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Recent changes in the U.S. business cycle
The U.S. business cycle expansion that started in March 1991 is the longest on record. This paper uses statistical techniques to examine whether this expansion is a onetime unique event or whether its length is a result of a change in the stability of the U.S. economy. Bayesian methods are used to estimate a common factor model that allows for structural breaks in the dynamics of a wide range of macroeconomic variables. We find strong evidence that a reduction in volatility is common to the series examined. Further, the reduction in volatility implies that future expansions will be ...
Working Paper
A comparison of the real-time performance of business cycle dating methods
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 rules, we construct a new unrevised "real-time" data set of employment, industrial production, manufacturing and trade sales, and personal income. We then apply the rules to this data set to simulate the accuracy and timeliness with which they would have identified the NBER business cycle chronology had ...
Report
Nonlinear risk
This paper proposes a flexible framework for analyzing the joint time series properties of the level and volatility of expected excess stock returns. An unobservable dynamic factor is constructed as a nonlinear proxy for the market risk premia with its first moment and conditional volatility driven by a latent Markov variable. The model allows for the possibility that the risk-return relationship may not be constant across the Markov states or over time. We find a distinct business cycle pattern in the conditional expectation and variance of the monthly value-weighted excess return. ...
Report
Markov switching in disaggregate unemployment rates
We develop a dynamic factor model with Markov switching to examine secular and business cycle fluctuations in U.S. unemployment rates. We extract the common dynamics among unemployment rates disaggregated for seven age groups. The framework allows analysis of the contribution of demographic factors to secular changes in unemployment rates. In addition, it allows examination of the separate contribution of changes due to asymmetric business cycle fluctuations. We find strong evidence in favor of the common factor and of the switching between high and low unemployment rate regimes. We also find ...
Working Paper
What does financial volatility tell us about macroeconomic fluctuations?
This paper provides an extensive analysis of the predictive ability of financial volatility measures for economic activity. We construct monthly measures of aggregated and industry-level stock volatility, and bond market volatility from daily returns. We model log financial volatility as composed of a long-run component that is common across all series, and a short-run component. If volatility has components, volatility proxies are characterized by large measurement error, which veils analysis of their fundamental information and relationship with the economy. We find that there are ...
Journal Article
International business cycles: G7 and OECD countries
The progressive globalization of markets has sparked a worldwide interest in using economic indicators to analyze cyclical fluctuations. Governments and the private sector seeking to conduct their activities in light of both national and international economic conditions could benefit from international indicators that serve as a warning system to detect recessions in major economic partners and in industrialized countries as a whole. ; This article constructs just such a warning system. Using a Markov-switching dynamic factor model with a self-adjusting variable-bandwidth filter, the authors ...
Journal Article
Identifying business cycle turning points in real time
This paper evaluates the ability of a statistical regime-switching model to identify turning points in U.S. economic activity in real time. The authors work with a Markov-switching model fit to real gross domestic product and employment data that, when estimated on the entire postwar sample, provides a chronology of business cycle peak and trough dates close to that produced by the National Bureau of Economic Research (NBER). Next, they investigate how accurately and quickly the model would have identified NBER-dated turning points had it been used in real time for the past 40 years. In ...
Working Paper
Nonlinear relationship between permanent and transitory components of monetary aggregates and the economy
This paper uses several methods to study the interrelationship among Divisia monetary aggregates, prices, and income, allowing for nonstationary, nonlinearities, asymmetries, and time-varying relationships among the series. We propose a multivariate regime switching unobserved components model to obtain transitory and permanent components for each series, allowing for potential recurrent and structural changes in their dynamics. Each component follows distinct two-state Markov processes representing low or high phases. Since the lead-lag relationship between the phases can vary over time, ...
Working Paper
Forecasting Brazilian output in the presence of breaks: a comparison of linear and nonlinear models
This paper compares the forecasting performance of linear and nonlinear models under the presence of structural breaks for the Brazilian real GDP growth. The Markov-switching models proposed by Hamilton (1989) and its generalized version proposed by Lam (1991) are applied to quarterly GDP from 1975:1 to 2000:2 allowing for breaks at the Collor Plans. The probabilities of recessions are used to analyze the Brazilian business cycle. The ability of each model in forecasting out-of-sample the growth rates of GDP is examined. The forecasting ability of the two models is also compared with linear ...
Working Paper
Identifying business cycle turning points in real time
This paper evaluates the ability of a statistical regime-switching model to identify turning points in U.S. economic activity in real time. The authors work with Markov-switching models of real GDP and employment that, when estimated on the entire post-war sample, provide a chronology of business cycle peak and trough dates very close to that produced by the National Bureau of Economic Research (NBER). Next, they investigate how accurately and quickly the models would have identified turning points had they been used in real-time for the past forty years. In general, the models identify ...