shkolakz.ru 1 2 ... 4 5






ECONOMICS


OCCUPATIONAL ATTAINMENT AND IMMIGRANT ECONOMIC PROGRESS IN AUSTRALIA


By


Barry R. Chiswick


University of Illinois at Chicago

&

IZA-Institute for the Study of Labor


and



Paul W. Miller


University of Western Australia


DISCUSSION PAPER 08.0
3

OCCUPATIONAL ATTAINMENT AND IMMIGRANT ECONOMIC PROGRESS IN AUSTRALIA


by



Barry R. Chiswick


Department of Economics

University of Illinois at Chicago

&

IZA-Institute for the Study of Labor


and


Paul W. Miller

Business School

University of Western Australia


ABSTRACT


Using data from the 2001 Australian Census of Population and Housing, on adult men in full-time employment, this paper augments a conventional human capital earnings function with information on occupations. It also estimates models of occupational attainment. The results from both the earnings function and model of occupational attainment indicate that the limited international transferability of human capital skills results in immigrants entering into relatively low status occupations when they first enter the Australian labour market. Comparison with similar research for the US suggests that the different immigrant selection regimes (primarily family reunion in the US, skill-based immigration in Australia) do not impact on the negative association between occupational status and pre-immigration labour market experience. (115 words)

JEL Codes: J240, J310, J 620, F22



* We thank Derby Voon for research assistance and two anonymous referees for helpful comments. Chiswick acknowledges research support from the Institute of Government and Public Affairs, University of Illinois and the Smith Richardson Foundation. Miller acknowledges financial assistance from the Australian Research Council.


/home/server/kzdocs.docdat.com/pars_docs/refs/1/595/595.rtf


OCCUPATIONAL ATTAINMENT AND IMMIGRANT ECONOMIC PROGRESS IN AUSTRALIA


I Introduction

Immigrants’ labour market outcomes are generally discussed around three key concepts—the less-than-perfect international transferability of the human capital skills they acquired in their country of origin, the positive selectivity of immigrants for labour market success, especially economic immigrants, and their relatively rapid economic progress in the destination country.1 The less-than-perfect international transferability of human capital skills results in immigrants being at an economic disadvantage during their first year in the destination country. Immigrants’ rapid economic progress, particularly in the immediate post-arrival period, results in a narrowing of this gap and, especially for economic immigrants, can result in a “catch-up” of their economic position compared to that of their native-born counterparts (Chiswick, 1978). This catch-up will occur when the effects of positive selection more than off-set the lingering effects of imperfect skill transferability and any discrimination against immigrants. However, after three decades of intensive research, understanding of the process of immigrant labour market adjustment that gives rise to these patterns is still far from complete.

In a recent study, using data on adult men in the United States, Chiswick and Miller (2007) argue that insights into the labour market adjustment of immigrants can be gained through estimation of earnings equations that take account of occupational status.2 Equations that also include controls for occupation show the role that occupation has as an intermediary between immigrants’ human capital skills and their earnings. Nearly 60 percent of immigrants’ earnings gains in the US can be attributed to inter-occupational earnings differences, with just over 40 percent to intra-occupational differences, in contrast to 55 or 45 percent for native-born men in the US.



The comparison of the Australian analyses in this paper with the Chiswick and Miller (2007) findings is particularly relevant given the difference in the primary focus in rationing immigrant visas, the applicant’s skills in Australia and family reunification in the United States.

The structure of this paper is as follows. Section II reviews the data from the 2001 Australian Census of Population and Housing that is used in the statistical analyses, with a special emphasis on the information on occupation. It also outlines the specification of the estimating equation. Empirical results from the analysis of earnings are presented in Section III. Section IV provides information on the determinants of occupational attainment that assists in the explanation of the findings reported in Section III. A summary and conclusion are provided in Section V.


