We hope to be able to provide answers to the following questions: 1) Has there been a structural break in postwar U.S. real GDP growth toward more stabilization? 2) If so, when would it have been? 3) What's the nature of the structural break? For this purpose, we employ a Bayesian approach to dealing with structural break at an unknown changepoint in a Markov-switching model of business cycle. Empirical results suggest that there has been a structural break in U.S. real GDP growth toward more stabilization, with the posterior mode of the break date around 1984:1. Furthermore, we #nd a narrowing gap between growth rates during recessions and booms is at least as important as a decline in the volatility of shocks. Key Words: Bayes Factor, Gibbs sampling, Marginal Likelihood, Markov-Switching, Stabilization, Structural Break. JEL Classi#cations: C11, C12, C22, E32. 1. Introduction In the literature, the issue of postwar stabilization of the U.S. economy relative to the prewar period has...

Abstract: In the first half of this century, special attention was given to two features of the business cycle: the comovement of many individual economic series and the different behavior of the economy during expansions and contractions. Recent theoretical and empirical research has revived interest in each attribute separately, and we survey this work. Notable empirical contributions are dynamic factor models that have a single common macroeconomic factor and nonlinear regime-switching models of a macroeconomic aggregate. We conduct an empirical synthesis that incorporates both of these features. It is desirable to know the facts before attempting to explain them; hence, the attractiveness of organizing business-cycle regularities within a model-free framework. During the first half of this century, much research was devoted to obtaining just such an empirical characterization of the business cycle. The most prominent example of this work

. In this article we extend the Hamilton Markovchain regime switching model of real aggregate output to include the possibility of an occasional long regime. We model this long regime feature with a fat tailed duration distribution where the duration length can have high levels of variability and takeon extreme values. We show that an economy with a fat tailed expansion and/or contraction duration leads to long memory behavior in aggregate output. In addition, we find empirical support for our theoretical findings with estimates of the degree of occasional long swings in the US business cycle when the length of the expansion and contraction regimes are defined by the National Bureau of Economic Research recession dates. Our estimates of the tail index for the length of US economic booms and busts closely correspond to the magnitude of the long memory parameter estimated by Diebold and Rudebusch (1989) and Sowell (1992) for real US output, and suggest that a forecast of aggregate output based on a long history of past observations will be inferior to a projection that uses observations from the current regime. Keywords: Business cycles, duration, fat tailed distributions, long swings, long memory, regime switching model JEL Classification: C22, C52 1

We test for a change in the volatility of 215 US macroeconomic time series over the period 1960-1996. We find that about 90% of these series have experienced a break in volatility during this period. This result is robust to controlling for instability in the mean and business cycle nonlinearities. Real variables have seen a reduction in volatility since the early 1980s, which is accompanied by lower but steadier output growth. Furthermore, nominal variables have seen temporary increases in their volatility around the early 1980s. This suggests the existence of a trade-o# between short-term volatility and the long-term pattern of growth.

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We show in this article that fractionally integrated univariate models for GDP may lead to a better replication of business cycle characteristics. We firstly show that the business cycle features are clearly affected by the degree of integration as well as by the other short run components of the series. Then, we model the real GDP in France, the UK and the US by means of fractionally ARIMA (ARFIMA) models, and show that the three time series can be specified in terms of this type of models with orders of integration higher than one but smaller than two. Comparing the ARFIMA specifications with those based on ARIMA models, we show via simulations that the former better describes the business cycles features of the data at least for the cases of the UK and the US.

It is widely accepted that U.S. business expansions have been longer and contractions shorter since the end of World War II. Although previous writers have presented formal statistical tests results in support this proposition, they uniformly assume that the change in business-cycle behavior began during or after the war—they do not ask when the change in business-cycle behavior began. Using NBER reference dates, this paper examines this question by dividing the sample at several different places, thereby determining when it is most likely that the change in behavior began. It is found that it is most likely that business-cycle expansions became longer beginnning with the March 1933 expansion, a date which coincides with the U.S. leaving the gold standard. Our results are robust to consideration of Romer's (1994, 1999) alternative business-cycle chronology

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