1 ... 2 3 4 5

Notes: (a) Heteroscedasticity-consistent ‘t’ statistics in parentheses; (b) Column (i) specification has the mean occupational earnings at the Major Group level as the dependent variable, column (ii) specification has the mean occupational earnings at the Census occupational classification as the dependent variable; (c) = Variables not entered; (d) = The omitted category for the Speaks English variable is “Speaks only English” and that for the Year of Arrival variable is “After 1995”.

Source: 2001 Australian Census of Population and Housing.

The estimates in Table 4 for the Australian born show that the main determinant of occupational status, as measured by the t-ratio and magnitude of the partial effect, is educational attainment. Each year of schooling is associated with entry into occupations having 5 (specification (i)) to 6 (specification (ii)) percent higher earnings. In comparison, for men born in Australia, the effects on mean occupational earnings of labour market experience are very small, and sensitive to the level of aggregation of the occupational categories. Under either classification, the difference in mean occupational earnings between the least and most experienced workers is less than the effect of two years of schooling. Thus, among the native born, schooling is a far more important determinant of occupational attainment than is labour market experience. A similar pattern is found among the native born in the United States (Chiswick and Miller, 2007).

The results for immigrants from English-speaking countries are similar to the findings among the Australian born. While additional education apparently readily opens up access to higher-paying occupations, additional years of pre-immigration and post-immigration labour market experience are not associated with similar access.

Among the foreign born from non-English-speaking countries, years of education are also associated with higher mean occupational earnings, with the partial effect of 0.041 to 0.050 being around one percentage point less than that estimated for the other birthplace groups. This finding is consistent with the smaller partial effects of education on individual earnings among immigrants from non-English-speaking countries in Table 1. However, immigrants from non-English-speaking countries with moderate amounts of pre-immigration labour market experience have relatively low mean occupational earnings compared to those with even less pre-immigration experience. This is the same finding as in Chiswick and Miller (2007), on the basis of study of the US labour market. The finding is consistent with the increase in the payoff to labour market experience once occupation is held constant in the study of individual earnings (Tables 1 and 2). The effect of duration in Australia has a positive effect on mean occupational earnings, but this effect is also quite modest.

Finally, it is noted that proficiency in English is associated with substantial occupational advancement, though the estimated coefficients in Table 4 are only around one-half the magnitude of the effects found in the study of individual earnings (without the variables for occupation) in Table 1.

Findings similar to these are obtained when an ordered probit model is applied to the occupational data (ranked by mean earnings).(a) In particular, the main determinant of membership in a higher-ranked occupation is educational attainment. The effects of labour market experience on occupational outcomes for immigrants from non-English-speaking countries is opposite those estimated for the Australian born and immigrants from English-speaking countries. English proficiency is a major determinant of the likelihood of being employed in a high-earnings occupation among immigrants from non-English-speaking countries.

V Conclusion

The analyses for Australia using the 2001 Census data on adult men in full-time employment reported in this paper show that when occupation is held constant in the earnings equation, there is a reduction of 41 percent in the payoff to schooling for the Australian born, a similar reduction, of 43 percent, in the payoff to schooling for immigrants from English-speaking developed countries, and an even greater reduction, by 66 percent, in the payoff to schooling for immigrants from other countries. The latter have a much lower transferability of their skills to Australia.

At the same time, holding occupation constant is associated with a quite modest reduction, of less than 10 percent, in the payoff to labour market experience for the Australian born. It is also associated with only a minor reduction, of around 16 percent, in the payoff to pre-immigration experience for immigrants from English-speaking countries. However, controlling for occupation increases the payoff to pre-immigration labour market experience by 60 to 70 percent for immigrants from non-English-speaking countries. These remarkable differences are due to a negative association between occupational status in Australia and pre-immigration labour market experience for many immigrants from non-English-speaking countries. This may arise if there is negative selectivity among those from low transferability countries who immigrate to Australia at an older age, which is after many years of work experience in their country of origin.

The comparison of the findings for the Australian labour market with the study by Chiswick and Miller (2007) for the US labour market revealed that inter-occupational earnings mobility is of greater importance in gaining a payoff to education in Australia than in the US. This is likely to be linked to the more egalitarian distribution of earnings within occupations that is associated with the more centralised system of wage determination, and perhaps greater union power, in Australia than in the US.

These findings suggest that attention needs to be focussed on occupational outcomes at the time of labour market entry in the destination country. The different immigrant selection regimes of the US (emphasis on family reunion) and Australia (emphasis on skills) do not appear to matter in this regard. More fundamental labour market processes seem to be at work. The study of occupational attainment for sub-groups of the population who may face different transitions (e.g., have access to well established networks or settle in areas with tight labour markets) may assist in understanding these processes.


Australian Bureau of Statistics, (1997). Australian Standard Classification of Occupations, Second Edition, Catalogue No. 1220.0, Australian Government Publishing Service, Canberra.

Australian Bureau of Statistics, (2003). Technical Paper: Census of Population and Housing Household Sample File Australia 2001, Catalogue No. 2037.0, Australian Bureau of Statistics, Canberra.

Chiswick, B., (1978). ‘The Effects of Americanization on the Earnings of Foreign Born Men’, Journal of Political Economy, 86, 897-921.

Chiswick, B.R. and Miller, P.W., (2007). ‘Earnings and Occupational Attainment: Immigrants and the Native Born’, IZA-Institute for the Study for Labor, Bonn, Discussion Paper No. 2676, March.

