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A Unified Theory of Consistent Estimation for Parametric Models

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  • Bates, Charles
  • White, Halbert

Abstract

We present a general theory of consistent estimation for possibly misspecified parametric models based on recent results of Domowitz and White. This theory extends the unification of Burguete, Gallant, and Souza by allowing for heterogeneous, time-dependent data and dynamic models. The theory is applied to yield consistency results for quasi-maximum-likelihood and method of moments estimators. Of particular interest is a new generalized rank condition for identifiability.

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  • Bates, Charles & White, Halbert, 1985. "A Unified Theory of Consistent Estimation for Parametric Models," Econometric Theory, Cambridge University Press, vol. 1(02), pages 151-178, August.
  • Handle: RePEc:cup:etheor:v:1:y:1985:i:02:p:151-178_01
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    Cited by:

    1. Benedikt M. Potscher & Ingmar R. Prucha, 1994. "On the Formulation of Uniform Laws of Large Numbers: A Truncation Approach," NBER Technical Working Papers 0085, National Bureau of Economic Research, Inc.
    2. Marmer, Vadim & Otsu, Taisuke, 2012. "Optimal comparison of misspecified moment restriction models under a chosen measure of fit," Journal of Econometrics, Elsevier, vol. 170(2), pages 538-550.
    3. Andrews, Donald W. K. & Fair, Ray C., 1987. "Inference in Econometric Models with Structural Change," Working Papers 636, California Institute of Technology, Division of the Humanities and Social Sciences.
    4. Xiu, Dacheng, 2010. "Quasi-maximum likelihood estimation of volatility with high frequency data," Journal of Econometrics, Elsevier, vol. 159(1), pages 235-250, November.
    5. Phillips, Robert F., 1996. "Forecasting in the presence of large shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 20(9-10), pages 1581-1608.
    6. Donald W.K. Andrews, 1986. "Consistency in Nonlinear Econometric Models: A Generic Uniform Law of Large Numbers," Cowles Foundation Discussion Papers 790, Cowles Foundation for Research in Economics, Yale University.

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