Ethnic and social stratification in peninsular Malaysia (The Arnold and Caroline Rose monograph series in sociology) 9780912764122, 0912764120

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Ethnic and Social Stratification

In Peninsular Malaysia

by

Charles Hirschman Department of Sociology Duke University

The Arnold and Caroline Rose Monograph Series of the American Sociological Association

ASA ROSE MONOGRAPH SERIES Other publications in this series Deviance, Selves and Others, Michael Schwartz and Sheldon Stryker (1971) Socioeconomic Background and Educational Performance, Robert Mason Hauser (1972) Black and White Self-Esteem: The Urban School Child, Morris Rosenberg and Roberta G. Simmons (1972) Looking Ahead: Self-conceptions, Race and Family as Determinants of Adolescent Orientation to Achievement, Cad Gordon (1972) Black Students in Protest: A Study of the Origins of the Black Student Movement, Anthony M. Orum (1972) Attitudes and Facilitation in the Attainment of Status, Ruth M. Gasson, Archibald O. Haller, William H. Sewell (1972) Patterns of Contact with Relatives, Sheila R. Klatzky (1972) Interorganizational Activation in Urban Communities: Deductions from the Concept of System, Herman Turk (1973) The Study of Political Commitment, John DeLameter (1973) Ambition and Attainment, A Study of Four Samples of American Boys, Alan C. Kerckhoff (1974) The Greek Peasant, Scott G. McNall (1974) Patterns of Scientific Research: A Comparative Analysis of Research in Three

Scientific Fields, Lowell L. Hargens (1974) |

Available from the American Sociological Association, 1722 N Street, N.W., Washington, D.C. 20036. Pre-paid costs: Members, $2.75 per title Non-members, $5.00 per title Complete Set, 20% discount

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THE ARNOLD AND CAROLINE ROSE MONOGRAPH SERIES IN SOCIOLOGY A gift by Amold and Caroline Rose to the American Sociological Association in 1968 provided for the establishment of the Arnold and Caroline Rose Monograph Series in Sociology. The conveyance provided for the publication of manuscripts in any subject matter field of sociology. The donors intended : the series for rather short monographs, contributions that normally are beyond the scope of publication in regular academic journals.

The Series is under the general direction of an editorial board appointed by the Council of the American Sociological Association and responsible to the Publications Committee of the Association. Competition for publication in the Series has been limited by the Association to Members and Student Members. Arnold Rose was my teacher and my friend. I was fully aware, before his untimely death, of his sense that sociology needed a publication outlet of the sort provided by this Series; and I was dimly aware of his hope that his and Caroline’s gift would meet that need. I am grateful to the American Sociological Association for providing me the opportunity to help fulfill Arnold’s hope. Sheldon Stryker Editor

Copyright American Sociological Association 1975 Library of Congress Number 75-135-44 International Standard Book Number 0-912764-12-0

, American Sociological Association 1722 N St., N.W. Washington, D.C. 20036 ili

TO MY MOTHER AND FATHER

1V

PREFACE This study is an attempt to describe and explain the socioeconomic inequalities among the ethnic communities of Peninsular Malaysia. While there are significant socioeconomic and cultural differences between ethnic communities, there are also many similarities. All the peoples of Malaysia, no matter what their ethnic identity, share the basic needs and desires of mankind. The delights of children, family, friends, and good food find expression

in every community. Problems of poverty and economic hardship are the overriding concern of the majority of Malaysians of all communities. It is to be hoped that from a clearer understanding of both the differences and similarities, the problems of inequality both within and between ethnic communities may be solved. A note on terminology is necessary. Peninsular Malaysia is that part of the nation of Malaysia which is on the mainland of Southeast Asia. It was formerly

known as West Malaysia and prior to the formation of Malaysia in 1963, it was known as Malaya. In order to be consistent, I will refer to the area as Peninsular Malaysia, even for earlier periods when it was known as British Malaya or the independent Federation of Malaya. The term, Malaysian, refers to all residents of Malaysia, be their ethnic community Malay, Chinese, or Indian.

This monograph is a revision of my Ph.D. dissertation which I completed at the University of Wisconsin in 1972. The advice and criticism of a number of my teachers and colleagues during my years of study at the Department of Sociology and Center for Demography and Ecology at the University of Wisconsin have contributed immeasurably toward my education and this research. During the analysis of the data and writing of the original dissertation, I received valuable advice from Professors Henry Finney, Robert V

Hauser, Judah Matras, James Scott, James Sweet, and Hal Winsborough. At Wisconsin, I was supported by a traineeship from the Center for Demography and Ecology and a fellowship from the Population Council. My trip to Malaysia and work there were made possible by a research grant from the Center for Development of the University of Wisconsin. I am indebted to a number of people who assisted me in carrying out this research, particularly in obtaining access to the data from the 1966-67 West Malaysian Family Survey. The use of these data, which were collected by the Malaysian Department of Statistics under the auspices of the National Family Planning Board of Malaysia, was kindly given to me by Dr. Arriffin bin Marzuki, former Director of the National Family Planning Board, and Professor James A. Palmore, under whose supervision the survey was conducted, kindly provided the data. Several other Americans and Malaysians were very

helpful during my period of work in Malaysia, particularly Mr. Ramesh Chander, Chief Statistician of Malaysia, Dr. Agoes Salim, Professors Milton Barnett, and J. Yuzuru Takeshita.

I have rethought, reanalyzed, and revised much of this monograph durino the year and a half that I have been in the Department of Sociology at Duke University. I have benefited from the advice and comments on this research from my colleagues, Richard Campbell, James House, Alan Kerckhoff, and William Mason. I am also indebted to Sharon Poss for her advice and assistance

with the computer. I have had the help of two very able research assistants, Sharifah Sabariah binte Syed Alwi in Malaysia and Lanier Rand at Duke. The final typing of the manuscript has been expertly done by Madge E. Lee and Jamilah binte Mohd Ali. My wife, Jo, has been a constant source of advice and encouragement at all stages of the research. Charles Hirschman Kuala Lumpur, Malaysia December, 1974.

V1

TABLE OF CONTENTS Page

Preface ...... 0... ccc eee eee teen eee e eee ee eee W

List of Tables ........ 00.0... e eee eee Wil List of Figures ........... 0... eee eee ee eee eee ee eee XK Chapter

1. Social Stratification and Ethnic Relations ................... 1 2. Peninsular Malaysian Society: Data and Description .......... 6

3. The Process of Structural Assimilation .....................15 4. Intergenerational Occupational Mobility: Ethnic Differences ....37 5. The Socioeconomic Life-Cycle Model and

Ethnic Stratification .... 0.0... 0. ee ee AD

6. The Socioeconomic Life Cycle: The Process of

Occupational and Income Attainment ......................62 7. Discussion and Conclusions .............00 ccc eee eee ee ee ell Appendix A Problems of Comparability in Measuring

Occupational Trends .................0 2 eee ee 84

Appendix B 1957 Malaysian Occupation Classification

By One- and Two- Digit Level..................89

Appendix C Comparable Categories From 1931, 1947, and 1957 Censuses, Based Upon the Ten Major

Occupational Categories of the 1957 Census...... .92

Appendix D Occupational Composition of Employed Males by Ethnic Community: Peninsular

Malaysia, 1931, 1947, 1957, 1967 ..............94 Appendix E Indexes of Dissimilarity Between Occupational -Distributions (Without Agriculture) of Employed Males, by Ethnic Community:

Peninsular Malaysia, 1931, 1947, 1957, 1967 .....97

Appendix F Six Sequential Models of the Effects of Social Background on Occupational Attainment of Married Men, by Occupation: Peninsular

Malaysia, 1966-1967 ........... eee eee ee ee 98 Vil

Appendix G Comparison of Variance Explained in Additive Models of Educational, Occupational and Income Attainment of Married Men, and Models with Additional Ethnic Interaction

Terms: Peninsular Malaysia, 1966-1967 .........103

References ......... 0.0.0... ccc cee cc eee cece eee teen eee ee LOT

Table Page

LIST OF TABLES

2.1 Ethnic composition of the population: Peninsular Malaysia,

1911, 1921, 1931, 1947, 1957, 1967 ........................ 9

2.2 Percentage of population of Peninsular Malaysia born in Peninsular Malaysia or Singapore, by ethnic community,

1921, 1931, 1947, 1957 .. oe ee eee eee LO

2.3 Sex ratio of Chinese and Indian population: Peninsular

Malaysia, 1911, 1921, 1931, 1947, 1957 .....................12

2.4 Percentage of the total population and of each ethnic community in urban areas: Peninsular Malaysia, 1911,

1921, 1931, 1947, 1957, 1967 ............................64.213

3.1 Mean years of schooling, by ethnic community, sex, and age

group: Peninsular Malaysia, 1957 ....................20244--16 3.2 Ranking of major occupational categories of married men, by mean monthly income and mean years of schooling, by

ethnic community: Peninsular Malaysia, 1966-1967 .............19 3.3. Occupational composition of employed males, by ethnic community: Peninsular Malaysia, 1931, 1947, 1957, 1967 .......22

3.4 Age distribution of the Chinese population, by sex:

Peninsular Malaysia, 1921, 1931, 1947.......................24 3.5. Detailed occupational composition of employed Chinese males in agricultural and fishing occupations: Peninsular

Malaysia, 1931, 1947 2... eee eee be

3.6 Detailed industrial composition of employed males in agricultural and fishing industries, by ethnic community:

Peninsular Malaysia, 1947, 1957, 1967 .....................-.-27 3.7 Detailed occupational composition of employed males in professional and technical occupations, by ethnic community:

Peninsular Malaysia, 1967 1.1.0.0... cece cee ee eee ne DO 3.8 Indexes of dissimilarity between occupational distributions of employed males, by ethnic community: Peninsular Malaysia,

1931, 1947, 1957, 1967 2... ce ee ee eee ee

3.9 Employment status of employed males, by ethnic community:

Peninsular Malaysia, 1967 ............ 00... e ee ee ee ee BO Vill

3.10 Distribution of establishments and paid employees in manufacturing industries, by number of employees:

Peninsular Malaysia, 1968 ......... 0... cece eee eee eee dO 4.1 Occupational composition of married men and their fathers,

by ethnic community: Peninsular Malaysia, 1966-1967 ..........40 4.2 Comparison of the observed occupational distribution of married men and their expected occupational distribution, by

ethnic community: Peninsular Malaysia, 1966-1967 .............43 4.3 Transition percentages, father’s occupation to current occupation of married men: Peninsular Malaysia, 1966-1967 .....45

4.4 Transition percentages, father’s occupation to current occupation of married men, by ethnic community:

Peninsular Malaysia, 1966-1967............ 0.0... AT

5.1 Socioeconomic characteristics of married men, by

ethnic community: Peninsular Malaysia, 1966-1967 .............54 5.2 Effects of social background of married men on the number of years of schooling and the probability of having an English-medium education: Peninsular Malaysia, 1966-1967 ......60 6.1 Seven models of the effects of social background of married men on monthly income: Peninsular Malaysia, 1966-1967 .......64 6.2 Effects of ethnicity of married men on occupational attainment in six sequential and cumulative models of social background variables in eight occupations:

Peninsular Malaysia, 1966-1967 ............ cece eee ee ee eee + 68 6.3. Comparison of variance explained in additive models of educational, occupational and income attainment of married men, and models with additional ethnic X father’s occupation interaction terms: Peninsular Malaysia, 1966-1967 ....73 6.4 Comparison of variance explained in additive models of occupational and income attainment of married men, and models with additional ethnic X years of schooling interaction

terms: Peninsular Malaysia, 1966-1967 .......................75 A.1 Comparison of the occupational composition of employed males, age ten and above, and of employed males, age 15 to 64, by ethnic community: Peninsular Malaysia, 1966-1967... ..86 D.1 Occupational composition of employed males, by ethnic community: Peninsular Malaysia, 1931, 1947, 1957, 1967 .......94 E.1 Indexes of dissimilarity between occupational distributions (without agriculture) of employed males, by ethnic community:

Peninsular Malaysia, 1931, 1947, 1957, 1967 .................97 F.1 Six sequential models of the effects of social background on occupational attainment of married men, by occupation:

Peninsular Malaysia, 1966-1967 ........... 0... cee eee eee IY 1X

G.1 Comparison of variance explained in additive models of educational, occupational and income attainment of married men, and models with additional ethnic X birthplace interaction terms: Peninsular Malaysia, 1966-1967 ....103 G.2 Comparison of variance’explained in additive models of occupational and income attainment of married men and models with additional ethnic X English education interaction

terms: Peninsular Malaysia, 1966-1967 ......................104 G.3 Comparison of the variance explained in additive models of occupational and income attainment of married men and models with additional ethnic X current residence

interaction terms: Peninsular Malaysia, 1966-1967 .............105 G.4 Comparison of variance explained in an additive model of income attainment of married men and models with additional ethnic X sales occupation and ethnic X agricultural occupation interaction terms:

Peninsular Malaysia, 1966-1967...................000000++ 106

Figure Page

LIST OF FIGURES

5.1 The basic model of the socioeconomic life-cycle ...............50 5.2 Socioeconomic life cycle model of the process of

stratification: Peninsular Malaysia ............. 0.0.00 eee eee DO

X

CHAPTER |

SOCIAL STRATIFICATION AND ETHNIC RELATIONS This study draws its intellectual heritage from two of the oldest areas of sociological inquiry, social stratification and race and ethnic relations. From the field of social stratification arises the central concern with the distribution of inequality in the population; the concepts and techniques developed over the past decade have guided much of the empirical analysis. From the field of race and ethnic relations arises the question of the factors accounting for the inequality between groups. The blending of these two perspectives has been a stimulus to some of the most significant work in contemporary sociology.

Theoretical Issues There is no shortage of ideas regarding race and ethnic relations in sociologi-

cal literature. Since the birth of modern sociology with the Chicago school and the writings of Robert Park (1950), the theme of racial and ethnic inequality and associated topics has been dominant in theory and research. The editor of a collection of articles on intergroup relations chosen from the issues of the American Sociological Review, (van den Berghe, 1972), counted 230 relevant pieces published between 1936 and 1969. Although most of the

work on race and ethnic relations has been focused entirely on the United States and has been social-psychologically oriented, a comparative macrosociological tradition of theory and research does exist. Robert Park’s theory of the race relations cycle has been the landmark Statement until quite recently. Park expressed his ideas most succin@ly in an article first published in 1926 (Park, 1950: 150): In the relations of races there 1s a cycle of events which tends everywhere to repeat itself. . . . The race relations cycle which takes the l

form, to state it abstractly, of contacts, competition, accommodation, and eventual assimilation, is apparently progressive and irreversible. Customs regulations, immigration restrictions and racial barriers may slacken the tempo of the movement; may perhaps halt it altogether for a time; but cannot change its direction; cannot, at any rate, reverse it.

In spite of his prolific writings Park never produced a complete and systematic exposition of his theory of race relations. The definitive work on race relations theory in his tradition was written by E. Franklin Frazier, whom Everett C. Hughes has called Park’s most complete student (G. Franklin Edwards, 1968:xvi). Frazier’s Race and Culture Contacts in the Modern World was published in 1957, but its theoretical roots seem to extend back two decades earlier. Frazier extended and elaborated Park’s ideas with a systematic consideration of the variation in racial encounters and relations, and how they are affected by ecological, economic, and political factors. But at the heart of Frazier’s theory is Park’s race relations cycle. Perhaps the process of eventual assimilation is retarded by European imperialism and racist doctrine, but eventually the association of race and culture with superiority and inferiority will disappear (Frazier, 1957: 338).

The criticisms of the theory of the race relations cycle have been amply documented in recent years (Berry, 1965; Lyman, 1968; Barth and Noel, 1972). Basically it is a grand theory which does not lend itself to generating testable hypotheses. Since there are no time limits to the various stages of the cycle, it is impossible to refute the theory. Also it is not exactly clear what

societal forces during the process of social change or modemization will contribute in what degree to the progress of the cycle. Much of the discussion

of the Park-Frazier theory suggests that the processes of urbanization and industrialization will increase interracial and interethnic contact. While these processes may lead to conflict and ethnic-racial stratification in the short run, the eventual process will be assimilation. It is interesting that another student of Park, Herbert Blumer (1965), strongly challenged the idea that industrialization will lead to a reduction of racial and ethnic divisions.

However, the contribution of the Park-Frazier theory cannot be underestimated. They offered a dependent variable—interracial and interethnic inequality—which has been the focus of most recent empirical research. They also emphasized the importance of considering societies as units of analysis, doing cross-cultural research, and taking account of historical forces. In fact, most of the significant theoretical work of the past twenty-five years (Cox, 1948; Lieberson, 1961; Shibutani and Kwan, 1965; van den Berghe, 1967;

Schermerhor, 1970; and Barth and Noel, 1972) draws heavily upon the groundwork done by Park and Frazier. All these more recent theoretical perspectives posit new typologies of racial-ethnic outcomes, or a new emphasis on certain societal factors as the most important determinants in the process. Modern sociological theory in the field of race and ethnic relations is much more sensitive to the question whether assimilation is a very likely outcome in multiracial societies or even a socially desirable goal (see Metzger, 1971

on ideological influences in American race relations theory). A significant development is the recognition of assimilation as a multidimensional concept 2

(Gordon, 1964). For instance, there could be changes in the assimilation process toward increasing cultural homogeneity yet little interethnic interaction in primary groups.

