Arbeitspapier

Robust estimation of wage dispersion with censored data: An application to occupational earnings risk and risk attitudes

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 (IABS). 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.

Sprache
Englisch

Erschienen in
Series: SOEPpapers on Multidisciplinary Panel Data Research ; No. 572

Klassifikation
Wirtschaft
Semiparametric and Nonparametric Methods: General
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Single Equation Models; Single Variables: Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
Human Capital; Skills; Occupational Choice; Labor Productivity
Wage Level and Structure; Wage Differentials
Microeconomic Behavior: Underlying Principles
Criteria for Decision-Making under Risk and Uncertainty
Thema
dispersion estimation
earnings risk
censoring
quantile regression
occupational choice
sorting
risk preferences
SOEP
IABS

Ereignis
Geistige Schöpfung
(wer)
Pollmann, Daniel
Dohmen, Thomas
Palm, Franz
Ereignis
Veröffentlichung
(wer)
Deutsches Institut für Wirtschaftsforschung (DIW)
(wo)
Berlin
(wann)
2013

Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Pollmann, Daniel
  • Dohmen, Thomas
  • Palm, Franz
  • Deutsches Institut für Wirtschaftsforschung (DIW)

Entstanden

  • 2013

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