Earnings and occupational attainment: immigrants and the native born



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Table 6

Estimates of Models of Occupational Attainment (Ranked by Mean Occupational Earnings), Foreign Born Males, Age 25-64, 2000

(Dependent Variable: Mean Occupational Natural Logarithm of Annual Earnings)

Variable


OLS-without English Variables

(i)


OLS-with English Variables

(ii)

Ordered Probit-without English Variables

(iii)

Ordered Probit-with English Variables

(iv)

Constant

9.138

(501.24)


9.356

(506.09)


0.132

(2.76)


0.600

(12.14)


Years of Education

0.055

(152.23)


0.048

(125.74)


0.131

(153.75)


0.117

(125.79)


Experience

-0.011

(20.50)


-0.008

(15.34)


-0.032

(24.16)


-0.026

(19.58)


Experience Squared/100

0.022

(22.11)


0.018

(18.96)


0.061

(24.51)


0.055

(21.96)


Years Since Migration (YSM)

0.003

(6.58)


0.001

(1.24)


0.005

(5.03)


-0.000

(0.37)


YSM Squared/100

0.002

(2.20)


0.001

(1.44)


0.001

(0.34)


0.001

(0.25)


Log Weeks Worked

0.066

(22.35)


0.059

(20.47)


0.104

(13.92)


0.091

(12.07)


Married

0.081

(27.15)


0.079

(26.98)


0.136

(17.87)


0.132

(17.32)


South

0.017

(5.60)


0.017

(5.50)


0.050

(6.39)


0.049

(6.29)


Metropolitan Area

0.090

(6.90)


0.098

(7.82)


0.328

(9.16)


0.348

(9.73)


Veteran

-0.017

(2.60)


-0.036

(5.49)


0.002

(0.12)


-0.039

(2.33)


Blacks

-0.081

(15.92)


-0.138

(25.75)


-0.100

(7.53)


-0.221

(16.12)


English Very Well

(a)

-0.027

(5.79)


(a)

-0.027

(2.47)


English Well

(a)

-0.172

(34.99)


(a)

-0.352

(29.38)


English Not Well

(a)

-0.235

(45.60)


(a)

-0.495

(37.21)


English Not at All

(a)

-0.214

(33.55)


(a)

-0.479

(27.06)




0.324

0.350

-

-



-

-

28957.58

31410.72

Sample Size

84,290

84, 290

84, 290

84, 290

Notes: ‘t’ statistics in parentheses.

(a) Variable not entered.



Source: 2000 US Census 1% PUMS.
Given the use of the geometric mean of earnings (i.e., the mean of the logarithm of earnings) in the occupation as the dependent variable in the occupational attainment model of columns (i) and (ii) in Tables 5 and 6, these results can be viewed as providing estimates of the determinants of inter-occupational earnings differentials.

The first point of note is that the payoff to years of education in column (ii) in Tables 5 and 6 is 8.3 percent for the native born, and 4.8 percent for the foreign born. The elasticity of individual earnings – the dependent variable in Tables 1 and 2 – with respect to the mean occupational earnings used as the dependent variable in Tables 5 and 6 is 0.76 for the native born, and 0.72 for the foreign born.8 Hence, these estimates of the payoffs to years of education are consistent with the findings of Tables 1 and 2, to the effect that about one-half of the growth in individual earnings associated with years of education comes about through access to higher paying occupations, although this proportion is around 10 percentage points higher for the foreign born than for the native born.

The second feature of the Table 3 results is that there is a slight, positive relationship between occupational status and potential labor market experience for the native born, but a negative relationship between occupational status and pre-immigration experience (total experience when duration in the U.S. is held constant), up to 22 years of experience, for the foreign born. In other words, in terms of occupational attainment it is better not to have worked abroad, but rather to have immigrated upon leaving school, than to have even a modest amount of foreign labor market experience.

Foreign work experience is typically associated with modest gains in post-arrival earnings in the study of individual earnings among the foreign born in the US. This is certainly the case in the results presented in Table 2 above. Hence, the Table 6 findings suggest that these earnings gains come about through achieving relatively high wages within occupations. In other words, a foreign-born worker with experience tends to be channelled into a lower-paying occupation (captured by mean occupational earnings), but within that occupation receives a relatively high rate of pay (captured in analyzes of individual earnings). It comes as no surprise that this is exactly the pattern of effects discussed in relation to the study of variation in individual earnings with experience following the inclusion of variables for occupation of employment in Table 2.