To achieve a true sociological theory explaining the determinants and the patterns of the evolution of multiracial or multiethnic societies will necessitate both historical and comparative research, a task which staggers the imagination. The process of change is sometimes only incremental over generations, presenting a problem which is not readily encompassed by the standard techniques of data collection. Additionally, the interaction of political, economic,

cultural, and familial institutions in the process of change in interracial or interethnic relations almost requires a general theory for the understanding of the interaction of subpopulations within society—a theory which is still far from being formulated. Perhaps the wisest course is to pursue an inductive Strategy, analyzing the more limited questions or hypotheses with data that are available.

The Study of Ethnic Stratification Two questions which may invite systematic investigation of issues relevant to a more general theory are: (1) What was the social process which led to the introduction of socioeconomic differences among racial and ethnic communities soon after encounter? (2) What are the social mechanisms which allow socioeconomic differences to be maintained over time, or alternatively, what are the social changes which led to a reduction or elimination of such differences over time? This first question, regarding the origins of ethnic stratification, has not been a focal issue in the literature, though there have been some attempts to deal with it. Shibutani and Kwan (1965:147) state that ‘‘the group whose culture is best suited for the exploitation of the resources of a given environment tends to become dominant’’. Later (1965:174), they refer more closely to occupational or economic differences in stating ‘“‘the niche that each ethnic group wins in the new web of life depends largely on the competitive advantages provided by its culture and leadership’’. Noel (1968) has attempted to develop a general theory of the origin of ethnic stratification based upon the independent var-

iables, ethnocentrism, competition, and differential power, which he then applies to the emergence of slavery in seventeenth-century America. I will not examine this first question in any great detail, other than to review the origins of the multiethnic society (chapter 2). The second question regarding the process of change in interethnic inequality is more directly amenable to empirical analysis, at least of periods since modern censuses and surveys have been providing adequate empirical data. From such

sources it is possible to analyze the process of change in the distribution of socioeconomic attainment and rewards. While some of the explanation of change or lack of change in such measures of inequality between ethnic groups

may lie outside the scope of census or survey data, a number of important conclusions can be reached.

Structural Assimilation The inequality in the distribution of some valued social status between ethnic 3

groups can be interpreted as a measure of ‘‘structural assimilation’’. Taeuber

and Taeuber (1964:375) characterize ethnic assimilation as the process of dispersion of members of each group throughout the social structure. They use such indicators as educational attainment, occupational distribution, income, and residential segregation as measures of participation. Eisenstadt’s perspective is similar in his study of the assimilation of immigrants to a new country; using his concept of institutional integration and dispersion (1953: 167-168), he examines the ‘‘extent to which immigrants were ‘disseminated’ within the main institutional spheres—family, economic, political, and religious—of the new country’’. Although it might seem at first glance, to be a simple exercise to chart empirically and interpret the trend of ‘‘structural assimilation’ in a multiethnic society, the task can become complicated. First of all, the various indicators may not all point in the same direction. There may be trends towards a more equal distribution of education, while residential segregation is increasing. The interpretation of the trends is particularly hazardous, especially if the causal mechanisms are unclear. Yet some of the most

significant work in the study of race and ethnic relations has been from the perspective of investigating ‘‘structural assimilation’, and with the use of census or national survey data at several points in time (Lieberson, 1963; Taeuber and Taeuber, 1965; Price, 1969; Farley and Hermalin, 1972). Such studies have clearly established the trend of ‘‘social facts’’ of ethnic inequality or segregation. Chapter 3 of this monograph attempts to examine the pattern of

Structural assimilation in Peninsular Malaysia by examining the pattern of occupational differentials among the three major ethnic groups from 1931 to 1967.

The Model of the Socioeconomic Life-Cycle A second question related to structural assimilation is the explanation of ethnic socioeconomic differences by reference to the pattern of intergenerational social mobility. This line of research follows from the development of models of the process of stratification introduced by Blau and Duncan (1967). The basic form of the model of the socioeconomic life-cycle (Duncan, 1967) measures the impact of father’s socioeconomic status on son’s socioeconomic attainment. This relationship can be shown ina standard table of social mobility (Blau and Duncan, 1967:28) or it can be reduced to the correlation coefficient between father’s occupation and son’s occupation. However, the real import

of the model of the socioeconomic life-cycle is the analysis it allows of the process whereby status of origin influences adult socioeconomic attainment. This is made possible by elaborating the model with the introduction of additional social background variables (father’s education, birthplace, mother’s characteristics, etc.), intervening variables (education, social-psychological attributes, etc.), and attainment variables (income, participation, etc.). Most of this work followed from the research of Otis Dudley Duncan and his students, and other sociologists utilizing the basic paradigm (Duncan, Featherman, and Duncan, 1972; Duncan, 1968a; Featherman, 1971a; Featherman, 1971b, Hauser, 1969; Hauser, 1971; Kelley, 1973; Jones, 1971; Sewell and Hauser, 1972). A growing literature has applied this model of the socioeconomic life-cycle 4

tics. .

to the study of ethnic stratification (Duncan and Duncan, 1968; Duncan, 1969; Duncan and Featherman, 1972; and Featherman, 1971c). Basically the model allows one to investigate the net effect of ethnicity as a determinant of ethnic inequality, after controlling for differences in social background characteris-

Ethnic differentials in achievement, which are independent of differentials in social background, can be accounted for by several alternative explanations. The two major competing explanations are the discrimination hypothesis

and the cultural hypothesis (discussed in chapters 5, 6, and 7). Most often, discrimination is thought to occur in the job market, as when, in choosing between two men of equal educational qualifications, an employer bases his decision upon ethnicity, and presumably, chooses a member of his own community.

. The other explanation, one very common in certain sociological circles (Rosen, 1959), is that of differential motivation or different cultural goals. Thus the members of a disadvantaged ethnic group are often said to have a lower propensity to achieve because their culture does not inspire them to be ambitious and calculating. How does one distinguish between these two explanations? Ideally, it would be necessary to have independent measures of the psychological orientation toward achivement in each ethnic group. If the effect of ethnicity upon achievement were completely mediated by this psychological orientation, the cultural explanation would have support. (Analysis

of ethnic stratification in the United States did not support this theory; see Featherman, 1971c). Lacking such information, one must make inferences of the basic explanation from other patterns. However, much of the subsequent analysis shows that the net effects of ethnicity in Malaysia are relatively small as determinants of educational and income attainment, although ethnicity does

appear to be an important factor in entry into several occupations. In these occupations, I argue that discrimination by employers is the most plausible explanation. In sum, I will examine the magnitude and persistence of ethnic occupational

differentials in Peninsular Malaysia and attempt to account for ethnic differentials in terms of differing social backgrounds. If social background does not account for ethnic differentials, I will examine the alternative explanations of discrimination and cultural propensities to achieve.

5

CHAPTER 2

PENINSULAR MALAYSIAN SOCIETY: DATA AND DESCRIPTION The chief ethnic communities of Peninsular Malaysian society are Malays, Chinese, and Indians. These three form a plural society', segmented along cultural as well as structural lines. In this chapter, I discuss some major differences among them, and in tandem introduce the sources of data to be used in the subsequent analysis.

Origins of a Multiethnic Society The migration-of the Malay peoples to Malaysia was so long ago that they are generally considered the indigenous population. Probably they first arrived

on the peninsula between 2,500 and 1,500 B.C. (Hodder, 1968:22). They displaced an aboriginal population from the seacoasts and plains to the jungle, where scattered communities of aborigines exist to this day. There has been a more recent stream of immigration in the past century of Malay peoples from Java and Sumatra. It is almost impossible to estimate the magnitude of this 'The term ‘‘plural society’’ was first used by J.S. Furnival (1948) in his work on the Dutch East Indies (now Indonesia). He was concerned with the segmentation consequent upon the imposition of the colonial economic system upon a traditional society. Gradually the term came to signify any society which had strong social divisions along ethnic, racial, religious, or linguistic lines. Some social scientists have tried to maintain the distinction between social pluralism (involving separate social institutions) and cultural pluralism (van den Berghe, 1967; M.G. Smith, 1960), while others have used the term without making theoretical distinctions (Haug, 1967). Recently the concept has been attacked because of the lack of consistency of interpretation (Cox, 1971; Cross,

1971). The use of the sociological concept, ‘‘plural society’’, is quite different from the political theory of pluralism (see Gillam, 1971). 6

movement because most of the migrants have become assimilated into the Malay population. But this was a substantial movement that has continued into the present century (Smith, 1952: 15-20; Saw Swee Hock, 1963: 110113).

From the earliest recorded times there has been contact between various ethnic and nationality groups on the Malaysian peninsula. As the extension of mainland Southeast Asia into island Southeast Asia, lying along the main sea route between China and the West, Peninsular Malaysia has been the historical cross-road of Southeast Asia (Lamb, 1964:99). Most of the early contacts arose from trade relationships. Indian traders and Indian civilization left a heavy imprint on Malay culture, a circumstance which during the early centuries of the Christian era brought about what is often referred to as the ‘‘Indian-

ization’’ of Southeast Asia (Lamb, 1964:104). If there were any permanent settlements of Indians on the Malaysian peninsula during this period, they have long since blended with the Malay population. There was also early contact with China, the first visitors being Buddhist monks, while traders from China are reported to have come to Malaysia in the fourteenth century (Purcell, 1967:16). The coastal city of Malacca, which had already become the center of an important empire about 1400, contained a diverse population of many nationalities, many of whom came to engage in trade and commerce. Contact with European peoples began with the capture of Malacca by the Portuguese in 1511. Then the Dutch captured it in 1641 and ruled it for about 150 years. The activities of early European colonialists were probably not very different from those in other Asian empires which rose and fell in the preceding 1,000 years. They were interested in trade and the control of navigation. Perhaps the most important legacy of this early colonialization is the Portugese Eurasian community. In the 16th and 17th centuries Portuguese soldiers intermarried with local women, and their descendents still live in villages near Malacca (Hodder, 1968:24-25). Most important in the creation of Malaysia’s present day multiethnic society was the period of British colonial rule. The British first arrived in Penang, an island off the West Coast, in 1786. Within 40 years they had gained control of the island of Singapore and the city of Malacca, and by the second decade of the twentieth century the entire peninsula came under direct British rule. The arrival of the British coincided with and perhaps stimulated the migration of Chinese to Malaysia. (They also migrated to other Southeast Asian coun-

tries.) Both the Chinese and the British began to exploit local resources, especially tin, and to engage in trade. Among their other economic ventures was the planting of various cash crops such as pepper, spices, sugar cane, and coffee on a commercial basis, first in the Straits Settlements (Penang, Malacca, and Singapore) but soon in nearby areas of the Malaysian peninsula. To obtain sufficient labor for the new agricultural plantations, the colonial

government as well as private interests encouraged Indians to immigrate. Although many of the crops as well as tin mining were not new to the Malay population, what was new was their greatly increased scale.

This period of colonial economic expansion and international migration 7

transformed the country. In about 1800 the population was estimated at a quarter of a million, but by the end of the century it reached two million (Hodder, 1968:26). The causes of migration from India and China as well as

the terrible working and living conditions to which the early migrants to Malaysia were subjected have been the subject of considerable historical research (Purcell, 1967; Jackson, 1961; Blythe, 1957; Parmer, 1960; Kernial Singh Sandhu, 1969). Immigration increased throughout the 19th century and

for the first three decades of the 20th century, until the 1930’s, when the Depression and restrictive legislation slowed it. As a point of reference, Blythe (1947:66) names 1850 as the beginning of large-scale immigration of Chinese to the mainland of Malaysia. The major flow of Indian migration began in the 1880’s and increased sharply in the second decade of the 20th century when the rubber plantation sector began to expand very rapidly (Kernial Singh Sandhu, 1969:312-313). The impact of international migration on Peninsular Malaysian society may be discovered by examining the changing ethnic composition of the country.

The Data Base A basic of British enterprise was the establishment of a governmentallysponsored census of the population. The colonial authorities first began to take a census of British Malaya in 1871 and continued every decade with the year ending in ‘‘one’’ until 1931. (Saw Swee Hock, 1968:2-3). Not surprisingly, this date (year ending in ‘‘one’’) was also census year in England. The planned

1941 Census was never taken because the Japanese during World War II controlled most of Southeast Asia, including what is now Peninsular Malaysia. In 1947 after World War II and the resumption of British colonialism, another census was taken. The next one was a decade later, in 1957. The 1957 Census of Population was the last taken during colonial rule. The next and most recent census was that of 1970.

The early censuses of 1871, 1881, 1891, and 1901 did not include all of what became British Malaya or what 1s now Peninsular Malaysia. British rule spread slowly over the Malayan peninsula (Gullick, 1969:44-52; Cowan, 1961), and these early censuses covered only the states of the country which the British controlled at the time. Thus the only population censuses for the entire area now known as Peninsular Malaysia are the 1911, 1921, 1931, 1947, and 1957 censuses. Since the 1970 Census data were not yet available at the time of this analysis, I made use of two important surveys taken in the late 1960’s. One survey is known as Malaysian Socioeconomic Sample Survey of Households — 1967-1968 (Choudhry, 1970) which, because it was a survey of households and not of the total population, is not completely comparable with the earlier censuses ‘(Appendix A). However, I used the 1967-68 Socioeconomic Survey data to extend the time-series analysis of population trends (see below and chapter 3). The other important source is the 1966-67 West Malaysian Family Survey (see National Family Planning Board of Malaysia, 1968), a survey of 5,457 married women in the reproductive years. In addition to data on fertility and family planning, which were the primary interest, this survey also gathered information on the social background of the husbands of the women inter8

viewed. (Analysis of the socioeconomic characteristics of these husbands is reported in chapters 4, 5 and 6.) I was able to analyze the Family Survey from the original data file which was on a computer tape. The following analysis and that in chapter 3 is based upon published tabulations of the censuses and the 1967-68 Socioeconomic Survey.

Ethnic Composition The data from the 1911, 1921, 1931, 1947, and 1957 censuses and a 1967 estimate (Dept. of Statistics, 1969a), reported in Table 2.1, show the popula-

Table 2.1: | Ethnic Composition of the Population: Peninsular Malaysia, 1911, 1921, 1931, 1947, 1957, 1967

Population in Thousands

Community 1911 1921 1931 1947 1957 § 1967

Malays 1370 1569 1864 2428 3126 4389 Chinese 693 856 81285 1884 2334 3257

Indians and Pakistanis 239 439 571 531 707 ~=1004

Others 37 43 68 65 112 137 Total 2339 2907 3788 4908 6279 = 8787 Percentage Distribution

Community 1911 1921 1931 1947 1957 = 1967 Malays 58.6% 54.0% 49.2% 49.5% 49.8% 50.0%

Chinese 29.6 294 33.9 38.4 37.2 37.1

Indians and Pakistanis 10.2 15.1 15.1 10.8 11.3 11.4

Others 1.6 1.5 1.8 1.3 1.8 1.6 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Sources:

Department of Statistics, 1971b : 3.

Department of Statistics, 1969a : 39. . tion by ethnic community from 1911 to 1967. During this period, the total population grew from 2.3 million to 8.8 million. Of the 8.8 million in 1967, 50 percent were Malays, over one-third were Chinese, and over one-tenth were Indians. The small ‘‘others’’ category of less than two percent includes Ceylonese, Thais, Eurasians, Europeans, and other small ethnic or nationality groups.

|9

The Malay proportion declined from 58.6 percent in 1911 to 49.2 percent in 1931 and has been stable at about 50 percent over the last 40 years or so. The

Chinese proportion grew from 29.6 percent in 1911 to 38.4 percent in 1947 and has declined only slightly since then. The Indian population grew by 50 percent from 1911 to 1921: their proportion of the total population increased

from 10.2 to 15.1 percent, a figure which held steady until 1931, declined to 10.8 percent in 1947, and has increased only slightly since then. During the period 1931 to 1947, when the Indian proportion declined from 15.1 to 10.8 percent, the absolute number of Indians declined by 40,000 as a result in the Depression of substantial out-migration of both males and females. From the limited statistical and historical accounts, it seems that immigration has had a significant influence upon ethnic composition since early in the nineteenth century (Jackson, 1961; Kernial Singh Sandhu, 1969). Not until the 1930’s did the colonial government’s restrictions and the declining demand for labor as a result of the Depression slow down the flow of migration.

The Immigrant Communities Most immigrants (Javanese, Chinese, and Indians) came to Malaysia not as permanent settlers, but only to earn some money and return to their homelands. Parmer (1960:17) estimates the average length of stay to have been two to three years, but over time many immigrants became permanent settlers. What proportion of migrants became permanently settled cannot be estimated, but there are data for several dates in the 20th century on the proportion of locally-born Chinese and Indians living in Malaysia.

