Earnings and occupational attainment: immigrants and the native born



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March 2007

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EARNINGS AND OCCUPATIONAL ATTAINMENT:

IMMIGRANTS AND THE NATIVE BORN
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
Keywords: Immigrants, Occupation, Earnings

JEL Codes: J240, J310, J 620, F22


* We thank Derby Voon for research assistance. Chiswick acknowledges research support from the Institute of Government and Public Affairs, University of Illinois. Miller acknowledges financial assistance from the Australian Research Council.


March 2007

EARNINGS AND OCCUPATIONAL ATTAINMENT:

IMMIGRANTS AND THE NATIVE BORN

ABSTRACT

This paper examines the determinants of occupational attainment and the impact of occupation on earnings. Results for both the native born and foreign born are presented, and these provide insights as to the earnings penalties associated with the less-than-perfect international transferability of human capital skills. It shows that around 50 percent of the earnings gains associated with years of schooling derives from inter-occupational mobility. When occupation is held constant, there is a large increase in the effect on earnings of pre-immigration labor market experience for the foreign born, but little change in either the payoff to labor market experience for the native born, or in the premium for post-arrival labor market experience for the foreign born.

The estimates of the models of occupational attainment show that years of schooling, and, among the foreign born, proficiency in English, are the key factors determining access to high-paying occupations. Labor market experience has little effect on occupational outcomes among the native born. However, evaluated at 10 years, foreign labor market experience has a modest negative impact on current occupational status. Examination of this negative effect using quantile regression shows that it is concentrated among those in high status jobs. (196 words)

March 2007
EARNINGS AND OCCUPATIONAL ATTAINMENT:

IMMIGRANTS AND THE NATIVE BORN
I. INTRODUCTION

Immigrants’ post-migration economic adjustment has typically been analyzed using an earnings function approach. In this approach, immigrants’ earnings are related to their years of formal schooling, years of pre-immigration experience, years of post-immigration experience, and a range of demographic and region of residence control variables. A set of stylized facts has emerged from this line of research in the US and other destination countries, including (i) the payoff to immigrants’ schooling is generally far less than the payoff obtained by the native born; (ii) pre-immigration labor market experience is associated with quite modest increases in immigrants’ post-arrival earnings; (iii) years of post-arrival labor market experience among the foreign born are rewarded at a higher rate than years of pre-migration labor market experience; and (iv) destination language proficiency is an important determinant of immigrants’ economic success.

Most researchers who study immigrants’ earnings adjustment do not include variables for occupation of employment in the estimating equation. The main reason for this appears to be that occupation is typically viewed as a grouped variant of the dependent variable, and therefore it is not legitimate to use it as a regressor (Mincer (1979) as cited in Sloane (1985, p. 125)). Similarly, earnings and occupation may both be viewed as (imperfect) measures of the same unmeasurable variable of interest, labor market outcome.

Occupation of employment might be included in the model, however, where the aim is to inform on the channels through which earnings gains are achieved. Groshen (1991, p. 883), for example, argued that “…attributes of individuals (for example, race, education, marital status) must operate through occupation, employer, or job-cell in order for them to affect wages.” Earlier, Duncan (1961, pp.116-117) had noted “…a man qualifies himself for occupational life by obtaining an education; as a consequence of pursuing his occupation, he obtains income. Occupation, therefore, is the intervening activity linking income to education”. In other words, education or any other variable can be viewed as having both direct and indirect impacts on earnings, with the indirect impacts operating via occupational attainment. These issues, however, do not appear to have been systematically explored in the context of the determinants of immigrants’ earnings.

This paper therefore has two aims. First, for immigrants in the US, earnings functions are estimated both with and without variables for occupation. For comparison purposes, earnings functions for the native born both with and without information on occupation are also presented. Alternative specifications are employed, where occupations are measured at different levels of aggregation. These results provide insights on the relative importance of the inter-occupational and intra-occupational channels of immigrants’, compared to natives’, economic progress. They show the potentially large, and intriguing, role that occupation apparently has in understanding variations in immigrants’ earnings. This then provides the empirical basis for the second aim of the paper, namely to examine models of occupational attainment among immigrants and the native born.

