An Empirical Investigation of Habit-Based Asset Pricing Models

A leading explanation of aggregate stock market behavior suggests that assets are priced as if there were a representative investor whose utility is a power function of the difference between aggregate consumption and a "habit" level, where the habit is some function of lagged and (possibly) contemporaneous consumption. But theory does not provide precise guidelines about the parametric functional relationship between the habit and aggregate consumption. This makes formal estimation and testing challenging; at the same time, it raises an empirical question about the functional form of the habit that best explains asset pricing data. This paper studies the ability of a general class of habit-based asset pricing models to match the conditional moment restrictions implied by asset pricing theory. Our approach is to treat the functional form of the habit as unknown, and to estimate it along with the rest of the model's parameters. The resulting specification for investor utility is semiparametric in the sense that it contains both the finite dimensional set of unknown parameters that are part of the power function and time-preference, as well as the infinite dimensional unknown habit function that must be estimated nonparametrically. This semiparametric approach allows us to empirically evaluate a number of interesting hypotheses about the specification of habit-based asset pricing models, and to formally test the framework's ability to explain stock return data relative to other models that have proven empirically successful