We include learning in a standard equilibrium business cycle model with explicit growth. We use the model to study how the economy's agents could learn in real time about the important trend-changing events of the postwar era in the U.S., such as the productivity slowdown, increased labor force...

We study a general equilibrium model where the multiplicity of stationary periodic perfect foresight equilibria is pervasive. We investigate the extent of which agents can learn to coordinate on stationary perfect foresight cycles. The example economy, taken from Grandmont (1985), is an...

This paper uses a Markov-switching model with structural breaks to characterize and compare regional business cycles in Japan for 1976-2005. An early 1990s structural break meant a reduction in national and regional growth rates in expansion and recession, usually resulting in an increase in the...

This paper documents changes in the cyclical behavior of nominal data series that appear after 1979:Q3 when the Federal Reserve implemented a policy to lower the inflation rate. Such changes were not apparent in real variables. A business cycle model with impulses to technology and a role for...

Recent research showing negative correlations between detrended output and prices during the postwar period has brought into question the conventional wisdom that prices are procyclical. However, this finding has been shown to be sensitive to the sample period considered. This paper examines the...

In this paper, we present a new approach to trend/cycle decomposition under the assumption that the trend is the permanent component and the cycle is the transitory component of an integrated time series. The permanent component is defined as the steady-state level of the series, a definition...

This paper evaluates the ability of formal rules to establish U.S. business cycle turning point dates in real time. We consider two approaches, a nonparametric algorithm and a parametric Markov-switching dynamic-factor model. In order to accurately assess the real-time performance of these...