Multicollinearity in the Presence of Errors-in-Variables Can Increase the Probability of Type-I Error

John Komlos

Journal of Economics and Econometrics, 2020, vol. 63, issue 1, 1-17

Abstract: Multicollinearity, in combination with errors-in-variables, can increase the likelihood of a Type-I error by inflating the value of the estimated coefficients by more than it magnifies their standard errors, thereby increasing the likelihood of obtaining statistically significant results. This anomalous result may be caused by an interaction effect between errors-in-variables and multicollinearity.

Keywords: Multicollinearity; errors-in-variables; Type-I error (search for similar items in EconPapers)
JEL-codes: J12 (search for similar items in EconPapers)
Date: 2020
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Working Paper: Multicollinearity in the Presence of Errors-in-Variables Can Increase the Probability of Type-I Error (2019)
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