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The causal effect of education on earnings

01 Jan 1999-Handbook of Labor Economics (Elsevier)-pp 1801-1863
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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01 Jan 2005
TL;DR: In this paper, the authors developed a comprehensive framework for the quantitative analysis of the private and fiscal returns to schooling and of the effect of public policies on private incentives to invest in education.
Abstract: This paper develops a comprehensive framework for the quantitative analysis of the private and fiscal returns to schooling and of the effect of public policies on private incentives to invest in education. This framework is applied to 14 member states of the European Union. For each of these countries, we construct estimates of the private return to an additional year of schooling for an individual of average attainment, taking into account the effects of education on wages and employment probabilities after allowing for academic failure rates, the direct and opportunity costs of schooling, and the impact of personal taxes, social security contributions and unemployment and pension benefits on net incomes. We also construct a set of effective tax and subsidy rates that measure the effects of different public policies on the private returns to education, and measures of the fiscal returns to schooling that capture the long-term effects of a marginal increase in attainment on public finances under conditions that approximate general equilibrium.

4 citations

01 Jan 2013
TL;DR: In this paper, the authors investigate the effect of fiscal externalities on the welfare analysis of government social programs and find that financial aid should be more generous, and that the optimal amount of aid roughly corresponds to eliminating tuition at public universities.
Abstract: The three chapters of this dissertation investigate the effect of fiscal externalities on the welfare analysis of government social programs. The first chapter introduces the subject of fiscal externalities, defined as the effects of a social program’s labour market impacts on income tax revenues, and assesses their importance in the context of optimal unemployment insurance. I calibrate and simulate a dynamic job search model, and perform a theoretical and numerical analysis of Baily’s (1978) twoperiod model of unemployment. The numerical results are significantly altered when fiscal externalities are taken into account: with moderate risk-aversion, the optimal replacement rate drops from around 40% to zero. However, higher risk-aversion moderates this effect, and a large positive effect of UI on wages could significantly increase the optimal benefit level. In the second chapter, I evaluate the optimal tuition subsidy policy for post-secondary education while taking into account two of the most prominent justifications for government financial aid: liquidity constraints and fiscal externalities. I present a simple model and apply a sufficient statistics method to solve for an equation for the welfare gain from increasing aid. I then use statistical extrapolations and a calibration and simulation of my model to estimate optimal student grants. I find that financial aid should be more generous, and that the optimal amount of aid roughly corresponds to eliminating tuition at public universities. These results are largely unchanged if students face no liquidity constraints, whereas general equilibrium effects of tuition subsidies on wages can significantly affect the results. iii In chapter 3, I add interactions between social programs to my study of fiscal externalities. I consider an example in which individuals can substitute between unemployment insurance and disability insurance, and demonstrate that the fiscal effects of substitution could significantly raise the optimal generosity of UI. I then present a general model which can be applied to any program of state-contingent transfers, and solve the model for a derivative of social welfare with respect to an individual program, with a simple and intuitive result that depends directly on the magnitude of fiscal externalities and program interaction effects.

4 citations

Journal ArticleDOI
TL;DR: The JCOIN Health Economics Analytic Team (HEAT) as discussed by the authors has worked closely with the Measures Committee to incorporate common economic measures and instruments across JCoIN studies, which will ensure rigorous economic evaluations within each trial; enhance comparability of findings across studies; and allow for cross-study analyses of trials with similar designs/settings (e.g., pre-reentry MOUD), to assess questions beyond the scope of a single study, while controlling for and evaluating the effect of intervention-, organizational-, and population-level characteristics.

4 citations

Journal ArticleDOI
TL;DR: In this article, the authors project the increase in human capital from higher education in Malawi and use a dynamic applied general equilibrium model to estimate the resulting macroeconomics impact, which is contingent upon endogenous adjustments, in particular how labour productivity affects competitiveness and if this in turn stimulates exports.
Abstract: Micro-econometric evidence reveals high private returns to education, most prominently in low-income countries. However, it is disputed to what extent this translates into a macro-economic impact. This paper projects the increase in human capital from higher education in Malawi and uses a dynamic applied general equilibrium model to estimate the resulting macroeconomics impact. This is contingent upon endogenous adjustments, in particular how labour productivity affects competitiveness and if this in turn stimulates exports. Choice among commonly applied labour market assumptions and trade elasticities results in widely different outcomes. Appraisal of such policies should consider not only the impact on human capital stocks, but also adjustments outside the labour market.

4 citations

Posted Content
TL;DR: The authors applied a recently introduced aggregation scheme for false discovery rate (FDR) control to German administrative data to determine the parts of the individual employment histories that are relevant for the career outcomes of women.
Abstract: We introduce tools for controlled variable selection to economists In particular, we apply a recently introduced aggregation scheme for false discovery rate (FDR) control to German administrative data to determine the parts of the individual employment histories that are relevant for the career outcomes of women Our results suggest that career outcomes can be predicted based on a small set of variables, such as daily earnings, wage increases in combination with a high level of education, employment status, and working experience

4 citations