Table 2.2 shows the proportion of each ethnic community that was born

Table 2.2: Percentage of Population of Peninsular Malaysia Born in Peninsular Malaysia or Singapore, by Ethnic Community, 1921, 1931, 1947, 1957.

Community 1921 1931 1947 1957

Malays — — 96.0% 97.4% Chinese 20.9 29.9 63.5 75.5

Indians 12.1 21.4 51.6 65.0 —

Total 56.4% 58.9% 78.3% 84.8% Source: Fell, 1960:15.

in Peninsular Malaysia or Singapore from 1921 to 1957. Since many of those not born in Peninsular Malaysia have come to be permanent residents, ‘‘locallyborn’’ is probably a conservative estimate of the number of permanent immigrant settlers. The major increase in the proportion of the locally-born occurred from 1931 to 1947. A decrease in new migration, a return emigration of the foreign-born, higher mortality among older persons who are more likely to be | foreign-born, or a change in the age structure as a result increasing fertility could account for the fact that by 1957 over three-fourths of the Chinese population and two-thirds of the Indian population had been born locally.

In retrospect, several events and issues in Malaysian social history appear important in determining the character of the contemporary multiethnic society.

Although the initial British control of the Straits Settlements stimulated the beginnings of modern Chinese and Indian migration to Peninsular Malaysia, 10

the major flow occurred in the latter part of the 19th century. Between 1874 and 1914 the British consolidated their rule over all the states of Peninsular Malaysia, the effect of which was to assure political and economic stability. Moreover, they created a structure of government-assisted opportunities through which British and also Chinese businessmen could increase their economic exploitation of the country. This, in turn, required more labor and more immigration. In the last years of the 19th century, rubber supplanted all other commercial agricultural crops and became the most important element of the economy. As other economic enterprises lost ground on the world market or required less labor (in the tin industry as a result of technological change) rubber plantations continued to absorb more labor.

Intermarriage In many multi-ethnic societies, such as Hawaii (Schmitt, 1965:465), Mexico, and Brazil (van den Berghe, 1967, chapters 2 and 3), there has been extensive intermarriage and racial amalgamation. But intermarriage, while not unknown in Malaysia, is extremely rare; indeed, a study of Malay marriage and kinship in Singapore reported almost no intermarriages (Djamour, 1957: 11). Asubcommunity of Chinese called ‘‘Baba Chinese’’ or ‘‘Straits Chinese’’ has acquired a great deal of Malay culture, including cuisine and dress. They speak Malay as their mother tongue, but keep their Chinese ethnic identity and have not become Muslims. They are reported to be the descendants of early Chinese immigrants who, perhaps before 1850, married local women. Freedman (1955:376) estimated the Straits Chinese as constituting about 15

percent of the total Chinese population in Peninsular Malaysia. They are predominately located in the old Straits Settlements of Penang and Malacca.

Malaysia was generally free of the virulent racism—except among some European colonialists—that infects some multi-ethnic societies. In former times Chinese parents sometimes used to sell unwanted female babies to Malay couples. They were raised as Malays and were completely accepted into the Malay community in spite of their physical appearance (Freedman, 1955:398). In fact, any non-Malay who converts to Islam is usually accepted as a member of the Malay community. A factor which might have led to more intermarriage was the unbalanced sex ratio of the early immigrant communities (Table 2.3). In the early decades of the 20th centuries there were only from 2 to 4 females for every 10 males of the Chinese and Indian population. Of course, there were alternatives to marriage in Malaysia: there was reportedly a great deal of prostitution, especially in the Chinese community (Purcell, 1967, chapter 9). Since most migrants did not plan to stay permanently there was probably minimal motivation to marry and launch upon family life. Moreover, intermarriage was discouraged by the geographical separation of the ethnic groups. Many Chinese and Indians lived in isolated tin-mining communities or on rubber plantations,

while the majority of Malays lived in rural villages. Towns and cities were potential sites of interethnic contact, but there most of the inhabitants were non-Malays. The most popular explanation of the infrequency of interethnic marriage is the religious barrier. Practically all Malays are Muslims, and Islam requires the conversion of potential non-Malay mates. In ethnic communities 11

Table 2.3: | Sex Ratio of Chinese and Indian Population: Peninsular Malaysia, 1911, 1921, 1931, 1947, 1967.

Females Per Thousand Males

Year Chinese Indian 1911 215 320

1921 371 424 1931 486 514 1947 815 687 1957 926 746 1967 999 896

Sources:

Del Tufo, 1949:57-58. Fell, 1960:9. Choudhry, 1970:15. with strong national and cultural traditions such as those of the Chinese and Indians, conversion is not common. The span of 100 to 200 years is possibly

too short to yield evidence of possible eventual ethnic amalgamation in Malaysia.

Differences Between Ethnic Communities Perhaps the major process of acculteration in the 20th century has been the creation of a common culture within each of the three primary ethnic communities. The common bond of being Chinese in Malaysia has created a common identity among the diverse linguistic, occupational, and clan groups of Chinese. Similarly, although Tamil-speakers from Ceylon and Indian are well aware of their differences, most other Malaysians regard them both as Indians. The regional differences in the Malay community between the East and West Coast, as well as the differences between indigenous Malays and those who

migrated a generation ago from Sumatra or Java are secondary to the more salient differences between the three major ethnic communities. Most Malays are of the Islamic faith, Chinese are predominantly Buddhist, and the majority

of Indians are Hindu. There is some religious diversity in the Chinese and Indian communities, both of which have sizeable Christian minorities. There are many Indian Muslims, particularly in the Pakistani community.

Language has been a major barrier. For the most part, each community has kept its mother tongue. This is also true of subcommunities of Chinese and Indians who speak different languages. Among middle-class persons (teachers, professionals, government workers, and the like) in the cities, English is the interethnic medium, while Malay is the basic vehicle of communication among the masses (U.A. Aziz, 1960:27). Most non-Malays, however, have a limited mastery of the Malay language. In 1957, only three percent of the Chinese population above age ten, and only five percent of the same Indian population said they were literate in Malay (Fell, 1960:94-95). 12

But perhaps most significant are socioeconomic divisions that have often been along ethnic lines of which an example is the pattern of urbanization. Living in an urban area permits access to educational and occupational oppor-

tunities as well as exposure to modernizing influences (Schnaiberg, 1971). In this the Chinese and Indians have had the advantage over the Malays. As shown in Table 2.4, the proportion of the population which is urban has

Table 2.4: Percentage of the Total Population and of Each Ethnic Community in Urban Areas:* Peninsular Malaysia, 1911,

1921, 1931, 1947, 1957, 1967. .

Year Community

Total Malay Chinese Indian

1911 10.7% — — — 1921 14.0% — — — 1931 15.1% — — — 1947 18.9% 7.3 31.1 25.8 1957 26.5% 17.6 11.2 51.8 44.7 35.1 30.6 1967 32.3%

* An urban area is defined as a gazetted area whose population numbers 10,000

or more. Sources:

Del Tufo, 1949: 39 and 47. Fell, 1960: 6 and 11. Choudhry, 1970: 68. greatly accelerated in recent years. The Chinese were the most urban community in 1967 followed by the Indians and the Malays. Yet, although each ethnic community became more urban, ethnic differentials have persisted. The dramatic rise of the proportion of Chinese in urban areas between 1947 and 1957 is usually attributed to the forced relocation of rural squatters ordered

by the colonial government during the ‘‘Emergency’’ of the early 1950’s (Fell, 1960:7). At that time, over half a million rural settlers, mostly Chinese,

were resettled into ‘‘new villages’’, many of which became small towns (Hamzah Sendut, 1962). ‘“The Emergency’’ was the popular name of a period of warfare between guerilla forces and the government, which officially lasted

from 1948 to 1960, although most of the active fighting had ended by the mid-1950’s (Short, 1964).

Almost any measure of socioeconomic status, whether education, occupation, or income reveals significant differences between the ethnic communi-

ties of West Malaysia (Arles, 1971). By and large, non-Malays (Chinese and Indians) have attained higher average levels of education and income than Malays. Among Chinese and Indians, also, a higher proportion of their 13

employed population is engaged in managerial, sales, and other occupations of higher status. The majority of Malays remain rural agriculturalists. Much of the analysis in the succeeding chapters is directed toward explaining these patterns. Nonetheless, while there are important differences in the mean values of socioeconomic status between ethnic groups, there is a great deal of overlap in the distributions. Not all Malays are peasants in rural areas, and not all Chinese are businessmen in the towns and cities. Just as there are popular stereotypes linking ethnic memberhip with occupation, there are equally misleading stereotypes regarding the ethnic division _ of power. It is often argued that the Malay community is the dominant political group in Malaysia while the Chinese control the economic sector. During the colonial era, the British were supposedly administering the country for the benefit of the indigenous Malay community. Since Independence, Malays have been over-represented in their proportion: in political and some govern-

mental positions, including the cabinet, the parliament, the military and police, and the basic administrative civil service of the country. Similarly, most shops and businesses in the cities and small towns throughout Malaysia are run by Chinese entrepreneurs. These popular stereotypes, however, have rarely been subjected to empirical analysis.

The popular belief that the Chinese community controls the economy is cast into doubt by some recent data published in the Second Malaysia Plan (Malaysia, 1971:40) showing the distribution of share capital in limited companies (corporations) in Peninsular Malaysia by ethnicity and nationality of share holders. Malays and Malay interests owned only 1.5 percent of such shares by value. Indians held less than one percent, and Chinese owned 22.8 percent. But most interesting was the fact that 62 percent of the value of shares were held by foreign interests, either individuals or companies.

While limited companies produce only 21 percent of the total GNP of Peninsular Malaysia (Department of Statistics, 1969b:2), they are the most modern sector of the economy, one which will grow as Malaysia becomes more industrialized and economically developed. The Chinese community, or at least some segment of it, has a firm stake there and has an advantage, compared with the other communities. However, the dominant power and perhaps ultimate control of this part of the economy is in non-Malaysian hands of individuals and companies from abroad. This means that this study of social stratification in Malaysia is ignoring a major element of the political economy—the foreign community. While negligible in terms of numbers, their socioeconomic position and influence is probably the highest in the social structure. But since data on the characteristics of foreigners are not available separately, it is not possible to include them in our analysis. In any case, the analysis made here of the distribution of status characteristics, is probably not appropriate to measure the participation and influence of the upper echelons of Peninsular Malaysia society. There has been some preliminary research on this topic (Puthucheary, 1960), but much more is needed for an understanding of these aspects of Malaysian social stratification.

14

CHAPTER 3

THE PROCESS OF STRUCTURAL ASSIMILATION As here defined, structural assimilation is the process of dispersion throughout the social structure of different ethnic or immigrant communities. While ethnic groups may be initially in various social strata and residential areas, in Park’s model the shifting and sorting of people over time comes to depend more on individual characteristics than on ethnicity. The major social institutions that serve as indicators of structural assimilation have been economic, educational, and residential. Thus the investigator looks at trends in the distribution of ethnic groups by occupation, educational attainment, or residence. (Taeuber and Taeuber 1964; Eisenstadt, 1953; Lieberson, 1963; Farley and Hermalin, 1972). If the distribution of status characteristics becomes more similar or more equal over time, one may conclude that structural assimilation is occurring.

The major social institutions mentioned above are generally thought of as spheres where secondary relationships predominate. This means that people do not form close personal ties, but generally come together in an office, school, or factory for reasons other than friendship with others in that location. In contrast, in other social structures, such as the family, social clubs, and informal groups, primary group relationships predominate, and in these structural assimilation has been investigated by using such measures as rates of intermarriage and informal association (Heer, 1967; Bumpass, 1970; Molotch, 1969).

National data on structural assimilation in primary group associations, especially of secular trends, are relatively rare; occupation, education, and residence are much more likely to be routinely reported in censuses and surveys. It should also be noted that an equal distribution of ethnic groups 15

in terms of educational attainment or occupation does not necessarily mean that they are engaged in secondary relationships in the same institutions: equal educational attainment may be achieved in separate schools, and an equal occupational distribution could be possible even if the ethnic groups worked in different industries at diverse locations. At best, these measures of structural assimilation give a rough idea of the relative level of interethnic inequality.

Trends in Educational Attainment In earlier research, I examined the differential distribution of ethnic groups by educational attainment in Peninsular Malaysia (Hirschman, 1972b). Data

from the 1957 Population Census of the Federation of Malaya were used to measure the trend in educational attainment, age groups being treated as representative of successive cohorts passing through the educational system during the 20th century. The oldest, 60-64 years old, had passed through the educational system from 40 to 50 years before 1957, while most of the youngest, 20-24, had completed their education in the few years preceding 1957, and a few may still be attending institutions of higher learning. Table 3.1 shows the mean years of schooling of nine five-year age groups

Table 3.1; | Mean Years of Schooling, by Ethnic Community, Sex, and Age Group: Peninsular Malaysia, 1957 Mean Years of Schooling

Age Group Males Females Malay Chinese Indian Malay Chinese Indian 20-24 3.9 4.7 4.7 1.5 2.4 2.1 25-29 3.5 4.1 5.0 1.1 1.6 2.1 30-34 3.3 4.6 4.7 0.8 1.7 1.6 35-39 3.0 4.5 4.0 0.5 1.3 1.0 40-44 45-49 2.8 2.4 3.9 3.4 3.4 3.0 0.3 0.2 0.9 0.6 0.7 0.5 50-54 1.9 2.9 2.7 0.1 0.4 0.5 55-59 1.7 2.6 2.4 0.1 0.3 0.4 60-64 1.3 2.4 2.2 0.1 0.2 0.4 Source: Calculated from tables in Fell, 1960:87-90.

in 1957, by ethnicity and sex. It is clear that there has been a general trend towards higher educational attainment among all Malaysians. However, certain significant ethnic differentials have not declined. In the oldest age group, the mean educational attainment of Malay males was 1.1 years less than that of Chinese males; in the youngest, the Malay-Chinese difference was .8 of a year. From this table education does not seem to indicate a great deal of structural assimilation during the first half of the 20th century. 16

More detailed analysis showed that the ethnic differential persisted because

Malays encountered a problem of access to schools. The Malays’ rates of entry into primary schools and of progression from primary to secondary schooling were lower than were the Chinese’ and Indians’. However, in primary or secondary schools, Malays were just as likely to go on to completion as were Chinese or Indians. These ethnic differentials in education seem to have resulted from the relative accessibility of schools: Malays were more likely to live in rural areas, but most schools, during the colonial era, were in the towns and cities.

Trends in the Occupational Structure There were major shifts in the occupational structure of Peninsular Malaysia between 1931 and 1967, when the proportion of all adult males employed in agriculture declined from 58 to 43 percent. There have been accompanying increases in the proportion of white-collar workers as well as craftsmen and production process workers (operatives). These changes correspond to wellknown shifts in the occupational structure in the course of economic development (Farrag, 1964; Moore, 1966; Treiman, 1970). Concealed in these broad patterns, however, is considerable ethnic variation. Each ethnic community had its particular occupational structure in 1931, the first year in our analysis. While some patterns of change in occupational distributions were similar in all three, there were differences in rates of change, and occasionally in the direction of change. The patterns of ethnic occupational structure continued to show wide variation in 1967.

As in most other longitudinal research, a satisfactory explanation of the process of change in the occupational structure or structural assimilation is extremely difficult to find. The causes of any social change or lack of change,

: are intertwined in historical conditions, to measure whose relative impact requires data far beyond the census material used to measure the trends. In the attempt to relate these patterns to the historical circumstances from which they arise I shall put forth hypotheses which require more investigation than is possible here, for one of the tasks of the research worker is to ask questions and suggest hypotheses for further investigation.

Data and Methods Data on the occupations of employed males by ethnicity has been assembled from the Population Censuses of Malaya (the eleven states which at present comprise Peninsular Malaysia) of 1931, 1947, 1957, and of 1967/68 from the Socioeconomic Survey of Households. These pose several problems of comparability (see Appendix A). For one thing, the age boundaries of the various tables on occupations varied from none, 10 plus, to 15-64 years. This means that raw numbers in an occupation from one time to another are not comparable

nonetheless, the numbers at either end of the age distributions are relatively small and seem to have only minor effects on the percentage distributions. Accordingly, occupational trends are measured with data in percentage form. Then the definition of the workforce was based on the ‘‘ gainful worker’’ concept in the 1931 and 1947 censuses, but somewhat different variations of the concept of the labor force were used in the 1957 Census and 1967/68 Socioeconomic Survey. This gave rise to the problem that unemployed and perhaps 17

some retired workers are classified as in the occupational distributions (based only on employed population in 1957 and 1967) in the earlier sources and not in the later ones; however, I suspect this to exert little influence and since I do not try to interpret small differences or changes it should not interfere

with the analysis. Perhaps the most important problem lies in the various schemes of occupational classification of the four sources of data. Working with the most detailed categories of each scheme of occupational classification, I constructed a roughly comparable series of occupational trends by ethnicity.

