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Education and persistence of earnings shocks

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  • Dal Bianco, Chiara
  • Maura, Francesco

Abstract

We estimate Arellano, Blundell and Bonhomme’s (2017) nonlinear earnings process on Italian data. We show that the persistence of earnings history is lower for low-educated households than for high-educated ones, with low-educated households taking longer to recover from bad shocks.

Suggested Citation

  • Dal Bianco, Chiara & Maura, Francesco, 2020. "Education and persistence of earnings shocks," Economics Letters, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:ecolet:v:196:y:2020:i:c:s0165176520303207
    DOI: 10.1016/j.econlet.2020.109527
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    References listed on IDEAS

    as
    1. Mariacristina De Nardi & Giulio Fella & Gonzalo Paz-Pardo, 2020. "Nonlinear Household Earnings Dynamics, Self-Insurance, and Welfare," Journal of the European Economic Association, European Economic Association, vol. 18(2), pages 890-926.
    2. Manuel Arellano & Richard Blundell & Stéphane Bonhomme, 2017. "Earnings and Consumption Dynamics: A Nonlinear Panel Data Framework," Econometrica, Econometric Society, vol. 85, pages 693-734, May.
    3. Costas Meghir & Luigi Pistaferri, 2004. "Income Variance Dynamics and Heterogeneity," Econometrica, Econometric Society, vol. 72(1), pages 1-32, January.
    4. Abowd, John M & Card, David, 1989. "On the Covariance Structure of Earnings and Hours Changes," Econometrica, Econometric Society, vol. 57(2), pages 411-445, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Earnings dynamic; Nonlinear persistence; Panel data;
    All these keywords.

    JEL classification:

    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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