2005
DOI: 10.2139/ssrn.803925
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Rising Wage Inequality: The Role of Composition and Prices

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Cited by 105 publications
(201 citation statements)
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References 21 publications
(56 reference statements)
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“…This provides additional support for the benefits of the quantile decomposition method. These findings regarding the variations of selected quantiles of the wage distribution help to shed light on the dynamic relationship between the human capital attainments of the work force and wage inequality (Autor et al, 2005;Melly, 2005). In fact, the standard inequality indexes (90/10, 90/50, 50/10) are easily derived from Table 4, allowing us to compute the related ratios both for the estimated variations and for the three components.…”
Section: Decomposition Of Changes In Wage Distributionmentioning
confidence: 87%
“…This provides additional support for the benefits of the quantile decomposition method. These findings regarding the variations of selected quantiles of the wage distribution help to shed light on the dynamic relationship between the human capital attainments of the work force and wage inequality (Autor et al, 2005;Melly, 2005). In fact, the standard inequality indexes (90/10, 90/50, 50/10) are easily derived from Table 4, allowing us to compute the related ratios both for the estimated variations and for the three components.…”
Section: Decomposition Of Changes In Wage Distributionmentioning
confidence: 87%
“…Also, it shows that a divergent behavior in the upper and lower tails of the wage distribution can be produced even when changes in the labor force composition (Autor, Katz and Kearney (2005)) are absent. The elasticity of total and marginal prices of skills are all that matter, and when one considers only data on the wage distribution, these e¤ects are di¢ cult to disentangle.…”
mentioning
confidence: 97%
“…2 Gosling, Machin, and Meghir (2000) use quantile regression to study the evolution of wage inequality in the UK. Some studies for the US are Autor, Katz and Kearney (2005), Chamberlain (1993), Buchinsky (1994), and Angrist, Chernozhukov and Fernández-Val (2006). bution function, or copula, of the errors in the outcome and the selection equation.…”
Section: Introductionmentioning
confidence: 99%
“…In Appendix D we describe an alternative estimator of ρ that relies on the copula restrictions (6). The method provides a fast and straightforward way to obtain good starting values to minimize the objective function in (15).…”
mentioning
confidence: 99%