The list of categories in the comparable classification was limited to the ten major occupations in the most recent (1957 and 1967/68) classification (see Appendix B). While such a short list of occupations lacks much of the flavor and diversity of the detailed tables, it does assure the relative comparability of a variety of schemes of classification. Occasionally, data on the detailed categories within a major occupational classification are presented to show internal variation. To indicate trends and differentials, the occupational composition of each ethnic group is presented for each of four periods in percentage form, which allows for a detailed discussion of comparative stability and change in the occupational structure of each community. The ethnic diversity in occupational composition is summarized with ‘‘delta’’ indexes of dissimilarity. A delta index, a measure of the inequality or unevenness of two percentage distributions, can be interpreted as the minimum percent of one population which would have to be redistributed to achieve equal percentage distributions across all categories. (For a more detailed discussion of the delta index and similar measures, see Duncan and Duncan, 1955 and Taeuber and Taeuber, 1965: 195-245).

Occupation and Social Inequality Because occupation is both the main activity of adult men and usually the main determinant of social rewards, including income, the occupational structure is often considered equivalent to the opportunity structure; in other words, entering an occupation usually entails reaching a position in a socioeconomic hierarchy. However, the construction of an occupational hierarchy, a task of ranking essentially nominal categories, has proved troublesome. An occupational hierarchy based on prestige scores, however, is largely con-

sistent across time and space (Hodge, Siegel, and Rossi, 1966; Hodge, Treiman, and Rossi, 1966). In turn, the prestige ranking of an occupational category shows a strong relationship to income and education (Duncan, 1961).

Since occupation is to be used to indicate comparative social status or social inequality, the socioeconomic correlates of different occupational positions must be demonstrated. Since I did not have access to an independent measure of prestige rankings of occupations in Malaysia, I calculated the average income and education in different occupations from the 1966/67 West Malaysian Family Survey data. Education would seem to measure level of skill while income is a major determinant of level of living.

Table 3.2 shows the mean education and income in eight major occupational categories. ‘‘Mean education’’ is the average number of years of schooling completed, and mean income shows the average monthly income in Malay18

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almost ten points from 1947 to 1957 and then by seven more points from 1957 to 1967. This was accompanied by increases in the percentages employed in professional and administrative as well as clerical and craft occupations, but in most other categories the percentage of the total employed seems rather stable. Service occupations rose in 1957, then declined. I think this is due to the large number of armed forces personnel, including many British and other Commonwealth troops, who were still mobilized for the ‘‘Malayan Emergency’’. Laborers declined between 1931 to 1947, then rose steadily in the rest of the time period being considered. The occupational trends in each ethnic group are similar, but there are differences in the magnitude and timing of shifts in the occupational structure. Malay men were much more likely to be in agricultural occupations, over 82 percent appearing in this category in 1931, dropping to slightly below 60 percent in 1967, most of the decrease occurring after 1947. However, the pro-

portion of Chinese and Indian males in agriculture also declined, leaving | only 24 and 35 percent, respectively, in this occupation in 1967. The case of Chinese employment in agriculture is especially interesting. The proportion of Chinese employed in agriculture rose from 40.8% in 1931 to 45.1% in 1947, then declined sharply during the next intervals. The decline after 1947 seems to be readily explained by the relocation of rural Chinese during the ‘‘Emergency’’ in the early 1950’s as well as by the rural-to-urban migration normal in a time of economic development. However, the increase during the 1930’s

and 1940’s is puzzling. Two potential factors need to be considered, the peculiar age distribution of the Chinese population and the possibility of urbanto-rural migration during the Depression and war years.

The male Chinese age structure during the first part of the twentieth century was unbalanced due to the heavy inflow of adult immigrants which contrasts with growth by natural increase (Table 3.4). There was a sharp relative

Table 3.4: Age Distribution of the Chinese Population by Sex: Peninsular Malaysia, 1921, 1931, and 1947.

1921 1931 1947 Age Males Females Males Females Males’ Females 0-14 14.3% 33.5% 20.3% 35.4% 37.6% 40.7%

15-49 75.1 56.7 69.2 55.0 49.5 48.4

50+ 10.6 9.8 10.5 9.6 12.9 10.9

Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Source: T.E. Smith, 1952:70. as well as an absolute decline in the number of male Chinese in the working ages (defined here as 15 to 49) from 1931 to 1947, the result of a restriction of male Chinese immigration during the 1930’s. As large cohorts of male Chinese left the working ages by death, retirement, or emigration, they were replaced by relatively smaller cohorts of locally-born Chinese who had come of working age. These additions to the Chinese work force were perhaps more 24

likely to be rural and agricultural than those who left the work force for the above reasons. Another possible explanation of the relative increase of Chinese men in agriculture is that the hard years of the Depression and the war **pushed’’ many marginal Chinese urban workers and tin miners to unclaimed jungle land

to eke out a subsistence living or to engage in small-scale agriculture. It is not possible to test this hypothesis; however, I have compared the types of agricultural activities of Chinese men in 1931 and 1947 (Table 3.5). The total

Table 3.5: Detailed Occupational Composition of Employed Chinese Males in Agricultural and Fishing Occupations*: Peninsular

Malaysia, 1931, 1947. |

ee

Occupation 1931 1947 Rice Farmers 5,174 33,940

Rubber Farmers 158,443 118,036

Coconut Farmers 3,755 3,342 Oil Palm Farmers 117 2,070

Fruit and Vegetable Farmers 41,514 68,991 Rearers and Poultry & Livestock 6,221 4,277 Forresters and Woodcutters 12,877 8,298 Other Agricultural Workers 29,901 6,957

Fishermen 13,496 17,491 Total Employed 271,496 263,402

*The Malaysian occupational classification for these years included nonagricultural activities such as forestry and woodcutting under ‘‘Agricultural.’’ Sources: Vlieland, 1932:294 and 319. Del Tufo, 1949:477.

number of Chinese men in agriculture and fishing declined, but there were substantial increases of them in the cultivation of rice, fruit and vegetables, and in fishing. This would seem to be consistent with the explanation of urban

to rural migration by the Chinese. Another influence on this process might

have been the Japanese mistreatment of Malaysian Chinese during the Japanese occupation of the country from 1941 to 1945. Both because the Japanese were then waging an active war in China and because most of the local resistance fighters in Malaysia were Chinese, the Japanese occupation forces were said to be more hostile to Chinese than to either Malays or Indians, and this may

have led some Chinese to migrate to rural areas to escape mistreatment. Of course, much happened between 1945 and 1947, and it is risky to conclude that the 1947 data reflect only the experience of the Depression and the War. The decline in agriculture since 1947 affected all three ethnic groups: the Malays and Chinese showed a reduction of twenty percentage points, while the Indians were fewer by ten percentage points (Table 3.3). Since the Indian and Chinese had a smaller share in agricultural occupations in 1947, their decline from 1947 to 1957 was a greater percentage of their initial agricultural 25

population than was the case of the Malays. In each ethnic community the common losses in agriculture reflected different kinds of agricultural activity. Most Malays in agriculture were subsistence farmers working their own land or tenants on the land of wealthier villagers. Almost all Indian agriculturalists were laborers on large rubber estates and more recently on oil palm estates. The Chinese were both: many worked as laborers on estates, but there were also many small Chinese farmers who grew vegetables, tobacco, or some other cash crop. Table 3.6 presents evidence that the sharp decline in Malay farmers was due to a decrease in the proportion of Malays classified as primary rice

cultivators from 46 percent in 1947 to 20 percent in 1967. There was in increase in proportion of Malays in rubber cultivation. Among the Chinese, the change from 1947 to 1957 was a decline in the growing of rice and ‘‘other crops’’, (both generally subsistence crops), while the 1957-1967 drop was largely in the rubber sector. Among the Indians, the decline has been almost completely in the rubber industry, the most rapid decrease occurring from 1957

to 1967. It seems evident the trend out of agricultural employment is not limited to any particular crop or subdivision within it. Table 3.3 shows increases in all groups in white collar occupations (professional and technical, administrative, executive, and managerial, and clerical). In professional occupations, it appears that general parity has persisted among the three ethnic groups over time. For instance, in 1931, professionals among the three ethnic group ranged from 1.1 to 1.5 percent and in 1967, it was from 4.6 to 5.4 percent. However, within this major occupation internal differences appear in the detailed occupational categories, classified by ethnicity (Table 3.7). While the majority of professionals from each group were teachers and ‘‘other professionals’’, Chinese and Indians were more likely to be in medical and other professions high in status than were Malays. For administrative and clerical occupations, there has been a growing differential between Malays and non-Malays (Table 3.3). Both classes of occupa-

tion increased, especially from 1947 to 1967, but the ethnic differentials remained. I think there are two major factors affecting the ethnic differential in white-collar jobs. First, in many white-collar occupations, paper credentials or education is a major determinant of who gets a job, so that much of the ethnic differentials in white-collar jobs reflect unequal educational qualifications. (This is a hypothesis which will be directly tested in chapter 6). The other consideration is the role of recruitment in the public and private sector. Many of the establishments in the private sector may give preference to relatives or clan members in hiring white-collar workers, and this is probably true of other jobs as well. Since Chinese and Indians are more urban and more likely to be employers, such a policy would effectively discriminate against Malays. It should also be noted that even if preferential hiring of non-Malays were not practiced, but widely believed to be practiced, it would discourage Malays from applying. Within the public sector the government must generally rely on more the universalistic criteria of paper qualifications, although there are practices which give preference to Malay applicants on certain government jobs. Basically, this is a quota system to maintain a balance between Malays and non-Malays—but these were flexible since only ‘‘qualified’’ applicants with proper educational credentials could be considered. 26

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31

In the Indian population a total of 32.6 gross percentage change in the occu-

pational structure resulted in only 21.0 points of cumulative change from 1931 to 1967. In particular, the two most recent periods do not seem to have given a common direction to change in the Indian occupational structure. Without quibbling over choice of words, one might say that the evolutionary

trend apparent in most of the period is an upgrading of the occupational Structure. This includes a movement out of agriculture and an increase in white collar and craft occupations. Actually the delta index measures only the amount of change in the occupational composition and not its direction. However, since we do know the overall trends as evidenced in the actual data on occupations, it seems fairly accurate to label the evolutionary trend of cumulative shift from 1931 to 1967 as a measure of the upgrading of the occupational structure. If this is so, then the upper panel shows that while the Chinese occupational structure progressed or redistributed itself by 27 percentage points, the Indian and Malay communities had a net redistribution only 21.0 and 22.8 percentage points, respectively.

The lower panel Table 3.8 shows the three inter-ethnic comparisons for each time point; each time-series can be interpreted as the trend in ethnic equality (or similarity) in the occupational structure. From 1931 to 1947, the occupational distributions of Malays and Chinese became more similar (a decline of almost nine points from 42.0 to 33.2). Then there was a divergence from 1947 to 1957 of seven points in the delta index, but it declined slightly again from 1957 to 1967. The degree of difference between the Malay and

Indian occupational structures was virtually constant from 1931 to 1957, then declined somewhat from 1957 and 1967. The pattern of difference between Chinese and Indian occupational structures fluctuated, declining from 1947 to 1957, and then widening from 1957 to 1967. The interpretation of Table 3.8 in relationship to the social, economic and political conditions of the period is perplexing. There are not parallel timeseries data on socioeconomic changes during this entire era, and even if there were, problems of how these social and economic changes differentially affected the occupational patterns of each ethnic group would remain unresolved.

In spite of the obvious risks I offer an interpretative framework for the trend in occupational differentials. Although this involves conjecture, it is an attempt } to raise issues not to provide a final interpretation of the socioeconomic causes of ethnic inequality. The discussion is focussed on the pattern of differentials between the Malays and the Chinese who together form 85 percent of the population.

Interpretation of Occupational Trends During the period of 1931 to 1947, the occupational structures of Malays and Chinese became less dissimilar, that is, more equal in terms of occupational distribution. The most important factor in the process was the proportion employed in agriculture which increased among the Chinese and decreased among the Malays. However, even if deltas are calculated on the basis of only non-agricultural occupations, the same lessening of inequality is evident (see Appendix E), albeit to a much smaller degree. I suggest that the economic Depression of the 1930’s and the continuing hardships of the Japanese occu32

pation in the early 1940’s were the prime cause of this growing similarity. The major decline of non-agricultural employment among the Chinese during this period was in the category of miners (10.5 to 4.0%) and laborers (8.1 to 2.8%). Perhaps the years of hardship forced many marginal urban workers and miners who lost their jobs to migrate to the fringes of the jungle to become subsistence farmers, and as well, discouraged rural Chinese from leaving agriculture. As noted earlier, immigration of Chinese males was all but stopped in the early 1930’s. This led to a situation where replacement in the Chinese work force was dependent on much smaller cohorts of Chinese adolescents replacing larger cohorts of older Chinese adults who died, retired, or emigrated. Perhaps this process worked in the direction of bringing more Chinese into farming than into other occupations. For Malays, the slow momentum of the twentieth century continued to lower the proportion in agriculture (82.4 to 78.2 percent) and increase slightly the number in other occupations. Among the social forces at work, increasing educational opportunity and contact with urban areas were probably the most important.

The year 1947 was two years after the end of the Japanese occupation and conditions may have changed substantially in that time. Whether the increased similarity in occupational distributions meant greater socioeconomic equality is an unanswered question. It is possible that the increasing proportion of Chinese in agriculture was at a higher economic level than the average Malay farmer. However, Table 3.5 indicated that most of the increase of the Chinese cultivators was in rice, fruit and vegetable farming, and in fishing. Although their crops may represent involvement in the market economy, their level of living was probably quite close to that of subsistence farmers.

The post-war period, 1947 to 1957, saw growing differences between the Malay and Chinese occupational structures. The proportion of Chinese employed in agriculture declined from 45.1 to 32.3 percent while the corresponding figures for Malays were 78.2 to 69.8 percent, and more Chinese~also became administrative, sales, and craft workers than did Malays (Table 3.3). As noted earlier, this was a period of economic recovery and growth, although uneven. Why were the Chinese more able to take advantage of the emerging opportunities than were the Malays? One reason might be that the Chinese were more likely to be in urban areas where the opportunities were greater. Also the relatively greater distribution of education among Chinese as compared to Malays must have made a difference, as did probably the forced relocation of hundreds of thousands of rural Chinese during the Emergency in the early 1950’s in ‘‘new villages’’, which resulted in a sharp increase in the proportion of urban Chinese. This undoubtedly led to occupational shifts, and probably also provided greater educational opportunities for Chinese youth. It seems strange at first glance that ethnic socioeconomic differentials widened during years of economic progress, but that appears to have been the case.

There were continued changes in the occupational structures of Chinese and Malays from 1957 to 1967, and the gap between the two seems to have narrowed slightly (Table 3.3). This is evident in agricultural, sales, craft, and laborer occupations. As a consequence of the governmental building of more rural schools, thus providing more educational opportunities, and the 33

encouraging of progress in various areas, including the growing public sector, the Malay occupational structure in terms of percentage distribution shifted

as much in ten years as it had in the preceeding twenty-six. Whether these public efforts at ending ethnic inequality in occupational and other economic patterns will be successful will be a most important question in the coming

years. .

Conclusions Does it appear from this analysis that there is some trend toward ethnic assimilation or greater similarity in occupational composition as might have been predicted by Robert Park’s theories? While the theoretical writings on social change and ethnic relations do not really present a ‘‘testable proposition’’, they do offer indications as to the direction of change. However, the Malaysian data do not indicate any clear secular trend. Ethnic differentials (Malay-Chinese) narrowed between 1931 and 1947, then widened between 1947 and 1957, and then narrowed slightly between 1957 and 1967. The differentials within major occupational categories, the trend out of agriculture and the growth of white-collar occupations are similar in all groups, although it is more rapid among Chinese and Indians than among Malays. The major differentials in sales and craft occupations seem, however, to have narrowed only slightly in the last decade. Rather than searching for a single explanation such as industrialization or urbanization as the most important in ethnic occupational trends, it would seem more useful to seek explanations in the specific organizational changes within the occupational structure. For instance, the movement out of agriculture can be seen as the result of several social forces common to all groups in various types of farming activity. Important among factors ‘‘pushing’’ people out of agriculture might be: rural over-crowding or simply too many children to inherit a little land or a job on an estate, higher wages in urban areas, declining prices and terms of trade for agricultural products, and increasing education of rural youth. The growth of white-collar jobs has been stimulated by the growth of the public sector and to a lesser extent by large-scale commercial enterprise. Since many white-collar jobs are probably dependent upon ‘‘paper qualifications’’, ethnic differentials may reflect differences in educational attainment. Education in the English language schools, traditionally the most prestigious, has been almost a prerequisite of admission to higher education and whitecollar jobs. Since most English schools were in urban areas and proportionately more Indians and Chinese were there, this probably affected the unequal ethnic attainment of high-status jobs. Perhaps another set of structural limitations inhibits the increase of Malays in sales and craft occupations, where the greatest differentials exist. There most of the job opportunities are probably in small family enterprises. The mere habit of hiring employees from among kin or clan would restrict opportunities in ethnic communities with relatively few employers. Table 3.9 shows the distribution of males in each ethnic group by employment status. While almost 7 percent of employed Chinese men and almost 3 percent of Indians are employers, this is true of less than one percent of Malays. This tends to restrict 34

Table 3.9: | Employment Status of Employed Males by Ethnic Community: Peninsular Malaysia, 1967.

