Abstract

We present a semiparametric method to estimate group-level dispersion, which is particularly effective in the presence of censored data. We apply this procedure to obtain measures of occupation-specific wage dispersion using top-coded administrative wage data from the German IAB Employment Sample. We then relate these robust measures of earnings risk to the risk attitudes of individuals working in these occupations. We find that willingness to take risk is positively correlated with the wage dispersion of an individual’s occupation.

Highlights

  • Important economic issues often center on the shape of distributions

  • We demonstrate the usefulness of the estimation procedure in an application in which we relate the estimated occupation-specific wage dispersion in the German labor market as a measure of occupation-specific earnings risk to the risk attitudes of individuals working in these occupations

  • Consistent with previous studies (e.g., Bonin et al 2007; Fouarge et al 2014) that have assessed the relation between occupational earnings risk and risk preferences, we find evidence of a statistically significant correlation between our measure of occupational earnings risk and the risk attitudes of individuals working in a particular occupation: Those who state to be more willing to take risks are more likely to work in occupations with higher cross-sectional wage dispersion

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Summary

Introduction

Important economic issues often center on the shape of distributions. Examples include questions relating to income inequality, the shape of wage offer distributions, or the riskiness of returns to financial assets. Saks and Shore (2005), for example, use data from the National Postsecondary Student Aid Survey in the U.S and find that, as expected under decreasing absolute risk aversion utility, individuals with higher parental wealth more frequently choose college majors leading into occupations with greater conditional earnings variation (see King 1974), as estimated on U.S data from the Panel Study of Income Dynamics (PSID) and the Baccalaureate & Beyond survey.2 Bonin et al (2007) and Fouarge et al (2014) use direct measures of risk attitudes and relate them to an explicit statistic for the riskiness of occupations, the occupation-specific standard deviation of the residuals from a Mincer wage regression, in the German and Dutch labor markets respectively They find a significant positive relationship between this cross-sectional earnings risk measure and individuals’ stated willingness to take risks.

Estimation of Group‐Level Dispersion
Quantile Regression
Differences of Quantile Coefficients
Censored Quantile Regression
SOEP and IABS Data
Risk Attitudes
Riskiness of Occupations
Mincerian Human Capital Model
Estimates for Risk Aversion and Dispersion
Findings
Conclusion
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