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dc.contributor.authorGroen, Jan J. J.en_US
dc.contributor.authorKapetanios, Georgeen_US
dc.date.accessioned2010-05-06en_US
dc.date.accessioned2012-08-17T14:33:48Z-
dc.date.available2012-08-17T14:33:48Z-
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/10419/60807-
dc.description.abstractWe suggest a way to perform parsimonious instrumental variables estimation in the presence of many, and potentially weak, instruments. In contrast to standard methods, our approach yields consistent estimates when the set of instrumental variables complies with a factor structure. In this sense, our method is equivalent to instrumental variables estimation that is based on principal components. However, even if the factor structure is weak or nonexistent, our method, unlike the principal components approach, still yields consistent estimates. Indeed, simulations indicate that our approach always dominates standard instrumental variables estimation, regardless of whether the factor relationship underlying the set of instruments is strong, weak, or absent.en_US
dc.language.isoengen_US
dc.publisherFederal Reserve Bank of New York New York, NYen_US
dc.relation.ispartofseriesStaff Report, Federal Reserve Bank of New York 386en_US
dc.subject.jelC30en_US
dc.subject.jelC59en_US
dc.subject.jelC13en_US
dc.subject.ddc330en_US
dc.subject.keywordInstrumental variables estimationen_US
dc.subject.keywordmany instrumentsen_US
dc.subject.keywordfactor modelsen_US
dc.titleParsimonious estimation with many instrumentsen_US
dc.typeWorking Paperen_US
dc.identifier.ppn622766716en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:Staff Reports, Federal Reserve Bank of New York

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