Simple tests for exogeneity of a binary explanatory variable in count data regression models
AbstractThis article investigates power and size of some tests for exogeneity of a binary explanatory variable in count models by conducting extensive Monte Carlo simulations. The tests under consideration are Hausman contrast tests as well as univariate Wald tests, including a new test of notably easy implementation. Performance of the tests is explored under misspecification of the underlying model and under different conditions regarding the instruments. The results indicate that often the tests that are simpler to estimate outperform tests that are more demanding. This is especially the case for the new test.
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Bibliographic InfoPaper provided by University of Zurich, Socioeconomic Institute in its series Working Papers with number 0904.
Length: 30 pages
Date of creation: Feb 2009
Date of revision:
Publication status: published in Communications in Statistics: Simulation and Computation, 38(9), pp. 1834-1855, 2009
Endogeneity; Poisson; dummy variable; testing;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
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