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Vuong and Wald tests. Simplicity vs. Complexity

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  • Jesus Mur

    ()

  • Ana Angulo

    ()

Abstract

The specification of cross-sectional models is usually solved following a traditional procedure, highly supported by practitioners. In the first step, a simple model is proposed that will be subsequently improved with different elements if the evidence so advises. This procedure expedites the econometric solution and fits well into the Lagrange Multiplier approach, which contributes to explain its current popularity. However, there are other methods that could also be used, and some of them are considered in this paper. Specifically, we turn our attention to the Vuong test, developed in the context of the Kullback-Leibler information measure. This test represents an intermediate solution between the complexity inherent in the Wald test and the simplicity of the Lagrange Multiplier principle.

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Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa04p36.

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Date of creation: Aug 2004
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Handle: RePEc:wiw:wiwrsa:ersa04p36

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  1. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
  2. Sawa, Takamitsu, 1978. "Information Criteria for Discriminating among Alternative Regression Models," Econometrica, Econometric Society, vol. 46(6), pages 1273-91, November.
  3. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
  4. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-33, March.
  5. Raymond J.G.M. Florax & Hendrik Folmer & Sergio J. Rey, 2002. "Specification Searches in Spatial Econometrics: The Relevance of Hendry's Methodology," Urban/Regional 0202001, EconWPA.
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