Optimal IV Estimation of Systems With Stochastic Regressors and Var Disturbances With Applications to Dynamic Systems
AbstractThis paper considers the general problem of Feasible Generalized Least Squares Instrumental Variables (FGLS IV) estimation using optimal instruments. First we summarize the sufficient conditions for the FGLS IV estimator to be asymptotically equivalent to an optimal GLS IV estimator. Then we specialize to stationary dynamic systems with stationary VAR errors, and use the sufficient conditions to derive new moment conditions for these models. These moment conditions produce useful IVs from the lagged endogenous variables, despite the correlation between errors and endogenous variables. This use of the information contained in the lagged endogenous variables expands the class of IV estimators under consideration and thereby potentially improves both asymptotic and small-sample efficiency of the optimal IV estimator in the class. Some Monte Carlo experiments compare the new methods with those of Hatanaka (1976). For the DGP used in the Monte Carlo experiments, asymptotic efficiency is strictly improved by the new IVs, and experimental small-sample efficiency is improved as well.
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Bibliographic InfoPaper provided by FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil) in its series Economics Working Papers (Ensaios Economicos da EPGE) with number 333.
Date of creation: 01 Aug 1998
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- David Mandy & Carlos Martins-Filho, 2001. "Optimal Iv Estimation Of Systems With Stochastic Regressors And Var Disturbances With Applications To Dynamic Systems," Econometric Reviews, Taylor & Francis Journals, Taylor & Francis Journals, vol. 20(4), pages 485-505.
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