Estimation of the consumption CAPM with imperfect sample separation information

Abstract

We propose a consumption-based capital asset pricing model consumption (CAPM), in which the pricing kernel is calculated as the average of individuals' intertemporal marginal rates of substitution weighted by the probabilities of holding the asset in question. These probabilities are conditional on available imperfect sample separation information and are estimated simultaneously with the parameters of Euler equations. Using data from the US Consumer Expenditure Survey, we find that the consumption CAPM with probability-weighted agents yields a more precise estimate of the agent's risk aversion compared with the model, in which the available imperfect information on asset-holding status is erroneously regarded as a perfect sample separation indicator. Copyright © 2007 John Wiley & Sons, Ltd.

Uninsurable Risk and Financial Market Puzzles

“…and Du¢ e (1996), Sarkissian (2003), and Semenov (2008) in that it uses the cross-sectional distribution of consumption in level, rather than the cross-sectional distribution of consumption in growth rates, as the driving process for the pricing kernel. As we mentioned above, the use of the cross-sectional distribution of consumption in growth rates has a counterfactual implication that the cross-sectional distribution of consumption in level is not stationary, implying that the Gini coe¢ cient of consumption distribution goes to in…nity.…”

“…This requires careful modelling of international currency trades by motivating the transaction demand for currency in terms of a cash-in-advance constraint. In this respect, our approach is theoretically more elegant than KP (2007KP ( , 2009 Semenov (2008) we use the assumption of lognormality of the cross section consumption process to work out closed form expressions for the pricing kernels for alternative market environments. 5 These pricing kernels are empirically easily estimable using the Generalized Method of Moments (GMM) and are less vulnerable to the sampling and measurement error problems mentioned in KP.…”