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310
Trends in US Wage Inequality: Revising the Revisionists
, 2007
"... A large literature documents a substantial rise in U.S. wage inequality and educational wage differentials during the 1980s and early 1990s and concludes that these wage structure changes can be accounted for by shifts in the supply of and demand for skills reinforced by the erosion of labor market ..."
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Cited by 158 (3 self)
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A large literature documents a substantial rise in U.S. wage inequality and educational wage differentials during the 1980s and early 1990s and concludes that these wage structure changes can be accounted for by shifts in the supply of and demand for skills reinforced by the erosion of labor market institutions supporting low and middlewage workers. Drawing on an additional decade of data, several “revisionist ” studies reject this consensus to conclude that (1) the rise in wage inequality was an “episodic ” event of the firsthalf of the 1980s, (2) this rise was mainly caused by a falling minimum wage, and (3) increased residual wage inequality since the mid1980s reflects the confounding effects of labor force composition. We reexamine these claims using data from the Current Population Survey for 1963 to 2005 and find only limited support. A slowing of the growth of overall wage inequality in the 1990s hides a divergence in the paths of uppertail (90/50) and lowertail (50/10) inequality. Uppertail wage inequality has been increasing steadily since 1980 even after adjusting for labor force composition changes. Lowertail wage inequality increased sharply in the firsthalf of the 1980s but has flattened or narrowed since the late 1980s. Strong time series correlations of the real minimum wage and uppertail wage inequality raise questions concerning the causal interpretation of relationships between the minimum wage and both overall and
Is There a Glass Ceiling over Europe? Exploring the Gender
 Pay Gap across the Wages Distribution”, Industrial and Labor Relations Review 60
, 2007
"... Using harmonized data for the years 19952001 from the European Community Household Panel, the authors analyze gender pay gaps by sector across the wage dis tribution in eleven countries. In estimations that control for the effects of individual characteristics at different points of the distributio ..."
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Cited by 135 (3 self)
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Using harmonized data for the years 19952001 from the European Community Household Panel, the authors analyze gender pay gaps by sector across the wage dis tribution in eleven countries. In estimations that control for the effects of individual characteristics at different points of the distribution, they calculate the part of the gap attributable to differing returns between men and women. The magnitude of the gen der pay gap, thus measured, varied substantially across countries and across the public and private sector wage distributions. The gap typically widened toward the top of the wage distribution (the "glass ceiling " effect), and in a few cases it also widened at the bottom (the "sticky floor " effect). The authors suggest that differences in childcare provision and wage setting institutions across EU countries may partly account for the variation in patterns by country and sector. Although the mean gender wage gap has been extensively studied in the labor eco nomics literature, only relatively recently has attention shifted to investigating the degree to which the gender gap might vary across the wage distribution and why. Albrecht, Bjorklund, and Vroman (2003), using 1998 data for Sweden, showed that the gender wage gap was increasing throughout the wage distribution and accelerating at the top, and they interpreted this as evidence of a glass ceiling in Sweden. De la Rica, Dolado, and
Unconditional quantile regressions
 Technical Working Paper 339, National Bureau of Economic Research
, 2007
"... Preliminary Paper, Comments Welcome We propose a new regression method for modelling unconditional quantiles of an outcome variable as a function of explanatory variables. The method consists of running a regression of the (recentered) influence function of the unconditional quantile of the dependen ..."
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Cited by 68 (0 self)
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Preliminary Paper, Comments Welcome We propose a new regression method for modelling unconditional quantiles of an outcome variable as a function of explanatory variables. The method consists of running a regression of the (recentered) influence function of the unconditional quantile of the dependent variable on the explanatory variables. The influence function is a widely used tool in robust estimation that can easily be computed for each quantile of interest. The estimated regression model can be used to infer the impact of various explanatory variable on a given unconditional quantile, just like the regression coefficients are used in the case of the mean. Our approach can thus be used, for example, to decompose quantiles as a function of the different explanatory variables (as in a standard OaxacaBlinder mean decomposition), or to predict the effect of changes in policy or other variables on quantiles.
Quantile Regression under Misspecification, with an Application to the U.S
 Wage Structure. Econometrica
, 2006
"... Quantile regression (QR) fits a linear model for conditional quantiles, just as ordinary least squares (OLS) fits a linear model for conditional means. An attractive feature of OLS is that it gives the minimum mean square error linear approximation to the conditional expectation function even when t ..."
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Cited by 51 (5 self)
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Quantile regression (QR) fits a linear model for conditional quantiles, just as ordinary least squares (OLS) fits a linear model for conditional means. An attractive feature of OLS is that it gives the minimum mean square error linear approximation to the conditional expectation function even when the linear model is misspecified. Empirical research using quantile regression with discrete covariates suggests that QR may have a similar property, but the exact nature of the linear approximation has remained elusive. In this paper, we show that QR minimizes a weighted meansquared error loss function for specification error. The weighting function is an average density of the dependent variable near the true conditional quantile. The weighted least squares interpretation of QR is used to derive an omitted variables bias formula and a partial quantile regression concept, similar to the relationship between partial regression and OLS. We also present asymptotic theory for the QR process under misspecification of the conditional quantile function. The approximation properties of QR are illustrated using wage data from the US census. These results point to major changes in inequality from 19902000.
