Accounting for race and gender differences in college wage premium changes.

• Author: Eide, Eric

1. Introduction

   Much recent research has been devoted to the rapid rise in the college wage premium during the 1980s [3; 5; 10; 13; 14]. Murphy and Welch [13] estimated that between 1979 and 1986, the college wage premium for all age groups increased almost 20 percentage points, while the college wage premium for workers with one to five years of experience grew by 38 percentage points.

   While the size of the college wage premium increase is impressive, especially among recent graduates, there is substantial disparity in this change among individual race/gender groups [2; 4]. Coleman [4] found that the wage premium increase for graduates with one to five years of experience was 45 percentage points for white men, 30 percentage points for white women, and 27 percentage points for black men, while the wage premium decreased by 3 percentage points for black women.

   Why did the college wage premium change so differently for different race/gender groups? Part of the disparity may be due to differences in growth rates of major-specific wage premia. It is well established that the return to a college degree varies markedly by field of study, with relatively technical degrees earning the highest wage premia [1; 5; 6; 9; 17]. If wage premia associated with different majors changed differently over time among the race/gender groups, then their respective aggregate college wage premia would likely change differently as well.

   Another factor which may account for differences in college wage premium changes is changes in the distribution of graduates across majors. Grogger and Eide [5] found that men who graduated college in the mid-1980s were more likely to earn degrees in technical fields than were their predecessors from the mid-1970s. The authors found that this major distribution change, which increased the proportion of graduates in high-paying majors, accounts for one-fourth of the rise in the college wage premium between 1978 and 1986 for men who were recent graduates(1) Hence, differences in college wage premium changes across race/gender groups may partly be accounted for by graduates from some groups entering higher-paying fields in greater proportions than graduates from other groups.

   The purpose of this paper is to quantify how major-specific premia changes and major distribution changes account for college wage premium changes between 1978 and 1986 for the race/gender groups of white men, nonwhite men, white women, and nonwhite women.(2) First, I will use data on two cohorts of recent college graduates, one from the mid-1970s and another from the mid-1980s, to estimate how the value of a college degree changed both in the aggregate and by major for each race/gender group. Next, I will use the major-specific premia estimates to decompose the college wage premium change for each race/gender group into a component which accounts for major-specific premia changes (also referred to as price changes) and a component which accounts for major distribution changes (also referred to as quantity changes). These decompositions will show the extent to which major-specific premia changes and major distribution changes account for college wage premium changes differently for different race/gender groups, and thus will yield insight into why the college wage premium for different groups may change differently over time. I will also use the price and quantity data to conduct a qualitative analysis on changes in the net demand for recent graduates from each race/gender group.

2. Data

   The analysis is based on pooled data from two longitudinal surveys conducted by the U.S. Department of Education. The National Longitudinal Survey of the High School Class of 1972 (NLS72) is a longitudinal survey of roughly 21,000 high school seniors who graduated in 1972 [15]. The High School and Beyond (HSB) survey is a similar panel of about 12,000 members of the high school class of 1980, and was intended as a follow-up to the NLS72 [16]. Both studies collected extensive background information and administered similar sets of standardized tests in their base year surveys [7]. Subsequent interviews collected data on the respondents' post-secondary education, employment, and earnings.

   My sample includes individuals who participated in the base year survey and the follow-up interview from which data were drawn. Except where noted, I restrict the sample to full-time workers who were not full-time students. I further restricted the sample to persons whose hourly wage was between $1 and $100. All monetary values are expressed in 1986 dollars.

   The dependent variable in my analysis is the logarithm of the hourly wage.(3) The independent variables include educational attainment dummies, college major dummies, test scores, high school grade dummies, family background variables, labor market experience, region dummies, community residence dummies, a part-time school dummy, and a cohort dummy.

   Educational attainment dummies are for the mutually exclusive categories of high school graduate, persons with some college but no degree, college graduate, and postgraduate degree recipient.(4) For college graduates, I collapsed all fields of study into one of seven categories: business [TABULAR DATA FOR TABLE I OMITTED] (including economics), engineering, physical science (including math), life science, social science, education and letters, and other major.(5) I aggregated the majors into seven broad fields primarily because the cell sizes for nonwhite college graduates are too small for more detailed analysis.

   I use scores from three standardized tests which were administered during the student's senior year of high school: a math test, a vocabulary test, and a "mosaic" test which measures perceptual speed and accuracy. I also constructed two dummy variables from base-year self-reports of the student's high school grades: one indicates that the student had mostly A's and B's, and the other indicates that the student had mostly B's and C's. The test scores and high school grades are meant to proxy for individual ability.

   Family background is measured by dummy variables for parental income during the student's senior year of high school. Labor market experience is an annualized measure of weeks worked since the student completed his or her full-time schooling. The region dummies are four dummies corresponding to west, south, northeast, and central U.S. The community residence dummies correspond to urban, rural, and suburban areas.

   Table I presents the distribution of college graduates across majors for each race/gender group.(6) Panel A gives the distributions for men and panel B gives the distributions for women. Columns (5) and (6) of panel A show substantially increased proportions of both white and nonwhite men graduating in relatively technical fields. The changes were especially large for nonwhite men, where the proportion moving into business and engineering grew by over 30 percentage points and almost 13 percentage points, respectively. There were decreased proportions of both white and nonwhite men in the less-technical fields, especially social science and education/letters.

   A similar pattern for women is found in columns (5) and (6) of panel B. The largest changes are in the proportions of nonwhite and white women graduating in business, which saw increases of 22 percentage points and 21 percentage...