Explore the vast range of titles available.

We analyze gender differences in expected starting salaries along the wage expectations distribution of prospective university students in Germany, using elicited beliefs about both own salaries and salaries for average other students in the same field. Unconditional and conditional quantile regressions show 5–15% lower wage expectations for females. At all percentiles considered, the gender gap is more pronounced in the distribution of expected own salary than in the distribution of wages expected for average other students. Decomposition results show that biased beliefs about the own earnings potential relative to others and about average salaries play a major role in explaining the gender gap in wage expectations for oneself.

This paper provides a detailed exposition of an extension of the Oaxaca-Blinder decomposition method that can be applied to various distributional measures. The two-stage procedure first divides distributional changes into a wage structure effect and a composition effect using a reweighting method. Second, the two components are further divided into the contribution of each explanatory variable using recentered influence function (RIF) regressions. We illustrate the practical aspects of the procedure by analyzing how the polarization of U.S. male wages between the late 1980s and the mid 2010s was affected by factors such as de-unionization, education, occupations, and industry changes.

We propose a new regression method to evaluate the impact of changes in the distribution of the explanatory variables on quantiles of the unconditional (marginal) distribution of an outcome variable. The proposed method consists of running a regression of the (recentered) influence function (RIF) of the unconditional quantile on the explanatory variables. The influence function, a widely used tool in robust estimation, is easily computed for quantiles, as well as for other distributional statistics. Our approach, thus, can be readily generalized to other distributional statistics.

Indonesia is one of the world's largest developing countries, as evidenced by its position as the fourth most populous nation and its status as an archipelago. Each island and province has unique endowment factors, making national-level studies insufficient to fully capture regional disparities. This study addresses this issue by examining the relationship between structural transformation and regional inequality differentials in both regional and provincial contexts. To analyse the effects of structural transformation on regional inequality differentials, the recentred influence function (RIF) regression is employed. The study utilises data from the National Socioeconomic Survey (Susenas), covering a span of fifteen years (2004-2019). The analysis is categorised by the level of structural transformation across provinces (developed, developing or underdeveloped) and spatial groupings (Jawa versus non-Jawa regions). The key findings are as follows: first, structural transformation is most pronounced on the island of Jawa, though several other provinces also experience significant changes. Second, the composition effect is a major factor contributing to the increase in regional inequality differentials in both provincial and regional contexts, with labour endowment being crucial in explaining regional disparities. Third, the rise in regional inequality differentials is largely driven by urbanisation and sectoral shifts, which are components of structural transformation. These findings contribute to the literature by addressing the gap in the analysis of regional structural transformation in developing countries. Moreover, this study provides valuable insights for policymakers aiming to mitigate inequality disparities between islands and provinces.

We study the determinants of wage inequality and its fluctuations in six Central-Eastern European nations using European Union Statistics on Income and Living Conditions microdata from 2010 to 2019. Wage disparity in these countries changed in distinct ways. Inequality in Czechia and Romania is generally steady, has fallen consistently in Poland and Slovakia, and has increased in Bulgaria. Inequality has been steadily reducing in Hungary but has recently increased significantly. Therefore, this paper questions these countries' primary causes of wage inequality changes. In addition to providing a detailed description of inequality trends in these countries, we focus on examining the demographic and micro-level determinants alongside the minimum wage changes. We estimate these effects using RIF regression and RIF decompositions for various inequality measures. The changes in wage inequality in these countries were driven mainly by wage structure effects regardless of the increase or decrease in wage inequality. Changes in the returns to education and returns to permanent employment contracts are crucial in explaining decreased wage inequality. The increases in wage inequality in Hungary and Bulgaria are defined mainly by the changes in the estimated constants instead of micro-level determinants. The changes in the minimum wage explain most of the unknown factors in Bulgaria, and the spillover effects of the minimum wage may explain most of the unknown factors in Hungary. Our results can support the skill-biased technological change hypothesis in the case of Slovakia, Romania, Czechia, and Bulgaria.

We use large linked employer-employee data to analyze wage inequality patterns in Central and Eastern European (CEE) countries between 2002 and 2014. We show that, unlike in many other advanced economies, wage inequality levels have decreased in almost all CEE countries. These reductions in wage inequality resulted from disproportionately large increases in wages at the bottom of the wage distribution, and from decreases in between-firm wage inequality. We further find that the declines in wage inequality were driven by large wage structure effects that compensated for changes in the composition of workers.

This study estimates student loan borrowers’ repayment burdens (RBs) in South Korea. Using data from the Survey Report on Labor Conditions by Employment Type and novel administrative records, we estimate life-cycle earnings profiles by income quantile through RIF regression. These estimates are then used to derive RBs for hypothetical borrowers under income-contingent loans (ICLs) and mortgage-type loans, and to evaluate RBs for actual ICL borrowers by matching them with estimated income profiles. The findings suggest that Korea’s student loan system plays a positive role in expanding access to higher education, particularly through ICLs. Many low-income students who benefited from ICLs are later found in the top income deciles. However, raising the repayment threshold irrespective of borrower income may delay repayment and reduce system efficiency. These results underscore the importance of aligning repayment rules with borrowers’ earnings trajectories to ensure both equity and the long-term sustainability of the loan system.

This paper suggests a generalization of covariate shifts to study distributional impacts on inequality and distributional measures. It builds on the recentered influence function (RIF) regression method, originally designed for location shifts in covariates, and extends it to general policy interventions, such as location–scale or asymmetric interventions. Numerical simulations for the Gini, Theil, and Atkinson indexes demonstrate strong performance across a myriad of cases and distributional measures. An empirical application examining changes in Mincerian equations is presented to illustrate the method.

The purpose of the present paper is to analyse the gap among Italian macro-areas performances in terms of separate waste collection rate and density of separate waste collection. The aim is twofold: (1) to investigate if clear and effective infrastructure policies, in Southern Italy, have been realized that are able to reduce the gap in the separate waste collection process with the rest of Italy and (2) to evaluate if Southern Italian municipalities have improved their operational capacity in the separate waste collection process. In particular, we exploit data collected in 2012 by several Italian sources (ISPRA and ISTAT). We implement a recentered influence function regression technique that allows us to put two macro-areas in comparison (North vs. South and Centre vs. South). This technique, once measured the territorial gaps, allows to disentangle the gap in the two spatial units of analysis (at municipalities level and at macro-areas level). The estimates suggest that while in the North the issue of waste is managed effectively and responsibly with respect to the Southern area, the latter has exhibited an advantage with respect to the Central Italy; furthermore, Southern municipalities appear to be unable to pursue a virtuous waste management system generating the persistence of a marked territorial gap in terms of both SCR and DSC. The main policy implications are discussed.

The Pink Tide had a profound political and economic impact on Latin America. While the existing literature explores its drivers and reversal, this article addresses a gap by combining two decomposition methods with a dataset on values and perceptions. It makes three contributions. First, it quantifies the role of two key drivers: slow structural changes in society and faster shifts in political preferences. Second, it identifies which segments of the electorate experienced the largest preference shifts, using a novel combination of Oaxaca–Blinder and recentered influence function regressions—yielding the first empirical estimates of changes across the preference distribution. Third, it expands the use of these decomposition techniques beyond economic outcomes, offering tools for broader political analysis. The results show that 90 percent of the leftward shift during the Pink Tide stemmed from changes in voter preferences, not strategic “vote lending.” The entire ideological distribution moved leftward, not just centrist voters. Similarly, the rightward reversal was driven entirely by preference changes and extended across nearly the whole electorate.   JEL Classification Codes: D72; O54; C21; C51; P16