Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/59501
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dc.contributor.authorHausman, Jerry A.en
dc.contributor.authorNewey, Whitney K.en
dc.contributor.authorWoutersen, Tiemenen
dc.contributor.authorChao, Johnen
dc.contributor.authorSwanson, Normanen
dc.date.accessioned2011-06-14-
dc.date.accessioned2012-06-25T12:02:08Z-
dc.date.available2012-06-25T12:02:08Z-
dc.date.issued2011-
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
dc.language.isoengen
dc.publisher|aRutgers University, Department of Economics |cNew Brunswick, NJen
dc.relation.ispartofseries|aWorking Paper |x2011-11en
dc.subject.jelC12en
dc.subject.jelC13en
dc.subject.jelC23en
dc.subject.ddc330en
dc.subject.keywordinstrumental variablesen
dc.subject.keywordheteroskedasticityen
dc.subject.keywordmany instrumentsen
dc.subject.keywordjackknifeen
dc.subject.stwInstrumentalvariablen-Schätzmethodeen
dc.subject.stwHeteroskedastizitäten
dc.subject.stwMonte-Carlo-Methodeen
dc.subject.stwResamplingen
dc.subject.stwTheorieen
dc.titleInstrumental variable estimation with heteroskedasticity and many instruments-
dc.typeWorking Paperen
dc.identifier.ppn662031660en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:rut:rutres:201111en

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