Islands, Federated States of Micronesia, Nauru, Northern Mariana Islands, Palau

15

Polynesia

Cook Islands, Fiji, French Polynesia, Niue, Samoa, American Samoa, Tokelau, Tonga, Tuvalu, Wallis and Futuna, Pitcairn Islands

21

UK

UK, Channel Islands, Isle of Man

22

Ireland

Ireland

23

Western Europe

Austria, Belgium, France, Germany, Liechtenstein, Luxembourg, Monaco, Netherlands, Switzerland

24

Northern Europe

Denmark, Faroe Islands, Finland, Greenland, Iceland, Norway, Sweden, Aland Islands

31

Southern Europe

Andorra, Gibraltar, Holy See, Italy, Malta, Portugal, San Marino, Spain

32

South Eastern Europe

Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, North Macedonia, Greece, Moldova, Romania, Slovenia, Montenegro, Serbia, Kosovo

33

Eastern Europe

Belarus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Russian Federation, Slovakia, Ukraine

41

North Africa

Algeria, Egypt, Libya, Morocco, Sudan, Tunisia, Western Sahara, Spanish North Africa, South Sudan

42

Middle East

Bahrain, Gaza Strip and West Bank, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, Turkey, United Arab Emirates, Yemen

51

Mainland South East Asia Myanmar, Cambodia, Laos, Thailand, Vietnam

52

Maritime South East Asia Brunei Darussalam, Indonesia, Malaysia, Philippines, Singapore, Timor-Leste

61

Chinese Asia

China (excludes SARs and Taiwan), Hong Kong (SAR of China), Macau (SAR of China), Mongolia, Taiwan

62

Japan and the Koreas

Japan, Democratic People’s Republic of Korea (North), Republic of Korea (South)

71

Southern Asia

Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, Sri Lanka

72

Central Asia

Afghanistan, Armenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, Uzbekistan

81

North America

Bermuda, Canada, St Pierre and Miquelon, United States of America (continued)

16

3 Projection Methods, Data and Assumptions

Table 3.1 (continued) ABS code Country/region of birth

Constituent countries/territories

82

South America

Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Falkland Islands, French Guiana, Guyana, Paraguay, Peru, Suriname, Uruguay, Venezuela

83

Central America

Belize, Costa Rica, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama

84

Caribbean

Anguilla, Antigua and Barbuda, Aruba, Bahamas, Barbados, Cayman Islands, Cuba, Dominica, Dominican Republic, Grenada, Guadeloupe, Haiti, Jamaica, Martinique, Montserrat, Puerto Rico, St Kitts and Nevis, St Lucia, St Vincent and the Grenadines, Trinidad and Tobago, Turks and Caicos Islands, British Virgin Islands, United States Virgin Islands, St Barthelemy, St Martin (French part), Bonaire, Sint Eustatius and Saba, Curacao, Sint Maarten (Dutch part)

91

Central & West Africa

Benin, Burkina Faso, Cameroon, Cabo Verde, Central African Republic, Chad, Republic of Congo, Democratic Republic of Congo, Cote d’Ivoire, Equatorial Guinea, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, Sao Tome and Principe, Senegal, Sierra Leone, Togo

92

Southern & East Africa

Angola, Botswana, Burundi, Comoros, Djibouti, Eritrea, Ethiopia, Kenya, Lesotho, Madagascar, Malawi, Mauritius, Mayotte, Mozambique, Namibia, Reunion, Rwanda, St Helena, Seychelles, Somalia, South Africa, Swaziland, Tanzania, Uganda, Zambia, Zimbabwe

Source https://www.abs.gov.au/ausstats/[email protected]/Lookup/2901.0Chapter1102016

along with observed Total Fertility Rates and life expectancies at birth. The ‘projections’ from 2016 to 2020 can be considered hybrid estimates/projections. The projections proper start from 2020. Lower international migration is assumed between 2020–21 and 2025–26 due to the COVID-related closure of the Australian border in 2020 and the assumed gradual easing of immigration restrictions from 2022. Immigration assumptions for the Australian population as a whole, shown in Fig. 3.1, were prepared to act as constraints for the birthplace-specific immigration assumptions. However, separate Australia-wide projections are not calculated by the projection program. The migration assumptions in the Pre-COVID Trends scenario include immigration totals gradually increasing from 2025 to 26, continuing the trend of the 2011–19 period, while emigration rates remain close to their 2011–16 base period values. Recent policy settings in permanent and temporary immigration are assumed to return following the COVID-related border closure and low migration flows. Migration policy is notoriously hard to predict, but in the last 20 years both major political parties in Australia have been largely supportive of a high immigration policy (Betts &

3.2 Projection Scenarios

17

Table 3.2 Summary of migration assumptions in projection scenarios Scenario

Key features

Pre-COVID trends

National assumption: Actual immigration and emigration flows for 2016–17 to 2019–20 are used. Immigration then drops to 108,000 in 2020–21 before recovering to 560,000 by 2025–26 and then increasing by 5000 each subsequent year, in line with the recent pre-COVID trend Birthplace-specific populations: Immigration totals are based on annual average 2011–16 values adjusted to projected national immigration totals. Emigration rates drop in 2020–21 and 2021–22, but are then set marginally higher than those estimated for the 2011–16 base period from 2022 to 23 onwards to obtain national projected emigration totals in line with the pre-COVID trend

Global talent

National assumption: Actual immigration and emigration flows for 2016–17 to 2019–20 are used. National immigration totals are the same as in the Pre-COVID Trends scenario Birthplace-specific populations: Immigration flows by birthplace group change according to the Wittgenstein Centre’s projections of individual country populations aged 20–39 who have completed post-secondary education; these immigration flows are constrained to sum to national immigration totals. The same emigration rates as in the Pre-COVID Trends scenario are used

Higher immigration National population: Actual immigration and emigration flows for 2016–17 to 2019–20 are used. Immigration then drops to 108,000 in 2020–21 before increasing rapidly to 125% of the Pre-COVID Trends scenario from 2021 to 22 onwards Birthplace-specific populations: Immigration totals are based on annual average 2011–16 values adjusted to projected national immigration totals. Emigration rates are the same as in the Pre-COVID Trends scenario Lower immigration National population: Actual immigration and emigration flows for 2016–17 to 2019–20 are used. Immigration then drops to 108,000 in 2020–21 before increasing to 75% of the Pre-COVID Trends scenario from 2021 to 22 onwards Birthplace-specific populations: Immigration totals are based on annual average 2011–16 values adjusted to projected national immigration totals. Emigration rates are the same as in the Pre-COVID Trends scenario

Birrell, 2019) which privileges temporary migrants and skilled permanent migrants. This scenario therefore involves migration policy and the wider social and economic environment returning to the pre-COVID ‘normal’. The Global Talent scenario embodies an open and welcoming Australia seeking to benefit from the skills and expertise of the best and brightest around the world. Under this scenario, total immigration is assumed to be the same as that for the PreCOVID Trends scenario, but birthplace-specific immigration flows are based on the size of the young post-secondary educated population in origin countries projected by the Wittgenstein Centre (Lutz et al., 2018; http://dataexplorer.wittgensteincentre.org/ wcde-v2/). There were two steps to the calculations. First, a preliminary projection of immigration I from origin country/region i was calculated as the projected size of the tertiary-educated population of that country/region aged 20–39 multiplied by

18

3 Projection Methods, Data and Assumptions

Fig. 3.1 National immigration assumptions. Source ABS.Stat, https://stat.data.abs.gov.au/ (recorded data); authors’ projections

a base period immigration ratio: i I i [1] = P20−39

I i (base) i P20−39 (base)

in which: base = the 2011–16 base period [1] = preliminary. Immigration from each origin was then adjusted so that the sum of immigration flows from all origins equalled the total projected immigration flow for Australia as a whole: I Aus I i [2] = I i [1] i i I [1] Emigration rates are the same as those in the Pre-COVID Trends scenario. The Higher Immigration scenario assumes a policy of high immigration intakes to accelerate demographic and economic growth, and thereby strengthen Australia’s economic and political influence in the world. The scenario involves immigration totals increasing to 125% of the Pre-COVID Trends scenario values from 2021 to 22 onwards, while emigration rates are the same as those in the Pre-COVID Trends scenario. The Lower Immigration scenario assumes more restrictive immigration policies and sees Australia return to the volumes of international migration experienced in the first few years of the twenty-first century. A lower immigration intake and slower population growth is supported by a sizeable proportion of voters (Biddle, 2019;

3.2 Projection Scenarios

19

Essential Research, 2020) and environmental organisations. This scenario was implemented by assuming immigration totals for all birthplace groups would be 75% of the Pre-COVID Trends scenario values from 2021–22 onwards. Emigration rates from the Pre-COVID Trends scenario are used. In all scenarios, the same fertility and mortality assumptions applied. For fertility, a short-term COVID-related fall in fertility rates was assumed given that the literature generally finds economic recession is associated with a drop in fertility (e.g. Matysiak et al., 2021; Sobotka et al., 2011). We assumed a fall in the national Total Fertility Rate (TFR) to 1.55 in 2020–21 and 2021–22 before recovery over the next few years to the long-run TFR of 1.65. This long-run assumption was primarily informed by a detailed analysis of future Australian fertility undertaken by McDonald (2020). Mortality assumptions were prepared in terms of life expectancy at birth, with projection assumptions for the national Australian population prepared first. Although national-scale projections are not calculated by the projection model, birthplace-specific life expectancy assumptions are prepared relative to nationallevel assumptions because of the lengthy time series of national-level mortality data. Life expectancy in Australia was assumed to gradually increase to 91.0 years for females by 2065–66 and to 88.6 years for males. A simplified version of Ediev’s (2008) extrapolative mortality projection model was used to prepare the nationallevel projections. Birthplace-specific life expectancy assumptions were linked to the national projection by maintaining the base period differentials with national life expectancy into the future. For some countries and regions of birth with relatively small populations in Australia deaths data were not available; in these cases, life expectancy differentials for the total overseas-born population were used.

3.3 Input Data Preparation The reason for using 2016 as the ‘jump-off’ point of the projections is that, at the time of writing, this was the year of the most recent census data available. Census data on populations by country of birth by single years of age were required to disaggregate the ABS Estimated Resident Populations by country of birth from the published five-year age groups to single years of age. The 2016 jump-off year populations by sex and single years of age were estimated in two stages. First, the five-year age group ERPs were broken down to single years of age. Second, iterative proportional fitting was applied to ensure that single year of age population estimates (i) summed over all birthplace groups to the published ERP for Australia by single years of age, and (ii) summed over single year ages to the five-year age group birthplace-specific ERPs. Age-specific fertility rates were required for the national Australian population only, not birthplace-specific populations. The parametric model of Peristera and Kostaki (2007) was fitted to the age pattern of fertility rates for Australia from 1981 to 2019, and projected age patterns of fertility were calculated by extrapolating the model parameters out to 2066. The model projects a gradually ageing age profile of

20

3 Projection Methods, Data and Assumptions

fertility into the future. The TFR assumptions were prepared separately. Projected age-specific fertility rates were finalised by scaling the projected fertility age profiles to obtain consistency with the assumed TFRs. Life expectancies at birth for populations by birthplace and sex were calculated for the 2011–16 base period. Abridged life tables for selected countries and regions of birth were calculated using deaths and ERPs by country of birth obtained from the ABS (Australian Bureau of Statistics, 2012). Birthplace-specific life expectancy differences with national life expectancy were calculated, with national life expectancy at birth also derived from an abridged life table for consistency. Unfortunately, deaths by country of birth were available only for some of the countries in our selection of 25 individual countries of birth (Australia, Fiji, New Zealand, Germany, Ireland, Netherlands, UK, Greece, Italy, Lebanon, Indonesia, Malaysia, Philippines, Vietnam, China, India, Sri Lanka, USA, South Africa). Other birthplace populations were assumed to experience the mortality conditions of the overseas-born as a whole. Data on immigration and emigration flows by country of birth, sex and single years of age over the period 2011–16 were purchased from the ABS. Adjustments to the migration data were made to achieve consistent population accounts over the 2011– 16 period. This involved taking mid-2011 population estimates by sex and single years of age and ensuring that the application of cohort population accounting equations (subtracting or adding deaths, immigration, and emigration) over the 2011–16 interval resulted in mid-2016 populations by cohort that matched mid-2016 population estimates. Immigration and emigration were adjusted proportionally by the same amount using age-specific adjustment factors defined as the ratio of adjusted to original migration flows. These adjustment factors were then smoothed over age using linear splines (de Beer, 2011) to maintain plausible age profiles of immigration and emigration. For most birthplace groups the required adjustments were minor. Once adjusted migration flows had been finalised, model migration schedules were fitted to immigration flows and emigration rates to obtain smooth age patterns of migration (Wilson, 2020). It is generally sensible to smooth demographic rates over age to prevent noise being projected over many decades. As examples, Fig. 3.2 shows the age profile of immigration to Australia of the female Lebanon-born population smoothed using a model migration schedule, and Fig. 3.3 shows the emigration rate age profile of the India-born male population. Published net international migration totals by birthplace for 2016–17 to 2019–20 were used in preparing migration assumptions for the first four years of the projection horizon (Australian Bureau of Statistics, 2021b). The base period immigration and emigration totals by birthplace population were proportionally adjusted to achieve consistency with the net international migration totals.

