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On Testing Sample Selection Bias under the Multicollinearity Problem

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Author Info
Yamagata. T.

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Abstract

This paper examines and compares the finite sample performance of the existing tests for sample selection bias, especially under the multi-collinearity problem pointed out by Nawata (1993). The results show that under such multicollinearity problem, (i) the t-test for sample selection bias based on the Heckman and Greene variance estimator can be unreliable; (ii) the standard t-test (Heckman 1979) and the asymptotically efficient Lagrange multiplier test (Melino 1982) have correct size but very little power; (iii) however, the likelihood ratio test following the maximum likelihood estimation remains powerful.

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Publisher Info
Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0522.

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Length: 14
Date of creation: May 2005
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Handle: RePEc:cam:camdae:0522

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Related research
Keywords: Sample selection bias; t-test; Wald test; likelihood ratio test; Lagrange multiplier test;

Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models

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  1. Leung, Siu Fai & Yu, Shihti, 1996. "On the choice between sample selection and two-part models," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 197-229. [Downloadable!] (restricted)
    Other versions:
  2. Nawata, Kazumitsu, 1994. "Estimation of sample selection bias models by the maximum likelihood estimator and Heckman's two-step estimator," Economics Letters, Elsevier, vol. 45(1), pages 33-40, May. [Downloadable!] (restricted)
  3. Orme, Chris, 1990. "The small-sample performance of the information-matrix test," Journal of Econometrics, Elsevier, vol. 46(3), pages 309-331, December. [Downloadable!] (restricted)
  4. Olsen, Randall J, 1982. "Distributional Tests for Selectivity Bias and a More Robust Likelihood Estimator," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 23(1), pages 223-40, February. [Downloadable!] (restricted)
  5. Greene, William H, 1981. "Sample Selection Bias as a Specification Error: Comment," Econometrica, Econometric Society, vol. 49(3), pages 795-98, May. [Downloadable!] (restricted)
  6. Olsen, Randall J, 1980. "A Least Squares Correction for Selectivity Bias," Econometrica, Econometric Society, vol. 48(7), pages 1815-20, November. [Downloadable!] (restricted)
  7. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January. [Downloadable!] (restricted)
  8. Melino, Angelo, 1982. "Testing for Sample Selection Bias," Review of Economic Studies, Blackwell Publishing, vol. 49(1), pages 151-53, January. [Downloadable!] (restricted)
  9. Nawata, Kazumitsu, 1993. "A note on the estimation of models with sample-selection biases," Economics Letters, Elsevier, vol. 42(1), pages 15-24. [Downloadable!] (restricted)
  10. Kazumitsu Nawata & Michael McAleer, 2001. "Size Characteristics Of Tests For Sample Selection Bias: A Monte Carlo Comparison And Empirical Example," Econometric Reviews, Taylor and Francis Journals, vol. 20(1), pages 105-112. [Downloadable!] (restricted)
  11. Mroz, Thomas A, 1987. "The Sensitivity of an Empirical Model of Married Women's Hours of Work to Economic and Statistical Assumptions," Econometrica, Econometric Society, vol. 55(4), pages 765-99, July. [Downloadable!] (restricted)
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  12. Chesher, Andrew & Spady, Richard, 1991. "Asymptotic Expansions of the Information Matrix Test Statistic," Econometrica, Econometric Society, vol. 59(3), pages 787-815, May. [Downloadable!] (restricted)
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