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Model Adequacy Checks for Discrete Choice Dynamic Models

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Author Info

  • Igor Kheifets

    (New Economic School, Moscow)

  • Carlos Velasco

    (Department of Economics, Universidad Carlos III de Madrid)

Abstract

This paper proposes new parametric model adequacy tests for possibly nonlinear and nonstationary time series models with noncontinuous data distribution, which is often the case in applied work. In particular, we consider the correct specification of parametric conditional distributions in dynamic discrete choice models, not only of some particular conditional characteristics such as moments or symmetry. Knowing the true distribution is important in many circumstances, in particular to apply efficient maximum likelihood methods, obtain consistent estimates of partial effects and appropriate predictions of the probability of future events. We propose a transformation of data which under the true conditional distribution leads to continuous uniform iid series. The uniformity and serial independence of the new series is then examined simultaneously. The transformation can be considered as an extension of the integral transform tool for noncontinuous data. We derive asymptotic properties of such tests taking into account the parameter estimation effect. Since transformed series are iid we do not require any mixing conditions and asymptotic results illustrate the double simultaneous checking nature of our test. The test statistics converges under the null with a parametric rate to the asymptotic distribution, which is case dependent, hence we justify a parametric bootstrap approximation. The test has power against local alternatives and is consistent. The performance of the new tests is compared with classical specification checks for discrete choice models.

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Bibliographic Info

Paper provided by Center for Economic and Financial Research (CEFIR) in its series Working Papers with number w0170.

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Length: 19 pages
Date of creation: Feb 2012
Date of revision:
Handle: RePEc:cfr:cefirw:w0170

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Related research

Keywords: Goodness of fit; diagnostic test; parametric conditional distribution; discrete choice models; parameter estimation effect; bootstrap;

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References

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  1. Donald W. K. Andrews, 1997. "A Conditional Kolmogorov Test," Econometrica, Econometric Society, vol. 65(5), pages 1097-1128, September.
  2. Oscar Jorda & James D. Hamilton, 2003. "A model for the federal funds rate target," Working Papers 997, University of California, Davis, Department of Economics.
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  7. Richard Startz, . "Binomial Autoregressive Moving Average Models with an Application to U.S. Recessions," Working Papers UWEC-2006-10-FC, University of Washington, Department of Economics.
  8. de Jong, Robert M. & Woutersen, Tiemen, 2011. "Dynamic Time Series Binary Choice," Econometric Theory, Cambridge University Press, vol. 27(04), pages 673-702, August.
  9. Delgado, Miguel A. & Stute, Winfried, 2008. "Distribution-free specification tests of conditional models," Journal of Econometrics, Elsevier, vol. 143(1), pages 37-55, March.
  10. Basu Deepankar & de Jong Robert M, 2007. "Dynamic Multinomial Ordered Choice with an Application to the Estimation of Monetary Policy Rules," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(4), pages 1-35, December.
  11. Mora, Juan & Moro-Egido, Ana I., 2008. "On specification testing of ordered discrete choice models," Journal of Econometrics, Elsevier, vol. 143(1), pages 191-205, March.
  12. Jushan Bai, 2003. "Testing Parametric Conditional Distributions of Dynamic Models," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 531-549, August.
  13. Bai, Jushan & Ng, Serena, 2001. "A consistent test for conditional symmetry in time series models," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 225-258, July.
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Cited by:
  1. Igor Kheifets & Carlos Velasco, 2013. "New Goodness-of-fit Diagnostics for Conditional Discrete Response Models," Cowles Foundation Discussion Papers 1924, Cowles Foundation for Research in Economics, Yale University.

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