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Detecting Neglected Parameter Heterogeneity with Chow Tests

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  • Joachim Zietz

Abstract

The 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.

Suggested Citation

  • Joachim Zietz, 2005. "Detecting Neglected Parameter Heterogeneity with Chow Tests," Working Papers 200503, Middle Tennessee State University, Department of Economics and Finance.
    • Handle: RePEc:mts:wpaper:200503
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    File URL: http://capone.mtsu.edu/berc/working/WP-March%202005-Zietz.pdf
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    References listed on IDEAS

    as
    1. Joachim Zietz, 2001. "Heteroskedasticity and Neglected Parameter Heterogeneity," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 63(2), pages 263-273, May.
    2. William A. Brock & Steven N. Durlauf, 2001. "Discrete Choice with Social Interactions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 68(2), pages 235-260.
    3. Godfrey, L G & Orme, C D, 1994. "The Sensitivity of Some General Checks to Omitted Variables in the Linear Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(2), pages 489-506, May.
    4. Ashley, Richard, 1984. "A Simple Test for Regression Parameter Instability," Economic Inquiry, Western Economic Association International, vol. 22(2), pages 253-268, April.
    5. Davidson, Russell & MacKinnon, James G, 1992. "A New Form of the Information Matrix Test," Econometrica, Econometric Society, vol. 60(1), pages 145-157, January.
    6. Chesher, Andrew D, 1984. "Testing for Neglected Heterogeneity," Econometrica, Econometric Society, vol. 52(4), pages 865-872, July.
    7. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    8. Chesher, Andrew & Spady, Richard, 1991. "Asymptotic Expansions of the Information Matrix Test Statistic," Econometrica, Econometric Society, vol. 59(3), pages 787-815, May.
    9. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    10. repec:bla:obuest:v:63:y:2001:i:2:p:263-73 is not listed on IDEAS
    11. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-1294, September.
    12. Thursby, Jerry G., 1992. "A comparison of several exact and approximate tests for structural shift under heteroscedasticity," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 363-386.
    13. Alastair Hall, 1987. "The Information Matrix Test for the Linear Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 54(2), pages 257-263.
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    Cited by:

    1. Ann-Sofie Isaksson, 2011. "Social divisions and institutions: assessing institutional parameter variation," Public Choice, Springer, vol. 147(3), pages 331-357, June.

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    More about this item

    Keywords

    Parameter Heterogeneity; Chow Test; Cross-Section Data; Monte-Carlo Study;
    All these keywords.

    JEL classification:

    • 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

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