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Previous literature has recognized the importance of regime changes in the calculation of ex-ante equity premia. However, the methodologies used to estimate equity premia only allow for very restrictive forms of regime transitions. This paper addresses the issue by postulating an evolving model for the law of motion of dividend growth, consumption growth and dividend-price ratio. Model parameters are then used to compute conditional and unconditional U.S. equity premia. We substantially extend and confirm previous work on the declining equity premium, and uncover important macroeconomic factors driving the equity premium. We find that the equity premium has declined, particularly from 1950 to 1971 and from 1988 to 2000. Our results point to changing consumption volatility as an important priced factor. We find that volatility of consumption growth is a good indicator of economic uncertainty and, as such, its changes are reflected in expected returns, and are priced by the market. We also find that not accounting for parameter time variation induces large pricing errors, as too little variation in dividend yields is attributed to changes in expected dividend growth.

We present a novel specification of a dynamic multinomial ordered choice model, where the latent variable is a function of strictly stationary exogenous variables and lags of the choice variable. We prove that such a model with weakly dependent errors will have a strictly stationary solution which is L-2 near epoch dependent. We also derive consistency and asymptotic normality of the maximum likelihood estimator for a probit specification of the model. We illustrate a possible application of the model by estimating a discrete version of a robust ``difference" monetary policy rule for the period 1990:2006 at a monthly frequency.

One of the most familiar empirical stylized facts about output dynamics in the United States is the positive autocorrelation of output growth. This paper shows that positive autocorrelation can be better captured by shifts between business cycle states rather than by the standard view of autoregressive coefficients. The result is extremely robust to different nonlinear alternative models and applies not only to output but also to the most relevant macroeconomic variables.

We propose a simple computational method in the context of generalized method of moments for improving the efficiency of regression coefficient estimates. The gains in efficiency arise by incorporating additional moment conditions in the estimation framework based on maximal overlap wavelet packet transforms of the continuous explanatory variables. A major advantage of the proposed method is that it does not require additional exogenous auxiliary information but relies on wavelet packet transforms of the existing continuous explanatory variables. Based on existing theory, we provide theoretical arguments for the proposed methodology, for both linear and non-linear models, and demonstrate its advantages with both an empirical application concerning two brand demand models and a Monte Carlo simulation study.

Despite expansionary fiscal and monetary policies, the Japanese real economy has been stagnating since the bubble bursting in the early nineties. Within a multivariate setup, this paper proposes to test for and date a possible structural shift in the response of Japanese macroeconomic fluctuations to aggregate supply and aggregate demand shocks. The econometric methodology directly derives from Andrews (1993) and Bai, Lumsdaine and Stock (1998) theoretical results. Our empirical study from monthly post-1980 observations reveals i) a significant structural break in the end of 1991, and ii) a sharp decrease in the influence of demand shocks on Japanese output fluctuations after this date.