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The causal effect of education on earnings
TL;DR: This paper surveys the recent literature on the causal relationship between education and earnings and concludes that the average (or average marginal) return to education is not much below the estimate that emerges from a standard human capital earnings function fit by OLS.
Abstract: This paper surveys the recent literature on the causal relationship between education and earnings. I focus on four areas of work: theoretical and econometric advances in modelling the causal effect of education in the presence of heterogeneous returns to schooling; recent studies that use institutional aspects of the education system to form instrumental variables estimates of the return to schooling; recent studies of the earnings and schooling of twins; and recent attempts to explicitly model sources of heterogeneity in the returns to education. Consistent with earlier surveys of the literature, I conclude that the average (or average marginal) return to education is not much below the estimate that emerges from a standard human capital earnings function fit by OLS. Evidence from the latest studies of identical twins suggests a small upward "ability" bias -- on the order of 10%. A consistent finding among studies using instrumental variables based on institutional changes in the education system is that the estimated returns to schooling are 20-40% above the corresponding OLS estimates. Part of the explanation for this finding may be that marginal returns to schooling for certain subgroups -- particularly relatively disadvantaged groups with low education outcomes -- are higher than the average marginal returns to education in the population as a whole.
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TL;DR: In this article, the authors analyzed the factors that influence rural non-agricultural employment and earnings and found that education stands out as one of the key factors that shape employment outcome and earnings potential.
56 citations
TL;DR: The authors used data from the 1979 National Longitudinal Survey of Youth (NLSS) to estimate wage models in which college-educated workers are classified according to their degree attainment, college type, and college transfer status.
Abstract: Using data from the 1979 National Longitudinal Survey of Youth, we estimate wage models in which college-educated workers are classified according to their degree attainment, college type, and college transfer status. The detailed taxonomy produces modest improvements in explanatory power relative to standard specifications, and reveals considerable heterogeneity in the predicted wages of college-educated workers. We find that transfer students receive an “indirect” wage benefit insofar as changing colleges allows them to earn a degree. Some transfer students receive an additional “direct” wage benefit, presumably because switching schools increases their skill investment opportunities.
56 citations
TL;DR: In this article, the positive relationship between return to education and the risk involved in this investment is studied using results for 16 countries, and it seems that most of the countries fit the pattern well: higher risk-higher return and the tradeoff is rather large.
56 citations
TL;DR: In this article, the authors investigated the effects of human capital on productivity using micro panel data of rural households in the North-West Frontier Province, Pakistan, where a sub-stantial job stratification is observed in terms of income and education.
Abstract: This paper investigates the effects of human capital on productivity using micro panel data of rural households in the NorthWest Frontier Province, Pakistan, where a sub stantial job stratification is observed in terms of income and education. To clarify the mechanism underlying this stratification, the human capital effects are estimated for wages (individual level) and for selfemployed activities (household level), and for farm and nonfarm sectors. Estimation results show a clear contrast between farm and non farm sectors — wages and productivity in nonfarm activities rise with education at an increasing rate, whereas those in agriculture respond only to the primary education.
56 citations
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TL;DR: In this paper, the authors used the Qualification and Career survey (QC) data set with information on 1 percent of all individuals employed in Germany in 1998/1999 and used a one-step full-information maximum likelihood and a two stage least squares estimation to regress the impact of training participation on earnings.
Abstract: While there is a broad literature on the general wage eect of training, little is known about the eects of dierent training forms and about the eects for heterogeneous training participants This study therefore adds two aspects to the literature on earnings eects of training First, the earnings eect of training is calculated for different types of employees, ie discriminating between qualification level, experience, job tenure, and other attributes Second, we distinguish between the earnings impact of external and internal training For our analysis, we use the Qualification and Career survey, a rich German data set with information on 01 percent of all individuals employed in Germany in 1998/1999 We use a one-step full-information maximum likelihood and a two stage least squares estimation to regress the impact of training participation on earnings correcting for the endogeneity of training participation By using a broad list of employee and employer characteristics, we try to avoid omitted variable bias We find the training earnings markup to be positively correlated with qualification and experience The analysis of internal and external training reveals that this result is driven by external training only Internal training does not have a significant earnings eect The correction for selection into training leads to an increase in the training coecients and a decrease of its significance
56 citations