TY  - JOUR
AU  - West,Kenneth D.
AU  - Wong,Ka-fu
AU  - Anatolyev,Stanislav
TI  - Instrumental Variables Estimation of Heteroskedastic Linear Models Using All Lags of Instruments
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 13134
PY  - 2007
Y2  - May 2007
UR  - http://www.nber.org/papers/w13134
L1  - http://www.nber.org/papers/w13134.pdf
N1  - Author contact info:
Kenneth D. West
Department of Economics
University of Wisconsin
1180 Observatory Drive
Madison, WI  53706
Tel: 608/262-0033
Fax: 608/262-2033
E-Mail: kdwest@wisc.edu

Ka-fu Wong
School of Economics and Finance
The University of Hong Kong
Pokfulam
Hong Kong, CHINA
E-Mail: kafuwong@econ.hku.hk

Stanislav Anatolyev
Access Industries Associate Professor of Economics
New Economic School
Nakhimovsky prospect, 47, room 1721(3)
Moscow, 117418, Russian Federation
E-Mail: sanatoly@nes.ru
AB  - 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.
ER  -