3.3 Input Data Preparation

21

Fig. 3.2 The age pattern of immigration of Lebanon-born females smoothed using a model migration schedule

Fig. 3.3 The age pattern of emigration of Indian-born males smoothed using a model migration schedule

22

3 Projection Methods, Data and Assumptions

References Australian Bureau of Statistics. (2012, 2013, 2014, 2015, 2016, 2017). Deaths, Australia (years 2011 to 2016). https://www.abs.gov.au/AUSSTATS/[email protected]/DetailsPage/3302.02011?OpenDo cument Australian Bureau of Statistics. (2016). Census of population and housing: Census dictionary. https:// www.abs.gov.au/ausstats/[email protected]/Lookup/2901.0Chapter1102016. Accessed on September 28, 2019. Australian Bureau of Statistics. (2021a). ABS.Stat ERPs by birthplace. http://stat.data.abs.gov.au/ Australian Bureau of Statistics. (2021b). Migration, Australia. https://www.abs.gov.au/statistics/ people/population/migration-australia/2019-20#data-download Betts, K., & Birrell, B. (2019). Immigration, population growth and voters: who cares, and why? The October/November 2018 TAPRI survey. The Australian Population Research Institute. Melbourne. https://apo.org.au/sites/default/files/resource-files/2019-04/apo-nid230416.pdf Biddle, N. (2019). Big Australia, Small Australia, Diverse Australia: Australia’s views on population. Report No. 28: January 2019. Canberra: The Australian National University. https://csrm. cass.anu.edu.au/sites/default/files/docs/2019/1/ANUpoll-28-population.pdf de Beer, J. (2011). A new relational method for smoothing and projecting age-specific fertility rates: TOPALS. Demographic Research, 24(18), 409–454. https://www.demographic-research.org/vol umes/vol24/18/ Ediev, D. M. (2008). Extrapolative projections of mortality: Towards a more consistent method part I: The central scenario. Vienna Institute of Demography Working Papers. https://www.oeaw.ac. at/fileadmin/subsites/Institute/VID/PDF/Publications/Working_Papers/WP2008_03.pdf Essential Research. (2020). Essential Report: Most Important Issues. https://essentialvision.com. au/most-important-issues-4 Keyfitz, N., & Caswell, H. (2005). Applied mathematical demography. Springer. Lutz, W., Goujon, A., KC, S., Stonawski, M., & Stilianakis, N. (2018). Wittgenstein centre human capital data explorer. http://dataexplorer.wittgensteincentre.org/wcde-v2/ Matysiak, A., Sobotka, T., & Vignoli, D. (2021). The great recession and fertility in Europe: A sub-national analysis. European Journal of Population, 37(1), 29–64. https://doi.org/10.1007/ s10680-020-09556-y McDonald, P. (2020). A projection of Australia’s future fertility rates. Canberra: Centre for Population Research Paper, The Australian Government. https://population.gov.au/downloads/McDona ldFertilityProjections.pdf Peristera, P., & Kostaki, A. (2007). Modeling fertility in modern populations. Demographic Research, 16(6), 141–194. https://www.demographic-research.org/volumes/vol16/6/ Rees, P. (1984). Spatial population analysis using movement data and accounting methods: theory, models, the ‘MOVE’ program and examples. Working paper 404: School of Geography, University of Leeds, UK. Sobotka, T., Skirbekk, V., & Philipov, D. (2011). Economic recession and fertility in the developed world. Population and Development Review, 37(2), 267–306. https://doi.org/10.1111/j. 1728-4457.2011.00411.x Wilson, T. (2020). Modelling age patterns of internal migration at the highest ages. Spatial Demography, 8(2), 175–192. https://doi.org/10.1007/s40980-020-00062-7 Wilson, T., & Rees, P. (2021). A brief guide to producing a national population projection. Australian Population Studies, 5(1), 77–100. https://doi.org/10.37970/aps.v5i1.84

Chapter 4

The Future Demography of Australia’s Migrant Populations

Abstract The future of Australia’s population by birthplace composition according to the four specified projection scenarios is presented in this chapter. In all scenarios the overseas-born population composition becomes less Europe-born and more Asiaborn and more Africa & Middle East-born. The changing size and age-sex structure of these populations is illustrated, and the substantial contribution of international migration in all scenarios is demonstrated through a comparison with a ‘No Migration’ variant projection. The diversity of Australia’s population is projected to increase in all scenarios, especially at the older ages. Keywords Population scenarios · Population projections · Birthplace populations · Diversity · Australia

4.1 Pre-COVID Trends Scenario Under the Pre-COVID Trends scenario Australia’s total population increases from 24.2 million in 2016 to 40.8 million by 2066 (an increase of 16.6 million or 69%). The Australia-born population is projected to grow by 50% over the 2016–66 projection horizon, from 17.3 to 26.0 million (+8.7 million) while the overseas-born populations combined grow by 114%, from 6.9 million to 14.8 million (+7.9 million). However, the overseas-born population experiences a COVID-related decline of almost 300,000 between 2020 and 2023, after which growth resumes. Because this post-COVID growth is substantially higher than that of the Australia-born population, the overseas-born share of the national population rises from 28.4% in 2023 to 36.3% in 2066. Figure 4.1 illustrates the growth of population from 1901 through to 2066 for a broad classification of birthplaces which aligns with available country of birth detail in early census reports. The oldest settlement migrant group, the UK & Ireland-born, are projected to increase from a 2016 total of 1.25 million to reach 1.60 million by 2066, while populations born in all other European countries (Other Europe) are expected to decline from their total of 1.09 million in 2016 to 0.97 million by 2066. The largest numerical and proportional change will occur for the Asia-born population of Australia, which is projected to grow from 2.68 million in 2016 to © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 T. Wilson et al., The Changing Migrant Composition of Australia’s Population, SpringerBriefs in Population Studies, https://doi.org/10.1007/978-3-030-88939-5_4

23

24

4 The Future Demography of Australia’s Migrant Populations

Fig. 4.1 Australia’s population by broad birthplace group, 1901–2066, Pre-COVID Trends scenario. Notes The growth between 1991 and 1996 is partly due to a switch from census counts to Estimated Resident Populations (which includes allowance for census underenumeration). Population estimates are shown up to 2016, while between 2016 and 2020 the numbers consist of projections constrained to known net international migration totals and are effectively hybrid estimates/projections. Projections proper are from 2020 onwards. Source ABS; authors’ projections

8.23 million by 2066, an increase of 207%. High growth is also anticipated for the Africa & Middle East-born population which increases from 0.79 to 1.97 million over the projection horizon (+1.17 million or 148%), and the Americas-born which is projected to grow from 323,000 to 798,000 (+475,000 or 147%). The Other Oceania population (Oceania except Australia and New Zealand) is projected to more than double, from 167,000 in 2016 to 351,000 by 2066 (110%), while the New Zealandborn increases by 56%, from 568,000 to 889,000. Australia’s birthplace populations are projected to experience a wide variety of age structure developments. Figure 4.2 illustrates the 2016, 2041 and 2066 agesex structures for six broadly-defined birthplace populations: the Australia-born and overseas-born at the highest level of aggregation; and the four largest overseas birthplace categories shown in Fig. 4.1: the UK & Ireland-born, Other Europe-born, Africa & the Middle East-born, and Asia-born. The Australia-born population grows across all age groups and shifts to a more pyramidal shape over time. Growth is especially high in the childhood ages because overseas-born populations give birth to Australia-born babies, and the overseas-born populations in the main childbearing ages grow considerably during the projections. The result is an increasing number of births over time, which maintains the youthful population age structure. The median age of the Australia-born increases up to the mid-2030s, and then changes little for the rest of the projection horizon. The median age of 33.5 years in 2016 increases to 36.1 by 2036 and then changes little in subsequent decades, ending at 36.1 years in 2066.

4.1 Pre-COVID Trends Scenario

25

Fig. 4.2 Population age-sex structures for selected broad birthplace groups, 2016, 2041 and 2066, Pre-COVID Trends scenario. Source ABS ERPs (2016); authors’ projections (2041 and 2066)

26

Fig. 4.2 (continued)

4 The Future Demography of Australia’s Migrant Populations

4.1 Pre-COVID Trends Scenario

Fig. 4.2 (continued)

27

28

4 The Future Demography of Australia’s Migrant Populations

The age structure of the overseas-born population as a whole is shaped by the size and age profile of initial immigration flows, subsequent cohort progression to higher ages, and depletion through emigration and mortality. The peak age groups for immigration are the younger adult ages (in the 20s and 30s), with similar peak age groups for emigration. The considerable immigration flows and moderate emigration flows in the Pre-COVID Trends scenario increase the size of the overseas-born population substantially over the course of the projection horizon, ensuring that the amount of structural ageing projected to occur in the overseas-born population is relatively modest. The UK and Ireland-born population consisted of relatively large numbers in the 45–75 year old age range in 2016, reflecting immigration flows of those born in the three decades following World War Two. A substantial proportion of this age group arrived in Australia in the 1990s and 2000s (Raymer et al., 2018), later than might be expected given that migration peaks in the young adult ages from the early 20s to the mid-30s. This is because of the distribution of ages at immigration from the UK and Ireland, and fluctuating levels of migration over time. The Other Europe-born population is currently a relatively old population which reflects post-World War II European migration history to Australia. There was substantial immigration in the late 1940s and throughout the 1950s and 1960s aided by migration schemes agreed with European governments and the International Refugee Organisation (Jordens, 2001). The surviving migrants from this period comprise the upper third of the 2016 population age structure. Over the next few decades these cohorts will be replaced by younger migrants, producing a population total in 2066 which is only slightly smaller than in 2016 but very different in age structure. The Africa and Middle East-born population is noticeably younger than the more established Europe-born populations, with the majority in the younger ages being arrivals in the twenty-first century. It is projected to grow strongly over coming decades, with cohort flow to higher ages expanding the population considerably in the middle and older adult ages, while continuing to grow at younger ages due to high net international migration gains. The Asia-born population of Australia is currently relatively young with an age structure shaped mostly by young migrants who arrived in Australia in the present century. Over the coming decades continued high levels of immigration, together with substantial proportions of immigrant cohorts remaining in Australia long-term, generate projections of population growth across all age groups, as well as population ageing. Table 4.1 provides more geographical detail by summarising projections for the 26 ABS 2-digit birthplace groups. Aside from the Australia-born, projected growth over the 50 years to 2066 is dominated by those born in Chinese Asia (China, Mongolia, and Taiwan) and Southern Asia (India, Pakistan, Sri Lanka and surrounding countries), with increases of about 1⅓ million and 2⅓ million, respectively. Together, populations born in these two regions make up almost half the projected growth in the total overseas-born population over the projection horizon. Substantial population growth is also projected for those born in Maritime South East Asia (just over

4.1 Pre-COVID Trends Scenario

29

Table 4.1 Projections of Australia’s population by ABS country of birth grouping, 2016–66, PreCOVID trends scenario ABS

Growth, 2016–66

Code

Country/region of 2016 birth

2041

2066

No

%

11

Australia

17,278,000

21,436,000

26,000,000

8,722,000

50

12

New Zealand

568,000

699,000

889,000

321,000

56

13

Melanesia

40,000

61,000

77,000

38,000

95

14

Micronesia

2,000

2,000

3,000

1,000

94

15

Polynesia

126,000

201,000

271,000

145,000

115

21

UK§

1,202,000

1,215,000

1,422,000

220,000

18

22

Ireland

88,000

131,000

181,000

93,000

106

23

Western Europe

272,000

221,000

253,000

-19,000

-7

24

Northern Europe

36,000

38,000

46,000

11,000

29

31

Southern Europe

276,000

195,000

216,000

-60,000

-22

32

South Eastern Europe

350,000

228,000

198,000

-152,000

-43

33

Eastern Europe

152,000

184,000

255,000

103,000

68

41

North Africa

80,000

105,000

142,000

61,000

76

42

Middle East

349,000

637,000

918,000

569,000

163

51

Mainland South East Asia

395,000

673,000

930,000

535,000

136

52

Maritime South East Asia

556,000

960,000

1,359,000

803,000

144

61

Chinese Asia

715,000

1,441,000

2,112,000

1,398,000

196

62

Japan and the Koreas

161,000

270,000

374,000

213,000

132

71

Southern Asia

796,000

2,023,000

3,156,000

2,361,000

297

72

Central Asia

61,000

168,000

298,000

236,000

385

81

North America

160,000

234,000

305,000

145,000

90

82

South America

137,000

282,000

426,000

290,000

212

83

Central America

20,000

36,000

53,000

33,000

164

84

Caribbean

6,000

10,000

14,000

8,000

133

91

Central and West Africa

34,000

83,000

136,000

102,000

302

92

Southern and East Africa

331,000

544,000

771,000

440,000

133

Overseas-born

6,912,000

10,642,000

14,808,000

7,895,000

114 (continued)