The structure of this paper is as follows. Section II provides estimates of three specifications of an earnings function: one that does not include variables for occupation; a second that standardizes for occupation at the major group level, and a third that distinguishes among approximately 500 occupations. The results from this exercise appear to establish a clear case for the study of occupational attainment. Section III provides a brief review of the approaches that have been taken when modelling occupational attainment. Section IV presents estimates of several models of occupational attainment for the foreign born and the native born. These follow the literature and use mean earnings to rank occupations. Section V is the conclusion.


II. EARNINGS AND OCCUPATIONS

The analyses in this section are based on data for adult males (ages 25-64 years) from the 2000 U.S. Census one percent Public Use Microdata Sample. This sample provides details on earnings and work activity in 1999, together with information on a rich array of personal characteristics. Of specific note is that it codes the occupation in which the individual works in considerable detail. In particular, the 2000 Census occupational classification system consists of 509 specific categories for employed people that are structured into 23 major occupational groups.1

The typical human capital earnings function employed in the literature relates the natural logarithm of annual earnings to educational attainment (EDUC), measured by the years of full-time equivalent education, potential labor market experience, measured by age minus education minus six years, (EXP), the natural logarithm of weeks worked (WEEKS), years since migration for the foreign born (YSM), and a set of dichotomous variables for foreign birth (FOR = 1), race (BLACK=1), marital status (MARRIED=1), location (METROPOLITAN AREA=1 and SOUTH=1), veteran status (VETERAN=1), and sometimes, for English language proficiency. The self-reported census information on English language proficiency allows five separate categories of skills to be identified, namely those who speak only English at home (speaking “English only”), which serves as the benchmark, and those who speak a language other than English at home and speak English “Very Well”, “Well”, “Not Well” or “Not at All”. For the native born, however, owing to the small numbers in the classifications of limited English skills, the categories of “Not Well” and “Not at All” are combined, whereas they are kept separate in the estimations for the foreign born. Both the potential labor market experience and years since migration variables are entered into the model in quadratic form. All variables are defined in Appendix A.

Estimates of earnings functions with and without controls for occupation are presented in Table 1 for the native born and Table 2 for the foreign born. Column (i) of each table lists results from a conventional model, and is presented to serve as a benchmark against which the impact of standardization for occupation can be assessed. Hence, they will not be discussed. Instead, the focus will be on the changes to the estimated coefficients as occupation is held constant, at two different levels of disaggregation.



Table 1

Estimates of Earnings Equations, Native Born Males, Age 25-64, 2000 (Dependent Variable: Natural Logarithm of Earnings)


Variable



Standard Model

(i)

Model

with 23 Occupation Dummies

(ii)

Model

with 509 Occupation Dummies

(iii)

Percent Change from Standard Model(a)

Column (ii) Model

Column (iii) Model

Constant

4.347

(193.00)


-

-

-

-

Years of Education

0.106

(202.06)


0.082

(149.40)


0.058

(103.56)


-22.6

-45.3

Experience

0.033

(71.94)


0.033

(76.61)


0.032

(76.36)


0.0

-3.0

Experience Squared/100

-0.057

(55.56)


-0.057

(64.00)


-0.055

(63.64)


0.0

-3.5

Log Weeks Worked

1.009

(183.28)


0.983

(369.42)


0.956

(370.62)


-2.6

-5.3

Married

0.269

(111.24)


0.235

(99.60)


0.202

(87.93)


-12.6

-24.9

South

-0.057

(24.68)


-0.065

(28.61)


-0.075

(34.28)


+14.0

+31.6

Metropolitan Area

0.211

(35.63)


0.198

(36.17)


0.162

(30.66)


-6.2

-23.2

Veteran

-0.046

(16.95)


-0.041

(15.20)


-0.046

(17.59)


-10.9

0.0

Blacks

-0.153

(42.96)


-0.102

(27.85)


-0.076

(21.39)


-33.3

-50.3

English Very Well

-0.059

(11.61)


-0.046

(9.29)


-0.040

(8.32)


-22.0

-32.2

English Well

-0.096

(7.50)


-0.087

(7.18)


-0.070

(5.99)


-9.4

-27.1

English Not Well/Not at All

0.012

(0.65)


0.015

(0.88)


0.009

(0.55)


+25.0

-25.0



0.335

0.367

0.412

-

-

Sample Size

533,906

533,906

533,906

-

-

Notes: ‘t’ statistics in parentheses; a = changes computed with reference to absolute values of coefficients.

Source: 2000 US Census 1% PUMS.

