Abstract

People's occupations have a significant amount of information about their wages. However, because people—especially young workers—go through multiple occupations and employment statuses during their working lives, we find that their occupations at a young age do not predict their lifetime earnings well. When educational attainment and gender are considered, we find that across education-gender groups the differences in lifetime earnings are even larger than the differences in average occupational wages: Workers in high-wage education-gender groups (men with college degrees, for example) work more (at the extensive margin) and are more likely to have higher-paying occupations.

Yongseok Shin is a professor of economics at Washington University in St. Louis and a research fellow at the Federal Reserve Bank of St. Louis. C.Y. Kelvin Yuen is a Ph.D. candidate in economics at Washington University in St. Louis.

INTRODUCTION

Occupations signify people's economic standing: One can safely assume that doctors and lawyers are better off than cooks and janitors. In this article, we ask how much information on people's labor market outcomes is encapsulated in their occupations. We first consider how much of overall wage inequality can be accounted for by the differences in average wages of occupations (between-occupation inequality). We then examine how informative a person's occupation at a young age (i.e., 25 years of age) is about that person's lifetime earnings. Because the calculation of lifetime earnings takes into account the fact that people go through multiple occupations and employment statuses, we will look for patterns of mobility across occupations. Finally, we divide the data by education and gender groups to see how average wages and lifetime earnings vary across occupations within and across the groups. 

Our first finding is that occupations provide a significant amount of information on workers' wages in the cross section—average wages of occupations vary significantly: Even when we divide occupations into only 22 occupation categories, the highest average wage (legal) is nearly three times the lowest average wage (food preparation and serving). However, because workers go through multiple occupations and employment statuses during their working lives, especially when young, we find that their occupations at a young age do not predict their lifetime earnings well.

Our second finding is about the earnings gaps between education-gender groups. Even within the same occupation category, some groups (for example, men with college degrees) earn more than others. When we compute between-group differences in lifetime earnings, conditioning on occupation category at age 25, the fact that people go through multiple occupation categories and employment statuses amplifies the between-group wage differences within an occupation category. This amplification occurs because workers in high-wage education-gender groups work more (at the extensive margin) and are more likely to remain in higher-paying occupation categories.

In recent years, many macro-labor models of tasks and occupations have equated workers' occupations with their skill levels (see the review of Acemoglu and Autor, 2011). Once we factor in occupational mobility, however, our analysis suggests that the link between occupation and skill may be weaker than has often been assumed. 

Our finding on inequality in wage and lifetime earnings between education-gender groups relates to studies showing that occupation-specific human capital and tenure explains wage growth and inequality (see the review of Sanders and Taber, 2012).

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