Variance Function Regressions for Studying Inequality

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Variance Function Regressions for Studying Inequality

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dc.contributor.author Western, Bruce
dc.contributor.author Bloom, Deirdre
dc.date.accessioned 2009-03-10T19:47:50Z
dc.date.issued 2009-03-10T19:47:50Z
dc.identifier.citation Western, Bruce and Deirdre Bloome. 2009. Variance function regressions for studying inequality. Working paper, Department of Sociology, Harvard University. en
dc.identifier.uri http://nrs.harvard.edu/urn-3:HUL.InstRepos:2645469
dc.description.abstract Regression-based studies of inequality model only between-group differences, yet often these differences are far exceeded by residual inequality. Residual inequality is usually attributed to measurement error or the influence of unobserved characteristics. We present a regression that includes covariates for both the mean and variance of a dependent variable. In this model, the residual variance is treated as a target for analysis. In analyses of inequality, the residual variance might be interpreted as measuring risk or insecurity. Variance function regressions are illustrated in an analysis of panel data on earnings among released prisoners in the National Longitudinal Survey of Youth. We extend the model to a decomposition analysis, relating the change in inequality to compositional changes in the population and changes in coe cients for the mean and variance. The decomposition is applied to the trend in US earnings inequality among male workers, 1970 to 2005. en
dc.description.sponsorship Sociology en
dc.language.iso en_US en
dash.license OAP
dc.title Variance Function Regressions for Studying Inequality en
dash.depositing.author Western, Bruce

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  • FAS Scholarly Articles [7374]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University

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