Similarly, there are only modest increases in mean occupational earnings with weeks worked. A ten percent increase in weeks worked is associated with an increased in mean occupational earnings by less than one percent in the OLS analyses (Table 5 and 6). As argued in Section II, access to occupations that are, on average, better paying is primarily on the basis of pre-labor market skills, such as educational attainment, rather than on the basis of post-schooling characteristics, such as labor market experience and weeks worked.9

There are modest increases in mean occupational earnings or occupational status with years in the US, but only when English skills are not held constant. This implies that improved English skills are the vehicle through which immigrants get access to better paying occupations in the post-arrival period.

The English proficiency variables are associated with highly significant changes in mean occupational earnings for the foreign born, ranging from 3 percent to 24 percent differences in mean occupational earnings, and more modest changes in mean occupational earnings – of between 2 and 3 percent – among the native born. These estimated effects are attenuated versions of the effects reported in analyzes of individual earnings. The comparison with the typical study of individual earnings for the foreign born (see Table 2) implies that over one-half of the gain in earnings associated with the acquisition of English skills comes about through inter-occupational mobility. Clearly, knowing the links between language and other human capital skills and the occupation of employment is important to understanding immigrant labor market outcomes. This highlights the importance of research on the determinants of destination language proficiency among immigrants.
B. Quantile Regression Analysis

The analyzes for the occupational attainment model were repeated using quantile regression (see Buchinsky, 1998) in order to quantify the impact of the explanatory variables across the distribution of occupational attainment scores. The results (not reported here for space reasons but available upon request) show that the effect of educational attainment is relatively small among workers in low-status occupations. Moreover, the effect of education increases with decile of the distribution for the foreign born, but changes little beyond the fifth decile for the native born. Analyzes of the effects of education across the distribution of individual earnings (Chiswick, Le and Miller, 2006) have shown that the payoff to education increases with the decile of the earnings distribution, although the increases in the payoff to educational attainment tend to taper off in the higher deciles. Hence the pattern of effects of educational attainment in the study of occupational status is an attenuated version of the pattern reported in the earnings function literature. This might be expected, given the focus on an occupational average earnings as the dependent variable rather than on an individual measure as in the study of earnings.

The effects of English proficiency on occupational status for the foreign born are similar to that described above for educational attainment, with the effects at the first decile being only around one-half the size of the effects across the middle and top end of the distribution of occupational status scores. Among the native born, however, the opposite pattern is observed: the earnings penalty associated with limited English skills is larger at the bottom of the occupational status distribution than it is at the top of the distribution.

Labor market experience has a very minor impact on the occupational status of the native born regardless of the point on the occupational status distribution where this is examined. In comparison, among the foreign born, labor market experience acquired in the country of origin has a negative impact on occupation status which, with the exception of the 9 decile, becomes more pronounced the higher the decile of the occupational status distribution? This relationship is displayed in Figure 1.


Figure 1

Payoffs to Pre-Immigration Experience by Decile,

Adult Foreign Born Males in the US


Source: Appendix B, Table B.2.
It is clear from Figure 1 that the adverse consequences of pre-immigration experience for post-arrival occupational status, argued above to be associated with the less-than-perfect international transferability of human capital skills, is of far greater importance among those who enter, on average, high-paying occupations than it is for those who enter low-paying occupations. As low-paying occupations will presumably be characterised by low levels of human capital skills, there is less to lose in the migration and hence this result is intuitively reasonable.

Years since migration have a very strong and consistent influence on occupational attainment across the first one-half of the occupational status distribution, but a more modest, and variable, effect across the top half of the occupational status distribution. Chiswick, Le and Miller (2006) also report that the increases in individual earnings with duration of residence are greater in the lower deciles of the (individual) earnings distribution than they are in the upper deciles of the earnings distribution. They attribute this to the so-called importance of initial conditions phenomenon: that the greatest post-arrival gains in relative earnings are recorded by the immigrants with relatively low earnings at arrival as they are making greater destination-specific investments in human capital (see Duleep and Regets (1996)(1997)).


