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Open Access Publications from the University of California

M-Testing Using Finite and Infinite Dimensional Parameter Estimators

  • Author(s): White, Halbert
  • Hong, Yongmiao
  • et al.

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

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