A Consistent Model Specification Test with Mixed Discrete and Continuous Data

33 Pages Posted: 2 May 2006

See all articles by Cheng Hsiao

Cheng Hsiao

University of Southern California - Department of Economics; National Taiwan University; National Bureau of Economic Research (NBER)

Jeffrey Racine

Syracuse University

Qi Li

Texas A&M University - Department of Economics

Date Written: April 2006

Abstract

In this paper we propose a nonparametric kernel-based model specification test that can be used when the regression model contains both discrete and continuous regressors. We employ discrete variable kernel functions and we smooth both the discrete and continuous regressors using least squares cross-validation methods. The test statistic is shown to have an asymptotic normal null distribution. We also prove the validity of using the wild bootstrap method to approximate the null distribution of the test statistic, the bootstrap being our preferred method for obtaining the null distribution in practice. Simulations show that the proposed test has significant power advantages over conventional kernel tests which rely upon frequency-based nonparametric estimators that require sample splitting to handle the presence of discrete regressors.

Keywords: Consistent test, parametric functional form, nonparametric estimation

JEL Classification: C12, C14

Suggested Citation

Hsiao, Cheng and Racine, Jeffrey and Li, Qi, A Consistent Model Specification Test with Mixed Discrete and Continuous Data (April 2006). IEPR Working Paper No. 06.47, Available at SSRN: https://ssrn.com/abstract=900166 or http://dx.doi.org/10.2139/ssrn.900166

Cheng Hsiao (Contact Author)

University of Southern California - Department of Economics ( email )

3620 South Vermont Ave. Kaprielian (KAP) Hall, 300
Los Angeles, CA 90089
United States

National Taiwan University

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Taipei, 106
Taiwan

National Bureau of Economic Research (NBER)

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Cambridge, MA 02138
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Jeffrey Racine

Syracuse University ( email )

900 S. Crouse Avenue
Syracuse, NY 13244-2130
United States

Qi Li

Texas A&M University - Department of Economics ( email )

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College Station, TX 77843-4228
United States
979-845-7349 (Phone)

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