Jackknife instrumental variables estimation in Stata
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 endogenous 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 variants perform remarkably well
even when 2SLS does not. In a weak-instrument experiment, the two best
performing jackknife estimators also outperform LIML.
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Brian P. Poi
View all articles with these keywords:
jive, 2SLS, LIML, JIVE, instrumental variables, endogeneity, weak instruments
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