A Shrinkage Instrumental Variable Estimator for Large Datasets
Andrea Carriero (),
George Kapetanios () and
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George Kapetanios: Queen Mary, University of London
No 626, Working Papers from Queen Mary University of London, School of Economics and Finance
This paper proposes and discusses an instrumental variable estimator that can be of particular relevance when many instruments are available. Intuition and recent work (see, e.g., Hahn (2002)) suggest that parsimonious devices used in the construction of the final instruments, may provide effective estimation strategies. Shrinkage is a well known approach that promotes parsimony. We consider a new shrinkage 2SLS estimator. We derive a consistency result for this estimator under general conditions, and via Monte Carlo simulation show that this estimator has good potential for inference in small samples.
Keywords: Instrumental variable estimation; 2SLS; Shrinkage; Bayesian regression (search for similar items in EconPapers)
JEL-codes: C13 C23 C51 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
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Journal Article: A SHRINKAGE INSTRUMENTAL VARIABLE ESTIMATOR FOR LARGE DATASETS (2015)
Working Paper: A Shrinkage Instrumental Variable Estimator for Large Datasets (2015)
Working Paper: A Shrinkage Instrumental Variable Estimator for Large Datasets (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:qmw:qmwecw:wp626
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