TY  - JOUR
AU  - Stambaugh,Robert F.
TI  - Estimating Conditional Expectations when Volatility Fluctuates
JF  - National Bureau of Economic Research Technical Working Paper Series
VL  - No. 140
PY  - 1993
Y2  - August 1993
UR  - http://www.nber.org/papers/t0140
L1  - http://www.nber.org/papers/t0140.pdf
N1  - Author contact info:
Robert F. Stambaugh
Finance Department
The Wharton School
University of Pennsylvania
Philadelphia, PA   19104-6367
Tel: 215/898-5734
Fax: 215/898-6200
E-Mail: stambaugh@wharton.upenn.edu
AB  - Asymptotic variance of estimated parameters in models of conditional expectations are calculated analytically assuming a GARCH process for conditional volatility.  Under such heteroskedasticity, OLS estimators or parameters in single-period models can posses substantially larger asymptotic variances the GMM estimators employing additional multiperiod moment conditions - an approach yielding no efficiency gain under homoskedasticity.  In estimating models of long- horizon expectations, the VAR approach provides an efficiency advantage over long-horizon regressions under homoskedasticity, but that ordering can reverse under heteroskedasticity, especially when the conditional mean and variance are both persistent.  In such cases, the VAR approach maintains a slight efficiency advantage if the OLS estimator is replaced by an alternative GMM estimator. Heteroskedasticity can increase dramatically the apparent asymptotic power advantages of long-horizon regressions to reject constant expectations against persistent alternatives.
ER  -