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On the role of unobserved preference heterogeneity in discrete choice models of labour supply

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  • Daniele Pacifico

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Abstract

The aim of this paper is to analyse the impact of unobserved preference heterogeneity in empirical applications of discrete choice models of labour supply. Typically, unobserved heterogeneity is estimated either with continuous or discrete mixture models. However, in order to avoid estimation difficulties, most of the empirical analysis assumes a relatively constrained mixture, standard examples being models where only few coefficients are allowed to vary with independent normal distributions or with discrete distributions with few mass points. We compare labour supply elasticities obtained with these typical specifications of unobserved heterogeneity with those from a more general model that we are able to estimate through an EM algorithm for the nonparametric estimation of mixed models. Results show that labour supply elasticities change significantly with respect to a basic model without unobserved heterogeneity only when the joint distribution of the varying tastes is left completely unspecified. Copyright Springer-Verlag 2013

Suggested Citation

  • Daniele Pacifico, 2013. "On the role of unobserved preference heterogeneity in discrete choice models of labour supply," Empirical Economics, Springer, vol. 45(2), pages 929-963, October.
  • Handle: RePEc:spr:empeco:v:45:y:2013:i:2:p:929-963 DOI: 10.1007/s00181-012-0637-6
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    Citations

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    Cited by:

    1. André de Palma & Nathalie Picard & Ignacio Inoa, 2014. "Discrete choice decision-making with multiple decision-makers within the household," Chapters,in: Handbook of Choice Modelling, chapter 16, pages 363-382 Edward Elgar Publishing.
    2. Shun-ichiro Bessho & Masayoshi Hayashi, 2015. "Should the Japanese tax system be more progressive? An evaluation using the simulated SMCFs based on the discrete choice model of labor supply," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 22(1), pages 144-175, February.
    3. Yuan, Yuan & You, Wen & Boyle, Kevin J., 2015. "A guide to heterogeneity features captured by parametric and nonparametric mixing distributions for the mixed logit model," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205733, Agricultural and Applied Economics Association;Western Agricultural Economics Association.
    4. Kabatek, J., 2013. "Iteration Capping For Discrete Choice Models Using the EM Algorithm," Discussion Paper 2013-019, Tilburg University, Center for Economic Research.
    5. Henk-Wim de Boer & Egbert Jongen & Jan Kabatek, 2014. "The effectiveness of fiscal stimuli for working parents," CPB Discussion Paper 286, CPB Netherlands Bureau for Economic Policy Analysis.
    6. Ambra Poggi & Matteo G. Richiardi, 2012. "Imputing Individual Effects in Dynamic Microsimulation Models.An application of the Rank Method," LABORatorio R. Revelli Working Papers Series 124, LABORatorio R. Revelli, Centre for Employment Studies.
    7. Lars Kunze & Nicolai Suppa, 2013. "Job Characteristics and Labour Supply," Ruhr Economic Papers 0418, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    8. Shun-ichiro Bessho & Masayoshi Hayashi, 2011. "Should Japanese Tax System Be More Progressive?," Global COE Hi-Stat Discussion Paper Series gd10-181, Institute of Economic Research, Hitotsubashi University.
    9. Peter Haan & Daniel Kemptner & Arne Uhlendorff, 2015. "Bayesian procedures as a numerical tool for the estimation of an intertemporal discrete choice model," Empirical Economics, Springer, vol. 49(3), pages 1123-1141, November.
    10. Patricia Apps & Jan Kabátek & Ray Rees & Arthur Soest, 2016. "Labor supply heterogeneity and demand for child care of mothers with young children," Empirical Economics, Springer, pages 1641-1677.
    11. Kabátek, Jan, 2015. "Essays on public policy and household decision making," Other publications TiSEM 8cdb178e-ad98-42e5-a7e1-b, Tilburg University, School of Economics and Management.
    12. Matteo Richiardi & Ambra Poggi, 2014. "Imputing Individual Effects in Dynamic Microsimulation Models. An application to household formation and labour market participation in Italy," International Journal of Microsimulation, International Microsimulation Association, vol. 7(2), pages 3-39.
    13. repec:zbw:rwirep:0418 is not listed on IDEAS
    14. Kunze, Lars & Suppa, Nicolai, 2013. "Job Characteristics and Labour Supply," Ruhr Economic Papers 418, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

    More about this item

    Keywords

    Labour supply; Unobserved heterogeneity; Mixed logit models; EM algorithm; J22; H31; H24; C25; C14;

    JEL classification:

    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • H31 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Household
    • H24 - Public Economics - - Taxation, Subsidies, and Revenue - - - Personal Income and Other Nonbusiness Taxes and Subsidies
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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