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A Correction/Update to “When Is It Justifiable to Ignore Variable Endogeneity In A Regression Model?â€


  • Richard Ashley

    (Virginia Polytechnic Institute and State University)

  • Christopher F. Parmeter

    (University of Miami)


This note corrects an error -- pointed out in Kiviet (2016) -- in the Ashley and Parmeter (2015a) derivation of the asymptotic distribution of the OLS parameter estimator in the usual k-variate multiple regression model, but where some or all of the explanatory variables are endogenous. This sampling distribution lies at the heart of the Ashley and Parmeter (2015a) sensitivity analysis of a hypothesis test rejection p-value with respect to potential endogeneity in the explanatory variables in such regression models, so this correction is of practical importance. We also discuss the settings in which Kiviet's way of displaying univariate sensitivity analysis results is an improvement (and in what settings it is not), and we provide new analytic results for our sensitivity analysis in an important special case.

Suggested Citation

  • Richard Ashley & Christopher F. Parmeter, 2018. "A Correction/Update to “When Is It Justifiable to Ignore Variable Endogeneity In A Regression Model?â€," Working Papers 2018-01, University of Miami, Department of Economics.
  • Handle: RePEc:mia:wpaper:2018-01

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    References listed on IDEAS

    1. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    2. Kiviet, Jan F., 2016. "When is it really justifiable to ignore explanatory variable endogeneity in a regression model?," Economics Letters, Elsevier, vol. 145(C), pages 192-195.
    3. Kinal, Terrence W, 1980. "The Existence of Moments of k-Class Estimators," Econometrica, Econometric Society, vol. 48(1), pages 241-249, January.
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    Publication Status: Submitted;

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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