Employment Status Total Malays Chinese Indians

Employers 3.3% 0.9% 6.9% 2.9%

Own Account Workers 29.1 40.4 21.3 8.4 Employees/Wage &

Salary Earners 60.2 50.5 63.5 87.3 Unpaid Family Workers 7.3 8.2 8.3 1.4

Total 100.0% 100.0% 100.0% 100.0% Source: Choudhry, 1970 (Appendix): 42-43. recruitment of Malays into sectors of the occupational structure where ethnicity may be considered as a criterion for employment, such as in small-scale commerce and industry. While a majority of jobs in manufacturing in 1968 were in establishments of 50 employees or more, a substantial number were in much smaller businesses (Table 3.10). It seems likely that the sales or commercial

Table 3.10: Distribution of Establishments and Paid Employees in Manufacturing Industries, by Number of Employees: Peninsular Malaysia, 1968.

Paid Number of Number of

Full-Time Establish- Percent Paid Percent

Employees ments Distribution Employees Distribution

None 3,347 37.2% 1,823 1.4%

1-4 2,738 30.4 8,506 6.5 5-9 957 10.6 7,725 5.9 10-19 738 8.2 11,455 8.8 20-29 394 3.7 4.413,188 10,42510.1 8.0 30-49 334

50-99 275 3.0 19,186 14.7 100-199 133 1.5 22,617 18,662 17.4 14.3 200-499 77 0.8

500+ 20 0.2 16,670 12.8 Total 9,013 100.0% 130,257 100.0%

Source: Department of Statistics, No date, Census of Manufacturing Industries, 1968:37. sector is also largely made up of small stores and shops where to reduce ethnic differentials would be most difficult. Not only are ethnic preferences probably Operative there, but relatively few Malays may consider seeking employment 35

where so few of their community are to be found. In other words, the threat of discrimination may be as real a barrier as the actual practice of it. Perhaps only when the economy is made up of large-scale economic organizations, more sensitive to government pressure than to family obligations, will there be a sizeable narrowing of these differentials. The period of forty years would have provided a sufficient length of time for ethnic occupational differentials to decline sharply if there were perfectly free social mobility (independence of son’s occupation and father’s occupation; see Lieberson and Fuguitt, 1966). The fact that such differentials are still large after this length of time indicates that there are still structural blocks to occupational mobility. Additional quantitative analysis of ethnic occupational trends and differentials and their co-variation with social changes in the society and economy should allow for a more precise explanation of the Malaysian case and provide more basis for comparative theoretical development.

36

CHAPTER 4

INTERGENERATIONAL OCCUPATIONAL MOBILITY: ETHNIC DIFFERENCES While the historical analysis in the earlier chapters was dependent upon the published tabulations from censuses and the 1967-68 Socioeconomic Survey, this and the subsequent chapters report material based upon analyses from the unit record data file of the West Malaysian Family Survey. As noted earlier, this was a national probability sample of 5,457 women between the ages of 15 and 45, with the sample stratified according to size of place. But all the data here have been weighted to give a representative sample of the universe of married women, age 15 to 45 in Peninsular Malaysia (for details on survey

methods and weighting procedures, see National Family Planning Board, 1968:1-22). The analysis here is based upon data on a number of social and economic characteristics of their husbands, supplied by these women. The question whether a sample of husbands with wives in the childbearing years is representative of the entire male Malaysian labor force is addressed elsewhere (Hirschman, 1972a, chapter 4). It seems that, in general, the weighted sample of husbands is an adequate surrogate of the population of males in the working ages.

Social Mobility The evidence in chapter 3 shows that substantial occupational differentials between Malays, Chinese, and Indians have persisted for a long time, in spite of major changes in the occupational structure. A basic question is: How much of the current occupational structure reflects an inheritance of occupational status from father to son? The investigation of intergenerational occupational mobility, often called the study of social mobility, has been a major focus of sociologists in the past 37

two decades (Rogoff, 1953; Glass, 1954; Lipset and Bendix, 1959; Miller, 1960; Lopreato, 1965; Svalastoga, 1965; and Cutwright, 1968). Most of their research focused on urban industrialized societies, with a strong interest in measuring the amount of ‘‘opportunity’’ available. From this perspective, investigators sought to discover if the son of a manual worker had less chance of achieving a high-status occupation than the son of a non-manual worker, and if so, how much less. Related questions were of the variation in the availability of opportunity across time or between countries.

Earlier research applied the techniques of analyzing social mobility to the differential intergenerational occupational mobility of ethnic, racial, and immigrant communities (Matras, 1965, chapter 4; Lieberson and Fuguitt, 1966; and Duncan, 1968b). The goal was to describe and explain the different patterns

of social mobility among sub-groups of the population. The extent to which various ethnic or racial communities fare unequally in the process of social mobility has been interpreted as lack of assimilation or discrimination by one group or another.

Measurement of Social Mobility Most of the research in this area has used the standard occupational mobility table which presents the occupational distribution of a sample of adult men and a similar distribution of their fathers’ occupations in the marginals of the table with the patterns of intergenerational mobility shown in the cells.

A variety of statistical procedures can be used to describe the mobility patterns in the cells of the basic table. One can discuss the proportion which is mobile—either upward or downward, the effect of being the son of a highStatus or low-status father on the probability of eventually entering a given occupation—and various other summary statistics of mobility. However, there are limits to the utility of such tables in examining anything more than the bivarate association of father’s and son’s occupation. (A number of the methodological issues regarding the use and interpretation of mobility tables were discussed by Duncan, 1966b.) Any attempt at multivariate analysis using the standard social mobility table framework quickly becomes very cumbersome. It is possible to introduce third variables as controls and construct additional social mobility tables for each category of the control variable, but the result is very small frequencies in many cells, unless the sample is very large or the social mobility table has very few rows and columns. Additionally, reading and interpreting very large

tables, controlling for other variables, becomes a complex task for both the analyst and the reader. In this analysis, I presented standard intergenerational occupational mobility tables separately for the three major ethnic groups— which demonstrates how difficult it becomes to summarize multivariate analysis using large mobility tables. Some analysts have tried to construct mobility indices, based upon difference scores between social positions of origin and of destination, and have then correlated this index with other relevant variables. The difficulty is that the mobility indexes of two individuals could be of equal magnitude but their actual movement in the social structure may be quite different. And to correlate other relevant characteristics, such as education, with 38

such a mobility index would be to lose the critical information of origins and destinations. Another limitation in the analysis of mobility tables is that the intergenerational changes in them cannot be related in a determinate way with changes in the occupational structure over a span of years (Duncan, 1966b). Let us consider the usual case where the data on the distribution of men by occupation has been gathered from a representative survey of adult males. The distribution of the fathers by occupation is based upon their primary occupation as reported by their sons (sample of adult males). The array of these fathers by occupation does not refer to a specific earlier generation in the labor force at any point in time. Because of the variance in ages of fathers and sons, the distribution of fathers in the labor force of a specific cohort of sons may range from when the data were gathered (some fathers would be still currently working) to 70 or 80 years earlier. Another complication is that some fathers would be counted more than once because they have several sons in the current labor force while other men in the parental generation would not be counted at all, having no sons in the current labor force. These demographic facts limit any effort to relate traditional analysis of social mobility to the redistribution of status positions (occupations) over time or any effort to separate structurally induced mobility (resulting from changes in the occupational structure due to technological change) from exchange mobility (based upon the compensating movements of some persons up and others down). There have been several efforts to construct the appropriate models which would take into account the complicated processes of labor force entry and exit, differential fertility, and intra- and inter-generational mobility in dealing with overall changes in the occupational structure (Matras, 1961; Matras, 1967). However, it does not appear likely that such models can be widely utilized because of the dearth of the necessary empirical data.

| An alternative conceptual framework for the study of social mobility has been suggested by Blau and Duncan (1967). Basically, they view the process of social mobility from a life-cycle perspective: an individual begins life at this origin status (father’s occupation), passes through the educational system and reaches an occupational destination. This view of the process or model

leads to an evaluation of the relative effects of various social background factors upon socioeconomic attainment by multiple regression techniques. This form of analysis will be pursued in subsequent chapters; in this chapter, I utilized the traditional intergenerational mobility table and variations of it to

describe the ethnic stratification system of Peninsular Malaysia. Such an analysis will provide an introduction to the subsequent chapters as well as provide a summary perspective on the process of mobility.

Intergenerational Occupational Mobility, by Ethnicity Table 4.1 provides the percentage distribution of the social origins and adult occupational attainment of the sample of married men from the West Malaysia Family Survey. (I refer to the sample of married men as sons to contrast them

with their fathers, whose occupational composition specifies their social origins.) As noted above, the distribution of fathers by occupation does not represent a real population at an earlier point in time, but these figures are 39

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differences in the expected distribution of current occupations. In a complementary fashion, the effect of ethnic differences in transition rates can be measured by comparing ethnic differences in current occupation (observed) and subtracting the ethnic differences in the expected distributions. For instance, the delta index between Malay and Chinese current occupational distributions was 51.4, and between the expected Malay and Chinese occupational distributions was 22.0. The difference between these two figures (51.4-

22.0=29.4) is a result of the differences between the Malay and Chinese transitions rates shown in the first two panels of Table 4.4. Clearly these ethnic differences in transition rates determine over half of the ethnic inequality (between Chinese and Malay males) in occupational distributions.

These patterns are shown in the cells of Table 4.4. We begin by examining the cells which represent occupational inheritance where sons follow their fathers’ careers (within these broad categories). In a square matrix, which had the same number of occupational categories for both the sons and their fathers, the occupational inheritance cells would be the diagonal of the table. Since this table has eight major occupational categories for sons and only four for fathers, occupational inheritance cells may have several occupational categories for sons to match those of the fathers’ classification. The appropriate cells representing occupational inheritance have been underlined in Table 4.4.

In general, Chinese men seem more likely to inherit white-collar and blue-

collar (especially craft and laborer) occupations than are Indians and Malays. In the agricultural sector, the relationship is reversed: over 76 percent of the sons of Malay farmers inheriting their fathers’ jobs, and almost 67 percent of Indian sons of farmers do likewise, while only 36 percent of the sons of Chinese

farmers go into agriculture. Socially mobile sons of Chinese farmers (also of blue-collar and white-collar fathers) are particularly likely to enter sales or craft occupations, which are perhaps more open to them because many of the employers are Chinese. Malay sons of blue-collar fathers are more likely to enter professional occupations than are either Chinese or Indians. Downward mobility into agriculture is much more common among Malays and Indians than among Chinese. It is possible that some of the Malays have retired from their regular urban occupations and bought land in the village. Sons of Malay professionals are more likely to get into service and transport and communication occupations than are the comparable groups of Chinese and Indians, a situation which may reflect the internal heterogeneity of some of these categories. For instance, military and police forces are categorized as service workers. A military or police career may be more likely among sons of the Malay middle class than among Chinese or Indian youths. Although this analysis allows us to separate the effects of dissimilar originstatus composition and differential rates of social mobility in explaining ethnic inequality in occupational attainment, it is not a convenient context in which to extend inquiry into other variables. Differential composition by rural and urban origin, as well as differences in educational patterns may be important

in accounting for ethnic differences in occupational distributions, but to examine them it would be necessary to extend the tabular analysis beyond the limits of the numbers of cases in the sample. Table 4.4 contained 135 cells, 46

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which was acceptable since our total number of observations was 5,457. However, almost half of the number of observations were in three cells, representing farmers who were sons of farmers. To expand the analysis with additional control variables would result not only in many empty cells and many with

small frequencies, but also in more complex description and interpretation than seems prudent. For this reason, I postpone multivariate analysis till the next chapter, where regression techniques are used. Conclusion Analysis of ethnic differentials in social mobility in the occupational structure rests on the assumption that the distribution of occupations of adult men can be explained by the distribution of their social origins (fathers’ occupations) and the transition matrix of intergenerational rates of occupational mobility. One might argue that what I have considered determinants of the distribution of occupations are merely components, and that the real determinants are the causes that have led to differential distribution of social origins and the factors in the social structure that influence differential patterns of recruitment or selection into occupations. To this I can only respond that this is a preliminary examination of ethnic inequality, and that analysis of more remote causes must be built upon a firm foundation of more proximate determinants or components.

Approximately 43 percent of the delta index of inequality between the occupational compositions of Malay and Chinese men is due to differences in social origins while the remainder (57%) is due to differential transition rates of father-to-son mobility. The delta indexes between Malays and Indians and between Chinese and Indians are considerably smaller than the Malay-Chinese gap (24.6 and 31.6 to compared to 51.4). Sixty percent of the Malay-Indian difference is due to differential social origins, in contrast to 24 percent of the Chinese-Indian difference. (These figures summarize the patterns that can be

seen from inspection of Table 4.1 and 4.4). Malays, and to a lesser extent Indians are less successful in achieving urban occupations than are Chinese, because they are more likely to come from agricultural origins and are less able to leave to enter other occupations as adults. Malays and to some extent Indians also seem less able than Chinese to pass on or inherit urban occupations from their fathers. Sales or craft occupations seem to be the most likely destination of socially mobile Chinese men while Malays and Indians are most often socially mobile downward into agriculture.

This chapter has provided a description of ethnic patterns of mobility in the occupation structure. The succeeding chapters analyze the same question within the theoretical and methodological context of what has been called the status attainment process (Haller and Portes, 1973).

48

CHAPTER 5

SE THE SOCIOECONOMIC LIFE-CYCLE MODEL AND ETHNIC STRATIFICATION

What determines the ethnic differentials in socioeconomic attainment? To go further into this question, this chapter introduces a new strategy of analysis and then applies it in an examination of the ethnic variations in educational achievement. The following chapter will further extend this analysis to socioeconomic differentials in occupation and income. One might characterize this analysis as continuing the thrust of the traditional analysis of social mobility, but it reformulates the problem from one dealing with the bivariate association between father’s and son’s occupation to a multivariate analysis of the determinants of the son’s occupation, father’s occupation being but one of several independent variables.

The Socioeconomic Life-Cycle Model The theoretical perspective and techniques of analysis in this phase of the research can most aptly be called the Socioeconomic Life-Cycle Model (Duncan, 1967). In various other contexts, it has been referred to as the process of Stratification (Duncan, 1968a), and the status attainment process (Sewell and Hauser, 1972; Haller and Portes, 1973). However named, it originated in the pathbreaking publication of Blau and Duncan (1967, especially chapter 5). In a sense, this is an extension of the father-son mobility analysis presented in the preceding chapter. However, attention is shifted from the mobility pattern to a Statistical analysis of factors affecting socioeconomic achievement. For example, occupation is posited as the dependent variable, and then the effects of certain background variables, one of which is father’s occupation are measured. This procedure allows for the construction of a causal model as simple

or as complex as the data permit, with no basic change in the conceptual framework. It also allows for the use of sophisticated statistical techniques, 49

permitting a more powerful examination of theoretical differences than was possible with the conventional techniques. The basic assumption behind this model is that an individual moves through a sequence of socioeconomic positions, and that positions in later life are affected by earlier ones.

The simplest version of this model identifies three stages: origin status, education, and adult status (Figure 5.1). Origin status, the position in the

—

Figure 5.1: The Basic Model of the Socioeconomic Life-Cycle

_ Socioeconomic NN Educational a Attainment

socioeconomic hierarchy into which one is born, is usually measured by father’s occupation, but other indicators, such as family income would be use-

ful if data were available. The next stage, education, is seen as largely dependent upon origin status for economic support, parental encouragement, and other familial resources. In turn, education is usually considered both as an intervening variable and an important independent determinant of socioeconomic achievement. While education is generally thought most important in the imparting of greater skills or ‘‘job qualifications’’, it may also contribute to further achievement to the extent that it increases contact with or visibility to potential employers.

This basic model can be expanded almost indefinitely by the introduction of additional variables. For example, income can be considered as another achievement variable, and residence, migration, mother’s socioeconomic characteristics, ability or intelligence, and various psychological factors can be introduced as background variables (see Duncan, Feathermen, and Duncan, 1972 for an analysis of some of these topics). A whole series of important questions taken from the literature on stratification can be empirically investigated in this manner. First, how rigid is the system of social stratification? How much difference do humble or wealthy origins make in socioeconomic achievement? By what mechanisms are advantaged

positions passed on to succeeding generations? For instance, a successful father could pass his high status to his son by giving him a first-class education or alternatively, by hiring him in a high-status position in his own business or in some other firm or institution over which he has influence, regardless of his son’s education. Although the correlation between father’s and son’s occupation would be the same in both examples, the structure of stratification would be quite different.

