Revista de Análisis Económico (2010)
http://repositorio.uahurtado.cl/handle/11242/1442
2019-08-19T21:29:37ZIncome Nonresponse and Inequality Measurement
http://repositorio.uahurtado.cl/handle/11242/1910
Income Nonresponse and Inequality Measurement
Paraje, Guillermo; Weeks, Melvyn
This paper analyses the effects that income nonresponse has on certain well-known inequality coefficients (e.g. Gini, Theil and Atkinson indexes). A number of statistical methods have been developed to impute missing values of incomes for nonrespondents. By simulating several patterns of income nonresponse on actual sub-samples of the Argentinean household survey, this essay analyses the effects that different correction methods produce on a set of inequality coefficients. It is proved that methods often used to correct for nonresponse can introduce important biases on inequality coefficients if the patterns of missingness assumed by such methods do not coincide with the actual pattern.
2010-01-01T00:00:00ZDecomposing the Gender Wage Gap with Sample Selection Adjustment: Evidence from Colombia
http://repositorio.uahurtado.cl/handle/11242/1909
Decomposing the Gender Wage Gap with Sample Selection Adjustment: Evidence from Colombia
Badel, Alejandro; Peña, Ximena
Despite the remarkable improvement of female labor market characteristics, a sizeable gender wage gap exists in Colombia. We employ quantile regression techniques to examine the degree to which current small differences in the distribution of observable characteristics can explain the gender gap. We find that the gap is largely explained by gender differences in the rewards to labor market characteristics and not by differences in the distribution of characteristics. We claim that Colombian women experience both a glass ceiling effect and also (what we call) a quicksand floor effect because gender differences in returns to characteristics primarily affect women at the top and the bottom of the distribution. Also, self selection into the labor force is crucial for gender gaps: if all women participated in the labor force, the observed gap would be roughly 50% larger at all quantiles.
2010-01-01T00:00:00ZExploring the Urban-Rural Labor Income Gap in Uruguay: A Quantile Regression de Composition
http://repositorio.uahurtado.cl/handle/11242/1908
Exploring the Urban-Rural Labor Income Gap in Uruguay: A Quantile Regression de Composition
Bergolo, Marcelo; Carbajal, Fedora
This paper analyzes the differences in real hourly labor income (RHLI) distributions between urban and rural workers for Uruguay in 2006. A quantile regression decomposition technique is applied in order to examine the urban-rural gap across the entire RHLI distribution. The urban-rural gap was primarily explained by the differences in the distribution of covariates along the entire distribution. Differences in distribution of returns favored the rural workers in most of the RHLI distribution although its contribution decreased across quantiles. The resulting gap in returns was most relevant for the worst off rural workers compared to the urban counterparts in both Montevideo and the rest of the urban centers.
2010-01-01T00:00:00ZDiferenciales Salariales en Colombia: Un Análisis para Trabajadores Rurales y Jóvenes, 2002-2009
http://repositorio.uahurtado.cl/handle/11242/1907
Diferenciales Salariales en Colombia: Un Análisis para Trabajadores Rurales y Jóvenes, 2002-2009
Franco, Catalina; Ramos, Johanna
This paper examines the trends and magnitude of earnings differentials among urban and rural workers, and young (18-24 years) and old (25-65 years) workers from 2002 to 2009 in Colombia. Using household surveys data and constructing cells for comparing only workers with the same characteristics, the results from time series and matching decomposition methodologies show that earnings in the groups of interest have not diverged over time. However, the earnings differentials are high at around –50 percent for rural and –40 percent for young workers, of which 14 and 19 percentage points, respectively, remain unexplained after controlling for demographic and job-related characteristics.
2010-01-01T00:00:00Z