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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 tries to capture the disparity in expenditure on primary education based on gender among the religious groups (Hindu, Muslim, and Christian) in rural India. The gender gap in education expenditure for a certain demographic group is calculated using the Oaxaca–Blinder decomposition approach. Further, we tried to identify the various household-related factors which might influence the decision of spending on a child's education. We used the 75th-level National Sample Survey Office (NSSO) unit-level dataset of July 2017 to June 2018 (one academic year) to obtain data on education expenditure and other household factors which play a manifesting role in the gender gap in expenditure on education. Our finding suggests that the total differential (log mean boys education expenditure-log mean girls education expenditure) is positive among all religious groups signifying the gender bias in education expenditure. We also found that the magnitude of the “Unexplained Effect” component is higher compared to the “Explained Effect” component signifying that the treatment of characteristics by students differs by their sex at elementary education. Household size and if household members are employed on a casual basis, then their expenditure on education falls on the other hand income of the household, a household with computer availability and household member engaged in regular wage/salary earning plays a positive role in expenditure on primary education in rural India.

Purpose – The chapter studies gender occupational segregation of rural-urban migrant workers in China based on 2006 survey data from five Chinese cities.

Methodology – The multinomial logit (MNL) model is used to analyze migrant workers' occupational attainment by gender. The Oaxaca–Blinder decomposition method is employed to analyze factors affecting gender occupational segregation, which can be classified into observed factors and unobserved factors, including gender discrimination.

Findings – The index of dissimilarity based on the data shows that gender occupational segregation for migrant workers exists. The result of Oaxaca–Blinder decomposition shows that the unobserved effects account for more than three-fourths of the total gender occupational segregation.

Research limitations – The “index problem” and the assumption of the same occupational preference between men and women of the Oaxaca–Blinder decomposition need to be addressed further.

Social implications – The existing gender equality policies and social protection confined to urban workers should be extended to migrant workers. Increasing training investment in migrant workers is also recommended.

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.

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.

To explore income inequality in urban China, this paper investigates disparities between- and within-urban locals and rural migrants from 2002 to 2013, using three waves of the China Household Income Project (CHIP) data. While the existing literature concentrates on the wage disparity between these two groups, our results show that the Gini among the migrants increased by 17.86% between 2007 and 2013 and that among the locals increased by 15.54% from 2002 to 2007. The urban–migrant average income gap decreased during the whole period mainly due to higher growth in migrants’ average income. Estimates based on Mincerian earnings functions for both groups reveal the significant role of the education, occupation and type of contract in determining the within-group inequality. In addition, using a recentred influence function (RIF), we observe that short-term and other types of contracts, duration of the job, in-system ownership, marriage and skill have inequality-enhancing effects for migrants. The variation of skills has a larger impact on the income disparity among migrants than on that among urban locals. The RIF-based Blinder–Oaxaca decomposition of the mean difference of incomes shows that labour market discrimination between the two groups is not significant; however, both pure explained and unexplained differences are significant when applying the RIF decomposition to the variance of the logarithms of incomes. While the type of contract significantly reduces the pure explained difference between migrants and urban locals, occupation has a positive impact on this difference between these two groups. The heterogenity analysis shows that the factors influencing incomes in these two groups are different. We recommend labour market intervention to reduce unreasonable occupational and sectoral disparities, especially in the net inflow provinces, to mitigate urban inequality in China effectively.

The Blinder Oaxaca decomposition method for defining wage differentials (generally referred to as discrimination) from the wage equations of two groups has had a wide degree of application. However, the decomposition measures can very dramatically depending on the definition of the non-discriminatory wage chosen for comparison. This paper uses a form of extreme bounds analysis to define the limits on the measure of discrimination that can be obtained from these decompositions. A simple application is presented to demonstrate the use of the bootstrap to define the distributions of the discrimination measure.

This paper analyzes the age pay gap in Italy (22%), particularly as it is of interest in an aging society and as it may affect social cohesion. Instead of the traditional approach for model selection, we use a machine-learning approach (post double robust Least Absolute Shrinkage Operator [LASSO]). This approach allows us to reduce Omitted Variable Bias (OVB), given data restrictions, and to obtain a robust estimate of the conditional age pay gap. We then decompose the conditional gap and analyze the impact of four further potential sources of heterogeneity (workers', sectors', and occupations' permanent heterogeneity as well as sample selection bias). The results suggest that age discrimination in pay is only perceived but not real in Italy for both men and women.

In this paper I investigate the nature of the differential in poverty by ethnicity in rural China using data from the Chinese Household Income Project in 2002. For that, I compare observed poverty with that in a counterfactual distribution in which ethnic minorities are given a set of relevant village and household characteristics of the Han majority. In particular, I investigate the importance of the location of minorities in explaining their higher poverty levels. The ethnic poverty differential does not change after equalizing the distribution of the population by geographical region (unless we use a higher poverty line). However, it is reduced after equalizing other locational characteristics of minorities (such as them living in less developed and mountainous areas), their larger number of children, their low education, and their fewer skilled non-agriculture workers. Finally, the ethnic per capita (log) income differential is shown to be higher for higher percentiles, with an increasing role of the geographical region as the main driver of these higher differentials.

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).