Detecting Neglected Parameter Heterogeneity with Chow Tests
AbstractThe paper demonstrates through a number of Monte-Carlo experiments that, for the type of cross-section data sets typically encountered in applied economics, Chow tests on sorted variations of the data matrix can detect neglected parameter heterogeneity. The paper focuses on heterogeneity in the behavioral responses of economic actors that belong to different economically meaningful groups, such as the young, middle-aged, and old. Since the suggested methodology is easy to implement yet powerful, its routine use by applied economists would be desirable given the very significant estimation bias that can result from neglecting parameter heterogeneity.
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Bibliographic InfoPaper provided by Middle Tennessee State University, Department of Economics and Finance in its series Working Papers with number 200503.
Date of creation: Mar 2005
Date of revision:
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Web page: http://www.mtsu.edu/~berc/working/Economics_Working_Papers.html
More information through EDIRC
Parameter Heterogeneity; Chow Test; Cross-Section Data; Monte-Carlo Study;
Other versions of this item:
- Joachim Zietz, 2006. "Detecting neglected parameter heterogeneity with Chow tests," Applied Economics Letters, Taylor & Francis Journals, vol. 13(6), pages 369-374.
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-08-13 (All new papers)
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