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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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01 Jan 2014
TL;DR: In this article, the authors used various specifications of Mincer-type model to estimate returns to higher education in Pakistan using the 2008 PSLM survey and found that household income per month increases with attaining higher education indicating that private returns to the higher education (collectively graduate and undergraduate levels) is the highest as compared to other levels of education.
Abstract: The study estimated returns to various levels of education in Pakistan using the 2008 PSLM survey. The study used various specifications of Mincer-type model to estimate returns to higher education. Analysis showed that as compared to primary education, income of household increased by Rs. 540.3 with attaining education of middle, which further increases by Rs. 919.2 with secondary education. Under-graduates have a per month income of Rs. 3,334.5 higher than those having primary education which further increases to Rs. 4,378 for graduates. Hence, household income per month increases with attaining higher education indicating that private returns to higher education (collectively graduate and undergraduate levels) is the highest as compared to other levels of education. Promoting higher education in the country can be a very useful tool to fight the menace of poverty.
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TL;DR: The authors used a longitudinal survey from the city of Cape Town, South Africa to evaluate two main outcomes of young adults, namely labor market attachment and fertility, and its relation to orphanhood status, and found that although preexisting parental background characteristics and literacy and numeracy skills are comparable between orphans and non-orphans, the latter are less likely to be employed or to have children (females) early in their lives.
Abstract: More than 2 million South African children under age 17 have lost one or both of their parents. Previous research has established that parental death has a negative effect in terms of school enrollment and grade progression, but the relation between orphanhood and socioeconomic outcomes in young adults has been largely ignored in the literature. In this paper, I use a longitudinal survey from the city of Cape Town, South Africa to evaluate two main outcomes of young adults, namely labor market attachment and fertility, and its relation to orphanhood status. The uniqueness of this dataset lies within the combination of different survey waves with a life history calendar that records schooling, work, and fertility outcomes, as well as living arrangements for every year the young adult has lived since birth. Additional information on so-called “parental investments” (time and material support), family background, and literacy and numeracy test scores are also included. These features make it a rich source of data to understand fertility and labor market attachment for young adults in light of conditions earlier in life, and specifically to test for long lasting effects associated with parental death and to identify mediating factors. I find that although preexisting parental background characteristics and literacy and numeracy skills are comparable between orphans and non-orphans, the latter are less likely to be employed (true primarily for males) or to have children (females) early in their lives. Evidence is mixed regarding whether orphans earn lower wages than non-orphans. These results suggest that orphanhood may not only alter educational achievements, but that it may also leave a long-lasting “imprint” in terms of employment and fertility patterns.
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TL;DR: In this article, the authors analyzed to what extent returns associated with completing a university degree in Switzerland depend on the propensity to attend and complete this degree using data from the Swiss Household Panel and propensity score matching models.
Abstract: Recent literature on private returns to education considers diversity in the population, heterogeneity in wage gains and self-selection into schooling. This research addresses these issues by analyzing to what extent returns associated with completing a university degree in Switzerland depend on the propensity to attend and complete this degree. Using data from the Swiss Household Panel and propensity score matching models, I find that low propensity men — after controlling for labor market variables — benefit most from a university degree while returns for women are rather homogenous along the propensity score distribution. This finding suggests that completing university increases more the earning capability of men with disadvantaged family backgrounds than that of men with more favorable background, refuting the hypothesis of comparative advantage. An auxiliary analysis focusing on the relationship between returns to education and inherent ability within a quantile regression framework leads to similar conclusions.
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TL;DR: In this paper, the authors revisited the optimal distribution of income model in Fair (1971) and used the DFP algorithm with numeric derivatives to compute the Gini coefficient, which provides a metric for comparing the redistributive effects under different assumptions.
Abstract: This paper revisits the optimal distribution of income model in Fair (1971). This model is the same as in Mirrlees (1971) except that education is also a decision variable and tax rates are restricted to lie on a tax function. In the current paper the tax-rate restriction is relaxed. As in Fair (1971), a numerical method is used. The current method uses the DFP algorithm with numeric derivatives. Because no analytic derivatives have to be taken, it is easy to change assumptions and functional forms and run alternative experiments. Gini coefficients are computed, which provides a metric for comparing the redistributive effects under different assumptions. Ten optimal marginal tax rates are computed per experiment corresponding to ten tax brackets.The sensitivity of the results to the four main assumptions of the model are examined: 1) the form of the social welfare function that the government maximizes, 2) the form of the utility function that each individual maximizes, 3) the distribution of ability across individuals, and 4) the rate of return to education. The changes in the Gini coefficient from before-tax income to after-tax income for the experiments are compared to actual changes from various countries. Experiments using a lognormal distribution of ability match the data better than those using a lognormal distribution with a Pareto tail --- there is less actual redistribution than a Pareto tail implies. The numerical approach in this paper has advantages over the use of analytic expressions. When functional forms are changed, it may be easier to run a new numerical experiment then use an analytic expression, which can be complicated. Also, although not done in this paper, individual heterogeneity is straightforward to handle. The coding can have a different utility function for each individual. And different assumptions about education can be easily incorporated. The approach also shows the problematic nature of assuming a quasi-linear utility function --- a utility function with no income effects.
2 citations