Let's Take the Bias Out of Econometrics

Abstract

This study exposes the specious quality of ‘endogeneity bias’. It reviews how conceptualisation of the bias has evolved to embrace all major econometric problems, despite extensive lack of hard evidence. It reveals the crux of the bias – a priori rejection, as conditionally invalid, of explanatory variables in causal postulates of interest, and of the bias correction by consistent estimators – modification of those variables by non-uniquely and non-causally generated regressors. It demonstrates cognitive flaws in this estimator-centred approach and highlights the need to shake off the bias to let statistical learning play an active role in designing causally faithful models.