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Testing exogeneity under distributional misspecification

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Abstract

We propose a general test for exogeneity that is robust against distributional misspecification. The test can also be used to identify other types of misspecifications, such as the presence of a random coefficient. The idea is to sort the data with respect to a variable (a sorting score) and then split the sample into two parts. Using a Chow test, it can then be tested whether estimated parameters in the two sub-samples are different. We give conditions under which it is possible to test for exogeneity by using the (supposedly) endogenous variable as a sorting score. The resulting test does not need instrumental variables. Evidence from a Monte Carlo study and an empirical application suggets that the test can be useful for practitioners.

Suggested Citation

  • de Luna, Xavier & Johansson, Per, 2001. "Testing exogeneity under distributional misspecification," Working Paper Series 2001:9, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    • Handle: RePEc:hhs:ifauwp:2001_009
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    References listed on IDEAS

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    1. Smith, Richard J & Blundell, Richard W, 1986. "An Exogeneity Test for a Simultaneous Equation Tobit Model with an Application to Labor Supply," Econometrica, Econometric Society, vol. 54(3), pages 679-685, May.
    2. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    3. Shapiro, Carl & Stiglitz, Joseph E, 1984. "Equilibrium Unemployment as a Worker Discipline Device," American Economic Review, American Economic Association, vol. 74(3), pages 433-444, June.
    4. Weiss, Andrew, 1985. "Absenteeism and wages," Economics Letters, Elsevier, vol. 19(3), pages 277-279.
    5. Vella, Francis, 1993. "A Simple Estimator for Simultaneous Models with Censored Endogenous Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 34(2), pages 441-457, May.
    6. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
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    Cited by:

    1. Ahmed Bani-Mustafa & K. M. Matawie & C. F. Finch & Amjad Al-Nasser & Enrico Ciavolino, 2019. "Recursive residuals for linear mixed models," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(3), pages 1263-1274, May.
    2. de Luna, Xavier & Johansson, Per, 2006. "Exogeneity in structural equation models," Journal of Econometrics, Elsevier, vol. 132(2), pages 527-543, June.

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    More about this item

    Keywords

    Absenteeism at work; endogeneity; linear exponential family; random effect; random coefficient; selectivity;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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