When is it really justifiable to ignore explanatory variable endogeneity in a regression model?

Jan Kiviet

No 1607, Economic Growth Centre Working Paper Series from Nanyang Technological University, School of Social Sciences, Economic Growth Centre

Abstract: A procedure that aims to pinpoint the sensitivity of ordinary least-squares based inferences regarding the degree of endogeneity of some regressors has been put forward in Ashley and Parmeter, Economics Letters, 137 (2015) 70-74. Here it is demonstrated that this procedure is based on an incorrect and systematically too optimistic asymptotic approximation to the variance of inconsistent least- squares. Therefore, and because the suggested sensitivity Öndings pertain to a random set of estimated endogeneity correlations, the claimed signiÖcance levels are misleading. For a very basic one coe¢ cient model it is demonstrated why much more sophisticated asymptotic expansions under a stricter set of assumptions are required. This enables to replace some of the áawed sensitivity analysis results for an empirical growth model by Öndings based on a proper limiting distribution for a feasible inconsistency corrected least-squares estimator, given an adopted Öxed range for the correlation between the endogenous regressor and the disturbance. Finally it is discussed how similar results could be achieved for models with several possibly endogenous regressors estimated by possibly endogenous instruments.

Keywords: sensitivity analysis; simultaneity; asymptotic expansions; least-squares; growth regression (search for similar items in EconPapers)
JEL-codes: C13 C2 O5 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2016-05
New Economics Papers: this item is included in nep-sea
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Citations: View citations in EconPapers (9)

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Related works:
Journal Article: When is it really justifiable to ignore explanatory variable endogeneity in a regression model? (2016)
Working Paper: When is it really justifiable to ignore explanatory variable endogeneity in a regression model? (2015)
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