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Evaluating the Discrete Choice and BN Methods to Estimate Labor Supply Functions

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  • Sören Blomquist

Abstract

Estimated labor supply functions are important tools when designing an optimal income tax or calculating the effect of tax reforms. It is therefore of large importance to use estimation methods that give reliable results and to know their properties. In this paper Monte Carlo simulations are used to evaluate two different methods to estimate labor supply functions; the discrete choice method and a nonparametric method suggested in Blomquist and Newey (2002). The focus is on the estimators’ ability to predict the hours of work for a given tax system and the change in hours of work when there is a tax reform. The simulations show that the DC method is quite sensitive to misspecifications of the likelihood function and to measurement errors in hours of work. A version of the Blomquist Newey method shows the overall best performance to predict the hours of work.

Suggested Citation

  • Sören Blomquist, 2023. "Evaluating the Discrete Choice and BN Methods to Estimate Labor Supply Functions," CESifo Working Paper Series 10827, CESifo.
    • Handle: RePEc:ces:ceswps:_10827
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    References listed on IDEAS

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    1. Soren Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2014. "Individual heterogeneity, nonlinear budget sets, and taxable income," CeMMAP working papers CWP21/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Gruber, Jon & Saez, Emmanuel, 2002. "The elasticity of taxable income: evidence and implications," Journal of Public Economics, Elsevier, vol. 84(1), pages 1-32, April.
    3. Löffler, Max & Peichl, Andreas & Siegloch, Sebastian, 2013. "Validating Structural Labor Supply Models," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79819, Verein für Socialpolitik / German Economic Association.
    4. N. S. Blomquist & U. Hansson-Brusewitz, 1990. "The Effect of Taxes on Male and Female Labor Supply in Sweden," Journal of Human Resources, University of Wisconsin Press, vol. 25(3), pages 317-357.
    5. Soren Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2022. "Nonlinear Budget Set Regressions for the Random Utility Model," Working Papers 2219, Federal Reserve Bank of Dallas.
    6. Burtless, Gary & Hausman, Jerry A, 1978. "The Effect of Taxation on Labor Supply: Evaluating the Gary Negative Income Tax Experiments," Journal of Political Economy, University of Chicago Press, vol. 86(6), pages 1103-1130, December.
    7. Blomquist, Soren, 1996. "Estimation methods for male labor supply functions How to take account of nonlinear taxes," Journal of Econometrics, Elsevier, vol. 70(2), pages 383-405, February.
    8. Soren Blomquist & Whitney Newey, 2002. "Nonparametric Estimation with Nonlinear Budget Sets," Econometrica, Econometric Society, vol. 70(6), pages 2455-2480, November.
    9. Duncan, Greg J & Hill, Daniel H, 1985. "An Investigation of the Extent and Consequences of Measurement Error in Labor-Economic Survey Data," Journal of Labor Economics, University of Chicago Press, vol. 3(4), pages 508-532, October.
    10. Richard Blundell & Andrew Shephard, 2012. "Employment, Hours of Work and the Optimal Taxation of Low-Income Families," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(2), pages 481-510.
    11. Beffy, Magali & Blundell, Richard & Bozio, Antoine & Laroque, Guy & Tô, Maxime, 2019. "Labour supply and taxation with restricted choices," Journal of Econometrics, Elsevier, vol. 211(1), pages 16-46.
    12. Dagsvik, John K, 1994. "Discrete and Continuous Choice, Max-Stable Processes, and Independence from Irrelevant Attributes," Econometrica, Econometric Society, vol. 62(5), pages 1179-1205, September.
    13. van Soest, Arthur & Das, Marcel & Gong, Xiaodong, 2002. "A structural labour supply model with flexible preferences," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 345-374, March.
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    More about this item

    Keywords

    labor supply; tax reform; predictive power; estimation methods; Monte Carlo simulations;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • H20 - Public Economics - - Taxation, Subsidies, and Revenue - - - General
    • H30 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - General

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