30

4 The Future Demography of Australia’s Migrant Populations

Table 4.1 (continued) ABS Code

Growth, 2016–66 Country/region of 2016 birth

2041

2066

No

%

Total

32,078,000

40,808,000

16,617,000

69

24,191,000

Notes Rounding to the nearest 1000 has been applied. The ABS country of birth classification is shown in Table 3.1. § Includes Channel Islands and Isle of Man Source ABS ERPs (2016); authors’ projections (2041 and 2066)

¾ million) (Malaysia, Indonesia, Philippines and neighbouring countries), Mainland South East Asia (just over ½ million) (Thailand, Vietnam and nearby countries), and the Middle East (over ½ million). In contrast, population decline is anticipated for some more established migrant groups, especially those born in South Eastern Europe (Greece, the Balkan countries, and neighbours), in which the population of 350,000 in 2016 is projected to decline to 198,000 by 2066. Amongst the oldest migrant groups, growth is also projected. The UK-born population increases from about 1.20 million to 1.42 million over the course of the projections, while the Ireland-born grow from 88,000 to 181,000. The shifts in the birthplace distribution of the population resulting from coming changes to the size and age structures of birthplace-specific populations are summarised in Table 4.2. This shows how the percentage distribution of the Australian population across 26 birthplace groups is projected to change for all ages as a whole and the broad age groups of 0–14, 15–64 and 65+. The least amount of distributional change is evident for the 0–14 year old population, where the percentage Australia-born remains high. This is not surprising because net international migration tends to be relatively low for children and many in the 0–14 year old population will be Australia-born children of migrants. However, the birthplace composition in the main workforce ages of 15–64 is projected to change to a greater extent, with declines in the proportions who are Australia-born, as well as those born in the UK and much of continental Europe. There are percentage point increases for populations born in most other parts of the world, especially Southern Asia and Chinese Asia. The largest shift is projected to occur in the 65+ age group (Table 4.2). The Australia-born share of this age group falls gradually from 62.4% in 2016 to 57.7% by 2066. However, among the overseas-born populations there is a notable distributional shift. There is large percentage point decline expected for those born in the UK (11.0% in 2016 to 5.3% by 2066) and much of continental Europe (e.g., those born in Southern Europe comprised 4.5% of the 65+ population in 2016 but they are projected to be just 0.8% by 2066). In contrast, the share of the 65+ population born in Asian birthplaces increases substantially, particularly Southern Asia (1.4–7.6%), Chinese Asia (1.8–5.4%), and also Maritime South East Asia, and Mainland South East Asia.

4.1 Pre-COVID Trends Scenario

31

Table 4.2 Percentage distribution of Australia’s population by ABS country of birth grouping and broad age group, 2016 and 2066, Pre-COVID Trends scenario ABS

2016

2066

Country/region of birth

All ages

0–14

15–64

65+

All ages

0–14

15–64

65 +

11

Australia

71.4

91.3

67.8

62.4

63.7

90.1

59.0

57.7

12

New Zealand

2.3

1.1

2.8

1.8

2.2

1.1

2.5

2.2

13

Melanesia

0.2

0.1

0.2

0.1

0.2

0.1

0.2

0.3

14

Micronesia

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

15

Polynesia

0.5

0.1

0.7

0.4

0.7

0.1

0.7

1.0

21

UK§

5.0

1.2

4.7

11.0

3.5

1.1

3.5

5.3

22

Ireland

0.4

0.1

0.4

0.5

0.4

0.1

0.5

0.4

23

Western Europe 1.1

0.2

0.9

3.4

0.6

0.2

0.7

0.7

24

Northern Europe

0.1

0.0

0.2

0.3

0.1

0.0

0.1

0.1

31

Southern Europe

1.1

0.1

0.7

4.5

0.5

0.1

0.6

0.8

32

South Eastern Europe

1.4

0.1

1.2

4.4

0.5

0.1

0.5

0.8

33

Eastern Europe

0.6

0.1

0.6

1.5

0.6

0.1

0.7

0.9

41

North Africa

0.3

0.1

0.4

0.5

0.3

0.1

0.3

0.5

42

Middle East

1.4

0.6

1.7

1.2

2.2

0.8

2.5

2.7

51

Mainland South 1.6 East Asia

0.4

2.1

1.0

2.3

0.4

2.5

2.9

52

Maritime South East Asia

2.3

0.9

2.9

1.5

3.3

1.0

3.8

3.7

61

Chinese Asia

3.0

0.6

3.9

1.8

5.2

0.9

6.2

5.4

62

Japan and the Koreas

0.7

0.3

0.9

0.2

0.9

0.3

1.1

0.8

71

Southern Asia

3.3

1.4

4.3

1.4

7.7

2.0

9.3

7.6

72

Central Asia

0.3

0.1

0.3

0.1

0.7

0.1

0.8

0.9

81

North America

0.7

0.4

0.8

0.5

0.7

0.5

0.8

0.7

82

South America

0.6

0.1

0.7

0.5

1.0

0.1

1.2

1.3

83

Central America 0.1

0.0

0.1

0.1

0.1

0.0

0.1

0.2

84

Caribbean

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.1

91

Central and West Africa

0.1

0.1

0.2

0.0

0.3

0.1

0.4

0.4

92

Southern and East Africa

1.4

0.6

1.7

1.0

1.9

0.5

1.9

2.7

Overseas-born

28.6

8.7

32.2

37.6

36.3

9.9

41.0

Code Percent

42.3 (continued)

32

4 The Future Demography of Australia’s Migrant Populations

Table 4.2 (continued) ABS

2016 Total

100.0

2066 100.0

100.0

100.0

100.0

100.0

100.0

100.0

Source Calculated from ABS ERPs (2016) and authors’ projections (2041 and 2066)

To the extent that a greater proportion of the population will be overseas-born, Australia will become more diverse. We also calculated an index of birthplace diversity (Alesina et al., 2016) which measures the probability that two persons randomly drawn from the population were born in different countries (or in our case one of 26 different birthplace groups). The index increases from 0.483 in 2016 to 0.581 in 2066, indicating a moderate increase in diversity in the future. What is driving the varied growth projections of the birthplace populations? In terms of the demographic components of change, the Australia-born population grows substantially from natural increase, with births contributed by both Australiaborn and overseas-born parents resident in Australia. It experiences net international migration losses, but high growth overall thanks to natural change and a young age structure. All overseas-born population groups change only through immigration, emigration, and mortality. Much depends on the immigration and emigration assumptions, while the age structure of populations plays a crucial role in the extent to which they are depleted by mortality. The oldest populations (those born in Southern Europe, South Eastern Europe and Western Europe, all of which have median ages in excess of 60 years in 2016) have their growth rates reduced the most due to mortality, while many Asian-born populations are much younger and experience relatively little impact from mortality, at least in the early years of the projection horizon. More results from the Pre-COVID Trends projection scenario can be found in Chap. 6. This comprises summary profiles for Australia and the overseas-born, each of the 26 ABS birthplace populations, and the selected individual countries of birth which were included in this study.

4.2 Global Talent Scenario The Global Talent scenario results in much higher projected populations for those born in Africa and Asia relative to the Pre-COVID Trends scenario (Table 4.3). Most dramatically, the Southern Asia-born is projected to increase to 4.16 million by 2066, just over 1 million more than in the Pre-COVID Trends scenario, reflecting the huge projected growth of this region’s population, and specifically its well-educated population according to the Wittgenstein Centre projections. The Southern & East Africa-born population is projected to be 1.44 million by 2066, ⅔ million higher than in the Pre-COVID Trends scenario, while the Maritime South East Asia-born is

4.2 Global Talent Scenario

33

Table 4.3 Projections of Australia’s population by ABS country of birth grouping, 2016–66, Global Talent scenario ABS

Growth, 2016–66

Code

Country/region of 2016 birth

2041

2066

No

%

11

Australia

17,278,000

21,323,000

25,855,000

8,577,000

50

12

New Zealand

568,000

707,000

809,000

241,000

42

13

Melanesia

40,000

78,000

135,000

95,000

240

14

Micronesia

2000

2000

3000

2000

100

15

Polynesia

126,000

209,000

257,000

131,000

104

21

UK§

1,202,000

1,128,000

1,170,000

−32,000

−3

22

Ireland

88,000

109,000

121,000

33,000

37

23

Western Europe

272,000

223,000

236,000

−36,000

−13

24

Northern Europe

36,000

38,000

43,000

7000

20

31

Southern Europe

276,000

186,000

180,000

−97,000

−35

32

South Eastern Europe

350,000

229,000

168,000

−182,000

−52

33

Eastern Europe

152,000

147,000

156,000

4000

3

41

North Africa

80,000

127,000

221,000

140,000

175

42

Middle East

349,000

672,000

1,091,000

742,000

213

51

Mainland South East Asia

395,000

707,000

1,018,000

623,000

158

52

Maritime South East Asia

556,000

1,148,000

1,895,000

1,339,000

241

61

Chinese Asia

715,000

1,184,000

1,474,000

759,000

106

62

Japan and the Koreas

161,000

195,000

177,000

17,000

10

71

Southern Asia

796,000

2,356,000

4,163,000

3,367,000

423

72

Central Asia

61,000

131,000

216,000

155,000

253

81

North America

160,000

208,000

240,000

80,000

50

82

South America

137,000

267,000

363,000

226,000

166

83

Central America

20,000

36,000

52,000

32,000

159

84

Caribbean

6000

9000

11,000

5000

88

91

Central and West Africa

34,000

123,000

310,000

276,000

817

92

Southern and East Africa

331,000

709,000

1,441,000

1,110,000

335

Overseas-born

6,912,000

10,929,000

15,951,000

9,038,000

131 (continued)

34

4 The Future Demography of Australia’s Migrant Populations

Table 4.3 (continued) ABS Code

Growth, 2016–66 Country/region of 2016 birth

2041

2066

No

%

Total

32,252,000

41,806,000

17,615,000

73

24,191,000

Notes Rounding to the nearest 1000 has been applied. The ABS country of birth classification is shown in Table 3.1. § Includes Channel Islands and Isle of Man Source ABS ERPs (2016); authors’ projections (2041 and 2066)

projected to be 1.89 million by 2066, over ½ million higher. Higher growth than in the Pre-COVID Trends scenario is also projected for those born in the Middle East, Mainland South East Asia, other regions of Africa, and Melanesia. Populations which grow substantially less than those in the Pre-COVID Trends scenario include the Chinese Asia-born (1.47 million rather than 2.11 million), and those born in Japan & the Koreas (177,000 rather than 374,000). Populations born in the older migrant origins of the UK, Ireland, and regions of continental Europe, also experience slower growth. The distribution of the population by birthplace in 2066 is 61.8% Australiaborn (slightly lower than the 63.7% of the Pre-COVID Trends scenario) though a larger share is Africa-born (4.7% rather than 2.6%), slightly more Asia-born (21.4% rather than 20.2%), but a smaller share of the Europe-born (5.0% rather than 6.3%). Not surprisingly, the birthplace diversity index increases a little more than in the Pre-COVID Trends scenario (being 0.600 rather than 0.581 in 2066). Overall, the projected composition of the overseas-born in the Global Talent scenario is a function of the anticipated shift in the geographical distribution of the world’s young educated people. The combined overseas-born population in this scenario is 16.0 million rather than 14.8 million in the Pre-COVID Trends scenario due primarily to lower emigration. Lower projected emigration results from a greater proportion of the overseas-born population comprising immigrant groups with low emigration rates.

