This paper considers VAR models incorporating many time series that interact through a few dynamic factors. Several econometric issues are addressed including estimation of the number of dynamic factors and tests for the factor restrictions imposed on the VAR. Structural VAR identification based...

Recent research documents that aggregate stock prices are driven by shocks with persistence levels ranging from daily intervals to several decades. Building on these insights, we introduce a parsimonious equilibrium model in which regime-shifts of heterogeneous durations affect the volatility of...

We analyze the impact of time series dependence in market microstructure noise on the properties of estimators of the integrated volatility of an asset price based on data sampled at frequencies high enough for that noise to be a dominant consideration. We show that combining two time scales for...

I discuss economic approaches to the demand for harmfully addictive substances and estimate time-series demand functions for the period from 1975 through 2003. My estimates suggest that changes in price can explain a good deal of the observed changes in cigarette smoking, binge alcohol drinking,...

I estimate a model in which new technology entails random adjustment costs. Rapid adjustments may cause productivity slowdowns. These slowdowns last longer when retooling is costly. The model explains why growth-rate disasters are more likely than miracles, and why volatility of growth relates...

We develop analytic asymptotic methods to characterize time series properties of nonlinear dynamic stochastic models. We focus on a stochastic growth model which is representative of the models underlying much of modern macroeconomics. Taking limits as the stochastic shocks become small, we...

Over the postwar, the U.S., Europe and Japan have experienced what may be thought of as medium frequency oscillations between persistent periods of robust growth and persistent periods of relative stagnation. These medium frequency movements, further, appear to bear some relation to the high...

This paper considers the problem of forecasting a collection of short time series using cross sectional information in panel data. We construct point predictors using Tweedie's formula for the posterior mean of heterogeneous coefficients under a correlated random effects distribution. This...

When the VAR representation of a times series has a non-fundamental representation, standard SVAR techniques cannot be used to exactly identify the effects of structural shocks. This problem is know to potentially arise when one of the structural shocks represents news about the future. However,...