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We examine the cardinal gap between wage distributions of the incumbents and newly hired workers based on entropic distances which are well-defined welfare theoretic measures. Decomposition of several effects is achieved by identifying several counterfactual distributions of different groups. These go beyond the usual Oaxaca–Blinder decompositions at the (linear) conditional means. Much like quantiles, these entropic distances are well-defined inferential objects and functions whose statistical properties have recently been developed. Going beyond these strong rankings and distances, we consider weak uniform ranking of these wage outcomes based on statistical tests for stochastic dominance. The empirical analysis is focused on employees with at least 35 hours of work in the 1996–2012 monthly Current Population Survey (CPS). Among others, we find incumbent workers enjoy a better distribution of wages, but the attribution of the gap to wage inequality and human capital characteristics varies between quantiles. For instance, highly paid new workers are mainly due to human capital components, and in some years, even better wage structure.

Building on recent advances in inverse probability weighted identification and estimation of counterfactual distributions, the authors examine the history of wage earnings for women and their potential wage distributions in the United States. These potentials are two counterfactuals, what if women received men’s market “rewards” for their own “skills,” and what if they received the women’s rewards but for men’s characteristics? Using the Current Population Survey data from 1976 to 2013, the authors analyze the entire counterfactual distributions to separate the “structure” and human capital “composition” effect. In contrast to Maasoumi and Wang (2019), the reference outcome in these decompositions is women’s observed earnings distribution, and inverse probability methods are employed, rather than the conditional quantile approaches. The authors provide decision theoretic measures of the distance between two distributions, to complement assessments based on mean, median, or particular quantiles. We assess uniform rankings of alternate distributions by tests of stochastic dominance in order to identify evaluations robust to subjective measures. Traditional moment-based measures severely underestimate the declining trend of the structure effect. Nevertheless, dominance rankings suggest that the structure (“discrimination”?) effect is bigger than human capital characteristics.

Many developing and transition countries, and even some in the industrialized West, experience periods in which a substantial proportion of the workforce suffer wage arrears. We examine the implications for estimates of wage gaps and inequality using the Russian labor market as a test case. Wage inequality grew rapidly as did the incidence of wage arrears in Russia in the 1990s. Given data on wages and the incidence of wage arrears we construct counterfactual wage distributions, which give the distribution of pay were arrears not present. The results suggest that wage inequality could be some 30 percent lower in the absence of arrears. If individuals in arrears are distributed across the underlying wage distribution, as appears to be the case in Russia, we show that it may be feasible to use the wage distribution for the subset of those not in arrears to estimate the underlying population wage distribution parameters.

The purpose of this paper is to perform an investigative analysis of the distribution of agricultural growth in China and the evolution of the decision mechanism.

The kernel density estimation method was used to investigate the distribution of agricultural growth in China using 1988‐2008 panel data of the 29 provinces on the mainland. A nonparametric income distribution approach was employed to decompose China's agricultural output growth into farmland accumulation, capital deepening, labor‐scale change, technical change, and efficiency change based on stochastic frontier function. A further investigation of the evolution of the decision mechanism for agricultural growth was then performed using counterfactual analysis.

The results of this analysis indicate that: from 1996, the distribution of agricultural output per worker evolved from a unimodal into a bimodal distribution; technical change is the primary impetus to distribution shift; and capital deepening and efficiency change play a dominant role in the deformation of the distribution of agricultural output per worker from a unimodal to a bimodal distribution.

The paper is an original work and its methodology makes a meaningful contribution to understanding China's agricultural growth. That is, the use of income distribution analysis method to analyze agricultural growth does not only allow a more in‐depth understanding of the gap between regional agricultural growth rates, but also makes up for the existing lack of convergence in agricultural growth in China.

This study uses migrant household survey data from 2008 to 2009 to examine how parental migration decisions are associated with the nutritional status of children in rural and urban China. Results from instrumental variables regressions show a substantial adverse effect of children’s exposure to parental migration on height-for-age Z scores of left-behind children relative to children who migrate with their parents. Additional results from a standard Blinder–Oaxaca decomposition, a quantile decomposition, and a counterfactual distribution analysis all confirm that children who are left behind in rural villages – usually because of the oppressive hukou system – have poorer nutritional status than children who migrate with their parents, and the gaps are biggest at lower portions of the distribution.

We examine the potential effect of naturalization on the U.S. immigrants’ earnings. We find the earning gap between naturalized citizens and noncitizens is positive over many years, with a tent shape across the wage distribution. We focus on a normalized metric entropy measure of the gap between distributions, and compare with conventional measures at the mean, median, and other quantiles. In addition, naturalized citizen earnings (at least) second-order stochastically dominate noncitizen earnings in many of the recent years. We construct two counterfactual distributions to further examine the potential sources of the earning gap, the “wage structure” effect and the “composition” effect. Both of these sources contribute to the gap, but the composition effect, while diminishing somewhat after 2005, accounts for about 3/4 of the gap. The unconditional quantile regression (based on the Recentered Influence Function), and conditional quantile regressions confirm that naturalized citizens have generally higher wages, although the gap varies for different income groups, and has a tent shape in many years.

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.

Income inequality rose in Germany since the 1970s. To quantify the impact of different socio-economic trends on inequality, the author constructs counterfactual distributions of net household income with rich German data from the Microcensus in 1976 and 2011. The procedure allows to study the effect of marital sorting in education and includes indirect effects such as the influence of education on employment. When comparing the income distribution in West Germany for 1976 and 2011, the author finds that the prevalence of singlehood accounts to a large extent for the observed increase in inequality. The inequality increase is also associated with a change of employment among males and single females. When comparing West and East Germany in 2011, the author finds that the stronger labour market attachment of East German married females combined with the high East German unemployment produces even more income inequality than the West German employment structure. Moreover, the smaller household size boosts inequality in East Germany, whereas education works against it. In both comparisons, the author finds no significant impact of positive assortative mating in education or ageing.

This chapter uses the nonlinear difference-in-difference (NL-DID) methodology developed by Athey and Imbens (2006) to estimate the effects of a treatment program on the entire distribution of an outcome variable. The NL-DID estimates the entire counterfactual distribution of an outcome variable that would have occurred in the absence of treatment. This chapter extends the Monte Carlo results in Athey and Imbens's (2006) to assess the efficacy of the NL-DID estimators in finite samples. Furthermore, the NL-DID methodology recovers the entire outcome distribution in the absence of treatment. Further, we consider the empirical size and power of tests statistics for equality of mean, medians, and complete distributions as suggested by Abadie (2002). The results show that the NL-DID estimator can effectively be used to recover the average treatment effect, as well as the entire distribution of the treatment effects when there is no selection during the treatment period in finite samples.

We investigate the reasons why income inequality is so high in Spain in the EU context. We first show that the differential in inequality with Germany and other countries is driven by inequality among households who participate in the labor market. Then, we conduct an analysis of different household income aggregates. We also decompose the inter-country gap in inequality into characteristics and coefficients effects using regressions of the Recentered Influence Function for the Gini index. Our results show that the higher inequality observed in Spain is largely associated with lower employment rates, higher incidence of self-employment, lower attained education, as well as the recent increase in the immigration of economically active households. However, the prevalence of extended families in Spain contributes to reducing inequality by diversifying income sources, with retirement pensions playing an important role. Finally, by comparing the situations in 2008 and 2012, we separate the direct effects of the Great Recession on employment and unemployment benefits, from other more permanent factors (such as the weak redistributive effect of taxes and family or housing allowances, or the roles of education and the extended family).