4.3 Lower Immigration Scenario In the Lower Immigration scenario, projected populations are, not surprisingly, lower for all birthplace groups (Table 4.4). The lower immigration assumption of this scenario generates lower net international migration gains to the population over time relative to the Pre-COVID Trends scenario. After the COVID-related drop in immigration, net international migration varies between 115,000 per year in the mid-2020s and 165,000 by the end of the projection horizon. The outcome of the migration assumptions is a total population of 35.7 million in Australia by 2066. The overseas-born population is projected to grow to 11.2 million by 2066, about 3½ million lower than in the Pre-COVID Trends scenario but still 4.3 million greater

4.3 Lower Immigration Scenario

35

Table 4.4 Projections of Australia’s population by ABS country of birth grouping, 2016–66, Lower Immigration scenario ABS

Growth, 2016–66

Code

Country/region of 2016 birth

2041

2066

No

%

11

Australia

17,278,000

21,042,000

24,477,000

7,199,000

42

12

New Zealand

568,000

577,000

666,000

98,000

17

13

Melanesia

40,000

52,000

59,000

20,000

49

14

Micronesia

2000

2000

2000

1000

50

15

Polynesia

126,000

170,000

206,000

80,000

64

21

UK§

1,202,000

1,041,000

1,075,000

-127,000

-11

22

Ireland

88,000

106,000

136,000

48,000

55

23

Western Europe

272,000

184,000

189,000

-83,000

-30

24

Northern Europe

36,000

31,000

35,000

-1,000

-4

31

Southern Europe

276,000

168,000

163,000

-114,000

-41

32

South Eastern Europe

350,000

208,000

155,000

-195,000

-56

33

Eastern Europe

152,000

155,000

193,000

41,000

27

41

North Africa

80,000

91,000

110,000

30,000

37

42

Middle East

349,000

532,000

699,000

350,000

100

51

Mainland South East Asia

395,000

570,000

714,000

319,000

81

52

Maritime South East Asia

556,000

791,000

1,027,000

470,000

84

61

Chinese Asia

715,000

1,157,000

1,580,000

865,000

121

62

Japan and the Koreas

161,000

212,000

277,000

116,000

72

71

Southern Asia

796,000

1,667,000

2,400,000

1,604,000

202

72

Central Asia

61,000

139,000

228,000

167,000

272

81

North America

160,000

181,000

224,000

64,000

40

82

South America

137,000

232,000

323,000

186,000

136

83

Central America

20,000

30,000

41,000

21,000

103

84

Caribbean

6000

8000

11,000

5000

77

91

Central and West Africa

34,000

69,000

104,000

70,000

208

92

Southern and East Africa

331,000

464,000

593,000

262,000

79

Overseas-born

6,912,000

8,836,000

11,210,000

4,297,000

62 (continued)

36

4 The Future Demography of Australia’s Migrant Populations

Table 4.4 (continued) ABS Code

Growth, 2016–66 Country/region of 2016 birth

2041

2066

No

%

Total

29,878,000

35,687,000

11,496,000

48

24,191,000

Notes Rounding to the nearest 1000 has been applied. The ABS country of birth classification is shown in Table 3.1. § Includes Channel Islands and Isle of Man Source ABS ERPs (2016); authors’ projections (2041 and 2066)

than in 2016. The Australia-born population is projected to grow to 24.5 million by 2066, about 1½ million lower than in the Pre-COVID Trends scenario, primarily due to a smaller overseas-born population having fewer Australia-born babies. The birthplace distribution of Australia’s population in 2066 includes a higher Australia-born share than in the Pre-COVID Trends scenario (68.6% rather than 63.7%) and lower shares for all overseas-born population groups. The index of birthplace diversity in 2066 (0.520) is slightly greater than it was in 2016 (0.483).

4.4 Higher Immigration Scenario In the Higher Immigration scenario, all 26 birthplace populations experience higher growth over the projection horizon than in the Pre-COVID Trends scenario, as would be expected (Table 4.5). The higher immigration assumptions in this scenario generate net international migration gains of around 340,000 per year in the immediate years following the COVID-related drop in migration. This gradually falls over time to about 300,000 per year by the end of the projection horizon. The result is a total projected population of Australia in 2066 of 45.9 million, with 18.4 million (40.1%) being overseas-born. The total population is 5.1 million higher than in the PreCOVID Trends scenario, while the overseas-born population is 3.6 million higher. The Australia-born population in 2066 is projected to grow to 27.5 million, about 1½ million higher than in the Pre-COVID Trends scenario, due to a larger overseas-born population having a greater number of Australia-born babies. The birthplace distribution of Australia’s population in 2066 includes a lower Australia-born share than in the Pre-COVID Trends scenario (59.9% rather than 63.7%) and higher shares for all overseas-born population groups. The index of birthplace diversity in 2066 (0.625) is considerably greater than it was in 2016 (0.483).

4.4 Higher Immigration Scenario

37

Table 4.5 Projections of Australia’s population by ABS country of birth grouping, 2016–66, Higher Immigration scenario ABS

Growth, 2016–66

Code

Country/region of 2016 birth

2041

2066

No

%

11

Australia

17,278,000

21,830,000

27,524,000

10,245,000

59

12

New Zealand

568,000

822,000

1,112,000

544,000

96

13

Melanesia

40,000

69,000

96,000

56,000

141

14

Micronesia

2000

3000

4000

2000

139

15

Polynesia

126,000

233,000

336,000

210,000

167

21

UK§

1,202,000

1,388,000

1,770,000

568,000

47

22

Ireland

88,000

155,000

227,000

138,000

157

23

Western Europe

272,000

257,000

317,000

45,000

16

24

Northern Europe

36,000

45,000

58,000

22,000

62

31

Southern Europe

276,000

222,000

270,000

-6,000

-2

32

South Eastern Europe

350,000

248,000

241,000

-109,000

-31

33

Eastern Europe

152,000

214,000

316,000

164,000

108

41

North Africa

80,000

120,000

174,000

93,000

116

42

Middle East

349,000

743,000

1,137,000

789,000

226

51

Mainland South East Asia

395,000

776,000

1,146,000

752,000

191

52

Maritime South East Asia

556,000

1,129,000

1,692,000

1,136,000

204

61

Chinese Asia

715,000

1,726,000

2,645,000

1,930,000

270

62

Japan and the Koreas

161,000

328,000

470,000

309,000

192

71

Southern Asia

796,000

2,379,000

3,913,000

3,117,000

392

72

Central Asia

61,000

197,000

367,000

306,000

499

81

North America

160,000

287,000

386,000

226,000

141

82

South America

137,000

333,000

529,000

393,000

287

83

Central America

20,000

42,000

65,000

45,000

226

84

Caribbean

6000

11,000

18,000

11,000

189

91

Central and West Africa

34,000

97,000

168,000

134,000

397

92

Southern and East Africa

331,000

625,000

949,000

618,000

187

Overseas-born

6,912,000

12,449,000

18,406,000

11,494,000

166 (continued)

38

4 The Future Demography of Australia’s Migrant Populations

Table 4.5 (continued) ABS Code

Growth, 2016–66 Country/region of 2016 birth

2041

2066

No

%

Total

34,279,000

45,930,000

21,739,000

90

24,191,000

Notes Rounding to the nearest 1,000 has been applied. The ABS country of birth classification is shown in Table 3.1. § Includes Channel Islands and Isle of Man Source ABS ERPs (2016); authors’ projections (2041 and 2066)

4.5 The Contribution of Migration to Projected Growth A simple approach to identifying the demographic drivers of projected population growth is to examine the demographic components of change, i.e., births, deaths, and migration. But this does not permit the interactions between migration, fertility and mortality to be determined. For example, lower net international migration will, all other things being equal, result in fewer births because of lower population growth in the main childbearing ages. To understand the contribution of international migration to the projection scenarios, we prepared a No Migration projection in which there was no international migration but the same fertility and mortality assumptions as in the main scenarios. The total projected population for the No Migration scenario is shown alongside the main scenarios for the Australian population overall, the Australia-born, and the overseas-born in Fig. 4.3. As the graphs make clear, a substantial amount of population growth in the four main scenarios is generated by net international migration. The top graph of Fig. 4.3 shows that, without migration between 2016 and 2066, Australia’s population would grow slowly up to the early 2040s (to 25.7 million, about 1.5 million higher than in 2016) before gradually declining. By 2066 the four main scenarios give much higher populations than the No Migration projection: 11.2 million higher for the Lower Immigration scenario, 16.3 million for the Pre-COVID Trends scenario, 17.3 million for the Global Talent scenario, and 21.5 million for the Higher Immigration scenario. For the Australia-born population (shown by the middle graph of Fig. 4.3), differences between the No Migration projection and the main scenarios are mostly due to different numbers of births. The lack of net international migration leads to far fewer Australia-born babies to overseas-born parents over the projection horizon. For the overseas-born population (lower graph), the No Migration scenario means the overseas-born cohorts in the population are not being replenished. They gradually age and are depleted by mortality. If the No Migration projections ran for a further 50 years, almost all the overseas-born population would have died out. The influence of net international migration on the 2-digit birthplace groups is shown in Tables 4.6a and 4.6b, with part (a) of the table presenting projected populations in 2041 and part (b) populations in 2066. Without migration, the overseas-born populations are, not surprisingly, much smaller than they would be in the Pre-COVID

4.5 The Contribution of Migration to Projected Growth

39

Trends scenario and smaller than they were in 2016. By 2066 they vary from 12% of their size in 2016 (Southern Europe-born) to 69% (Southern Asia-born). The speed with which the birthplace populations decline without migration is due to mortality, which is largely a function of the age structure of the population (but also to some extent the level of mortality assumed in each population). Generally, the greater the proportion of the population in the older ages where death rates are highest, the faster the population decline due to mortality. The share of the population aged 65+ in 2016 was 60% among the South Europe-born population, for example, while for the Southern Asia-born it was just 6%. The difference in overseas birthplace population sizes in 2066 between any of the main scenarios and the No Migration projection is due to both the crude net migration rate—the rate by which each birthplace population is assumed to grow by net international migration—and population age structure. Most European birthplaces have below-average crude net migration rates and older than average population age structures. Asian-born birthplaces all have young population age structures, and a mix of mostly average and above-average crude net migration rates in the main scenarios. Both these factors aid population growth. Above-average crude net migration rates are also experienced by those born in South America, Central America, the Caribbean, and Central & West Africa.

Fig. 4.3 The projected population of Australia, the Australia-born and the overseas-born, 2016–66, by scenario

40

Fig. 4.3 (continued)

4 The Future Demography of Australia’s Migrant Populations

4.5 The Contribution of Migration to Projected Growth

41

Table 4.6a Projected populations by birthplace, 2041, by scenario Pre-COVID trends

Global talent

Lower immigration

Higher immigration

No migration

Australia

21,436

21,323

21,042

21,830

20,460

New Zealand

699

707

577

822

461

Melanesia

61

78

52

69

33

Micronesia

2

2

2

3

1

Polynesia

201

209

170

233

101

UK

1215

1128

1041

1388

729

Ireland

131

109

106

155

68

Western Europe 221

223

184

257

145

Northern Europe

38

38

31

45

25

Southern Europe

195

186

168

222

112

South Eastern Europe

228

229

208

248

180

Eastern Europe

184

147

155

214

91

North Africa

105

127

91

120

58

Middle East

637

672

532

743

285

Mainland South 673 East Asia

707

570

776

345

Maritime South 960 East Asia

1148

791

1129

474

Chinese Asia

1441

1184

1157

1726

640

Japan & the Koreas

270

195

212

328

145

Southern Asia

2023

2356

1667

2379

725

Central Asia

168

131

139

197

56

North America

234

208

181

287

133

South America

282

267

232

333

110

Central America

36

36

30

42

17

Caribbean

10

9

8

11

4

Central & West 83 Africa

123

69

97

31

Southern & East Africa

544

709

464

625

279

Overseas-born

10,642

10,929

8836

12,449

5249

Thousands

(continued)

42

4 The Future Demography of Australia’s Migrant Populations

Table 4.6a (continued)

Total

Pre-COVID trends

Global talent

Lower immigration

Higher immigration

No migration

32,078

32,252

29,878

34,279

25,710

Source Authors’ projections Table 4.6b Projected populations by birthplace, 2066, by scenario Pre-COVID trends

Global talent

Lower immigration

Higher immigration

No migration

Australia

26,000

25,855

24,477

27,524

21,456

New Zealand

889

809

666

1,112

255

Melanesia

77

135

59

96

16

Micronesia

3

3

2

4

1

Polynesia

271

257

206

336

48

UK

1422

1170

1075

1770

278

Ireland

181

121

136

227

42

Western Europe 253

236

189

317

63

Northern Europe

46

43

35

58

13

Southern Europe

216

180

163

270

33

South Eastern Europe

198

168

155

241

57

Eastern Europe

255

156

193

316

44

North Africa

142

221

110

174

34

Middle East

918

1091

699

1137

163

Mainland South 930 East Asia

1018

714

1146

200

Maritime South 1359 East Asia

1895

1027

1692

287

Chinese Asia

2112

1474

1580

2645

456

Japan & the Koreas

374

177

277

470

100

Southern Asia

3156

4163

2400

3913

546

Central Asia

298

216

228

367

40

North America

305

240

224

386

81

Thousands

(continued)