Chiswick, B.R. and Miller, P.W. (2008). ‘The “Negative” Assimilation of Immigrants: A Special Case’, photocopy, Business School, The University of Western Australia, Crawley, WA, Australia.

Duncan, O.D., (1961). ‘Properties and Characteristics of the Socioeconomic Index’, in Albert J. Reiss Jr (ed.), Occupational and Social Status, New York: Free Press, 139-161.

Evans, M.D.R., (1987). ‘Language Skill, Language Usage and Opportunity: Immigrants in the Australian Labour Market’, Sociology, 21, 253-274.

Miller, P.W., Mulvey, C., and Martin, N., (1995). ‘What do Twins Studies Reveal about the Economic Returns to Education? A Comparison of Australian and US Findings’, American Economic Review, 85, 586-599.

Mincer, J., (1974). Schooling, Experience and Earnings, National Bureau of Economic Research, Cambridge.

Nickell, S., (1982). ‘The Determinants of Occupational Success in Britain’, Review of Economic Studies, 49, 43-53.

Sicherman, N. and Galor, O., (1990). ‘A Theory of Career Mobility’ Journal of Political Economy, Vol. 98, 169-192.


Table A1

Census Occupation Classification, Australia, 2001

Census Code



Managers and Administrators n.f.d.


Generalist Managers


Specialist Managers


Farmers and Farm Manangers


Professionals n.f.d.


Science, Building and Engineering Professionals


Business and Information Professionals


Health Professionals


Education Professionals


Social, Arts and Miscellaneous Professionals


Associate Professionals n.f.d.


Science, Engineering and Related Associate Professionals


Business and Administrative Associate Professionals


Managing Supervisors (Sales and Service)


Health and Welfare Associate Professionals


Other Associate Professionals


Tradespersons and Related Workers n.f.d.


Mechanical and Fabrication Engineering Tradespersons


Automative Tradespersons


Electrical and Electronics Tradespersons


Construction Tradespersons


Food Tradespersons


Skilled Agricultural and Horticultural Workers


Other Tradespersons and Related Workers


Advanced Clerical and Services Workers n.f.d.


Secretaries and Personal Assistants


Other Advanced Clerical and Services Workers


Intermediate Clerical, Sales and Services Workers n.f.d.


Intermediate Clerical Workers


Intermediate Sales and Related Workers


Intermediate Services Workers


Intermediate Production and Transport Workers n.f.d.


Intermediate Plant Operators


Intermediate Machine Operators


Road and Rail Transport Drivers


Other Intermediate Production and Transport Workers


Elementary Clerical, Sales and Services Workers n.f.d.


Elementary Clerks


Elementary Sales Workers


Elementary Services Workers

Table A1 (continued)


Labourers and Related Workers n.f.d.




Factory Labourers


Other Labourers and Related Workers n.f.d.

The Major Group Occupations are aggregates of these codes:

Managers and Administrators

(codes 1-4)


(codes 5-10)

Associate Professionals

(codes 11-16)


(codes 17-24)

Advanced Clerical

(codes 25-27)

Intermediate Clerical

(codes 28-31)

Production Workers

(codes 32-36)

Elementary Clerical

(codes 37-40)


(codes 41-44)

n.f.d.= Not further defined



The variables used in the statistical analysis of the 2001 Australian Census of Population and Housing are defined below. The analyses are restricted to male full-time workers (i.e., working 35 hours or more per week) aged 20-64 years.

Dependent Variables

Log of Hourly Earnings

Natural logarithm of hourly earnings (where earnings are defined as gross earnings from all sources). As weekly earnings was coded in intervals, midpoints of intervals were used to construct a continuous measure. The open-ended upper category was assigned a value of 1.5 times the lower threshold level. Weekly hours were recorded in intervals so midpoints were used to construct a continuous measure. Hourly earnings was then constructed by dividing weekly earnings by weekly hours worked.

Explanatory Variables

Years of Education

This is a continuous variable that records the equivalent years of full-time education completed by the individual. Individuals holding a Postgraduate degree are assigned 19 years of education, Graduate Diploma and Graduate Certificate holders are assumed to have 17 years, Bachelor degree holders have the equivalent of 15.5 years of education, advanced Diploma and Diploma holders are coded as having 14 years, holders of Certificate are assigned 13 years, those who have completed either Year 9 or any years through to Year 12 are coded as 9, 10, 11 and 12 years of education, respectively, and those who did not go to school or attained Year 8 or below are assumed to have 7 years of education.


The experience variable was derived using the Mincer (1974) Proxy; Age – Years of Education – 5.

Marital Status

Binary variable set to one if an individual is married and set to zero otherwise.

English Proficiency

Five English skills categories are distinguished: (i) speaks only English at home; speaks a language other than English at home and speaks English (ii) very well; (iii) well; (iv) not well; (v) not at all. In the analyses for immigrants from non-English-speaking countries, dichotomous variables are included in the estimating equation for the latter four variables, with the “speaks only English at home” group being the benchmark group.

Government Employment

This is a binary variable that distinguish between those working in government organisations and those working in the private sector.

Birthplace of Individual

Individuals who were born overseas (OSENG for overseas born from English-speaking developed countries; OSNENG for overseas born from all other countries) are distinguished from the Australian born.

Duration of Residence in Australia

This records the number of years an individual born overseas has lived in Australia. Three dummy variables were created based on the limited Census information: Arrived 1991-1995, Arrived 1986-1990, Arrived before 1986. The benchmark group is those who arrived after 1996-2001.

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