II Data and Earnings Equation

The data are from the 2001 Australian Census of Population and Housing one percent sample of households (Australian Bureau of Statistics, 2003). They include information on age, birthplace, educational attainment, marital status, current employment status, earnings and occupation, among other variables. The Expanded Confidentialized Unit Record Files (CURF) available only through the Remote Access Data Laboratory (RADL) is used in this study. 3

The information on occupation is coded according to the Australian Standard Classification of Occupations (ASCO), second edition (Australian Bureau of Statistics, 1997). In the one percent sample only 44 occupational categories are distinguished (See Appendix A). These are used in two forms in the analyses. First, the 44 occupational categories are aggregated into the nine ASCO Major Groups. Second, all of the 44 separate occupational categories are used as the basis of the empirical investigation.4

The analyses are restricted to males aged 20-64 who were employed on a full-time basis (i.e., they worked 35 or more hours per week) in the week before Census night and who reported positive weekly earnings. Appendix B contains definitions of all variables and a table of means and standard deviations.


The earnings function initially estimated takes the following form:

(1)

where the dependent variable is the natural logarithm of weekly earnings, is a vector of the individual and job-related characteristics that affect the earnings of individual i, is the error term, and is a vector of parameters to be estimated. The variables considered in consist of years of schooling, labour market experience and its square, dichotomous variables for government employment, marital status, and birthplace (Australia or foreign born), and variables for duration of residence for immigrants and English language proficiency. Controlling for duration in Australia, the labour market experience variables measure the effect on earnings of pre-immigration labour market experience.

The estimates obtained from equation (1) provide a benchmark set of results for the links between productivity related characteristics and earnings. Two extensions of equation (1) are considered. The first of these involves augmentation with dichotomous variables for the Major Group occupations. Eight dichotomous variables are considered, with Managers and Administrators as the benchmark group. The second extension involves including dichotomous variables for each of the 44 occupations included in the Census classification.

Each of these extensions controls for the occupational earnings structure, albeit at different levels of detail. The coefficients on the variables for occupation provide information on the effect on earnings of employment in the particular occupation. This is a direct effect of occupation on earnings. With occupation held constant, the coefficients of the other explanatory variables reflect their effect on earnings within occupations. Hence, comparison of the estimates in the equation with the occupation variables with estimates from the benchmark equation (1) provide information on the effect of these variables on earnings through intra- and inter-occupational change.



III Analysis for Earnings

(i) Earnings Functions

The results from these analyses are presented in Table 1 and summarised in Table 2. These tables have separate panels for the Australian born, immigrants from English-speaking developed countries, and immigrants from non-English-speaking countries.

The payoff to years of schooling declines by between 24 and 47 percent when the occupational structure is taken into account at the major group level (9 occupational categories). The largest decline is for immigrants from non-English-speaking countries, and the smallest is for the Australian born. For immigrants from non-English-speaking countries, these results indicate that almost one-half of the increase in earnings associated with each extra year of schooling comes about through this extra schooling facilitating access to higher paying occupations.

There are further reductions in the payoff to schooling when the finer degree of detail on occupation is included in the estimating equation. Among the Australian born, the payoff to schooling falls by 41 percent, from 8.8 percent to 5.2 percent. The change in the payoff to schooling for the foreign born from English-speaking countries is similar: it falls from 8.1 percent to 4.6 percent, a 43 percent reduction. In other words, slightly more than 40 percent of the increments in earnings associated with extra years of schooling for immigrants from English-speaking countries derives from inter-occupational earnings differences, and slightly less than 60 percent derives from increases in earnings within occupations.

Among immigrants from non-English-speaking countries, however, the payoff to a year of schooling falls from 5.8 to 2.0 percent when account is taken of employment in the 44 occupations. This is a 66 percent reduction in the payoff to schooling. In other words, two-thirds of the payoff to schooling for immigrants from non-English-speaking countries is associated with access to higher paying occupations. Schooling is indicated here as being of far greater importance for earnings via occupational change for immigrants from non-English-speaking countries than it is for immigrants educated in Australia or other English-speaking countries.


