Business Cycles

“An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switches,” International Economic Review, Vol. 39, No. 4, 969-96, 1998. (Download: Working Paper or IER)

Abstract: A dynamic factor model with regime switching is proposed as an empirical characterization of business cycles. The approach integrates the idea of comovements among macroeconomic variables and asymmetries of business cycle expansions and contractions. The first is captured with an unobservable dynamic factor and the second by allowing the factor to switch regimes. The model is estimated by maximizing its likelihood function and the empirical results indicate that the combination of these two features leads to a successful representation of the data relative to extant literature. This holds for within and out-of-sample and for both revised and real time data.   

“Dating Business Cycle Turning Points in Real Time,” with James D. Hamilton, “Nonlinear Time Series Analysis of Business Cycles,” ed. Van Dijk, Milas, and Rothman, Elsevier’s Contributions to Economic Analysis series, 1-54, 2006. (Download DatingBC)

Abstract: This paper discusses formal quantitative algorithms that can be used to identify business cycle turning points. An intuitive, graphical derivation of these algorithms is presented along with a description of how they can be implemented making very minimal distributional assumptions. We also provide the intuition and detailed description of these algorithms for both simple parametric univariate inference as well as latent-variable multiple-indicator inference using a state-space Markov-switching approach. We illustrate the promise of this approach by reconstructing the inferences that would have been generated if parameters had to be estimated and inferences drawn based on data as they were originally released at each historical date. