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Bayesian treatment effects models with variable selection for panel outcomes with an application to earnings effects of maternity leave

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  • Jacobi, Liana
  • Wagner, Helga
  • Frühwirth-Schnatter, Sylvia

Abstract

We propose two alternative Bayesian treatment effect modeling and inferential frameworks for panel outcomes to estimate dynamic earnings effects of a long maternity leave on mothers’ subsequent earnings. Modeling of the endogeneity of the treatment and the panel structure of the earnings are based on the modeling tradition of the Roy switching regression model and the shared factor approach, respectively. We implement stochastic variable selection to test, for example, for the presence of different dynamics under the treatment. Exploiting a change in maternity leave policy and Austrian registry data we identify substantial negative but steadily decreasing earnings effects over a 5 years period.

Suggested Citation

  • Jacobi, Liana & Wagner, Helga & Frühwirth-Schnatter, Sylvia, 2016. "Bayesian treatment effects models with variable selection for panel outcomes with an application to earnings effects of maternity leave," Journal of Econometrics, Elsevier, vol. 193(1), pages 234-250.
    • Handle: RePEc:eee:econom:v:193:y:2016:i:1:p:234-250
    DOI: 10.1016/j.jeconom.2016.01.005
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    Cited by:

    1. Gerlinde Mauerer & Eva-Maria Schmidt, 2019. "Parents’ Strategies in Dealing with Constructions of Gendered Responsibilities at Their Workplaces," Social Sciences, MDPI, vol. 8(9), pages 1-17, September.
    2. Andrés Ramírez–Hassan & Rosember Guerra–Urzola, 2021. "Bayesian treatment effects due to a subsidized health program: the case of preventive health care utilization in Medellín (Colombia)," Empirical Economics, Springer, vol. 60(3), pages 1477-1506, March.
    3. Guyonne Kalb, 2018. "Paid Parental Leave and Female Labour Supply: AÂ Review," The Economic Record, The Economic Society of Australia, vol. 94(304), pages 80-100, March.
    4. Murat K. Munkin, 2022. "Count Roy model with finite mixtures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1160-1181, September.

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    More about this item

    Keywords

    Switching regression model; Shared factor model; Factor analysis; Spike and slab priors; Markov chain Monte Carlo method;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

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