Testing Distributional Assumptions: A GMM Approach

Nour Meddahi and Christian Bontemps

No 487, Econometric Society 2004 North American Winter Meetings from Econometric Society

Abstract: In this paper, we consider testing marginal distributional assumptions. Special cases that we consider are the Pearson's family like the Gaussian, Student, Gamma, Beta and uniform distributions. The test statistics we consider are based on the first moment conditions derived by Hansen and Scheinkman (1995) when one considers a continuous time model. These moment conditions are valid even if the observations are not a sample of a continuous time model. We treat in detail the parameter uncertainty problem when the considered process is not observed but depends on estimators of unknown parameters. We also consider the time series case and adopt a HAC approach for this purpose. This is a generalization of Bontemps and Meddahi (2002) who considered this approach for the Normal case

Keywords: GMM; Hansen-Scheinkman moment conditions; parameter uncertainty; serial correlation (search for similar items in EconPapers)
JEL-codes: C12 C15 (search for similar items in EconPapers)
Date: 2004-08-11
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Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Testing distributional assumptions: A GMM aproach (2012)
Working Paper: Testing Distributional Assumptions: A GMM Approach (2007)
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