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No. 626: A Shrinkage Instrumental Variable Estimator for Large Datasets

Andrea Carriero , Queen Mary, University of London
George Kapetanios , Queen Mary, University of London
Massimiliano Marcellino , Bocconi University and EUI

March 1, 2008

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Abstract

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.

J.E.L classification codes: C13, C23, C51

Keywords:Instrumental variable estimation, 2SLS, Shrinkage, Bayesian regression

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