Jackknife instrumental variables estimation in Stata

Brian Poi ()

Stata Journal, 2006, vol. 6, issue 3, 364-376

Abstract: The two-stage least-squares (2SLS) instrumental variables estimator is commonly used to address endogeneity. However, the estimator suffers from bias that is exacerbated when the instruments are only weakly correlated with the en- dogenous variables and when many instruments are used. In this article, I discuss jackknife instrumental variables estimation as an alternative to 2SLS. Monte Carlo simulations comparing the jackknife instrument variables estimators to 2SLS and limited information maximum likelihood (LIML) show that two of the four vari- ants perform remarkably well even when 2SLS does not. In a weak-instrument experiment, the two best performing jackknife estimators also outperform LIML. Copyright 2006 by StataCorp LP.

Keywords: jive; 2SLS; LIML; JIVE; instrumental variables; endogeneity; weak instruments (search for similar items in EconPapers)
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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