Table 1

Estimates of Earnings Functions by Birthplace, Males Aged 20-64 Years, 2001




Variables

Australian

Born

Foreign Born

English-Speaking Countries

Non-English-Speaking Countries

(i)(b)

(ii)

(iii)

(i) (b)

(ii)

(iii)

(i) (b)

(ii)

(iii)

Constant

1.403

(58.13)

1.721

(49.28)

2.022

(36.97)

1.559

(24.91)

2.237

(28.24)

2.153

(15.12)

1.944

(30.68)

2.422

(31.12)

2.468

(22.30)

Education

0.088

(52.41)

0.067

(31.36)


0.052

(24.71)

0.081

(22.37)

0.050

(11.57)

0.046

(10.87)

0.058

(16.84)

0.031

(7.82)

0.020

(5.22)

Experience

0.028

(22.79)

0.027

(21.05)

0.026

(21.89)

0.029

(8.53)

0.025

(7.63)

0.026

(8.13)

0.008

(2.70)

0.011

(3.68)

0.014

(4.84)

Experience Squared/100

-0.047

(17.86)

-0.048

(18.45)

-0.044

(17.65)

-0.051

(7.49)

-0.046

(6.93)

-0.047

(7.26)

-0.015

(2.46)

-0.022

(3.71)

-0.027

(4.69)

Married

0.097

(12.11)

0.088

(11.13)

0.083

(10.83)

0.151

(7.05)

0.125

(6.08)

0.109

(5.37)


0.100

(4.97)

0.093

(4.82)

0.086

(4.69)

Government

0.150

(19.20)

0.135

(17.32)

0.116

(14.43)

0.106

(4.91)

0.091

(4.42)

0.109

(4.75)

0.162

(7.66)

0.154

(7.33)

0.145

(6.74)

Speaks English:(d)




























Very Well

(c)

(c)

(c)

(c)

(c)

(c)

-0.030

(1.35)

-0.021

(1.01)

-0.021

(1.04)

Well

(c)

(c)

(c)

(c)

(c)

(c)

-0.135


(5.50)


-0.086

(3.51)

-0.066

(2.79)

Not Well

(c)

(c)

(c)

(c)

(c)

(c)

-0.226

(6.90)

-0.183

(5.60)

-0.152

(4.86)

Not at All

(c)

(c)

(c)

(c)

(c)

(c)

-0.421

(4.89)

-0.397

(4.84)

-0.312

(3.70)

Year of Arrival: (d)




























1991-1995

(c)

(c)

(c)

-0.040

(0.92)

-0.033

(0.81)

-0.030

(0.76)

0.011

(0.32)

0.025

(0.75)

0.012


(0.39)


1986-1990

(c)

(c)

(c)

-0.055

(1.58)

-0.030

(0.92)

-0.026

(0.85)

0.031

(0.99)

0.039

(1.31)

0.030

(1.04)

Before 1986

(c)

(c)

(c)

-0.085

(3.31)

-0.077

(3.25)

-0.069

(3.05)

0.107

(3.65)

0.100

(3.56)

0.083

(3.06)

Occupation(e)

NI

INC

INC

NI

INC

INC

NI

INC

INC



0.190

0.210

0.291

0.194

0.256

0.306

0.168

0.223

0.300

Sample Size

20,709


20,709

20,709

3,127

3,127

3,127

3,752

3,752

3,752

Notes: (a) Heteroscedasticity-consistent ‘t’ statistics in parentheses; (b) specification (i) is the benchmark model that does not contain information on occupation, specification (ii) contains dichotomous variables for the Major Group occupations, while specification (iii) contains dichotomous variables for the more detailed (44) Census occupational categories; (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”; (e) NI = Occupation Not Included, INC = Occupation Included.

Source: 2001 Australian Census of Population and Housing.



следующая страница >>