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Instrumental Variables Estimation of Heteroskedastic Linear Models Using All Lags of Instruments / Kenneth D. West, Ka-fu Wong, Stanislav Anatolyev.

NBER Working papers Available online

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Format:
Book
Author/Creator:
West, Kenneth D.
Contributor:
National Bureau of Economic Research.
Wong, Ka-fu.
Anatolyev, Stanislav.
Series:
Working Paper Series (National Bureau of Economic Research) no. w13134.
NBER working paper series no. w13134
Language:
English
Physical Description:
1 online resource: illustrations (black and white);
Place of Publication:
Cambridge, Mass. National Bureau of Economic Research 2007.
Summary:
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.
Notes:
Print version record
May 2007.

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