Ceiling and Floors: Gender Wage Gaps by Education in Spain."
 IZA Discussion Paper
, 2005
"... ABSTRACT This paper analyses the gender gap throughout the wage distribution in Spain using data from the ECHP. Quantile regression and panel data techniques are used to estimate wage equations for high and lesseducated workers at relevant percentiles in a given representative year (1999), and ove ..."
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Cited by 51 (0 self)
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ABSTRACT This paper analyses the gender gap throughout the wage distribution in Spain using data from the ECHP. Quantile regression and panel data techniques are used to estimate wage equations for high and lesseducated workers at relevant percentiles in a given representative year (1999), and over time (1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001). In contrast with the steep increasing pattern found in other countries, the flatter evolution of the Spanish gender gap hides an intriguing composition effect when the sample of workers is split by education. For higheducated workers, in line with the predictions of conventional glass ceiling hypothesis, the gap increases as we move up the distribution. However, our main finding is that the gap for the group with lower education has a strong negative slope, i.e, a much higher gap at the bottom than at the top of the distribution. This declining pattern is even more acute when selectivity is corrected and remains similarly shaped when differences in characteristics are eliminated from the gap. We label this novel pattern as glass floors and argue that it can be explained by statistical discrimination exerted by employers in countries where lesseducated women have low participation rates. Such a hypothesis is further confirmed when the panel structure of the ECHP is exploited. JEL Classification: J16 and J71.
Decomposing Wage Distributions Using Recentered Influence Function Regressions” unpublished manuscript
, 2007
"... We propose a twostage procedure to decompose changes or differences in the distribution of wages (or of other variables). In the first stage, distributional changes are divided into a wage structure effect and a composition effect using a reweighting method. The reweighting allows us to estimate di ..."
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Cited by 48 (1 self)
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We propose a twostage procedure to decompose changes or differences in the distribution of wages (or of other variables). In the first stage, distributional changes are divided into a wage structure effect and a composition effect using a reweighting method. The reweighting allows us to estimate directly these two components of the decomposition without having to estimate a structural wagesetting model. In the second stage, the two components are further divided into the contribution of each explanatory variable using novel recentered influence function (RIF) regressions. These regressions estimate directly the impact of the explanatory variables on the distributional statistic of interest. The paper generalizes the popular OaxacaBlinder decomposition method by extending the decomposition to any distributional measure (besides the mean) and by allowing for a much more flexible wage setting model. We illustrate the practical aspects of the procedure by analyzing how polarization of U.S. male wages that took place between the late 1980s and the mid 2000s was affected by factors such as deunionization, education,
Counterfactual Distributions with Sample Selection Adjustments: Econometric Theory and an Application to the Netherlands
 Labour Economics
"... J71. We thank Rob Alessie for a discussion that led to this paper, and we thank Alejandro Badel and participants at the ESPE meeting in New York and the Econometric Society meetings in San Diego and at seminars at the University of British Columbia Several recent papers use the quantile regression d ..."
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Cited by 43 (4 self)
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J71. We thank Rob Alessie for a discussion that led to this paper, and we thank Alejandro Badel and participants at the ESPE meeting in New York and the Econometric Society meetings in San Diego and at seminars at the University of British Columbia Several recent papers use the quantile regression decomposition method of Machado and Mata (2005) to analyze the gender gap in log wages across the distribution. Since employment rates often differ substantially by gender, sample selection is potentially a serious issue for such studies. To address this issue, we extend the MachadoMata technique to account for selection. In addition, we prove that this procedure yields consistent and asymptotically normal estimates of the quantiles of the counterfactual distribution that it is designed to simulate. We illustrate our approach by analyzing the gender log wage gap between men and women who work full time in the Netherlands. Because the fraction of women working full time in the Netherlands is quite low, this is a case in which sample selection is clearly important. We find a positive selection of women into
Causal inference with observational data
 Stata Journal
"... Identifying the causal impact of some variables XT on y is difficult in the best of circumstances, but faces seemingly insurmountable problems in observational data, where XT is not manipulable by the researcher and cannot be randomly assigned. Nevertheless, estimating such an impact or “treatment e ..."
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Cited by 36 (1 self)
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Identifying the causal impact of some variables XT on y is difficult in the best of circumstances, but faces seemingly insurmountable problems in observational data, where XT is not manipulable by the researcher and cannot be randomly assigned. Nevertheless, estimating such an impact or “treatment effect ” is the goal of much research, even much research that carefully states all findings in terms
The U.S. gender pay gap in the 1990s: slowing convergence
 Industrial and Labor Relations Review
, 2006
"... Die ZBW räumt Ihnen als Nutzerin/Nutzer das unentgeltliche, räumlich unbeschränkte und zeitlich auf die Dauer des Schutzrechts beschränkte einfache Recht ein, das ausgewählte Werk im Rahmen der unter ..."
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Cited by 31 (0 self)
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Die ZBW räumt Ihnen als Nutzerin/Nutzer das unentgeltliche, räumlich unbeschränkte und zeitlich auf die Dauer des Schutzrechts beschränkte einfache Recht ein, das ausgewählte Werk im Rahmen der unter