Titlebook: Economic Applications of Quantile Regression; Bernd Fitzenberger,Roger Koenker,José A. F. Machad Book 2002 Physica-Verlag Heidelberg 2002

Guileless

MERIT

https://doi.org/10.1007/978-3-030-68858-5ple period; (c) there is a significant sample selection bias for all age groups at almost all quantiles; (d) toward the end of the sample period there is a significant convergence of the returns at the various quantiles, especially for the younger cohorts and age groups; and (e) the semiparametric e

TRAWL

Individual heterogeneity in the returns to schooling: instrumental variables quantile regression usr returns to schooling consistent with a non-trivial interaction between schooling and unobserved abilities in the generation of earnings. The estimated returns are never lower than 9 percent and can be as high as 13 percent at the top of the conditional distribution of wages but they vary significa

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Overthrow

Book 2002squares regression methods which are designed to estimate conditional mean models, quantile regression provides an ensemble of techniques for estimating families of conditional quantile models, thus offering a more complete view of the stochastic relationship among variables. This volume collects 12

Expurgate

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Wage inequality in a developing country: decrease in minimum wage or increase in education returns,ation increased significantly, which could explain the increase of wage dispersion by its effects on the upper tail of the wage distribution. To derive these conclusions we follow a parametric and nonparametric quantile regression approach.

concert

How wide is the gap? An investigation of gender wage differences using quantile regression,e take into account the endogeneity of educational choice and the participation decision of women. The results suggest that the absolute wage gap and the component of the latter that can be attributed to different returns to characteristics increase over the wage scale.

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Asymmetric labor supply, endogenous to the model. Contrary to previous works using conditional mean estimators, it is found that labor supply elasticities vary significantly and asymmetrically across hours of work. While the income and wage elasticities at the standard work week are zero, for those working longer hours the elasticities are negative.