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dc.contributor.authorHausman, Jerry A.en_US
dc.contributor.authorNewey, Whitney K.en_US
dc.contributor.authorWoutersen, Tiemenen_US
dc.contributor.authorChao, Johnen_US
dc.contributor.authorSwanson, Normanen_US
dc.date.accessioned2011-06-14en_US
dc.date.accessioned2012-06-25T12:02:08Z-
dc.date.available2012-06-25T12:02:08Z-
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/10419/59501-
dc.description.abstractThis 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 like White'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.en_US
dc.language.isoengen_US
dc.publisherDep. of Economics, Rutgers, the State Univ. of New Jersey New Brunswick, NJen_US
dc.relation.ispartofseriesWorking Papers, Department of Economics, Rutgers, the State University of New Jersey 2011,11en_US
dc.subject.jelC12en_US
dc.subject.jelC13en_US
dc.subject.jelC23en_US
dc.subject.ddc330en_US
dc.subject.keywordinstrumental variablesen_US
dc.subject.keywordheteroskedasticityen_US
dc.subject.keywordmany instrumentsen_US
dc.subject.keywordjackknifeen_US
dc.subject.stwInstrumentalvariablen-Schätzmethodeen_US
dc.subject.stwHeteroskedastizitäten_US
dc.subject.stwMonte-Carlo-Methodeen_US
dc.subject.stwResamplingen_US
dc.subject.stwTheorieen_US
dc.titleInstrumental variable estimation with heteroskedasticity and many instrumentsen_US
dc.typeWorking Paperen_US
dc.identifier.ppn662031660en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:Working Papers, Department of Economics, Rutgers University

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