Efficient Estimation in Models with Independence Restrictions

53 Pages Posted: 30 Mar 2015 Last revised: 24 Aug 2016

See all articles by Alexandre Poirier

Alexandre Poirier

Georgetown University - Department of Economics

Date Written: March 7, 2016

Abstract

Unconditional or 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

JEL Classification: C13, C14

Suggested Citation

Poirier, Alexandre, Efficient Estimation in Models with Independence Restrictions (March 7, 2016). Available at SSRN: https://ssrn.com/abstract=2586879 or http://dx.doi.org/10.2139/ssrn.2586879

Alexandre Poirier (Contact Author)

Georgetown University - Department of Economics ( email )

Washington, DC 20057
United States

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