A MONTE CARLO COMPARISON OF VARIOUS ASYMPTOTIC APPROXIMATIONS TO THE DISTRIBUTION OF INSTRUMENTAL VARIABLES ESTIMATORS

Jinyong Hahn and Atsushi Inoue

Econometric Reviews, 2002, vol. 21, issue 3, 309-336

Abstract: We examine empirical relevance of three alternative asymptotic approximations to the distribution of instrumental variables estimators by Monte Carlo experiments. We find that conventional asymptotics provides a reasonable approximation to the actual distribution of instrumental variables estimators when the sample size is reasonably large. For most sample sizes, we find Bekker[11] asymptotics provides reasonably good approximation even when the first stage R2 is very small. We conclude that reporting Bekker[11] confidence interval would suffice for most microeconometric (cross-sectional) applications, and the comparative advantage of Staiger and Stock[5] asymptotic approximation is in applications with sample sizes typical in macroeconometric (time series) applications.

Keywords: Many instruments; Weak instruments; JEL Classification : C31 (search for similar items in EconPapers)
Date: 2002
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Citations: View citations in EconPapers (32)

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DOI: 10.1081/ETC-120015786

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