Testing the Fixed Effects Restrictions? A Monte Carlo Study of Chamberlain's Minimum Chi-Squared Test
AbstractChamberlain (1982) showed that the fixed effects (FE) specification imposes testable restrictions on the coefficients from regressions of all leads and lags of dependent variableson all leads and lags of independent variables. Angrist and Newey (1991) suggested computing this test statistic as the degrees of freedom times the R2 from a regression of within residuals on all leads and lags of the exogenous variables. Despite the simplicity of these tests, they are not commonly used in practice. Instead, a Hausman (1978) test is used based on a contrast of the fixed and random effects specifications. We advocate the use of the Chamberlain (1982) test if the researcher wants to settle on the FE specifications, we check this test's performance using Monte Carlo experiments, and we apply it to the crime example of Cornwell and Trumbull (1994).
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Bibliographic InfoPaper provided by Center for Policy Research, Maxwell School, Syracuse University in its series Center for Policy Research Working Papers with number 115.
Length: 12 pages
Date of creation: Mar 2009
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Panel data; fixed effects (FE); random effects (RE); Chamberlain test; minimum chi-squared (MCS); Angrist-Newey test;
Other versions of this item:
- Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2009. "Testing the fixed effects restrictions? A Monte Carlo study of Chamberlain's Minimum Chi-Squared test," Statistics & Probability Letters, Elsevier, vol. 79(10), pages 1358-1362, May.
- Baltagi H-B & Bresson G. & Pirotte A., 2007. "Testing the fixed effects restrictions? A Monte Carlo study of Chamberlain’s Minimum Chi-Squared test," Working Papers ERMES 0703, ERMES, University Paris 2.
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
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