ABSTRACT This paper draws on Engle's autoregressive conditionally heteroskedastic modeling strategy to formulate a conditional CAPM with time‐varying risk and expected returns. The model is estimated by generalized method of moments. A CAPM that allows mean excess returns to shift in January survives generalized method of moments specification tests for a number of omitted variables. However, a residual dividend yield component is found to remain in the excess returns of smaller firms. We find significant monthly and quarterly components in the risk premia and beta estimates.

We propose the parametric Dynamic Seemingly Unrelated Regression (DSUR) estimator for simultaneous estimation of multiple cointegrating regressions. DSUR is efficient when the equilibrium errors are correlated across equations and is applicable for panel cointegration estimation in environments where the cross section is small relative to the available time series. We study the asymptotic and small sample properties of the DSUR estimator for both heterogeneous and homogeneous cointegrating vectors. We then apply the method to analyse two long-standing problems in international economics. Our first application revisits the estimation of long-run correlations between national investment and national saving. Our second application revisits the question of whether the forward exchange rate is an unbiased predictor of the future spot rate.

We study a Lucas asset-pricing model that is standard in all respects, except that the representative agent's subjective beliefs about endowment growth are distorted. Using constant relative risk-aversion (CRRA) utility, with a CRRA coefficient below 10; fluctuating beliefs that exhibit, on average, excessive pessimism over expansions; and excessive optimism over contractions (both ending more quickly than the data suggest), our model is able to match the first and second moments of the equity premium and risk-free rate, as well as the persistence and predictability of excess returns found in the data. (JEL E44, G12)

ABSTRACT The Euler equations derived from intertemporal asset pricing models, together with the unconditional moments of asset returns, imply a lower bound on the volatility of the intertemporal marginal rate of substitution. This paper develops and implements statistical tests of these lower bound restrictions. While the availability of short time series of consumption data often undermines the ability of these tests to discriminate among different utility functions, we find that the restrictions implied by a number of widely studied financial data sets continue to pose quite a challenge to the current generation of intertemporal asset pricing theories.