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Efficient estimation in models with independence restrictions

Alexandre Poirier

Journal of Econometrics, 2017, vol. 196, issue 1, 1-22

Abstract: Unconditional and conditional independence restrictions are used in many econometric models to identify their parameters. However, there are few results about efficient estimation procedures for finite-dimensional parameters under these independence restrictions. This paper computes the efficiency bound for finite-dimensional parameters under independence restrictions, and proposes an estimator that is consistent, asymptotically normal and which achieves the efficiency bound. The estimator is based on a growing number of zero-covariance conditions that are asymptotically equivalent to the independence restriction. The results are illustrated with examples, including an instrumental variables regression model and partially linear regression models. A small Monte Carlo study is performed to investigate the estimator’s small sample properties and to quantify the efficiency gains that can be made by using the proposed efficient estimator.

Keywords: Efficiency bounds; Independence; Estimation (search for similar items in EconPapers)
JEL-codes: C13 C14 (search for similar items in EconPapers)
Date: 2017
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Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

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Handle: RePEc:eee:econom:v:196:y:2017:i:1:p:1-22