In most societies, there are both rigidity (at various stages in the process) and possibilities for movement in the stratification system. While research in 50

recent years has begun to present empirical analysis of these patterns (Blau and Duncan, 1967; Featherman, 1971la, 1971b; Kelly and Perlman, 1971; Jones, 1971; and Kelley, 1973), it is probably still too early to pronounce a given level of mobility very high or low.

Applying the Model to Ethnic Stratification Although this model of the socioeconomic life-cycle has usually been applied to studies of stratification of the total population, it can also be applied to studies of the differential achievement of sub-groups, such as ethnic communities. It is then possible to measure the relative importance of ethnicity as a determinant of achievement as compared to other determinants, education and social origins. In other words, it can be used to discover if the differential distribution of origin characteristics among various ethnic groups accounts for their socioeconomic differences rather than being the effect of ethnicity itself. Generally, we think that ethnic groups which are socially and economically unequal must have different patterns of mobility. Duncan and Duncan (1968: 356) note that social investigators often assume that the mobility differentials produce the relative socioeconomic positions of minorities. However, this need not necessarily be the case in the short run. As has been noted (chapter 4), ethnic groups could have reached unequal levels of socioeconomic achievement simply as a result of the fact that they began life unequally. The disadvantage of certain ethnic groups may be one common to all poorer persons, irrespective of ethnic status; then a given ethnic group with a lower socioeconomic distribution in one generation may pass it on to the next generation by inheritance. This pattern could be described as the inheritance of poverty. From Markov chain analysis Lieberson and Fuguitt (1966) have shown that such a structure can not be maintained indefinitely; if different ethnic groups, initially unequal, experience the same mobility regime, then a similar distribution of status positions will emerge in several generations.

The model of the socioeconomic life-cycle has been used to compare the process of stratification among the various minorities in American society (Blau and Duncan, 1967, chapter 6; Duncan and Duncan, 1968; Duncan, 1969; Featherman, 1971c). Although most American minority groups reach lower than average socioeconomic achievement there seems little evidence of a strong ethnic disadvantage beyond poor social origins, except among Black

: and Spanish-origin Americans. In other words, that persons in America from various European ethnic communities are more likely to be in lower-status occupations than the average is a disadvantage largely attributable to the poverty of their origins, not to any additional handicap they faced because of their ethnic status. However, Blacks and Spanish-origin Americans seem to face additional disadvantages which cannot be explained by the greater likelihood of their coming from more humble origins.

Culture and Discrimination as Explanations How can this additional disadvantage of certain ethnic groups be interpreted? Two major theoretical alternatives which are widely discussed in both popular and sociological circles are culture and discrimination. The cultural 51

thesis is that the ethnic groups each have their own traditions which offer more or less motivation to achievement. In the simplest form, this posits that certain ethnic groups emphasize values of thrift, hard work, and deferred gratification

which gives then an advantage over other cultures whose value structure is more oriented towards sociability and leisure. These ideas have often been expressed in the American sociological literature under a general theory of ‘‘the need for achievement’’ (Rosen, 1959). In Malaysia, the cultural differences between the Malay and Chinese community are often stressed by the man in the street and the social scientist alike. A recent book described these differences as follows:

Malay values give the highest priority to getting along with others, and Malay social behavior is concerned with ways of showing mutual respect between persons according to a carefully calibrated scale of social status, with highest status given to a traditional hereditary ruling group. Chinese values are primarily oriented toward con-

tributing to the success and prestige of the patrilineal family, with effective competition and skill at accumulating wealth receiving the greatest social rewards (Henderson, 1970:249). From this perspective, one would argue that even with equivalent socioeconomic backgrounds (same origin status and education), Malays would be less likely to achieve because they are less motivated. An alternative explanation of the same empirical finding (ethnicity has a net effect on achievement, independent of social origin) is that Malays encounter discrimination in Malaysian society. Discrimination can occur in a variety of institutional environments, such as schools, the job market, or economic institutions, and teachers, employers, and job supervisors may give preferential treatment to certain ethnic groups and not to others. It is pehaps easier to discriminate in certain employment markets where formal qualifications are not

required and probably more difficult in educational institutions and certain occupations, such as the professions, where ‘‘paper qualifications’’ and other objective criteria are supposedly used. I have no direct way of distinguishing between these alternative explanations of any residual ethnic ‘‘effect’’ on achievement since the survey did not gather data on psychological orientation to work or the perception of discrimination (For some pioneering work, see Featherman, 1971c; and Duncan and Featherman, 1972.) However, I will attempt to speculate on the relative merits of these arguments, basing my discussion upon the findings that emerge.

A Model of the Socioeconomic Life-Cycle of Peninsular Malaysia In essence, I am adapting to another society a model of the process of socioeconomic attainment developed in studies of stratification in the United States. It is necessary to maintain sufficient comparability for a cumulative research

tradition to be enlarged, yet it is also important to include other variables which might be relevant to the particular situation. Fortunately, the data (Family Survey) of this phase of the analysis were especially rich in the range of variables that could be included in the model of socioeconomic attainment (Figure 5.2). The variables are arranged in chronological order in terms of the life-cycle, with occasional exceptions. Thus each variable is assumed to have 52

Figure 5.2: SOCIOECONOMIC LIFE-CYCLE MODEL OF THE PROCESS OF STRATIFICATION: PENINSULAR MALAYSIA

Occupation Income Occupation Residence |

an effect (or influence) on all variables following it in the life cycle (moving from left to right in the diagram). The great value of the socioeconomic life-cycle model is that it provides a logical rationale to order variables in a causal sequence, facilitating interpre-

tation of the empirical analysis. The first three characteristics, Ethnicity, Father’s Occupation, and Birthplace, are all assumed to be fixed at birth and to remain constant throughout the life-cycle. It is possible to change ethnic Status as a result of religious conversion (a Chinese or Indian who converts to Islam is often said to have ‘“become a Malay’’), but this is a rare occurrence. Thus there is no temporal variation among the three variables to suggest causal priority. For reasons to be explained later, I do, however, order these variables

in the subsequent statistical analysis of the determinants of socioeconomic attainment.

The expected effects of Father’s Occupation and Birthplace upon later variables in the model are suggested by previous work in social stratification: men born into urban families whose fathers are high in status enjoy more advantages and opportunities. The Family Survey asked the occupation of the father at the time when the son (husband of wife being interviewed) was twelve years old. This is about the age at which a youth would be completing primary schooling and perhaps entering secondary school—a critical stage in the socioeconomic life-cycle. The next two variables are number of Years of Schooling and the medium of instruction in the highest level of school attended (Educational Medium). Generally, it is to be expected that the higher the level of education, the greater the probability of increased socioeconomic achievement. English-medium schooling has reputedly played a key role in education for positions of high status in the professions as well as for work in the government bureaucracy. Current Residence in included as a variable to measure the 53

relative access to job opportunities. Most of the occupational positions of higher status are primarily found in cities, and there is a wide variation in the urban-rural distribution of each ethnic community.

It might be argued that Current Residence is prior to Occupation, or alternatively it might be that Occupation exerts the pull to move to current location. The relationship between residence or migration and the process of socioeconomic attainment is undoubtedly complex, and it has been simplified by an assumption which seems to be the most reasonable. Occupation and Income are taken as the key dependent variables representing socioeconomic achievement in the contemporary Malaysian stratification system. An overview of ethnic variation among the variables in this model (Table 5.1), shows the percentage distributions of all variables in the total population and each ethnic group. The distributions of Occupation and Father’s Occupation are the same

Table 5.1: | Socioeconomic Characteristics of Married Men, by Ethnic Community: Peninsular Malaysia, 1966-1967 Percentage Distribution

Total Pop. Malay Chinese Indian Father’s Occupation*

Prof. and Admin. 4.0% 3.1% 6.5% 4.2%

Clerical 2.3 1.222.0 4.1 7.7 4.9 Sales 8.2 3.9 Service 2.2 1.8 2.0 5.3

Process 5.6 3.4 9.0 12.4

Craft and Production

Transport and

Communication 2.3 1.7 3.78.3 3.2 Laborer 3.4 1.1 8.3 Agricultural 58.9 72.0 26.5 41.0

Not Reported 13.1 11.7 18.0 13.0 Place of Birth Rural 34.9% Small74.2% Town 89.2% 12.8 6.4 31.460.8% 16.4 Town or City 11.5 4.2 29.1 19.4

Not Reported 1.5 0.2 4.6 3.4 of Schooling 0Years 20.3% 1-3 16.925.6% 14.2 5.8% 24.1 14.6% 19.8

4-5 23.222.1 25.719.5 16.6 11.6 23.1 6 20.2

7-8 6.0 4.4 7.4 13.1 9-10 5.1 2.8 10.5 7.7

1] 2.3 1.5 3.4 4.9 12 or more 2.9 1.7 6.4 2.9

Not Reported 3.1 2.0 6.4 2.2 54

Medium of Education

English | 9.5% 6.1% 12.5% 22.7% Other or Not Reported 90.5 93.9 87.5 77.3 Current Residence

Rural 71.8% 85.9% Non-Metro Urban 14.832.1% 9.3 31.462.9% 16.7 Metropolitan 13.4 4.8 36.5 20.4 Husband’s Occupation

Prof. and Admin. 6.8% 6.3% 9.1% 4.4%

Clerical 4.2 2.824.5 7.2 5.3 6.7 Sales 8.4 3.9 Service 5.8 6.4 4.7 5.0 Processes 8.4 4.5 19.1 12.5

Craft and Production

Transport and

Communication 6.110.9 5.2 7.5 9.0 Laborer 6.4 4.3 11.8 Agricultural 53.3 66.0 16.3 45.2

Not Reported 0.6 0.6 0.6 0.1 Monthly Income

No Income 1.2% 1.6% 0.6% 0.6%

$1-49 28.4 40.4 2.0 7.9 50-99 24.9 27.1 12.5 35.6 100-149 12.118.9 23.0 14.4 21.5 150-19915.6 9.8 6.2

200-299 8.9 6.1 18.3 8.1 300-499 5.9 3.9 11.4 7.2 500-749 1.9 1.0 4.8 1.9

$750 or more 1.3 Not Reported 2.2 0.3 1.2 2.9 5.7 1.8 1.0

*Occupational category titles have been abbreviated; for complete listing, see Table 3.2.

Source: 1966-67 West Malaysian Family Survey as those presented in chapter 4. Place of Birth is classified into three categories plus a residual category of ‘‘Not Reported’’. Almost nine out of ten Malay men

in the sample were born in rural areas, while 60 percent of the Indians, and about a third of the Chinese were born in rural areas. Years of Schooling contains eight categories and the residual Not Reported category. Malays are somewhat more concentrated in the lower educational attainment categories than are Chinese or Indians. Under the variable, Educational Medium, the categories are English and Other Language or Not Reported, a category which includes those who have had no formal education as well as those educated in a non-English medium school. Other languages used 55

in the classroom of Malaysian schools were Malay, Chinese (usually Mandarin), and Tamil, the commonest language among Malaysian Indians. Only about one man out of ten in the total sample had an English-medium schooling,

and Indians had the highest proportion in this category. If a man had part of his education in a vernacular schol and part in an English school, he was classified as having had an English-medium education.

Current Residence 1s defined by the size of the place where the respondent lived at the time of the survey. Metropolitan includes the five largest cities of Peninsular Malaysia, all of which had populations of 75,000 or more according to the 1957 Census of Population. Non-metropolitan areas include smaller cities and towns whose population ranged from 7,760 to 74,999, and rural areas make up the rest of the country, specifically all places with less than 7,760 residents. As the figures show, Chinese are much more likely to live in metropolitan and non-metropolitan urban areas than are Indians and Malays. Chinese men have higher monthly cash incomes on the average than either Indians or Malays, Income being measured as the total cash income received by the husband during the last month. At the time, in 1966-67, when these data were collected, about three Malaysian dollars were equal to one United States dollar ($3M = $1 US). However, this rule of thumb no longer holds. Income, stated as a single figure, suggests a precise measure, but it is possible that cash income is not a complete measure of remuneration: in the subsistence sector, home-grown food and rent-free housing may be important additions, unmeasured because they do not enter the money economy. Even in cities, an employee may receive bonuses, special allowances for housing, and other subsidies not counted in his regular income.

Multiple Classification Analysis The basic statistical technique used here is multiple classification analysis (Andrews, et. al., 1967), a method which differs from usual regression techniques in that all independent variables are categorical rather than quantitative. These categorical variables (often called dummy variables) are coded in binary fashion where ‘‘1’’ indicates presence of a characteristic and ‘‘0’’ indicates absence. For example, the nominal variable of Ethnicity becomes four inde-

pendent dummy variables: Malay, Chinese, Indian, and Ethnicity Not Reported. This last category just insures the inclusion of cases where data are missing for a variable. In any regression equation this method will produce a Statistical measure of effect or simply a regression coefficient of the dependent variable on each category of the independent variables. Because there are more coefficients than there are independent normal equations based upon the least-squares criterion (Melichar, 1965:374), it is necessary to add a constraint to each set of categories of an independent variable. This is usually done by constraining the ‘‘b’’ (regression coefficient) of one category of each set to zero by simply omitting it from the regression equation. For instance, in the regression equation of Income on all independent variables, one category each of the occupations, current residences, educational levels,

educational media, birthplaces, father’s occupations, and ethnic groups is omitted. The set of regression coefficients which comes out of all this represents statistical measures of the ‘‘effect’’ of being within a category of a parti56

cular variable. However, the coefficients are not interpretable in isolation; the ‘‘effects’’ are deviations from the omitted category in the calculation. It is a fairly simple procedure (Melichar, 1965: 374-375) to transform all the coefficients, including those omitted, into deviations from the overall grand mean of the dependent variable. This allows for an interpretation of each coefficient as the net effect or deviation from the average value of the dependent variable (e.g., Income) as a result of being in a particular category of an independent

variable. ,

To handle independent variables in multiple classification analysis requires simply the coding of each category of all independent variables as dummy variables, including a missing data category, followed by ordinary leastSquares regression analysis, one category of each independent variable being always left out in the actual regression procedure. Then, by using Melichar’s procedure, all the unstandardized regression coefficients can be adjusted into deviations from the grand mean of the dependent variable, and in the same pro-

cedure, a coefficient may be recovered for the omitted category.

Dependent Variables In the model of the socioeconomic life-cycle here presented, Education, Occupation, and Income are treated as dependent variables. Under Education,

there are two variables of interest: Years of Schooling, and the Attendance at English-Medium Schools. A variable in the original data tape, which coded education of the husband in single years of completed scholing, had a slightly different distribution and a different number of missing values from the variable Years of Schooling (Table 5.1), but I used the variable Single Years of Schooling as a dependent variable for educational attainment, because it gives an exact value for each individual. In the regression analysis I used a pairwise, present

procedure which calculates the matrix of correlation coefficients (for input into the regression analysis), based upon the maximum number of observations between each pair of variables. Using Single Years of Schooling as a dependent variable resulted in missing data only for the dependent variable since all missing data categories of independent variables were simply coded as dummy variables. This means that almost all coefficients in the correlation matrix are estimated on the basis of 5457 observations, except those coefficients

paired with educational attainment (Single Years of Completed Schooling) from which 255 weighted cases (actually 453 unweighted cases) were excluded.

Medium of Education, as a dependent variable, was coded as a dummy variable where *‘1’’ meant at least a portion of education in an English-medium

school and ‘‘0’’ meant no formal schooling or education completely in nonEnglish medium schools. The grand mean of such a variable is the proportion of the total sample of husbands that had some English-medium education. An occasional problem in the use of a proportion as a dependent variable

in regression analysis is that some predicted values will be outside the real limits (below 0.0 or above 1.0). As this seemed not to be a major problem in most equations, I did not utilize Logit analysis or other techniques to deal with it.

To treat occupation as a dependent variable required some adaption of the 57

original variable (occupation of husband) which was coded in a two-digit classification that ranged from 00 to 99 (Appendix B). The classification into eight major occupational categories (chapter 4) was derived by grouping occupations into meaningful units containing sufficient numbers and hierarchically arranged in rank order according to mean income and education of the incumbants (Table 3.2). The occupational-prestige and socioeconomic-status scales

of occupations that have been used in studies of stratification in the U.S. (Duncan, 1961: 109-138; Hodge, Siegal, and Rossi, 1966: 322-334), did not seem suited to a society whose economic bases were quite different. Instead, I coded each major occupation as a separate binary, dependent variable, resulting in eight dummy variables, each having as its mean, the proportion it contained of the total sample of married men. In percentage terms, this ranges from a low of 4.2 in clerical occupations to a high of 53.3 in agriculture. Using this procedure with eight separate dependent variables means that the influence of independent variables is measured as effects upon entry into that occupation in contrast to all other occupations.

Income is a simpler variable because, like education, it provides natural interval-scale measurement. Actually, Income was originally coded into nine categories ranging from zero income to $750 or more per month plus the residual category, Not Reported. In order to create an interval-scale measure of income, each observation was assigned the income represented by the midpoint of the appropriate category; for instance, a man whose income was between $150 and $199 was coded as $175. To those in the highest category, $750 or more, a value of $900 was assigned. Similar to the use of education as a dependent variable which also has missing values, a pairwise-present procedure was used so that correlation coefficients with Income as a variable were based on 118 fewer cases (unweighted 194 cases) than the total sample of 5457.

