Efficient Estimation of Linear Asset Pricing Models with Moving-Average Errors

55 Pages Posted: 27 Jun 2007 Last revised: 29 Mar 2023

See all articles by Lars Peter Hansen

Lars Peter Hansen

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

Kenneth J. Singleton

Stanford University - Graduate School of Business

Date Written: March 1997

Abstract

This paper explores in depth the nature of the conditional moment restrictions implied by log-linear intertemporal capital asset pricing models (ICAPMs) and shows that the generalized instrumental variables (GMM) estimators of these models (as typically implemented in practice) are inefficient. The moment conditions in the presence of temporally aggregated consumption are derived for two log-linear ICAPMs. The first is a continuous time model in which agents maximize expected utility. In the context of this model, we show that there are important asymmetries between the implied moment conditions for infinitely and finitely-lived securities. The second model assumes that agents maximize non-expected utility, and leads to a very similar econometric relation for the return on the wealth portfolio. Then we describe the efficiency bound (greatest lower bound for the asymptotic variances) of the CNN estimators of the preference parameters in these models. In addition, we calculate the efficient CNN estimators that attain this bound. Finally, we assess the gains in precision from using this optimal CNN estimator relative to the commonly used inefficient CMN estimators.

Suggested Citation

Hansen, Lars Peter and Singleton, Kenneth J., Efficient Estimation of Linear Asset Pricing Models with Moving-Average Errors (March 1997). NBER Working Paper No. t0086, Available at SSRN: https://ssrn.com/abstract=994221

Lars Peter Hansen (Contact Author)

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Kenneth J. Singleton

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