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  1. A semi-nonparametric copula model for earnings mobility
    Published: [2023]
    Publisher:  [Universität Bern, Faculty of Business, Economics and Social Sciences, Department of Economics], Bern, Switzerland

    In this paper we develop a novel semi-nonparametric panel copula model with external covariates for the study of wage rank dynamics. We focus on nonlinear dependence between the current and lagged worker's ranks in the wage residuals distribution,... more

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    DS 182
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    In this paper we develop a novel semi-nonparametric panel copula model with external covariates for the study of wage rank dynamics. We focus on nonlinear dependence between the current and lagged worker's ranks in the wage residuals distribution, conditionally on individual characteristics. We show the asymptotic normality of the Sieve estimator for our preferred mobility measure, which is an irregular functional of both the finite- and infinite-dimensional parameters, in the double asymptotics with N,T → ∞. We derive an analytical bias correction for the incidental parameters bias induced by the individual fixed-effects. We apply our model to US data and we find that relative mobility at the bottom of the distribution is high for workers with a college degree and some experience. On the contrary, less-educated individuals are likely to remain stuck at the bottom of the wage rank distribution year after year.

     

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/278294
    Series: Discussion papers / Universität Bern, Faculty of Business, Economics and Social Sciences, Department of Economics ; 23, 02 (January, 2023)
    Subjects: Wage dynamics; rank; functional copula model; nonlinear autoregressive process; Sieve semi-nonparametric estimation
    Scope: 1 Online-Ressource (circa 52 Seiten), Illustrationen