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Size Characteristics Of Tests For Sample Selection Bias: A Monte Carlo Comparison And Empirical Example


  • Kazumitsu Nawata
  • Michael McAleer


The t-test of an individual coefficient is used widely in models of qualitative choice. However, it is well known that the t-test can yield misleading results when the sample size is small. This paper provides some experimental evidence on the finite sample properties of the t-test in models with sample selection biases, through a comparison of the t-test with the likelihood ratio and Lagrange multiplier tests, which are asymptotically equivalent to the squared t-test. The finite sample problems with the t-test are shown to be alarming, and much more serious than in models such as binary choice models. An empirical example is also presented to highlight the differences in the calculated test statistics.

Suggested Citation

  • Kazumitsu Nawata & Michael McAleer, 2001. "Size Characteristics Of Tests For Sample Selection Bias: A Monte Carlo Comparison And Empirical Example," Econometric Reviews, Taylor & Francis Journals, vol. 20(1), pages 105-112.
  • Handle: RePEc:taf:emetrv:v:20:y:2001:i:1:p:105-112 DOI: 10.1081/ETC-100104082

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    References listed on IDEAS

    1. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
    2. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    3. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    4. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    5. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    6. Granger, Clive W J, 1986. "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 213-228, August.
    7. Osborn, Denise R., 1993. "Seasonal cointegration," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 299-303.
    8. Cheung, Yin-Wong & Lai, Kon S, 1993. "A Fractional Cointegration Analysis of Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 103-112, January.
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    Cited by:

    1. repec:ebl:ecbull:v:3:y:2007:i:54:p:1-10 is not listed on IDEAS
    2. Yamagata, Takashi, 2006. "The small sample performance of the Wald test in the sample selection model under the multicollinearity problem," Economics Letters, Elsevier, vol. 93(1), pages 75-81, October.
    3. Belkar, R. & Fiebig, D.G., 2008. "A Monte Carlo comparison of estimators for a bivariate probit model with selection," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 250-256.
    4. Kim, Chang-Jin & Piger, Jeremy & Startz, Richard, 2008. "Estimation of Markov regime-switching regression models with endogenous switching," Journal of Econometrics, Elsevier, vol. 143(2), pages 263-273, April.
    5. Takashi Yamagata & Chris Orme, 2005. "On Testing Sample Selection Bias Under the Multicollinearity Problem," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 467-481.
    6. Rochelle Belkar & Denzil G. Fiebig & Marion Haas & Rosalie Viney, 2006. "Why worry about awareness in choice problems? Econometric analysis of screening for cervical cancer," Health Economics, John Wiley & Sons, Ltd., vol. 15(1), pages 33-47.
    7. Maria Ana Odejar & Kostas Mavromaras & Mandy Ryan, 2004. "Messy Data Modelling in Health Care Contingent Valuation Studies," Econometric Society 2004 North American Summer Meetings 406, Econometric Society.
    8. Kazumitsu Nawata, 2007. "A monte carlo analysis of the type II tobit maximum likelihood estimator when the true model is the type I tobit model," Economics Bulletin, AccessEcon, vol. 3(54), pages 1-10.

    More about this item


    Sample selection bias; t-test; Wald test; JEL Classification: C12; C24;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models


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