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In contrast to studies that identify the expected earnings premium associated with any STEM degree or with specific college majors, we account for workers’ majors and the percent of total college credits completed in STEM courses (STEM intensity). We find that STEM intensity is an important determinant of log-earnings for many STEM and non-STEM majors, and that estimated earnings gaps between pairs of majors can change dramatically when STEM intensity is accounted for. In light of this evidence, we believe policy initiatives focused on drawing students into STEM should emphasize the potential value of STEM coursework for non-STEM majors. [ABSTRACT FROM AUTHOR]

Using a sample of college graduates from the NLSY97, we introduce a new approach to assessing wage benefits of STEM training, STEM jobs, and the match between the two: rather than classify individuals dichotomously as STEM or non-STEM, we measure the STEM-intensities of both their college coursework and their occupational requirements. While the orthodox approach simply predicts that 'STEM pays,' we find that workers at the top of both gender-specific STEM-intensity distributions are predicted to out-earn their counterparts at the bottom by a substantial margin -- even when we condition on their dichotomous STEM classification -- but that predicted log-wages do "not" increase monotonically with STEM-intensity throughout the entire joint distribution.

Economists have invested a great deal of effort in trying to understand the motivation for family transfers, yet recent empirical work testing the seemingly appealing models of altruism and exchange has led to decidedly mixed results. A major stumbling block has been the lack of adequate data. We take a fresh look at the issue using responses to an innovative survey question that directly asks mother about the planned division of their estates. We find that both altruism and exchange are frequently offered as explanations of behavior and are of nearly equal importance. Furthermore, the explanations are consistent with observable characteristics of the mother, lending support to the validity of the question. We also find that among step or adopted families, genetic ties play an important role. Because motivating factors appear to differ across families the lack of a consensus among previous researchers about motives ought not to be surprising.

Researchers often identify degree effects by including degree attainment ("D") and years of schooling ("S") in a wage model, yet the source of independent variation in these measures is not well understood. We argue that "S" is negatively correlated with ability among degree-holders because the most able graduate the fastest, but positively correlated among dropouts because the most able benefit from increased schooling. Using NLSY79 data, we find support for this argument; our findings also suggest that highest grade completed is the preferred measure of "S" for dropouts, while age at school exit is a more informative measure for degree-holders. (Contains 3 figures, 6 tables, and 15 footnotes.)

Uses data for male high-school graduates to estimate a wage model that includes detailed measures of high-school coursework and postschool work experience as covariates. High-school employment's direct effect on subsequent wages is small and relatively short-lived. Vocational courses and postgraduation work experience provide indirect benefits. (30 references) (MLH)

Uses National Longitudinal Study of Youth data to determine how estimated returns to schooling are influenced by career starting date choice. Defines schooling and experience measures for four alternative starting dates. Uses results to estimate standard wage model for samples of white and nonwhite men. Returns to schooling increase dramatically when using increasingly late starting date, because "pre-career" work experience biases schooling effects. (27 references) (MLH)