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Institutional Constraints and Random Heterogeneity in Structural Discrete Choice Models of Household Labour Supply


  • Alan Duncan


Despite a growing literature in the application of Conditional or Mixed Logit methods to the estimation of labour supply models, relatively little attention has been paid to the role of institutional constraints in employment choices. We argue that the failure adequately to control for optimising errors in models of this form lead to substantial biases in structural preference parameters. We show how an alternative class of DOGEV estimator can be used to control for general patterns of optimising error in models of this form, and provide empirical examples of the effects such errors have on modelled preferences

Suggested Citation

  • Alan Duncan, 2004. "Institutional Constraints and Random Heterogeneity in Structural Discrete Choice Models of Household Labour Supply," Econometric Society 2004 Australasian Meetings 342, Econometric Society.
  • Handle: RePEc:ecm:ausm04:342

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    References listed on IDEAS

    1. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
    2. Antonio Alvarez & Carlos Arias, 2003. "Diseconomies of Size with Fixed Managerial Ability," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 134-142.
    3. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    4. Yair Mundlak, 1961. "Empirical Production Function Free of Management Bias," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 43(1), pages 44-56.
    5. Jovanovic, Boyan, 1982. "Selection and the Evolution of Industry," Econometrica, Econometric Society, vol. 50(3), pages 649-670, May.
    6. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics,in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, March.
    8. Zvi Griliches, 1957. "Specification Bias in Estimates of Production Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 39(1), pages 8-20.
    9. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    10. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    11. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
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    More about this item


    labour supply models; employment choices; modelling institutional constraints;

    JEL classification:

    • A - General Economics and Teaching


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