We propose a Bayesian procedure for exploiting small, possibly long-lag linear predictability in the innovations of a finite order autoregression. We model the innovations as having a log-spectral density that is a continuous mean-zero Gaussian process of order 1/√T. This local embedding makes...

When a rate of return is regressed on a lagged stochastic regressor, such as a dividend yield, the regression disturbance is correlated with the regressor's innovation. The OLS estimator's finite-sample properties, derived here, can depart substantially from the standard regression setting....

We consider the problem of short-term time series forecasting (nowcasting) when there are more possible predictors than observations. Our approach combines three Bayesian techniques: Kalman filtering, spike-and-slab regression, and model averaging. We illustrate this approach using search engine...

We propose methods for evaluating density forecasts. We focus primarily on methodsquot; that are applicable regardless of the particular user's loss function. We illustrate the methodsquot; with a detailed simulation example, and then we present an application to density forecasting ofquot;...

Since 1968, the Survey of Professional Forecasters has asked respondents to provide aquot; complete probability distribution of expected future inflation. We evaluate the adequacy ofquot; those density forecasts using the framework of Diebold, Gunther and Tay (1997). The analysisquot; reveals...

This paper develops and illustrates a simple method to generate a DSGE model-based forecast for variables that do not explicitly appear in the model (non-core variables). We use auxiliary regressions that resemble measurement equations in a dynamic factor model to link the non-core variables to...

We develop a nonlinear state-space model that captures the joint dynamics of consumption, dividend growth, and asset returns. Our model consists of an economy containing a common predictable component for consumption and dividend growth and multiple stochastic volatility processes. The...

This paper studies the asymptotic relationship between Bayesian model averaging and post-selection frequentist predictors in both nested and nonnested models. We derive conditions under which their difference is of a smaller order of magnitude than the inverse of the square root of the sample...

We present evidence that the equity premium and the premium of value stocks over growth stocks are explained in the 1982 1996 period with a stochastic discount factor (SDF) calculated as the weighted average of individual households' marginal rate of substitution with low and economically...