On Testing Sample Selection Bias under the Multicollinearity Problem
AbstractThis 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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Bibliographic InfoPaper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0522.
Date of creation: May 2005
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Web page: http://www.econ.cam.ac.uk/index.htm
Sample selection bias; t-test; Wald test; likelihood ratio test; Lagrange multiplier test;
Other versions of this item:
- 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.
- 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
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