The Model as a Set of Equations To estimate the relationships in Figure 5.2, I did not use the technique of path analysis (Duncan, 1966a), but the logic of my use of multiple classification analysis is quite similar. Multiple classification analysis provides a suitable framework within which to deal with the problem of many categorical independent variables. It also requires no assumption of linear relationship between independent and dependent variables. One equation with all independent variables in the model would allow for the estimation of a net effect of each independent variable on the dependent variable. Such a simple equation, however, would not really provide a proper framework to analyze the

theoretical model in Figure 5.2. I am interested not only in the net effects (‘‘direct effects’’, in path analysis terminology) but also the way in which certain background factors affect intermediate variables, which in turn affect the dependent variables. The usual procedure when multiple classification analysis is used is to estimate both gross and net effects and sometimes effects net of a key variable (Bumpass and Sweet, 1972). The gross effects are simply the coefficients resulting with only one independent variable in the model. Substantively, they are the differences in means of the dependent variable in each category of the independent variable. A net effect is the coefficient in an equation with several independent variables; it is interpreted in much the same way 58

as a partial regression coefficient when other variables are statistically controlled. In the subsequent analysis, I present a sequence of models or equations in which I add one independent variable (set of categories) at a time until all background variables are included. This allows observation of how the gross effects of earlier variables are modified by each subsequent variable. The ordering of variables is crucial to any interpretation. Since ethnic differences are the pri-

mary focus of this study, Ethnicity is always the only variable in the intial model. The results of this first model show gross effects or the observed differences on any dependent variable between ethnic communities, then Father’s Occupation, Birthplace, Years of Schooling, Educational Medium, Current Residence, and Occupation are added in that order’. The changes in the co-

efficients of Ethnicity from model to model show what ethnic differences would be if ethnic groups had the same distribution of social characteristics on the other variables in the model. For instance, part of the income gap between Malays and non-Malays 1s due to the fact that Malays are more likely to have been the sons of farmers and others of lower status than non-Malays. The

tions. (

ethnic coefficients in the second model (with only Ethnicity and Father’s Occupation in the model) show what would be the gap in Income between Malays and non-Malays if they had the same distribution of fathers’ occupaThis logic of the procedure is continued throughout the analysis so that one can observe what variables are most responsible for ethnic differentials. Inas-

much as the basic order follows a rough chronological pattern, the set of models demonstrates not only the relative effects of both distant and proximate variables, but also how early influences are mediated by other events in the socioeconomic life-cycle. The most debatable point of the ordering of variables is perhaps that of Father’s Occupation and Birthplace. Although the present order allows Birthplace only to have an effect which is net of Father’s Occupation, this is not to suggest that there is any strong theoretical reason for this particular sequence.

Social Background and Education Table 5.2 shows the effects of social background on Years of Schooling in the left-hand panel and on the likelihood of an English-medium education in the right-hand panel. Each panel has three models which successively add Ethnicity, Father’s Occupation, and Birthplace. In the left panel all coefficients are expressed as deviations from the grand mean of 4.4 years of education.

The first model shows that Malays have an average of 0.5 of a year less schooling than the average of the total population, while Chinese have about 1.1 years more; that is, there is a gap of slightly over one and a half years between the average Chinese and Malay. One might ask how much of this ethnic gap is due to the fact that Chinese and Malays have an unequal distribution of origin statuses. For instance, Chinese are more likely to be sons of white-collar workers and others in occu“These are the seven variables used in predicting Income. Fewer variables are included in the models predicting the occupation and the education variables. 59

Table 5.2: Effects* of Social Background of Married Men on the Number of Years of Schooling and the Probability of Having an English-Medium Education: Peninsular Malaysia, 1966-1967.

English-Medium

Years of Schooling Education

Grand Mean = 4.4 Years Grand Mean = 9.5 Percent

Ethnicity (1) (2) (3) (1) (2) (3) Malay -0.51.1 -0.2 0.2% Chinese 0.6-0.1 02—-3.4% 3.0 -1.7-14% 4x—6.0 Indian 0.6 0.3 0.2 13.2 10.0 8.9 Father’s Occupation Professional and

Administrative 3.3 2.9 30.8% 27.0%

Clerical 3.4 1.0 2.9 45.3 Sales 1.3 6.2 39.9 3.5

Service 1.6 1.2 13.5 9.5 Process 0.9 0.7 5.6 3.2

Craft and Production Transport and

Communication 1.4 1.1 14.5 11.3 Laborer —O0O.1 —0.4 -1.8 —-4.7 Agricultural —0.6 —0.5 —6.1 —4.5

Rural | —0.30.9 —3.8% Smalltown 9.4 Birthplace

Town or City 1.2 14.4 R? 4.2 14.3 16.7 3.5 16.5 20.2

*The coefficients of the residual Not Reported categories of the independent variables have been omitted from this table. Source: 1966-67 West Malaysian Family Survey.

pations high in status, while Malays are more likely to be sons of farmers. We can control statistically for this difference in background with Model 2, which shows that being the son of a professional or clerical worker adds about three years to one’s education. Most other urban occupations add about a year. When Father’s Occupation is controlled, the ethnic differential narrows to 0.8 of a year of school. In the third model, Birthplace is added. Being born in a small town adds 0.9 of a year of school while a town or city adds about 1.2 years. Some of the effects of Father’s Occupation are reduced in this model. Similarly,

the ethnic differential is narrowed to about 0.3 of a year of school between 60

Malays and non-Malays. The inclusion of two variables reduced the ethnic differential between Malays and Chinese by 80%. Clearly, most of the educational gap is a result of the fact that each group begins life in unequal circumstances. There may be other aspects of unequal social origins (not measured here) which might reduce the gap even further. The probability of receiving an English-language education can be analyzed in a similar manner. The grand mean of this variable is 9.5 percent of the total sample. Chinese men were three percent more likely, and Malays three percent

less likely to have attended an English-medium school, while Indians were 13 percent more likely. Addition of Father’s Occupation and Birthplace results in a major shift in the Malay and Chinese coefficients. The reason why Chnese are more likely to have attended English schools is that they enjoy an advantaged origin because of Father’s Occupation and Birthplace. Controlling for these variables shows that there is actually a net Chinese effect of minus

almost six percent. Controlling for the relatively disadvantaged ongins of Malays results in a slightly positive effect for their ethnic coefficient. Controlling for social background leaves Indians still with a net positive effect of nine percent for Ethnicity. Perhaps rural Indians (most likely born on estates) had closer access to English-medium schools than did rural Malays. Also interesting is the extremely strong effect of being the son of a professional or clerical worker or of having been born in an urban area on the changes of being educated in an English-medium school.

Basically, most of the ethnic differentials in education are a result of differential social background. Observers of Malaysian society have developed various cultural explanations of the supposedly inferior achievement of Malay students. T.H. Silcock (1963a: 26) had said: ‘*Most of the Malays were peasants and fishermen. Their environment was not conducive to education and their culture did not induce them to want it.’’ The latter half of this statement is certainly misleading. It does not appear that there is much residual educational differential between Malays and non-Malays to be explained by culture or anything else. If each ethnic community had the same distributions of Father’s Occupation and Birthplace, educational dif-

ferentials would be substantially less.

61

CHAPTER 6

THE SOCIOECONOMIC LIFE CYCLE: THE PROCESS OF OCCUPATIONAL AND INCOME ATTAINMENT This chapter will be focused on analysis of the relative effects of ethnicity and social background on income and occupational attainment, a much more complicated analysis than was called for when education was the dependent variable. First of all, the number of independent variables has been expanded. For the equation with Income as a dependent variable there are seven independent variables, as compared to three in the analysis of educational attainment. Since each category of the seven independent variables has a separate coefficient or effect, there are actually thirty-five measured determinants of income. For Occupation as the dependent variable, there are six independent variables or twenty-six categorical effects. Additionally, since each occupational category is treated as a separate dependent variable, there will actually be eight occupational attainment models, each with the full set of independent

variables. Later, I will complicate the analysis even further by testing the assumption of additivity by examining the possibility of interactions between Ethnicity and other social background variables in the process of status attainment. The question guiding the analysis is: What factors account for ethnic inequality in income and occupation in Peninsular Malaysia? In particular:

Are these differences due to the unequal distribution of social background characteristics, or to some other factor associated with ethnicity?

Social Background and Income Although Occupation should follow next in chronological sequence, I will begin with an analysis of the effects of social background on Income, which has only a single dependent variable, and will therefore be more simple and straightforward. Income refers to the monthly cash income of husbands married to women in the childbearing years. The grand mean of income of the sample 62

is $134 (Malaysian dollars) per month. As has been noted, each husband was assigned the mean of his income category.

Table 6.1 shows the sequence of seven cumulative models of the effects of social background on Income. The first model includes a single social background variable, Ethnicity, as an independent variable. The second model adds Father’s Occupation to Ethnicity as the independent variables in the regression

equation. Each subsequent model adds successive variables in the socioeconomic life cycle until the seventh model, which includes all seven of the social background variables. The coefficients in the table are expressed as deviations from the grand mean, net of other variables in the model. We begin with a comparison of the relative magnitude of the effects in the seventh or final model. Net ethnic differences are —$14 for Malays and +$34

for Chinese, a gap of $48. Many other factors loom much larger as direct determinants of income: the net effect of being the son of a professional is positive, $47; the net difference attributable to having been born in a town or city rather than in a rural area is $28. There seems to be a consistent pattern in which higher education leads to increasingly higher income, especially after nine or ten years of schooling. To have passed the Lower Certificate of Education, which is the national examination on the completion of nine years of

schooling (Form Three), is a minimal requirement for a number of jobs. English-medium education has a net additional effect of adding $63 to the average monthly income. One who lives in a metropolitan area receives $41 more than one living in a rural area. With the exception of a professional occupation, being a service worker has the highest net effect ($52) of any urban career.

All these factors explain 51 percent of the variation (R*) of Income. This can be compared with an R? of 13 to 22 percent (depending on which age group is chosen) of the variation in income in the U.S. adult male population (Dun-

can, Featherman, Duncan, 1972: 40). Social background is found to exert a greater influence of upon Income in Malaysia than the United States—but this finding might be a result of using different variables. Each of the seven independent variables in Table 6.1 adds a statistically significant increment to the proportion of variance explained. Table 6.1 also reveals how the observed ethnic differential is affected by other statuses in the socioeconomic life cycle. From the model of gross effects in the first column, the Chinese-Malay differential in income is found to be $133, but from the last column or final model, the gap is shown to have narrowed to $48. Almost two-thirds of the gross difference in income is due to differences in social background or compositional differences. Again, as in the case of education, it would be difficult to construct a strong theory of cultural differences to account for ethnic differences in economic achievement, since most of the differential can be accounted for by unequal distribution of social background characteristics. Whether ethnic differences in motivation account

for part or all of the residual ethnic difference is a question that cannot be directly addressed here. What variables contribute most to a reduction in the ethnic differential as one moves from the first gross effects model to the final complete net effects 63

Table 6.1: Seven Models of the Effects* of Social Background of Married Men on Monthly Income: Peninsular Malaysia, 1966-1967.

Ethnicity ag @) @38 4 & © VF

Malay —37 -—-27 -18 -16 -17 -12 —14

Chinese 96 70 50 34 Indian 26 12475 43 Il -5 -534 6 Father’s Occupation Professional and

Administrative 158 141 83 72 67 47

Clerical 28 26 Sales 150 51 =—-:125 38 22 62 224217 8

Service 53 34 14 10 Q -ll Process 33 21 13 12 5 —3

Craft and Production Transport and

Communication 75 61 47 40 23 18 Laborer —-15 -27 -13 -13 —9 —]

Agricultural —32 -25 -17 —-14 -10 ~-6 Place of Birth

Rural —19 -I11 -10 —6 —6 Smallor Town 39 43 2238 1825 11229 Town City 73

01-3 —47 -40 -36 -—23 —33 —7 -27 —7 -22 —4 -15 4-5 —14 6 —3 2 0 —2 Years of Schooling

7-8 34 24 21 7 9-10 112 =74 71 48 11 180 =121 = =6115 88 12 or more 234 189 I77 ~~ = 124

Other ~9 -—7 ~~—7 English 84 69 63 Medium of Education

Rural —-17 —10 Non-Metropolitan Urban 40 21 Current Residence

Metropolitan 49 31 Administrative 143

Clerical 33 Husband’s Occupation

Professional and

64

Sales 40 Service 52 Process 8

Craft and Production

Communication —2 Laborer —29 Agricultural —30

Transport and

R? 13.5 24.0 27.3 40.7 42.5 44.3 51.3 *Effects are expressed as deviations from the grand mean of $134 (Malaysian Dollars). The coefficients of the residual Not Reported categories of the independent variables have been omitted from this table.

Source: 1966-67 West Malaysian Family Survey. model? About 50% of the Malay disadvantage and 50% of the Chinese advantage in Income results from the unequal distribution of Father’s Occupations

and Birthplaces, as does also most of the Indian advantage. Comparing the ethnic coefficients in Model 4 with those in Model 3 will answer the question: How much of ethnic inequality in Income is due to unequal educational attainment which is not the result of unequal social origin? As noted in the preceding chapter, net educational differences are small after social origins are statistically held constant, so it is not surprising that these net educational differences are not a major cause of ethnic inequality in income. It is also interesting to note the sharp drop in several of the coefficients of Father’s Occupation from Model 3 to Model 4 and from Model 2 to Model 3. This pattern reflects the fact that much of the effect of high-status fathers is attributable to their having given their sons an above-average education.

Model 5 shows that the addition of Educational Medium actually widens the net Chinese-Malay gap. This is not because English schooling does not boost achievement—it does—but rather that the net Malay-Chinese differential in English-medium education is not the cause of the Malay-Chinese income gap. Model 6 shows that Chinese are more likely to live in urban areas (net of every preceding variable) than Malays and this accounts for another portion of the gap in income. Assortment by occupation after all other factors are controlled does not seem to reduce the gap any further. This may indicate that there is no widespread pattern of discrimination that makes the movement into an occupation a cause of ethnic differentials in income. The change from —$5

to +$6 for the effect on Income of the ethnic group, Indian, from Model 6 to Model 7 suggests that Indian men slightly underachieve in the occupational assortment process relative to their previous social background. To summarize the analysis of the determinants of Income among Malaysian men as measured in Table 6.1: (1) The seven variables in the final model, accounting for 51 percent of the variance in Income, provide a rather powerful

model by social science standards. (2) Although the net or direct effects of Ethnicity are not negligible (the Malay-Chinese differential of $48 is 36 per65

cent of the mean income of $134), they are not much larger than most other coefficients in the complete model, and in several cases less than the effects of other variables. (3) Of the observed differential of $133 between Malays and Chinese (first model), almost two-thirds can be attributed to the differential distribution of social background characteristics, in particular, Father’s Occupation and Birthplace. Consequently, I conclude that most of the ethnic differential in income is due to the unequal distribution of rural agrarian backgrounds among Malay, Chinese, and Indian men. The residual ethnic differential may be consistent with either the cultural explanation or one in terms of discrimination; it is not possible to test the alternatives. Perhaps finer measurement of occupational categories would have reduced the remaining ethnic differential even further.

Social Background and Occupation Earlier data (Table 5.1) have shown that Malay men are more likely to be in agriculture than Chinese or Indians and less likely to be in most urban occupations than Chinese or Indians. Again the fundamental question is: Are ethnic differentials in each occupation due to differences in the distribution of social background characteristics, or to some unique ethnic effect? The analysis of the process of occupational attainment is complicated by the

fact that the eight occupational categories are each treated separately as a dependent variable. As discussed earlier, this list of occupations forms only an approximate social hierarchy; a numeric socioeconomic scale would not be justified. Consequently, I coded each of the eight occupational groups separately asa dummy variable (1 for being in the given occupation, 0 if not in it). This

method has the virtue of analyzing each occupational category as a single entity. The assumption of some dubious scalar relationship among occupations is not required. At the same time, however, all variation within each occupational category is lost. If I had used a single numeric occupational scale, there might have been interpretable differentiation within professional, sales, or other

major categories. In this analysis, all detailed occupational titles within the eight broad categories are coded alike. The same analytical procedures used before were repeated here for each of the eight occupations. Each of the six background variables (Ethnicity, Father’s Occupation, Birthplace, Years of Schooling, Educational Medium, and Current Residence) were entered sequentially in six cumulative models for each of the eight occupations. The full results are so detailed and complex that they threaten to overwhelm and confuse rather than to enlighten. (The complete results are presented in Appendix F, and only partial results are discussed in this chapter.) Table 6.2 shows the effect of Ethnicity upon the probability of engaging in any given Occupation. All of the eight Occupations listed down the left-hand column, with the three ethnic communities under each. The first column, the

grand mean of the dependent variable, is simply the percentage of all employed husbands in each occupation. The next six columns show the effects of Ethnicity, expressed as deviations from the grand mean, in six models of the process of occupational attainment. The first model includes Ethnicity 66

only as an independent variable. Thus the effects are gross effects, representing differences as they exist in the population. The second model includes both Ethnicity and Father’s Occupation as independent variables in the regression equation. Here the ethnic effects are net of Father’s Occupation; they could be interpreted as the ethnic differences which would exist if all ethnic groups had the same distribution of fathers by occupation. Each successive model adds an additional independent variable, and the ethnic effects change accordingly. The ethnic effects in the sixth model show the net ethnic differences after all other variables are statistically controlled.

