Cross-Section Regression with Common Shocks
AbstractThis paper considers regression models for cross-section data that exhibit cross-section dependence due to common shocks, such as macroeconomic shocks. The paper analyzes the properties of least squares (LS) estimators in this context. The results of the paper allow for any form of cross-section dependence and heterogeneity across population units. The probability limits of the LS estimators are determined, and necessary and sufficient conditions are given for consistency. The asymptotic distributions of the estimators are found to be mixed normal after recentering and scaling. The t, Wald, and F statistics are found to have asymptotic standard normal, χ-super-2, and scaled χ-super-2 distributions, respectively, under the null hypothesis when the conditions required for consistency of the parameter under test hold. However, the absolute values of t, Wald, and F statistics are found to diverge to infinity under the null hypothesis when these conditions fail. Confidence intervals exhibit similarly dichotomous behavior. Hence, common shocks are found to be innocuous in some circumstances, but quite problematic in others. Copyright The Econometric Society 2005.
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Bibliographic InfoArticle provided by Econometric Society in its journal Econometrica.
Volume (Year): 73 (2005)
Issue (Month): 5 (09)
Other versions of this item:
- Donald W.K. Andrews, 2004. "Cross-section Regression with Common Shocks," Yale School of Management Working Papers ysm401, Yale School of Management.
- Donald W.K. Andrews, 2003. "Cross-section Regression with Common Shocks," Cowles Foundation Discussion Papers 1428, Cowles Foundation for Research in Economics, Yale University.
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
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