4.5 The Contribution of Migration to Projected Growth

43

Table 4.6b (continued) Pre-COVID trends

Global talent

Lower immigration

Higher immigration

No migration

South America

426

363

323

529

65

Central America

53

52

41

65

9

Caribbean

14

11

11

18

2

Central & West 136 Africa

310

104

168

21

Southern & East Africa

771

1441

593

949

163

Overseas-born

14,808

15,951

11,210

18,406

3016

Total

40,808

41,806

35,687

45,930

24,472

Source Authors’ projections

References Alesina, A., Harnoss, J., & Rapoport, H. (2016). Birthplace diversity and economic prosperity. Journal of Economic Growth, 21(2), 101–138. https://doi.org/10.1007/s10887-016-9127-6 Jordens, A. (2001). Post-war non-British migration. In J. Jupp (Ed.), The Australian People (pp. 65– 70). Cambridge: Cambridge University Press. Raymer, J., Shi, Y., Guan, Q., Baffour, B., & Wilson, T. (2018). The sources and diversity of immigrant population change in Australia, 1981–2011. Demography, 55(5), 1777–1802. https:// doi.org/10.1007/s13524-018-0704-5

Chapter 5

Discussion and Conclusions

Abstract This chapter summarises the key points of the research, notes some of the benefits of a large and diverse migrant population, and describes policy challenges which lie ahead. These include measures to avoid economic and geographic segregation, prevent discrimination, and manage public opinion. We also mention some of the limitations of our study. Keywords Projection scenarios · Population ageing · Population diversity · Policy implications · Australia International migration will undoubtedly continue to play a leading role in shaping Australia’s demographic development in the future. The precise form of that development is hard to predict, particularly several decades ahead, but the scenarios presented in this paper offer some pointers to possible futures. Under the Pre-COVID Trends, Global Talent and Higher Immigration scenarios the total resident population of the country increases substantially over the 2016–66 projection horizon (by about 16.6 million, 17.6 million, and 21.7 million respectively). Even under the Lower Immigration scenario, the population increases by 11.5 million between 2016 and 2066. The No Migration projection adds only another 1½ million by the early 2040s, demonstrating that the vast bulk of population growth in the other scenarios will be due to international migration. This includes both direct effects from migration flows and the consequent impact on natural increase and population age structure. Under Pre-COVID Trends, Global Talent, and Higher Immigration scenarios, Australia’s overseas-born population will grow substantially both in numerical terms and as a proportion of the total population, and the population will become more diverse. Its composition will shift to one which is more Asia-born under both these scenarios, though the Global Talent scenario results in a larger Africa-born, Maritime South East Asia-born and Southern Asia-born populations than in the Pre-COVID Trends scenario, and smaller Europe-born and Chinese Asia-born populations. Under the Global Talent scenario, the composition of Australia’s overseas-born population is increasingly influenced by the world’s shifting population geography and notably the increase in Africa’s population. As demonstrated by Table 4.2, the birthplace composition undergoes the greatest change in the older age groups. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 T. Wilson et al., The Changing Migrant Composition of Australia’s Population, SpringerBriefs in Population Studies, https://doi.org/10.1007/978-3-030-88939-5_5

45

46

5 Discussion and Conclusions

Irrespective of which scenario comes closest to reality, the projections signal opportunities as well as policy challenges ahead. While there have been longstanding debates on the relationship between diversity and development, a recent cross-national study indicated that immigration-driven diversity is generally good for a country’s economic performance (Bove & Elia, 2017). In the case of Australia, there is little doubt that the country has benefited economically, demographically, geo-politically, culturally, and socially from the greater diversity shaped by its contemporary migration trends (see Castles et al., 2013; Hugo, 2006; McDonald & Markus, 2021; Wahlqvist, 2002). Australians are currently well-positioned to reap the transformative benefits from the diverse lifestyle options and the vast transnational linkages facilitated by the shifts in the country’s population composition. Although Australia has been quite successful at accommodating large immigration flows in the past (Hugo, 2006; Ongley & Pearson, 1995; Walsh, 2008), carefully formulated policy will be needed to avoid high levels of economic and geographical segregation, protect newcomers from discrimination, and ensure infrastructure expands as population does (see Vertovec, 2007 for an overview of policy challenges to address super-diversity in Britain). Public opinion is just as important. The management of immigration will require the Australian Government to emphasise the advantages of international migration given that a sizeable proportion of the Australian population currently supports lower immigration intakes. In Australia and developed countries across the world, immigration is an easy scapegoat for societal problems such as high housing costs, urban sprawl, traffic congestion, crime, unemployment, and pollution. Some of the electorate hold strong opinions on migration and sympathise with some minor political parties, well known for favouring much lower immigration together with restrictions on entry to refugees and Muslims. Elements of the environmental movement also hold firm anti-immigration views on environmental grounds. How governments manage coming demographic changes, and how they are perceived and debated in public will shape voting preferences and broader political systems. Extremist ideologies, underpinned by notions of resource scarcity, can amplify disadvantage and discrimination among particular population groups (Inglehart & Norris, 2016; Semyonov et al., 2006). It is important for government to be vigilant of these sentiments in some sections of the community and artfully manage demographic and social change. At the same time, there remains substantial political and community support for immigration and appreciation of the human capital and cultural diversity it brings (Dandy & Pe-Pua, 2010; Markus, 2014), and its potential impact in moderating population ageing (McDonald, 2018; McDonald & Temple, 2008; Parr & Guest, 2019). Indeed, the majority of Australians are seemingly supportive of multiculturalism, and perceive immigration as bringing in economic benefits to the country (McDonald & Markus, 2021). An expansion of research effort on the trends, drivers and outcomes of Australia’s international migration system would be very beneficial for evidence-based migration policy development. Increases to the size and diversity of the population will need to be accommodated by both government and private sector service providers. Nowhere will this be more apparent than in Australia’s aged care sector, which must deal with the consequences of population ageing. Under both Current Trajectory and Global Talent scenarios,

5 Discussion and Conclusions

47

Australia’s ageing populations will increase from Asian and African countries and decline from Southern European countries. This entails a rapid transition in current ethno-specific and mainstream aged care services, which principally service older Italian, Greek, and Anglo-Saxon families. In the future, aged care services will need to be developed and provided for South Asian, South-East Asian, and African families, while concurrently shrinking for other groups (e.g. Maltese, Dutch, and Germans). As Australia has received immigration from China for over 100 years (Hugo, 2008; Hugo et al., 2016), community and aged care services for Australian-Chinese families are well established, though these will need to be expanded to meet rising demand. The projected changes to Australia’s population composition indicate a continuation of many features of the third demographic transition. The overseas-born will increase in number and share of the population, particularly from non-English speaking countries, and their immediate descendants will inherit many of the ethnic, cultural, and religious characteristics of their parents. From a historical viewpoint, the coming changes can be viewed as an extension of a long-run process. Since the end of the Second World War immigration has grown and shifted to an increasing range of origins due to a range of interrelated factors, including the government’s large-scale immigration program which encouraged permanent settlements and family re-union, the shift from assimilationist policies in the 1960s to multiculturalism in the 1970s, and globalisation—all of which have arguably enabled Australia’s increasing engagement with its Asia–Pacific neighbours (Castles, 1995; Hugo, 2006). Australia’s postwar move to abandon discrimination against immigrants from non-European origins, and to subsequently replace it with selective immigration programs based on skills and occupation criteria, are akin to the experience of other traditional immigrant receiving countries like New Zealand and Canada (Ongley & Pearson, 1995). More generally, following earlier releases of national ethnic composition projections by Canada and New Zealand (Dion et al., 2015; Statistics New Zealand, 2017), our study has emphasised the importance of accounting for future diversity for research and policy making in Australia. Insights on the changing nature of Australia’s population diversity may inform public debates around population, and attempts to (i) measure the many facets of disadvantage and inequalities faced by migrant groups; (ii) understand the drivers of changing voter’s preference and behaviour; and (iii) canvass broader changes in Australia’s everyday culture and social life (see Coleman, 2010; Lomax et al., 2020; Norman et al., 2010; Rees et al., 2016, 2017). In interpreting results from our study, it is important to note the limitations. First, at the time of writing, the COVID-19 global pandemic is in effect. With rapid shrinkage in global economies, increased mortality, and a closing of national and subnational state/territory borders, it is difficult at this time to understand how the virus will change human development going forward. There is much uncertainty about the future of international migration, as evaluations of past projections demonstrate (e.g. Wilson, 2007). We cannot know precisely what migration policies will be in force decades ahead, or the wider global economic, geopolitical, and environmental world we will live in. Fertility and mortality will also deviate from our assumptions to some extent. We have also presented a set of projections, which distinguishes

48

5 Discussion and Conclusions

only between the Australia-born and various overseas-born categories, without any further disaggregation by immigrant generation or consideration of mixed unions (Dion et al., 2015). These more detailed projections can be the subject of subsequent research. Nonetheless, we believe our scenarios represent plausible and useful projections of Australia’s potential future demographic composition rendered all the more important in a post COVID-19 world, as countries seek to recover and rebuild their economies and societies. The Pre-COVID Trends scenario illustrates the demographic outcome of recent pre-pandemic demographic trends (and implicitly, migration policy settings and the wider global environment) returning. This seems a reasonable and plausible scenario at the present. But perhaps reality will turn out to be closer to the Global Talent scenario because it takes into account the changing distribution of human capital across the world and it seems unlikely that Australia’s immigration system will move away from emphasising skills. Accepting more migrants from origins with previously small migration flows will bring new challenges, but also new opportunities for migrants, and economic and cultural benefits for Australia.

References Bove, V., & Elia, L. (2017). Migration, diversity, and economic growth. World Development, 89, 227–239. https://doi.org/10.1016/j.worlddev.2016.08.012 Castles, S. (1995). How nation-states respond to immigration and ethnic diversity. Journal of Ethnic and Migration Studies, 21(3), 293–308. https://doi.org/10.1080/1369183X.1995.9976493 Castles, S., Hugo, G., & Vasta, E. (2013). Rethinking migration and diversity in Australia: Introduction. Journal of Intercultural Studies, 34(2), 115–121. https://doi.org/10.1080/07256868.2013. 781915 Coleman, D. (2010). Projections of the ethnic minority populations of the United Kingdom 2006– 2056. Population and Development Review, 36(3), 441–486. https://doi.org/10.1111/j.1728-4457. 2010.00342.x Dandy, J., & Pe-Pua, R. (2010). Attitudes to multiculturalism, immigration and cultural diversity: Comparison of dominant and non-dominant groups in three Australian states. International Journal of Intercultural Relations, 34(1), 34–46. https://doi.org/10.1016/j.ijintrel.2009.10.003 Dion, P., Caron-Malenfant, É., Grondin, C., & Grenier, D. (2015). Long-term contribution of immigration to population renewal in Canada: A simulation. Population and Development Review, 41(1), 109-126. https://doi.org/10.1111/j.1728-4457.2015.00028.x Hugo, G. (2006). Globalization and changes in Australian international migration. Journal of Population Research, 23(2), 107–134. https://doi.org/10.1007/BF03031812 Hugo, G. (2008). In and out of Australia: Rethinking Chinese and Indian skilled migration to Australia. Asian Population Studies, 4(3), 267–291. https://doi.org/10.1080/17441730802496508 Hugo, G., Wall, J., & Young, M. (2016). Migration in Australia and New Zealand. In M. J. White (Ed.), International handbook of migration and population distribution (pp. 333–370). Springer. Inglehart, R. F., & Norris, P. (2016). Trump, Brexit, and the rise of populism: Economic have-nots and cultural backlash. Harvard Kennedy School Research Working Paper. https://ces.fas.harvard. edu/uploads/files/Event-Papers/Inglehart-and-Norris-Populism.pdf Lomax, N., Wohland, P., Rees, P., & Norman, P. (2020). The impacts of international migration on the UK’s ethnic populations. Journal of Ethnic and Migration Studies, 46(1), 177–199. https:// doi.org/10.1080/1369183X.2019.1577726