The amount of variance explained (R”) of each model is also shown. Generally, an increment of one percent of variance explained means that the added variable is statistically significant.

Chinese are more likely than Malays or Indians to be in Professional and Administrative occupations (Model 1). However, the Malay-Chinese differential is reversed in Model 3 where Father’s Occupation and Birthplace are held constant. The Malay effect increases in a positive direction through Model 6, while the coefficients for Chinese, and especially Indians grow larger in a negative direction. This means that Malays are over-represented in terms of their social background characteristics in professional and administrative occupa-

tions, a finding which might be partially explained by the internal heterogeneity of this category, many Malay school teachers in rural areas being lumped together with non-Malay professionals and administrators in urban areas. The findings in this first panel of Table 6.2 cast doubt on any theories which posit either that Malays aspire less to professional careers or that they suffer from discrimination at the point of entry into professional careers (after controlling for differences in social background).

The same basic patterns are evident in clerical occupations. Although Malays are less likely to be clerical workers, their disadvantage is entirely due to unfavorable social background factors, especially Father’s Occupation and

Birthplace. The net coefficients (Model 6) give them a positive effect for Ethnicity while in the case of Chinese and Indians, it is negative. It might be noted that the final R? for clerical occupations, 22.3 percent, is higher than that for any other occupation except agriculture. The increments of variance explained associated with Years of Schooling (16.6—8.3=8.3 percent) and Educational Medium (21.4—16.6 = 4.8 percent) suggest that, independent of social origins, formal academic credentials are particularly important for entry into a clerical occupation. The significance of Ethnicity in both professional and clerical occupations as measured by R?® in the first model is negligible, compared with other social background characteristics.

The pattern in sales occupations is quite different. Here the gross Chinese effect is moderated, but it still remains quite large and positive after all background variables are controlled. Part of the Chinese advantage is due to a favorable distribution of Father’s Occupation (about 22 percent of their fathers are in Sales) and Current Residence. However, the Malay and Indian disadvantage in this sector does not seem to be much affected by any background variable. | argued earlier (chapter 3) that part of the Chinese advantage in Sales 67

Table 6.2: Effects of Ethnicity of Married Men on Occupational Attainment in Six Sequential and Cumulative Models of Social Background Variables in Eight Occupations: Peninsular Malaysia, 1966-1967.

Grand

Occupation Mean Model? Professional and

123456

Administrative 6.8%

Malay -04 03 09 41.29 1.2 1.3 Chinese 2.3 O05 —-10 —1.6 —1.4 -1.7 Indian —-2.4 -3.5 -3.9 -4.5 -4.6 —4.6

R? 03 45 5.1 13.1 13.1 13.2

Clerical 4.2% Malay -14 -06 02-1.2 05 O2 O23 0.7 Chinese 3.1 13 -1.1 —-1.1 Indian 2.5 12 0.5 -0.2 -1.6 —1.5

R? 10 6.1 8.3 16.6 21.4 22.3

Sales 8.4% Malay —4.5 -—-3.4 —-3.4 -3.5 —-3.4 —-3.1

Chinese 16.0 12.5 12.4 12.5 12.0 10.9 Indian —3.1 -—2.8 —-2.8 -—2.6 —2.1 —2.0

R? 8.9 14.2 14.2 15.0 15.3 15.7 Service 5.8%

Malay 05 1.0 12 #233 #213 £42.2

Chinese —1.1 -1.9 —2.4 —-2.8 -2.8 —5.7 Indian —0.8 -—2.0 -—2.1 -2.1 —-2.1 —2.0

R? 0.1 30 3.1 48 4.8 7.6 Craft and Production

Process 8.4%

Malay —3.9 -3.2 -2.9 -2.9 -2.9 —-2.1

Chinese 10.72.4 932.) #852.0 84 1.8 85 £5.8 Indian 4.1 1.9

R? 48 83 85 92 9.2 10.8

Transport and

Communication 6.1%

Malay —0.9 -0.3 02 02 02 £40.8

Chinese -0.12.2 —-1.4 —-1.5 Indian142.9 2.0-1.6 2.2 2.1—3.3 2.2

R? 04 02 2.5 2.8 2.5 4.0

Laborer 6.5% Malay —2.2 —2.1 -—2.0 —-2.0 -1.9 —1.7 Chinese 45 43 £44.1 3.9 3.7 2.9 68

Indian 5.4 49 49 49 352 £5.1

R? 19 33 #34 #40 4.1 £4.3 Agricultural 53.3%

Malay 12.7 80 55 49 5.0 1.7 Chinese — 36.9 —25.4 —18.6 —17.2 —18.2 —7.4 Indian —-8.1 -1.7 O11. 09 2.0 1.5 R? 16.4 27.4 30.0 35.0 35.5 44.6

‘Effects are expressed as deviations from the percentage of the total sample in that occupation. *Independent Variables in Sequential Models of Occupational Attainment. Model 1: Ethnicity. Model 2: Ethnicity, Father’s Occupation. Model 3: Ethnicity, Father’s Occupation, Birthplace Model 4: Ethnicity, Father’s Occupation, Birthplace, Years of Schooling. Model 5: Ethnicity, Father’s Occupation, Birthplace, Years of Schooling, Educational Medium. Model 6: Ethnicity, Father’s Occupation, Birthplace, Years of Schooling, Educational Medium, Current Residence. Source: 1966-1967 West Malaysian Family Survey. and Craft occupations might be due to the higher proportion of Chinese proprietors who are able to employ workers in their small shops throughout the country. If so, it seems that discrimination is a more likely explanation than one based upon differential cultural orientation towards achievement. Although discrimination implies invidious behavior, it may be the result simply of a natural preference for hiring a nephew rather than a stranger who speaks a different tongue. But no matter what the motive, the result is that entry into Sales occupations is more dependent upon Ethnicity than upon other characteristics.

Of the total 15.7 percent of variance explained in Sales occupations, 14.2

percent is already accumulated in Model 2 with only Ethnicity and Father’s | Occupation as independent variables.

As noted, Service occupations include a diverse lot with many police and military personnel among Malays, and many service workers in hotels, restaurants, and domestic employment among non-Malays. Malays have a positive gross effect while non-Malays have a negative effect in the first model, and this differential widens as other variables are controlled. Practically all the Chinese participation in this occupation can be accounted for by their favorable distributions by Current Residence (primarily urban) and by Father’s Occupation. The increments in variance explained in the case of Service occupations suggest that urban life is the primary determinant of entry, Birthplace and Current Residence being the most significant independent variables. The pattern of ethnic differences in Craft and Production Process occupations resembles that of Sales occupations. Chinese and to a lesser extent Indians have strong gross ethnic effects which remain strong though attenuated 69

after other variables are controlled. Both Father’s Occupation and Current Residence are also important to Chinese entering this occupation. But the strong net effects of Ethnicity which remain indicate ethnic selectivity into this occupation, independent of social background. The Malay pattern shows that part of their low participation in this occupation is due to their earlier disadvantages in respect to Father’s Occupation, Birthplace, and Current Residence. However, the net Malay effect in the sixth model is negative, indicating that Malays probably have some disadvantage in entering this occupation even if they have equivalent social background. I suspect that the predominance of

small shops in the industrial sector, which are likely to be owned by nonMalays, retards the entry of Malays into Craft and Production Process occupa-

tions. Also similar to the pattern of Sales occupations, the proportion of variance explained in Craft and Production Process occupations is largely attributable to the first two variables, Ethnicity and Father’s Occupation: 8.3 percent of the total figure of 10.8 percent in Model 6. Transport and Communication occupations show a positive gross effect in the case of Chinese which quickly disappears as other variables are introduced. Here again, Chinese owe much of their participation to their favorable background in terms of Father’s Occupation, Birthplace, and Current Residence. Although Malays are less than proportionately represented in Transport and Communication occupations (Model 1), their net ethnic coefficient is positive (Model 6). Indians, on the other hand, are slightly over-represented in this occupation (positive gross effect in Model 1), and this is not moderated very much by controlling for social background. There is a long history of Indian labor in the government departments which constructed the rail, road, and telecommunication networks of Peninsular Malaysia (Kernial Singh Sandhu, 1969: 285), and perhaps this has resulted in the selectivity in hiring Indians, independent of social background. Chinese and Indians are much more likely to be Laborers than are Malays

and the differential is relatively unaffected by the introduction of other variables, although Current Residence has some impact. In this respect, the pattern of ethnic coefficients is similar to those in Sales, and Craft and Production Process occupations. However, the composition of this occupation is quite diverse, among others, it includes miners. The pattern of ethnic coefficients in Agricultural occupations is very interest-

ing. The gross ethnic differentials as measured in Model | are quite large, in fact, Ethnicity as a single independent variable explains 16.4 percent of the variance. However, the successive addition of other social background variables in the socioeconomic life-cycle model results in a reduction of the direct effect of Ethnicity. In the complete model (Model 6) the net effects of being Malay and Indian are only slightly positive, while being Chinese has only a moderate negative effect (7.4). Most of the substantial differences in the proportion of each ethnic group in agriculture are due to social background characteristics which are independent of Ethnicity. Conclusions Two different patterns of occupational recruitment in the non-agricultural sector emerge from this analysis. First, in a number of occupations (Profes70

sional, Clerical, and partially for Service and Transport and Communication occupations) the advantage of non-Malays seems to be based upon an unequal distribution of background variables. In these occupations being a Malay often has a positive net effect (Model 6), though it is generally small. In other words,

Malay men would be somewhat more likely than non-Malays to be in these occupations if all ethnic communities had equivalent distributions of social background characteristics. With these findings it is difficult to entertain either the cultural thesis that Malays are less ambitious than non-Malays or that they face discrimination at the point of entry into these occupations. There is a different pattern of status attainment evident in Sales occupations, and among Craftsmen and Laborers. Here there is a strong gross differential (Model 1) between Malays and non-Malays. Although the ethnic differentials are somewhat narrowed—Father’s Occupation and Current Residence were generally most important—the remaining differences are still wide in Model 6 after all background factors are controlled. Clearly there is ethnic selectivity into these occupations. I think that the hypothesis of discrimination is more credible here than the cultural hypothesis that Malays are less motivated.

These occupations predominate in commerce and manufacturing, where the small family-managed shop is quite common. As mentioned in Chapter 3, the structure of job-creation and hiring in such industries favors ethnic groups which contain large numbers of owners or managers in small businesses. Since it appears that non-Malays constitute the majority of the employers, an ethnic selectivity in hiring Chinese or Indians is a not unanticipated empirical finding. To salvage the cultural explanation as the reason for the lower net Malay coefficients in Sales, Craft, and Laborer occupations, it would be necessary to construct a theory that Malay men are ambitious to engage in some urban careers but not in others. While this may be possible it is not very convincing. In the four occupations where Malays have a net positive effect (Professional, Clerical, Service, and Transport and Communication) the government plays a major role in job creation, whereas in Sales, Craft, and Laborer occupations the private sector is dominant. Perhaps the fact that the government usually must rely more on formal qualifications gives it a more universalistic basis for hiring. It should also be noted that the Malaysian government follows a system in which Malays are given preference. While paper qualifications, such as edu-

cation, must be considered first, Malays may be given preference among equally qualified applicants. The opposite process may be at work in the private sector.

Extensions of the Model The analyses of chapter 5 and 6 have been based on the multivariate regres-

sion procedure of multiple classification analysis. It has made possible an eight-variable analysis (in the case of income as a dependent variable)—a feat that would have been simply in the realm of imagination, had tabular analysis remained the technique of investigation. Because most of the variables have been categorical rather than quantitative, the use of conventional regressional analysis would not have been warranted. The use of multiple classification analysis has required no assumptions regarding the scale of measurement of independent variables nor the degree of linearity of relationships between 71

independent and dependent variables. The price exacted for all these advantages lies in the great mass of coefficients and results requiring substantive interpretation. The one equation predicting income with seven independent variables (Model 7 in Table 6.1) has 35 substantive categories, each of which has a net effect or regression coefficient on income—omitting the categories of some independent variables which include no answer, which also produced coefficients (not reported here). The analysis has become even more cumbersome with the series of sequential models or equations that shows the cumulative and mediating effect of social background variables upon ethnic inequality. The volume of coefficients for the analysis of the determinants of occupational attainment, separately for eight separate occupations, becomes so great that only partial results are presented in Table 6.2, the balance being reported in Appendix F. One might wonder with all this richness of detail in the analysis why I should seek to expand and complicate the present model of ethnic stratification. However, there remains the question, both statistical and theoretical, whether interactions exist among the variables in this analysis. Our model so far as made the assumption of additivity, which simply means that the effect of an independent variable upon a dependent variable is similar across categories of another variable. This assumption is not justified when the joint occurrence of two variables (or certain values of two variables) produces a unique effect or interaction not attnbutable to either variable in isolation. For instance, our additive model assumes that being the son of a farmer has a similar effect upon status attainment in each of several ethnic communities. Our estimate of the ethnic effect in the preceding analysis is supposedly constant across all categories of all other independent variables.

In most research where interactions are thought likely, it is possible to add an interaction term to the regression equation and examine its statistical significance and explanatory power. The task is not quite so straightforward, however, when as many as thirty-five additive independent variables are already in the model. The potential number of potential interaction terms is finite, but larger than most research workers would care to consider. First-order interaction effects are potentially important, but probably second- and third-order interaction effects also come to mind. Is the effect of being the son of sales worker in an urban area the same on a youth with only a primary school education as it is on a secondary school graduate? The list of theoretically interesting and potentially significant interaction effects could go on for many pages. Clearly one must have some a priori guide to the selection of interaction terms for testing. I will examine here only two of the possible first-order interaction terms of Ethnicity with other independent variables, specifically the Ethnic X Father’s Occupation and Ethnic X Years of Schooling interaction terms on status attainment. (For additional analysis of other ethnic-social background interaction see Appendix G.) The choice of Ethnic interaction terms with Father’s Occupation and Years | of Schooling was dictated for several reasons. First, Ethnic interactions require attention because Ethnicity is the theoretically most significant variable in the analysis. The primary objective of this research is to explain ethnic dif72

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ferentials in the stratification system, and it is significant if certain social back-

ground variables operate differently in some ethnic groups to produce differences in socioeconomic attainment. Father’s Occupation and Years of Schooling were chosen because they are generally the most powerful determinants of status attainment among the social background variables. Our method of analysis is to compare the variance explained in the com-

plete additive models of all social background variables with regression models which include interaction terms in addition to the basic set of additive terms. The interaction terms were created by multiplying each ethnic variable by each category of the other social background variable. In the case of Ethnic X Father’s Occupation interactions, eight interaction terms were created by multiplying the variable ‘‘Malay’’ by each of the Father’s Occupation categories, similarly eight Chinese, and eight Indian X Father’s Occupation inter-

action terms. Thus a total of 24 Ethnic X Father’s Occupation interaction variables was created. The results of a comparison of such interaction models with the simple additive model are shown in Table 6.3. The first column shows the variance explained in the complete additive model, the third column shows the variance explained by a model which includes eight additional interaction terms for Malay men. The fourth column presents the cumulative effect of eight more Chinese X Father’s Occupation terms, and the fifth column is based upon a model with all additive terms plus 24 Ethnic X Father’s Occupational interactions. The sixth column shows the net variance explained by interaction terms (column 5 minus column 1). As can be seen from these results, the additional variance explained is small compared to the large number of itneraction terms introduced. For the dependent variables, Years of Schooling and English Education, the number of additional interaction variables is larger than in the original additive equations. The 1.9 percent added to the variance explained of Years of Schooling and the 2.3 percent to that of English-medium Education, are rather small figures, although they are statistically significant increments to R?. I interpret this to mean that Father’s Occupation is an advantage or handicap that is not quite identical across all ethnic groups, but certainly the differences are not large enough to change the general pattern that was evident in the additive model.

For the dependent variables of Occupational and Income attainment, the increment to variance explained is less than one percent in all cases except for Clerical and Craft occupations, again, not enough to warrant reconsideration of the previous analysis based upon the assumption of additivity. Table 6.4 presents similar results following an examination of the relative significance of Ethnicity X Years of Schooling interactions in the process of occupational and income attainment. Once again, the introduction of interaction terms does not add much to the explanatory power over the additive models. For each equation of status attainment (eight separate occupations, plus one for income), twenty-four interaction terms were added in three sequential and cumulative models. First, eight Malay X Years of Schooling interactions were added (column 3), then eight more interaction terms of Chinese X Years of Schooling were added (column 4), and finally eight more Indian 74

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