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Instrumental Variable Estimation with Heteroskedasticity and Many Instruments

Hausman, Whitney Newey, Woutersen, Chao and Norman Swanson ()

Economics Working Paper Archive from The Johns Hopkins University,Department of Economics

Abstract: This paper gives a relatively simple, well behaved solution to the problem of many instruments in heteroskedastic data. Such settings are common in microeconometric applications where many instruments are used to improve efficiency and allowance for heteroskedasticity is generally important. The solution is a Fuller (1977) like estimator and standard errors that are robust to heteroskedasticity and many instruments. We show that the estimator has finite moments and high asymptotic efficiency in a range of cases. The standard errors are easy to compute, being likeWhite's (1982), with additional terms that account for many instruments. They are consistent under standard, many instrument, and many weak instrument asymptotics. Based on a series of Monte Carlo experiments, we find that the estimators perform as well as LIML or Fuller (1977) under homoskedasticity, and have much lower bias and dispersion under heteroskedasticity, in nearly all cases considered.

Date: 2009-09
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Related works:
Journal Article: Instrumental variable estimation with heteroskedasticity and many instruments (2012) Downloads
Working Paper: Instrumental Variable Estimation with Heteroskedasticity and Many Instruments (2011) Downloads
Working Paper: Instrumental variable estimation with heteroskedasticity and many instruments (2007) Downloads
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