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This chapter uses a college-by-graduate degree fixed effects estimator to evaluate the returns to 19 different graduate degrees for men and women. We find substantial variation across degrees, and evidence that OLS overestimates the returns to degrees with the highest average earnings and underestimates the returns to degrees with the lowest average earnings. Second, we decompose the impacts on earnings into effects on wage rates and effects on hours. For most degrees, the earnings gains come from increased wage rates, though hours play an important role in some degrees, such as medicine, especially for women. Third, we estimate the net present value and internal rate of return for each degree, which account for the time and monetary costs of degrees. Finally, we provide descriptive evidence that satisfaction gains are large for some degrees with smaller economic returns, such as education and humanities degrees, especially for men.

Purpose – The aim of this chapter is to measure the wage premium associated with various levels of educational attainment using micro-data from the Luxembourg Income Study. The study focuses on working-aged adults in eight developed countries for various years between 1984 and 2005.

Methodology – The chapter computes wage ratios reflecting the premium associated with low, medium, and high levels of educational attainment, which correspond to completion of less than secondary education, secondary education, and tertiary education, or an equivalent level of vocational training. These ratios, along with several other variables, are then related to the 90/10, 75/25, 90/50, and 50/10 wage ratios in a country-level unbalanced pooled cross-sectional time series analysis.

Findings – Returns to education account for an important share of cross-country variation in various modes of wage inequality, although other variables matter as well.

Research limitations – The data needed to compute returns to education data are unavailable for a number of countries and years.

Originality – The chapter offers a more precise measure of the returns to education than earlier cross-national work, which has typically focused on average levels of education and other aggregate measures.

This paper argues that the assumption of a homogeneous workforce, which is implicitly invoked in the decomposition analysis of changes in welfare indicators, hides the role that schooling and its returns may have on the understanding of these changes. Using Peruvian cross-sectional data for a period of 10 years (2004–2013) and counterfactual simulations, this paper finds that the main factor contributing to poverty reduction has been individuals’ changes in labor earnings, and the role of these changes has been less important in reducing income inequality. The main driving force of reduced income inequality has been the fall in returns to education, which at the same time has been one of the important factors to constraining the period’s remarkable progress in poverty reduction and expansion of the middle class.

We study how the returns to education in the adult labor market affect children's school enrollment. We show that when families are liquidity constrained, the expected relationship between higher returns and children's schooling is ambiguous. When liquidity constraints matter, the relationship can only be assessed empirically. For African-South African liquidity-constrained households, we find a positive relationship that is quite robust.

This paper documents how gender differences in occupational status (defined by earnings, education, and returns to skills) have evolved over time and across generations. The paper finds a persistent gender earnings gap, a reversal of the education gap, and a convergence in starting salaries and returns to experience. Divergent occupational choices might explain part of the persistent gender gaps and women’s failure to reach parity with men in the earnings distribution. Women choose more flexible jobs than men. But whereas men dominate women in high-powered occupations, they are also more likely to be in low-skilled low-pay occupations. Differential effects of children and time spent keeping house explain most of the gender gap in high-powered occupations but cannot explain fully why women choose more flexible occupations.

Between 1995 and 2012, the wage distribution of male workers in Brazil shifted to the right and became less dispersed. This paper attempts to identify the reasons for that movement in male wage distribution, focusing on the impact of education expansion on wage distribution. The Oaxaca-Blinder (OB) and Recentered Influence Function (RIF) decomposition results show that both changes in returns on skills and upgrades in the composition of work skills contribute to increases in the average wage and wages at the 10th and 50th percentiles. The shifts in returns to skills had a decreasing impact on wages at the 90th percentile and are identified as the primary force reducing wage inequality. Education expansion had an equalizing impact on wage distribution, primarily through the decline in return to education.

This chapter examines the impact of education on income inequality in 18 Latin American countries between 2000 and 2010. This period has raised interest in the academic community because inequality has fallen across the region, after several years of consistent high levels. Employing the novel technique proposed by Firpo, Fortin, and Lemieux (2007), the author’s research provides a detailed decomposition of inequality. Three main findings emerge from the author’s results: First, the expansion of education increases inequality in six countries but reduces inequality in four countries. Second, the changes in returns to education are the driving component of the effects of education on inequality. Those countries where education contributes to a fall in inequality are those where the returns to education fell at the top of the income distribution. Third, the rise in the average years of education, considered alone, had an inequality-increasing effect in most of the countries under analysis.

We use OECD-PIAAC data to estimate the earnings effects of both years of education and of numerical skills. Our identification strategy exploits differential exposure to educational reforms across birth cohorts and countries. We find that education has the strongest earnings effect. A one standard deviation increase in years of education raises earnings by almost 22 percentage points (corresponding to a return to education above 7 percentage points), which compares with a lower percentage points return to an equivalent increase in numerical skills. Our results suggest that the same set of unobservables drives the accumulation of both formal years of education and numeracy skills. OLS estimates underestimate returns to human capital, consistently with the idea that educational reforms favor the human capital acquisition of abler children from disadvantaged parental backgrounds. When we consider numerical skills alone education reforms cannot identify any significant effect of skills on wages, however, when we jointly consider schooling and skills as endogenous factors in a recursive structure we find a significant role for skills in determining wages.

This chapter addresses the following questions: To what extent do the socio-economic characteristics of circular/repeat migrants differ from the migrants who return permanently to the home country after their first trip (i.e. return migrants)? And, what determines each of these distinctive temporary migration forms? Using Albanian household survey data and both a multinomial logit model and a maximum simulated likelihood (MSL) probit with two sequential selection equations, we find that education, gender, age, geographical location and the return reasons from the first migration trip significantly affect the choice of migration form. Compared to return migrants, circular migrants are more likely to be male, have primary education and originate from rural, less developed areas. Moreover, return migration seems to be determined by family reasons, a failed migration attempt but also by the fulfilment of a savings target.