02151cam a22002297 4500001000600000003000500006005001700011008004100028100002400069245015000093260006600243490005100309500001600360520118500376530006101561538007201622538003601694700002601730710004201756830008601798856003701884t0086NBER20140420051729.0140420s1997 mau||||fs|||| 000 0 eng d1 aHansen, Lars Peter.10aEfficient Estimation of Linear Asset Pricing Models with Moving-Average Errorsh[electronic resource] /cLars Peter Hansen, Kenneth J. Singleton. aCambridge, Mass.bNational Bureau of Economic Researchc1997.1 aNBER technical working paper seriesvno. t0086 aMarch 1997.3 aThis 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. aHardcopy version available to institutional subscribers. aSystem requirements: Adobe [Acrobat] Reader required for PDF files. aMode of access: World Wide Web.1 aSingleton, Kenneth J.2 aNational Bureau of Economic Research. 0aTechnical Working Paper Series (National Bureau of Economic Research)vno. t0086.4 uhttp://www.nber.org/papers/t0086