V. CONCLUSION

This study investigates the role that occupation has in determining the earnings of immigrants and the native born. Occupations can be viewed as providing a link between individuals’ attributes and their earnings, and hence the inclusion of variables for occupation in the conventional earnings function is expected to offer fruitful insights. Indeed, the strength of the findings justifies an examination of the determinants of occupational attainment.

The empirical analyzes are based on the 2000 US Census, 1 percent Public Use Microdata Sample. This contains information on 509 specific occupational categories within 23 major occupational groups. The analysis is limited to males aged 25 to 64 years.

The estimation of earnings functions with and without controls for occupation shows that: (i) about one-half of the increase in earnings associated with formal education occurs through entrance into higher-paying occupations for both the native born and the foreign born; (ii) labor market experience among the native born does not appear to be associated with upward occupational mobility; (iii) the increase in the payoff to pre-immigration experience among the foreign born following standardization for occupation suggests that the impact of the less-than-perfect international transferability of immigrants’ human capital results in them being channelled into relatively low-paying occupations; and (iv) immigrants’ earnings growth in the post-arrival period occurs largely through intra-occupation earnings mobility.

Two models of occupational attainment were employed, namely an occupational attainment model estimated using Ordinary Least Squares with mean occupational earnings used as the measure of earnings (for around 500 specific occupations), and an ordered probit model where occupational categories were ranked by mean occupational earnings for 23 major occupational groups. Findings from these models further reinforced the empirical results from the comparison of the conventional earnings model and models incorporating occupation control variables. In particular, the estimates of the models of occupation attainment show that immigrants with foreign labor market experience tend to be channelled into lower-paying occupations.

Quantile regressions were estimated to quantify the impact of the explanatory variables across the occupational status distribution. The results from these regressions showed that the negative impact of foreign labor market experience on occupational status was relatively more intense in the upper half of the occupational status distribution. This accords well with the hypothesis regarding the less-than-perfect international transferability of human capital skills.

Knowing the occupation a person works in helps understand their relative earnings. Among immigrants in particular, this knowledge helps us better understand the earnings penalties associated with the less-than-perfect international transferability of human capital skills.
REFERENCES

Australian Bureau of Statistics, (1983). Census ’81 – Occupation, (Order No. 2148.0), Canberra, AGPS.