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Markus, A. (2014). Attitudes to immigration and cultural diversity in Australia. Journal of Sociology, 50(1), 10–22. https://doi.org/10.1177/1440783314522188 McDonald, P. (2018). Australia should continue its current comprehensive population policy–at least for the next decade. Australian Population Studies, 2(2), 3–11. McDonald, P., & Markus, A. (2021). It is all about the numbers of immigrants: Population and politics in Australia and New Zealand. In A. Goerres & P. Vanhuysse (Eds.), Global political demography: The politics of population change (pp. 275–301). Springer International Publishing. McDonald, P., & Temple, J. (2008). Demographic and labour supply futures for Australia. Canberra Department of Immigration and Citizenship. Norman, P., Rees, P., Wohland, P., & Boden, P. (2010). Ethnic group populations: The components for projection, demographic rates and trends. In J. Stillwell & M. van Ham (Eds.), Ethnicity and integration: Understanding population trends and processes (Vol. 3, pp. 289–315). Springer, Netherlands. Ongley, P., & Pearson, D. (1995). Post-1945 international migration: New Zealand, Australia and Canada compared. International Migration Review, 29(3), 765–793. https://doi.org/10.1177/019 791839502900308 Parr, N., & Guest, R. (2019). Migrant age profiles and long-run living standards in Australia. Australian Economic Review, 53(2), 183–197. https://doi.org/10.1111/1467-8462.12356. Rees, P., Wohland, P., & Norman, P. (2016). The United Kingdom’s multi-ethnic future: How fast is it arriving? In J. Lombard, E. Stern, & G. Clarke (Eds.), Applied spatial modelling and planning. Routledge. Rees, P. H., Wohland, P., Norman, P., Lomax, N., & Clark, S. D. (2017). Population projections by ethnicity: challenges and solutions for the United Kingdom. In S. D. (Ed.), The frontiers of applied demography (pp. 383–408). Springer. Semyonov, M., Raijman, R., & Gorodzeisky, A. (2006). The rise of anti-foreigner sentiment in European societies, 1988–2000. American Sociological Review, 71(3), 426–449. https://doi.org/ 10.1177/000312240607100304 Statistics New Zealand. (2017). National ethnic population projections: 2013(base)– 2038 (update). https://www.stats.govt.nz/information-releases/national-ethnic-population-projec tions-2013base2038-update Vertovec, S. (2007). Super-diversity and its implications. Ethnic and Racial Studies, 30(6), 1024– 1054. https://doi.org/10.1080/01419870701599465 Wahlqvist, M. L. (2002). Asian migration to Australia: Food and health consequences. Asia Pacific Journal of Clinical Nutrition, 11(s3), S562–S568. https://doi.org/10.1046/j.1440-6047.11.supp3. 13.x Walsh, J. (2008). Navigating globalization: Immigration policy in Canada and Australia, 1945– 20071. Sociological Forum, 23(4), 786–813. https://doi.org/10.1111/j.1573-7861.2008.00094.x Wilson, T. (2007). The forecast accuracy of Australian Bureau of Statistics national population projections. Journal of Population Research, 24(1), 91–117. https://doi.org/10.1007/BF03031880

Chapter 6

Birthplace Population Profiles

Abstract This section presents summary profiles of the Australian population by country of birth according to the Pre-COVID Trends scenario. There are three sections. The first section presents profiles for the Australian population as a whole, the Australia-born population and the overseas-born population. The second section presents profiles for 26 birthplaces defined the ABS 2-digit birthplace code; and the third section presents profiles for the 25 individual countries or territories of birth with the largest populations in Australian in 2016 (except for those already included earlier: Australia, New Zealand, and Ireland). Keywords Population pyramids · Population profiles · Population projections · Country of birth

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 T. Wilson et al., The Changing Migrant Composition of Australia’s Population, SpringerBriefs in Population Studies, https://doi.org/10.1007/978-3-030-88939-5_6

51

52

6 Birthplace Population Profiles

6.1 Aggregate Population Profiles 6.1.1 The Total Australian Population See Table 6.1 and Fig. 6.1. Table 6.1 Estimates and projections of the Australian population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

24,191

26,898

30,360

33,806

37,265

40,808

Population aged 65+ (’000)

3672

4881

6066

6985

8073

9174

% aged 0–14

18.9

17.8

16.7

16.7

16.6

16.2

% aged 15–19

65.9

64.0

63.3

62.6

61.7

61.4

% aged 65+

15.2

18.1

20.0

20.7

21.7

22.5

Median age (years)

37.2

39.1

40.2

40.6

41.4

41.9

Fig. 6.1 The age-sex structure of the Australian population, 2016 and 2041

6.1 Aggregate Population Profiles

53

6.1.2 Australia-Born See Table 6.2 and Fig. 6.2. Table 6.2 Estimates and projections of the Australia-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

17,278

19,031

20,604

22,305

24,099

26,000

Population aged 65+ (’000)

2290

3101

3881

4381

4843

5295

% aged 0–14

24.2

23.3

22.1

22.8

23.2

22.9

% aged 15–19

62.6

60.4

59.0

57.6

56.7

56.8

% aged 65+

13.3

16.3

18.8

19.6

20.1

20.4

Median age (years)

33.5

35.0

36.1

36.2

36.4

36.1

Fig. 6.2 The age-sex structure of the Australia-born population, 2016 and 2041

54

6 Birthplace Population Profiles

6.1.3 Overseas-Born See Table 6.3 and Fig. 6.3. Table 6.3 Estimates and projections of the overseas-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

6912

7867

9757

11,501

13,166

14,808

Population aged 65+ (’000)

1382

1779

2185

2604

3230

3879

% aged 0–14

5.8

4.6

5.2

4.9

4.6

4.4

% aged 15–19

74.2

72.7

72.4

72.4

70.8

69.4

% aged 65+

20.0

22.6

22.4

22.6

24.5

26.2

Median age (years)

44.3

45.8

45.9

46.4

47.6

48.8

Fig. 6.3 The age-sex structure of the overseas-born population, 2016 and 2041

6.2 ABS 2-Digit Category Birthplace Population Profiles

55

6.2 ABS 2-Digit Category Birthplace Population Profiles 6.2.1 New Zealand-Born See Table 6.4 and Fig. 6.4. Table 6.4 Estimates and projections of the New Zealand-born population, 2016–2066 2016

2026

2036

2046

2056

Total population (’000)

568

569

658

739

814

889

Population aged 65+ (’000)

66

109

143

165

181

197

% aged 0–14

9.0

6.9

8.8

8.7

8.5

8.3

% aged 15–19

79.5

74.0

69.4

68.9

69.3

69.5

% aged 65+

11.5

19.1

21.8

22.4

22.3

22.2

Median age (years)

41.8

46.1

45.3

44.4

44.6

44.9

Fig. 6.4 The age-sex structure of the New Zealand-born population, 2016 and 2041

2066

56

6 Birthplace Population Profiles

6.2.2 Melanesia-Born See Table 6.5 and Fig. 6.5. Table 6.5 Estimates and projections of the Melanesia-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

40

46

56

65

72

77

Population aged 65+ (’000)

4

9

17

24

27

28

% aged 0–14

6.5

4.5

5.0

4.7

4.6

4.6

% aged 15–19

84.1

76.3

64.7

58.5

58.3

58.9

% aged 65+

9.5

19.2

30.3

36.8

37.1

36.5

Median age (years)

44.7

52.1

55.0

56.1

56.3

56.2

Fig. 6.5 The age-sex structure of the Melanesia-born population, 2016 and 2041

6.2 ABS 2-Digit Category Birthplace Population Profiles

57

6.2.3 Micronesia-Born See Table 6.6 and Fig. 6.6. Table 6.6 Estimates and projections of the Micronesia-born population, 2016–2066 2016

2026

2036

2046

2056

Total population (’000)

2

2

2

2

3

2066 3

Population aged 65+ (’000)

0

0

1

1

1

1

% aged 0–14

9.3

4.7

4.9

4.6

4.5

4.4

% aged 15–19

84.1

78.3

68.6

62.1

58.7

57.6

% aged 65+

6.6

17.0

26.5

33.2

36.8

38.0

Median age (years)

39.3

47.4

52.1

55.3

56.7

57.2

Fig. 6.6 The age-sex structure of the Micronesia-born population, 2016 and 2041

58

6 Birthplace Population Profiles

6.2.4 Polynesia-Born See Table 6.7 and Fig. 6.7. Table 6.7 Estimates and projections of the Polynesia-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

126

148

185

217

245

271

Population aged 65+ (’000)

14

30

50

67

80

91

% aged 0–14

3.8

2.7

3.1

2.9

2.8

2.7

% aged 15–19

84.8

76.8

69.9

66.3

64.4

63.6

% aged 65+

11.4

20.5

26.9

30.7

32.8

33.7

Median age (years)

45.2

50.3

52.8

54.1

54.7

55.3

Fig. 6.7 The age-sex structure of the Polynesia-born population, 2016 and 2041

6.2 ABS 2-Digit Category Birthplace Population Profiles

59

6.2.5 UK-Born (Including Channel Islands and Isle of Man) See Table 6.8 and Fig. 6.8. Table 6.8 Estimates and projections of the UK-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

1202

1132

1185

1247

1321

1422

Population aged 65+ (’000)

403

457

506

481

464

482

% aged 0–14

4.7

3.5

5.0

5.2

5.3

5.3

% aged 15–19

61.8

56.2

52.3

56.2

59.5

60.8

% aged 65+

33.5

40.3

42.7

38.6

35.1

33.9

Median age (years)

55.7

60.6

59.8

56.3

54.5

54.4

Fig. 6.8 The age-sex structure of the UK-born population, 2016 and 2041

60

6 Birthplace Population Profiles

6.2.6 Ireland-Born See Table 6.9 and Fig. 6.9. Table 6.9 Estimates and projections of the Ireland-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

88

96

120

141

161

181

Population aged 65+ (’000)

17

19

20

24

31

38

% aged 0–14

6.6

5.2

6.4

6.0

5.6

5.4

% aged 15–19

74.0

75.4

76.8

77.3

74.9

73.4

% aged 65+

19.4

19.4

16.8

16.7

19.4

21.2

Median age (years)

40.3

42.8

41.7

42.3

43.7

45.0

Fig. 6.9 The age-sex structure of the Ireland-born population, 2016 and 2041

6.2 ABS 2-Digit Category Birthplace Population Profiles

61

6.2.7 Western Europe-Born See Table 6.10 and Fig. 6.10. Table 6.10 Estimates and projections of the Western Europe-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

272

233

224

221

233

253

Population aged 65+ (’000)

125

108

84

64

61

66

% aged 0–14

3.0

2.7

3.8

4.3

4.4

4.3

% aged 15–19

51.0

50.9

58.5

66.5

69.3

69.6

% aged 65+

46.0

46.4

37.6

29.2

26.3

26.1

Median age (years)

62.7

62.1

54.2

48.6

47.8

48.1

Fig. 6.10 The age-sex structure of the Western Europe-born population, 2016 and 2041

62

6 Birthplace Population Profiles

6.2.8 Northern Europe-Born See Table 6.11 and Fig. 6.11. Table 6.11 Estimates and projections of the Northern Europe-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

36

34

37

40

43

46

Population aged 65+ (’000)

10

10

11

10

10

11

% aged 0–14

5.6

5.1

6.6

6.8

6.8

6.7

% aged 15–19

67.6

64.4

65.0

67.5

68.8

68.9

% aged 65+

26.7

30.5

28.4

25.8

24.5

24.4

Median age (years)

50.0

52.3

47.9

45.9

45.8

46.1

Fig. 6.11 The age-sex structure of the Northern Europe-born population, 2016 and 2041

6.2 ABS 2-Digit Category Birthplace Population Profiles

63

6.2.9 Southern Europe-Born See Table 6.12 and Fig. 6.12. Table 6.12 Estimates and projections of the Southern Europe-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

276

228

204

190

195

216

Population aged 65+ (’000)

165

147

109

74

64

71

% aged 0–14

1.3

1.4

2.4

2.9

3.0

2.9

% aged 15–19

38.9

34.1

44.3

57.9

64.2

64.1

% aged 65+

59.8

64.4

53.2

39.2

32.8

33.0

Median age (years)

68.4

72.8

68.6

55.6

52.5

53.3

Fig. 6.12 The age-sex structure of the Southern Europe-born population, 2016 and 2041

64

6 Birthplace Population Profiles

6.2.10 South Eastern Europe-Born See Table 6.13 and Fig. 6.13. Table 6.13 Estimates and projections of the South Eastern Europe-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

350

294

247

214

198

198

Population aged 65+ (’000)

161

162

137

103

85

77

% aged 0–14

1.2

1.2

2.1

2.6

3.1

3.3

% aged 15–19

52.9

43.7

42.4

49.3

53.7

58.0

% aged 65+

45.9

55.1

55.5

48.1

43.2

38.8

Median age (years)

63.1

67.5

68.5

63.7

60.1

57.1

Fig. 6.13 The age-sex structure of the South Eastern Europe-born population, 2016 and 2041

6.2 ABS 2-Digit Category Birthplace Population Profiles

65

6.2.11 Eastern Europe-Born See Table 6.14 and Fig. 6.14. Table 6.14 Estimates and projections of the Eastern Europe-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

152

148

172

197

225

255

Population aged 65+ (’000)

