Instrumental Variables Estimation of Heteroskedastic Linear Models Using All Lags of Instruments

35 Pages Posted: 27 Jun 2007 Last revised: 17 Aug 2007

See all articles by Kenneth D. West

Kenneth D. West

University of Wisconsin - Madison - Department of Economics; National Bureau of Economic Research (NBER)

K. F. Wong

The University of Hong Kong - Faculty of Business and Economics

Stanislav Anatolyev

New Economic School; CERGE-EI

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Date Written: May 2007

Abstract

We propose and evaluate a technique for instrumental variables estimation of linear models with conditional heteroskedasticity. The technique uses approximating parametric models for the projection of right hand side variables onto the instrument space, and for conditional heteroskedasticity and serial correlation of the disturbance. Use of parametric models allows one to exploit information in all lags of instruments, unconstrained by degrees of freedom limitations. Analytical calculations and simulations indicate that there sometimes are large asymptotic and finite sample efficiency gains relative to conventional estimators (Hansen (1982)), and modest gains or losses depending on data generating process and sample size relative to quasi-maximum likelihood. These results are robust to minor misspecification of the parametric models used by our estimator.

Suggested Citation

West, Kenneth D. and Wong, K. F. and Anatolyev, Stanislav, Instrumental Variables Estimation of Heteroskedastic Linear Models Using All Lags of Instruments (May 2007). NBER Working Paper No. t0338, Available at SSRN: https://ssrn.com/abstract=989945

Kenneth D. West (Contact Author)

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K. F. Wong

The University of Hong Kong - Faculty of Business and Economics ( email )

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Stanislav Anatolyev

New Economic School ( email )

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