Brown, Randall S., Moon, Marilyn and Zoloth, Barbara S., (1980a). “Incorporating Occupational Attainment in Studies of Male-Female Earnings Differentials”, Journal of Human Resources, Vol. 15, pp. 3-28.
Brown, Randall S., Moon, Marilyn and Zoloth, Barbara S., (1980b). “Occupational Attainment and Segregation by Sex”, Industrial and Labor Relations Review, Vol. 33, pp. 506-17.
Buchinsky, Moshe, (1998). “Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research”, Journal of Human Resources, Vol. 33, No. 1, pp. 88-126.
Chiswick, Barry R. and Miller, Paul W., (1998). The Economic Cost to Native-born Americans of Limited English Language Proficiency, report prepared for the Centre for Equal Opportunity, August 1998: available at www.ceousa.org/earnings.html (Date accessed: 16 November, 2006)
Chiswick, Barry R., Le, Anh T. and Miller, Paul W., (2006). “How Immigrants Fare Across the Earnings Distribution: International Analyzes”, IZA Discussion Paper No. 2405.
Duleep, Harriett O. and Regets, Mark C. (1996). “The Elusive Concept of Immigrant Quality: Evidence from 1970-1990”, Discussion Paper PRIP-UI-41, Program for Research on Immigration Policy, Urban Institute, Washington, DC.
Duleep, Harriett O. and Regets, Mark C. (1997). “Measuring Immigrant Wage Growth Using Matched CPS Files”, Demography, Vol. 34, No. 2, pp. 239-249.
Evans, Mariah D.R., (1987). “Language Skill, Language Usage and Opportunity: Immigrants in the Australian Labour Market”, Sociology, Vol. 21, No. 2, pp. 253-274.
Evans, Mariah D.R. and Kelley, Jonathan, (1986). “Immigrants’ Work: Equality and Discrimination in the Australian Labour Market”, The Australian and New Zealand Journal of Sociology, Vol. 22, No. 2, pp. 187-207.
Groshen, Erica L., (1991). “Sources of Intra-Industry Wage Dispersion: How Much Do Employers Matter?”, The Quarterly Journal of Economics, Vol. 106, No. 3, pp. 869-884.
Jones, F. Lancaster, (1989). “Occupational Prestige in Australia: A New Scale”, Australian and New Zealand Journal of Sociology, Vol. 25, No. 2, pp. 187-199.
Kidd, Michael P. and Shannon, Michael, (1996). “Does Occupational Aggregation Matter in Determining the Size of the Gender Wage Gap?”, Industrial and Labor Relations Review, Vol. 49, No. 2, pp. 317-329.
Leigh, Duane E., (1976). “Occupational Advancement in the Late 1960s: An Indirect Test of the Dual Labor Market Hypothesis”, Journal of Human Resources, Vol. 11, pp. 155-171.
McKelvey, Richard D. and Zavoina, William, (1975). “A Statistical Model for the Analysis of Ordinal Level Dependent Variable”, Journal of Mathematical Sociology, Vol. 4, pp. 103-120.
Miller, Paul W. (1987). “The Wage Effect of the Occupational Segregation of Women in Britain”, The Economic Journal, Vol. 97, No. 388, pp. 885-896.
Miller, Paul W. and Volker, Paul A., (1985). “On the Determination of Occupational Attainment and Mobility”, Vol. 20, No. 2, pp. 197-213.
Mincer, Jacob, (1979). “A Comment on Sex Discrimination”, in C.B. Lloyd, E. S. Andrews and C. L. Gilroy (eds), Woman in the Labour Market, Columbia University Press, New York and Guildford, Surrey.
Nickell, Stephen, (1982). “The Determinants of Occupational Success in Britain”, Review of Economic Studies, Vol. 49, pp. 43-53.
Polachek, Solomon W., (1981). “Occupational Self-Selection: A Human Capital Approach to Sex Differences in Occupational Structure”, Review of Economics and Statistics, Vol. 63, pp. 60-69.
Schmidt, Peter and Strauss, Robert P., (1975), “The Prediction of Occupation using Multiple Logit Models”, International Economic Review, Vol. 15, pp. 471-485.
Sloane, Peter J., (1985). “Discrimination in the Labour Market”, in D. Carline, C.A. Pissarides, W. Siebert and J. Sloane (eds) Surveys in Labour Economics, Longman Group Limited, Essex, England.

APPENDIX A
DESCRIPTION OF VARIABLES
The variables used in the statistical analyzes are defined below. Mnemonic names are also listed where relevant.

Data Source: 2000 United States Census of Population, 1 percent Public Use Microdata Sample.
Definition of Population: Native-born and foreign-born men aged twenty-five to sixty-four. Only residents of the 50 States and the District of Columbia are considered.
Dependent Variables:

Individual Earnings: The natural logarithm of wage and salary and self-employment income. Responses of less than 100 are set to 100.
Mean Occupational Earnings: This is the mean of the natural logarithm of earnings in the person’s birthplace group (native born or foreign born) in the specific occupation in which he is employed.
Explanatory Variables:

Educational Attainment (EDUC): This variable records the total years of full-time equivalent education. It has been constructed from the Census data on educational attainment by assigning the following values to the Census categories: completed less than fifth grade (2 years); completed fifth or sixth grade (5.5); completed seventh or eighth grade (7.5); completed ninth grade (9); completed tenth grade (10); completed 11th grade (11); completed 12th grade or high school (12); attended college for less than one year (12.5); attended college for more than one year or completed college (14); Bachelor's degree (16); Master's degree (17.5); Professional degree (18.5); Doctorate (20).
Labor Market Experience (EXP): This is a measure of potential labor market experience, computed as AGE – Years of Education – 6.
Weeks Worked (WEEKS): The number of weeks the individual worked in 1999 is entered into the specification in natural logarithmic form.
Years Since Migration (YSM). This is computed from the year the foreign born person came to the United States to stay.
English Language Fluency: Dichotomous variables are used to capture proficiency levels among both the native born and immigrants. These distinguish individuals who speak a language other than English in the home and who speak English either: (i) “Very Well”; (ii) “Well”; (iii) “Not Well”; and (iv) “Not at All”. The benchmark group is those who speak only English at home. For the native born, the final two categories are combined into a single “Not Well/Not at All” category.
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