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Predicting gross wages of non-employed persons in Croatia

Author

Listed:
  • Slavko Bezeredi

    (Institute of Public Finance, Zagreb, Croatia)

  • Ivica Urban

    (Institute of Public Finance, Zagreb, Croatia)

Abstract

We present the findings of a study aimed at building a model for predicting wages of non-employed persons in Croatia. The predictions will be used in the calculation of marginal effective tax rate at the extensive margin and in labour supply modelling. The database used is 2012 “EU statistics on income and living conditions†. The paper comprehensively explains the data source, variables, subgroups of employed and non-employed, and the results of the linear regression model, the Heckman selection model and the quantile regression model. The quality of predictions obtained by different models is compared and discussed.

Suggested Citation

  • Slavko Bezeredi & Ivica Urban, 2016. "Predicting gross wages of non-employed persons in Croatia," Financial Theory and Practice, Institute of Public Finance, vol. 40(1), pages 1-61.
    • Handle: RePEc:ipf:finteo:v:40:y:2016:i:1:p:1-61
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    Citations

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    Cited by:

    1. Horie, Norio & Iwasaki, Ichiro & 岩﨑, 一郎, 2022. "Returns to Education in European Emerging Markets: A Meta-Analytic Review," RRC Working Paper Series 95, Russian Research Center, Institute of Economic Research, Hitotsubashi University.
    2. Teo Matkovic & Dinka Caha, 2017. "Patterns of welfare-to-employment transitions of Croatian Guaranteed Minimum Benefit recipients: a preliminary study," Public Sector Economics, Institute of Public Finance, vol. 41(3), pages 335-358.

    More about this item

    Keywords

    gross wages; estimation; prediction; unemployed; inactive; Heckman selection model; quantile regressions; Croatia;
    All these keywords.

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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