Let's take the bias out of econometrics

被引:4
|
作者
Qin, Duo [1 ]
机构
[1] Univ London, Dept Econ, SOAS, Russell Sq, London WC1H 0XG, England
关键词
Simultaneity; omitted-variable bias; self-selection; consistency; causality; CAUSAL INFERENCE; SAMPLE SELECTION; MARRIED-WOMEN; MODELS; RANDOMIZATION; VARIABLES; EARNINGS;
D O I
10.1080/1350178X.2018.1547415
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study exposes the cognitive flaws of 'endogeneity bias'. It examines 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 of causal variables as conditionally valid ones, and of the bias correction by consistent estimators - modification of those variables by non-uniquely and non-causally generated regressors. It traces the flaws to misconceptions about error terms and estimation consistency. It highlights the need to shake off the bias to let statistical learning play an active and formal role in econometrics.
引用
收藏
页码:81 / 98
页数:18
相关论文
共 50 条