54

51

49

56

67

80

% aged 0–14

2.4

1.9

2.4

2.3

2.2

2.1

% aged 15–19

62.0

63.6

69.2

69.4

68.0

66.5

% aged 65+

35.6

34.5

28.3

28.3

29.7

31.4

Median age (years)

55.8

52.3

51.5

50.9

51.8

53.3

Fig. 6.14 The age-sex structure of the Eastern Europe-born population, 2016 and 2041

66

6 Birthplace Population Profiles

6.2.12 North Africa-Born See Table 6.15 and Fig. 6.15. Table 6.15 Estimates and projections of the North Africa-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

80

85

98

112

127

142

Population aged 65+ (’000)

18

23

26

31

39

47

% aged 0–14

7.5

4.8

6.0

5.8

5.5

5.3

% aged 15–19

70.1

68.6

67.7

66.8

63.8

61.6

% aged 65+

22.5

26.5

26.3

27.4

30.7

33.1

Median age (years)

43.7

47.0

49.2

50.5

52.1

53.1

Fig. 6.15 The age-sex structure of the North Africa-born population, 2016 and 2041

6.2 ABS 2-Digit Category Birthplace Population Profiles

67

6.2.13 Middle East-Born See Table 6.16 and Fig. 6.16. Table 6.16 Estimates and projections of the Middle East-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

349

440

574

697

811

918

Population aged 65+ (’000)

44

75

117

156

202

245

% aged 0–14

8.3

7.0

7.5

6.8

6.3

6.0

% aged 15–19

79.0

75.9

72.2

70.8

68.7

67.3

% aged 65+

12.7

17.1

20.3

22.4

25.0

26.7

Median age (years)

41.0

44.2

45.4

46.4

47.8

49.1

Fig. 6.16 The age-sex structure of the Middle East-born population, 2016 and 2041

68

6 Birthplace Population Profiles

6.2.14 Mainland South East Asia-Born See Table 6.17 and Fig. 6.17. Table 6.17 Estimates and projections of the Mainland South East Asia-born population, 2016– 2066 2016

2026

2036

2046

2056

2066

Total population (’000)

395

476

611

731

833

930

Population aged 65+ (’000)

38

87

144

198

236

270

% aged 0–14

4.3

3.4

3.7

3.4

3.2

3.1

% aged 15–19

86.0

78.3

72.8

69.4

68.5

67.8

% aged 65+

9.7

18.4

23.5

27.1

28.3

29.0

Median age (years)

42.5

47.1

48.1

48.8

49.6

50.6

Fig. 6.17 The age-sex structure of the Mainland South East Asia-born population, 2016 and 2041

6.2 ABS 2-Digit Category Birthplace Population Profiles

69

6.2.15 Maritime South East Asia-Born See Table 6.18 and Fig. 6.18. Table 6.18 Estimates and projections of the Maritime South East Asia-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

556

672

869

1045

1206

1359

Population aged 65+ (’000)

56

110

160

217

277

339

% aged 0–14

7.4

5.7

6.2

5.7

5.3

5.1

% aged 15–19

82.4

77.9

75.4

73.6

71.7

70.0

% aged 65+

10.1

16.3

18.5

20.8

23.0

25.0

Median age (years)

39.2

43.4

44.2

45.3

46.7

47.9

Fig. 6.18 The age-sex structure of the Maritime South East Asia-born population, 2016 and 2041

70

6 Birthplace Population Profiles

6.2.16 Chinese Asia-Born See Table 6.19 and Fig. 6.19. Table 6.19 Estimates and projections of the Chinese Asia-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

715

909

1,281

1,591

1,863

2,112

Population aged 65+ (’000)

65

130

205

282

393

491

% aged 0–14

4.0

3.5

3.6

3.2

3.0

2.8

% aged 15–19

86.9

82.2

80.4

79.0

75.9

73.9

% aged 65+

9.2

14.3

16.0

17.7

21.1

23.3

Median age (years)

33.9

39.1

40.6

42.2

44.2

45.9

Fig. 6.19 The age-sex structure of the Chinese Asia-born population, 2016 and 2041

6.2 ABS 2-Digit Category Birthplace Population Profiles

71

6.2.17 Japan and Koreas-Born See Table 6.20 and Fig. 6.20. Table 6.20 Estimates and projections of the Japan and Koreas-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

161

180

244

294

336

374

Population aged 65+ (’000)

9

16

28

43

58

72

% aged 0–14

7.4

5.2

5.7

5.2

4.9

4.7

% aged 15–19

87.0

85.7

82.9

80.1

77.7

75.9

% aged 65+

5.7

9.1

11.4

14.7

17.4

19.4

Median age (years)

35.4

40.6

40.3

41.8

43.2

44.1

Fig. 6.20 The age-sex structure of the Japan and Koreas-born population, 2016 and 2041

72

6 Birthplace Population Profiles

6.2.18 Southern Asia-Born See Table 6.21 and Fig. 6.21. Table 6.21 Estimates and projections of the Southern Asia-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

796

1,258

1,774

2,265

2,726

3,156

Population aged 65+ (’000)

50

92

151

276

501

695

% aged 0–14

8.3

6.4

5.7

4.9

4.4

4.1

% aged 15–19

85.3

86.3

85.8

82.9

77.2

73.9

% aged 65+

6.3

7.3

8.5

12.2

18.4

22.0

Median age (years)

33.5

37.9

40.4

42.5

44.8

46.7

Fig. 6.21 The age-sex structure of the Southern Asia-born population, 2016 and 2041

6.2 ABS 2-Digit Category Birthplace Population Profiles

73

6.2.19 Central Asia-Born See Table 6.22 and Fig. 6.22. Table 6.22 Estimates and projections of the Central Asia-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

61

90

142

194

247

298

Population aged 65+ (’000)

3

7

15

30

52

80

% aged 0–14

6.4

4.6

4.6

3.7

3.2

2.8

% aged 15–19

89.5

88.2

85.0

81.1

75.7

70.4

% aged 65+

4.1

7.2

10.4

15.2

21.2

26.8

Median age (years)

32.3

38.1

41.4

44.5

47.4

50.2

Fig. 6.22 The age-sex structure of the Central Asia-born population, 2016 and 2041

74

6 Birthplace Population Profiles

6.2.20 North America-Born See Table 6.23 and Fig. 6.23. Table 6.23 Estimates and projections of the North America-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

160

169

215

250

279

305

Population aged 65+ (’000)

19

28

37

46

55

63

% aged 0–14

11.9

9.6

10.9

10.3

10.0

9.8

% aged 15–19

76.3

74.0

71.7

71.1

70.2

69.5

% aged 65+

11.8

16.5

17.4

18.5

19.7

20.7

Median age (years)

38.8

42.4

41.5

42.3

43.2

43.9

Fig. 6.23 The age-sex structure of the North America-born population, 2016 and 2041

6.2 ABS 2-Digit Category Birthplace Population Profiles

75

6.2.21 South America-Born See Table 6.24 and Fig. 6.24. Table 6.24 Estimates and projections of the South America-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

137

187

252

312

370

426

Population aged 65+ (’000)

20

31

44

63

93

121

% aged 0–14

3.1

2.3

2.2

2.0

1.8

1.7

% aged 15–19

82.4

81.3

80.4

77.9

73.1

69.9

% aged 65+

14.5

16.5

17.4

20.1

25.1

28.4

Median age (years)

39.6

42.8

44.9

46.7

49.0

50.9

Fig. 6.24 The age-sex structure of the South America-born population, 2016 and 2041

76

6 Birthplace Population Profiles

6.2.22 Central America-Born See Table 6.25 and Fig. 6.25. Table 6.25 Estimates and projections of the Central America-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

20

24

32

40

47

53

Population aged 65+ (’000)

2

5

7

11

15

18

% aged 0–14

3.3

2.2

2.4

2.1

2.0

1.8

% aged 15–19

86.2

79.0

75.7

70.0

65.6

63.9

% aged 65+

10.5

18.8

21.9

27.9

32.5

34.3

Median age (years)

40.5

46.8

50.4

52.2

53.6

55.2

Fig. 6.25 The age-sex structure of the Central America-born population, 2016 and 2041

6.2 ABS 2-Digit Category Birthplace Population Profiles

77

6.2.23 Caribbean-Born See Table 6.26 and Fig. 6.26. Table 6.26 Estimates and projections of the Caribbean-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

6

7

9

11

12

14

Population aged 65+ (’000)

1

2

3

3

4

5

% aged 0–14

5.3

3.8

4.4

4.1

3.8

3.6

% aged 15–19

74.0

68.6

66.9

66.5

65.2

63.7

% aged 65+

20.8

27.6

28.6

29.4

31.0

32.7

Median age (years)

49.2

52.4

52.0

52.2

53.1

54.5

Fig. 6.26 The age-sex structure of the Caribbean-born population, 2016 and 2041

78

6 Birthplace Population Profiles

6.2.24 Central and West Africa-Born See Table 6.27 and Fig. 6.27. Table 6.27 Estimates and projections of the Central and West Africa-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

34

49

72

94

116

136

Population aged 65+ (’000)

1

3

8

15

26

37

% aged 0–14

10.2

6.3

6.1

5.2

4.5

4.1

% aged 15–19

87.6

87.1

82.9

78.6

72.9

68.4

% aged 65+

2.2

6.6

10.9

16.2

22.6

27.5

Median age (years)

32.9

39.3

42.6

45.7

48.5

50.6

Fig. 6.27 The age-sex structure of the Central and West Africa-born population, 2016 and 2041

6.2 ABS 2-Digit Category Birthplace Population Profiles

79

6.2.25 Southern and East Africa-Born See Table 6.28 and Fig. 6.28. Table 6.28 Estimates and projections of the Southern and East Africa-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

331

390

494

593

685

771

Population aged 65+ (’000)

37

70

115

162

207

251

% aged 0–14

7.8

4.5

5.2

4.7

4.4

4.2

% aged 15–19

81.0

77.6

71.5

67.9

65.4

63.2

% aged 65+

11.1

17.9

23.4

27.4

30.2

32.5

Median age (years)

41.5

46.7

49.0

50.8

52.5

53.6

Fig. 6.28 The age-sex structure of the Southern and East Africa-born population, 2016 and 2041

80

6 Birthplace Population Profiles

6.3 Individual Countries and Territories of Birth 6.3.1 England-Born See Table 6.29 and Fig. 6.29. Table 6.29 Estimates and projections of the England-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

1002

950

1005

1065

1132

1220

Population aged 65+ (’000)

330

379

429

414

402

419

% aged 0–14

4.9

3.6

5.2

5.4

5.5

5.5

% aged 15–19

62.1

56.5

52.1

55.7

59.0

60.2

% aged 65+

33.0

39.8

42.7

38.9

35.5

34.4

Median age (years)

55.4

60.5

59.9

56.4

54.7

54.6

Fig. 6.29 The age-sex structure of the England-born population, 2016 and 2041

6.3 Individual Countries and Territories of Birth

81

6.3.2 China-Born (Excluding SARs and Taiwan) See Table 6.30 and Fig. 6.30. Table 6.30 Estimates and projections of the China-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

558

726

1036

1298

1528

1737

Population aged 65+ (’000)

52

97

160

223

316

399

% aged 0–14

3.8

3.3

3.4

3.0

2.7

2.6

% aged 15–19

86.9

83.4

81.2

79.8

76.6

74.4

% aged 65+

9.3

13.3

15.4

17.2

20.7

23.0

Median age (years)

33.6

38.6

40.4

42.0

44.2

46.0

Fig. 6.30 The age-sex structure of the China-born population, 2016 and 2041

82

6 Birthplace Population Profiles

6.3.3 India-Born See Table 6.31 and Fig. 6.31. Table 6.31 Estimates and projections of the India-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

489

764

1068

1357

1630

1885

Population aged 65+ (’000)

31

54

88

169

316

433

% aged 0–14

8.4

6.9

5.9

5.2

4.6

4.3

% aged 15–19

85.3

86.1

85.8

82.4

76.0

72.7

% aged 65+

6.3

7.0

8.3

12.5

19.4

23.0

Median age (years)

33.5

38.3

40.8

42.9

45.2

47.1

Fig. 6.31 The age-sex structure of the India-born population, 2016 and 2041

6.3 Individual Countries and Territories of Birth

83

6.3.4 Philippines-Born See Table 6.32 and Fig. 6.32. Table 6.32 Estimates and projections of the Philippines-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

253

340

463

578

686

787

Population aged 65+ (’000)

19

43

71

106

146

188

% aged 0–14

8.6

6.1

6.4

5.6

5.1

4.8

% aged 15–19

83.8

81.1

78.2

76.1

73.6

71.4

% aged 65+

7.6

12.8

15.4

18.3

21.3

23.8

Median age (years)

