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M-Testing Using Finite and Infinite Dimensional Parameter Estimators

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  • White, Halbert
  • Hong, Yongmiao

Abstract

The m-testing approach provides a general and convenient framework in which to view and construct specification tests for econometric models. Previous m-testing frameworks only consider test statistics that involve finite dimensional parameter estimators and infinite dimensional parameter estimators affecting the limit distribution of the m-test statistics. In this paper we propose a new m-testing framework using both finite and infinite dimensional parameter estimators, where the latter may or may not affect the limit distribution of the m-test. This greatly extends the potential and flexibility of m-testing. The new m-testing framework can be used to test hypotheses on parametric, semiparametric and nonparametric models. Some examples are given to illustrate how to use it to develop new specification tests

Suggested Citation

  • White, Halbert & Hong, Yongmiao, 1999. "M-Testing Using Finite and Infinite Dimensional Parameter Estimators," University of California at San Diego, Economics Working Paper Series qt9qz123ng, Department of Economics, UC San Diego.
    • Handle: RePEc:cdl:ucsdec:qt9qz123ng
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    Cited by:

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    2. Aït-Sahalia, Yacine. & Bickel, Peter J. & Stoker, Thomas M., 1994. "Goodness-of-fit tests for regression using kernel methods," Working papers 3747-94., Massachusetts Institute of Technology (MIT), Sloan School of Management.

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