Letís Take the Bias Out of Econometrics

Duo Qin

No 192, Working Papers from Department of Economics, SOAS University of London, UK

Abstract: This study exposes the specious quality of ëendogeneity biasí. 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 ñ a priori rejection, as conditionally invalid, of explanatory variables in causal postulates of interest, and of the bias correction by consistent estimators ñ 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.

Keywords: simultaneity; omitted variable; self-selection; multicollinearity; consistency; causal model; conditioning (search for similar items in EconPapers)
JEL-codes: B23 B40 C10 C50 (search for similar items in EconPapers)
Pages: 36
Date: 2015-09
New Economics Papers: this item is included in nep-ecm and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:soa:wpaper:192

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