Table 2

Estimates of Earnings Equations, Foreign Born Males, Age 25-64, 2000 (Dependent Variable: Natural Logarithm of Earnings)

Variable



Standard Model

(i)

Model

with 23 Occupation Dummies

(ii)

Model

with 491 Occupation Dummies

(iii)

Percent Change from Standard Model(a)

Column (ii) Model

Column (iii) Model

Constant

5.851

(108.21)


-

-

-

-

Years of Education

0.053

(69.16)


0.032

(40.31)


0.023

(28.66)


-39.6

-56.6

Experience

0.012

(11.08)


0.018

(17.69)


0.019

(19.04)


+50.0

+58.3

Experience Squared/100

-0.016

(8.12)


-0.028

(14.90)


-0.030

(16.31)


+75.0

+87.5

Years Since Migration (YSM)

0.011

(13.00)


0.012

(15.30)


0.012

(15.38)


+9.1

+9.1

YSM Squared/100

-0.011

(5.55)


-0.012

(6.96)


-0.014

(7.97)


+9.1

+27.3

Log Weeks Worked

0.875

(72.99)


0.856

(151.70)


0.841

(152.71)


-2.2

-3.9

Married

0.213

(35.73)


0.180

(31.38)


0.158

(28.07)


-15.5

-25.8

South

-0.071

(11.72)


-0.085

(14.48)


-0.088

(15.36)


+19.7

+23.9

Metropolitan Area

0.134

(5.00)


0.095

(3.56)


0.084

(3.22)


-29.1

-37.3

Veteran

-0.084

(6.52)


-0.052

(4.06)


-0.046

(3.69)


-38.1

-45.2

Blacks

-0.184

(17.17)


-0.110

(10.52)


-0.067

(6.51)


-40.2

-63.6

English Very Well

-0.080

(8.55)


-0.071

(8.52)


-0.057

(6.95)


-11.3

-28.8

English Well

-0.261

(26.19)


-0.177

(19.49)


-0.134

(15.06)


-32.2

-48.7

English Not Well

-0.373

(33.93)


-0.269

(26.57)


-0.217

(21.80)


-27.9

-41.8

English Not at All

-0.378

(27.46)


-0.300

(22.50)


-0.252

(19.23)


-20.6

-33.3



0.363

0.415

0.449

-

-

Sample Size

84,290

84, 290

84, 290

-

-

Notes: ‘t’ statistics in parentheses; a = changes computed with reference to absolute values of coefficients.

Source: 2000 US Census 1% PUMS.
Column (ii) of Tables 1 and 2 contains the results when separate intercept terms are included in the model for each of 23 major group occupations. As this set of occupational dichotomous variables holds constant the inter-occupation earnings structure, the coefficients on other variables (e.g., schooling, experience) record their impacts on intra-occupational earnings mobility. Following standardization for the occupational earnings structure at the major-group level, the payoff to schooling for the native born decreases from 10.6 percent to 8.2 percent, a 23 percent reduction. For the foreign born, following the control for occupation fixed effects (at the major group level) the payoff to schooling also decreases, although the reduction is considerably greater than for the native born. Thus, the payoff to schooling for the foreign born falls from 5.3 percent to 3.2 percent, a 40 percent change. In other words, among the native born and foreign born, about 23 percent and 40 percent, respectively, of the increase in earnings associated with additional years of schooling occurs through entrance into higher-paying occupations, as broadly defined here. The remaining part of the payoff to schooling is associated with higher earnings within the major group occupations.

In stark contrast to the situation with formal schooling, however, once occupation of employment is held constant, the payoff to experience for the native born does not change. In both the conventional earnings function and when the major group occupation is held constant, the payoff to experience for the native born is 2.2 percent at 10 years of experience, and 1.0 percent at 20 years of experience. These and other payoffs are summarized in Table 3. This suggests that earnings mobility with labor market experience among the native born is achieved through upward earnings mobility within an occupation rather than via movement across the major group occupations. An implication of this result is that occupational outcome – at the major group level – is on the basis of pre-labor market characteristics, such as the highest educational level attained. This is an intuitively reasonable implication.

Among the native born, speaking a language other than English at home is associated with lower earnings, 6 percent lower earnings if English is spoken “very well” and 10 percent lower earnings if English is spoken “well”.2 The negative effect becomes smaller in absolute magnitude when occupation is held constant. These effects imply that some of the earnings gain to the native born from greater proficiency (9 to 32 percent) is due to placement in higher paying occupations, but much of it arises from intra-occupational earnings mobility.

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