Robust tests for heteroskedasticity in the one-way error components model
AbstractThis paper constructs tests for heteroskedasticity in one-way error components models, in line with Baltagi etÂ al. [Baltagi, B.H., Bresson, G., Pirotte, A., 2006. Joint LM test for homoskedasticity in a one-way error component model. Journal of Econometrics 134, 401-417]. Our tests have two additional robustness properties. First, standard tests for heteroskedasticity in the individual component are shown to be negatively affected by heteroskedasticity in the remainder component. We derive modified tests that are insensitive to heteroskedasticity in the component not being checked, and hence help identify the source of heteroskedasticity. Second, Gaussian-based LM tests are shown to reject too often in the presence of heavy-tailed (e.g. t-Student) distributions. By using a conditional moment framework, we derive distribution-free tests that are robust to non-normalities. Our tests are computationally convenient since they are based on simple artificial regressions after pooled OLS estimation.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 160 (2011)
Issue (Month): 2 (February)
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Web page: http://www.elsevier.com/locate/jeconom
Error components Heteroskedasticity Testing;
Other versions of this item:
- Gabriel Montes-Rojas & Walter Sosa-Escudero, 2010. "Robust tests for heteroskedasticity in the one-way error components model," Post-Print peer-00768191, HAL.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
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