39.5

42.8

44.1

45.6

47.3

48.7

Fig. 6.32 The age-sex structure of the Philippines-born population, 2016 and 2041

84

6 Birthplace Population Profiles

6.3.5 Vietnam-Born See Table 6.33 and Fig. 6.33. Table 6.33 Estimates and projections of the Vietnam-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

243

290

368

436

495

550

Population aged 65+ (’000)

26

63

105

143

163

182

% aged 0–14

2.8

2.4

2.6

2.5

2.3

2.3

% aged 15–19

86.4

75.8

68.9

64.8

64.7

64.7

% aged 65+

10.8

21.9

28.5

32.7

33.0

33.0

Median age (years)

45.2

50.7

52.4

52.9

53.0

53.8

Fig. 6.33 The age-sex structure of the Vietnam-born population, 2016 and 2041

6.3 Individual Countries and Territories of Birth

85

6.3.6 Italy-Born See Table 6.34 and Fig. 6.34. Table 6.34 Estimates and projections of the Italy-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

196

156

136

125

128

143

Population aged 65+ (’000)

127

106

75

50

43

48

% aged 0–14

0.9

1.1

1.9

2.3

2.4

2.3

% aged 15–19

34.4

31.0

42.5

57.8

64.4

64.1

% aged 65+

64.7

67.9

55.6

39.9

33.2

33.6

Median age (years)

70.0

74.6

70.9

55.8

52.4

53.5

Fig. 6.34 The age-sex structure of the Italy-born population, 2016 and 2041

86

6 Birthplace Population Profiles

6.3.7 South Africa-Born See Table 6.35 and Fig. 6.35. Table 6.35 Estimates and projections of the South Africa-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

181

206

248

289

326

360

Population aged 65+ (’000)

21

38

63

87

106

124

% aged 0–14

7.7

4.5

5.3

5.0

4.8

4.6

% aged 15–19

80.4

76.9

69.3

64.9

62.7

60.8

% aged 65+

11.9

18.6

25.4

30.1

32.5

34.6

Median age (years)

42.4

48.1

50.6

52.6

54.2

54.9

Fig. 6.35 The age-sex structure of the South Africa-born population, 2016 and 2041

6.3 Individual Countries and Territories of Birth

87

6.3.8 Malaysia-Born See Table 6.36 and Fig. 6.36. Table 6.36 Estimates and projections of the Malaysia-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

153

174

216

251

282

312

Population aged 65+ (’000)

21

39

53

66

79

92

% aged 0–14

5.4

4.4

4.8

4.6

4.4

4.3

% aged 15–19

81.2

73.1

70.6

69.2

67.7

66.3

% aged 65+

13.4

22.4

24.5

26.2

27.9

29.4

Median age (years)

40.0

45.2

46.2

46.9

47.8

48.8

Fig. 6.36 The age-sex structure of the Malaysia-born population, 2016 and 2041

88

6 Birthplace Population Profiles

6.3.9 Scotland-Born See Table 6.37 and Fig. 6.37. Table 6.37 Estimates and projections of the Scotland-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

138

125

123

123

128

137

Population aged 65+ (’000)

51

56

55

48

44

45

% aged 0–14

3.5

2.6

3.9

4.3

4.4

4.4

% aged 15–19

59.3

52.5

51.5

56.8

61.3

63.0

% aged 65+

37.2

45.0

44.6

39.0

34.3

32.6

Median age (years)

58.4

62.7

61.3

56.8

54.3

54.0

Fig. 6.37 The age-sex structure of the Scotland-born population, 2016 and 2041

6.3 Individual Countries and Territories of Birth

89

6.3.10 Sri Lanka-Born See Table 6.38 and Fig. 6.38. Table 6.38 Estimates and projections of the Sri Lanka-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

124

160

214

267

317

365

Population aged 65+ (’000)

16

28

41

60

84

106

% aged 0–14

6.8

4.4

4.7

4.2

3.8

3.5

% aged 15–19

80.0

78.3

76.0

73.3

69.8

67.5

% aged 65+

13.2

17.3

19.2

22.5

26.4

29.0

Median age (years)

40.9

44.6

46.7

48.1

50.0

51.7

Fig. 6.38 The age-sex structure of the Sri Lanka-born population, 2016 and 2041

90

6 Birthplace Population Profiles

6.3.11 Germany-Born See Table 6.39 and Fig. 6.39. Table 6.39 Estimates and projections of the Germany-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

117

97

89

85

89

96

Population aged 65+ (’000)

58

48

38

28

27

28

% aged 0–14

2.0

1.8

2.7

3.1

3.2

3.2

% aged 15–19

48.1

48.3

55.3

63.7

66.9

67.5

% aged 65+

49.9

49.9

42.0

33.2

29.9

29.3

Median age (years)

64.9

64.9

58.4

52.2

50.8

50.9

Fig. 6.39 The age-sex structure of the Germany-born population, 2016 and 2041

6.3 Individual Countries and Territories of Birth

91

6.3.12 Greece-Born See Table 6.40 and Fig. 6.40. Table 6.40 Estimates and projections of the Greece-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

113

91

69

55

51

54

Population aged 65+ (’000)

76

67

45

27

19

19

% aged 0–14

1.6

1.7

3.3

4.6

5.3

5.4

% aged 15–19

31.6

24.8

31.4

47.0

57.7

60.5

% aged 65+

66.8

73.5

65.3

48.4

37.0

34.1

Median age (years)

71.0

76.9

76.4

63.4

55.1

54.0

Fig. 6.40 The age-sex structure of the Greece-born population, 2016 and 2041

92

6 Birthplace Population Profiles

6.3.13 South Korea-Born See Table 6.41 and Fig. 6.41. Table 6.41 Estimates and projections of the South Korea-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

112

129

179

220

255

287

Population aged 65+ (’000)

6

12

20

32

46

58

% aged 0–14

6.6

4.4

4.8

4.3

4.0

3.8

% aged 15–19

88.2

86.6

84.0

81.0

78.1

76.0

% aged 65+

5.2

8.9

11.2

14.7

17.9

20.2

Median age (years)

34.4

40.1

40.3

42.1

43.8

45.0

Fig. 6.41 The age-sex structure of the South Korea-born population, 2016 and 2041

6.3 Individual Countries and Territories of Birth

93

6.3.14 USA-Born See Table 6.42 and Fig. 6.42. Table 6.42 Estimates and projections of the USA-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

106

109

139

160

177

192

Population aged 65+ (’000)

13

18

23

27

32

36

% aged 0–14

14.1

11.6

13.2

12.6

12.3

12.2

% aged 15–19

73.5

72.1

70.3

70.4

69.9

69.3

% aged 65+

12.4

16.3

16.5

16.9

17.8

18.6

Median age (years)

38.0

40.8

39.6

40.2

40.9

41.4

Fig. 6.42 The age-sex structure of the USA-born population, 2016 and 2041

94

6 Birthplace Population Profiles

6.3.15 Hong Kong-Born See Table 6.43 and Fig. 6.43. Table 6.43 Estimates and projections of the Hong Kong-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

98

113

146

173

196

221

Population aged 65+ (’000)

10

26

37

46

57

67

% aged 0–14

4.6

4.5

4.9

4.6

4.4

4.2

% aged 15–19

84.8

72.3

69.9

68.6

66.6

65.4

% aged 65+

10.7

23.2

25.2

26.8

29.0

30.5

Median age (years)

39.4

45.0

47.1

48.2

48.9

50.4

Fig. 6.43 The age-sex structure of the Hong Kong-born population, 2016 and 2041

6.3 Individual Countries and Territories of Birth

95

6.3.16 Lebanon-Born See Table 6.44 and Fig. 6.44. Table 6.44 Estimates and projections of the Lebanon-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

94

96

103

108

112

117

Population aged 65+ (’000)

20

31

42

45

44

42

% aged 0–14

2.0

1.9

2.5

2.7

2.8

2.9

% aged 15–19

76.8

65.7

56.5

55.5

57.5

60.9

% aged 65+

21.2

32.4

41.0

41.8

39.8

36.3

Median age (years)

51.3

57.4

60.0

59.9

57.4

55.8

Fig. 6.44 The age-sex structure of the Lebanon-born population, 2016 and 2041

96

6 Birthplace Population Profiles

6.3.17 Indonesia-Born See Table 6.45 and Fig. 6.45. Table 6.45 Estimates and projections of the Indonesia-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

79

86

105

120

134

148

Population aged 65+ (’000)

8

12

16

22

27

32

% aged 0–14

5.6

4.8

5.3

5.1

4.9

4.8

% aged 15–19

84.1

81.6

79.9

76.8

74.7

73.4

% aged 65+

10.3

13.7

14.9

18.1

20.5

21.8

Median age (years)

36.4

41.5

41.4

41.9

42.8

43.5

Fig. 6.45 The age-sex structure of the Indonesia-born population, 2016 and 2041

6.3 Individual Countries and Territories of Birth

97

6.3.18 Netherlands-Born See Table 6.46 and Fig. 6.46. Table 6.46 Estimates and projections of the Netherlands-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

79

61

48

39

37

39

Population aged 65+ (’000)

46

39

27

16

12

12

% aged 0–14

2.2

1.8

3.0

4.2

4.7

4.8

% aged 15–19

39.6

33.6

41.0

54.0

62.3

64.5

% aged 65+

58.1

64.6

55.9

41.9

33.0

30.7

Median age (years)

67.4

73.5

70.0

58.2

52.8

52.1

Fig. 6.46 The age-sex structure of the Netherlands-born population, 2016 and 2041

98

6 Birthplace Population Profiles

6.3.19 Iraq-Born See Table 6.47 and Fig. 6.47. Table 6.47 Estimates and projections of the Iraq-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

75

110

151

191

229

264

Population aged 65+ (’000)

6

14

28

44

62

79

% aged 0–14

8.5

6.5

6.2

5.4

4.8

4.5

% aged 15–19

83.2

80.5

75.3

71.7

67.9

65.4

% aged 65+

8.3

13.0

18.5

22.9

27.2

30.1

Median age (years)

38.1

42.2

45.6

48.2

50.2

52.0

Fig. 6.47 The age-sex structure of the Iraq-born population, 2016 and 2041

6.3 Individual Countries and Territories of Birth

99

6.3.20 Fiji-Born See Table 6.48 and Fig. 6.48. Table 6.48 Estimates and projections of the Fiji-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

74

84

102

118

132

145

Population aged 65+ (’000)

9

19

30

42

50

56

% aged 0–14

3.1

2.0

2.4

2.3

2.2

2.1

% aged 15–19

84.6

75.6

67.9

62.4

59.8

59.4

% aged 65+

12.4

22.4

29.7

35.3

38.1

38.5

Median age (years)

44.9

51.0

54.8

57.2

57.7

58.0

Fig. 6.48 The age-sex structure of the Fiji-born population, 2016 and 2041

100

6 Birthplace Population Profiles

6.3.21 Thailand-Born See Table 6.49 and Fig. 6.49. Table 6.49 Estimates and projections of the Thailand-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

71

88

120

146

168

187

Population aged 65+ (’000)

2

5

10

18

26

33

% aged 0–14

10.0

7.3

7.6

7.0

6.6

6.3

% aged 15–19

87.3

86.8

83.8

80.6

77.8

75.8

% aged 65+

2.6

5.9

8.5

12.4

15.6

17.8

Median age (years)

33.8

38.5

38.9

40.3

41.6

42.4

Fig. 6.49 The age-sex structure of the Thailand-born population, 2016 and 2041

6.3 Individual Countries and Territories of Birth

101

6.3.22 Pakistan-Born See Table 6.50 and Fig. 6.50. Acknowledgements This work was funded by the Australian Research Council’s (ARC) Centre of Excellence in Population Ageing Research (CE1101029). We are grateful to Samir K C of the Wittgenstein Centre for supplying projections of national populations by education level.

Table 6.50 Estimates and projections of the Pakistan-born population, 2016–2066 2016

2026

2036

2046

2056

2066

Total population (’000)

70

115

183

247

306

361

Population aged 65+ (’000)

2

4

9

18

36

56

% aged 0–14

13.8

10.2

9.4

7.8

6.8

6.2

% aged 15–19

83.7

85.9

85.7

85.0

81.4

78.3

% aged 65+

2.5

3.9

4.8

7.2

11.8

15.5

Median age (years)

30.6

34.7

35.8

38.3

40.7

42.7

Fig. 6.50 The age-sex structure of the Pakistan-born population, 2016 and 2041

102

6 Birthplace Population Profiles

Ethics Approval Statement Ethics approval for this project was provided by the Melbourne School of Population and Global Health (MSPGH) Human Ethics Advisory Group (Ethics ID: 2,056,200.1). Declarations of Interest Disclosure We do not have a conflict of interest.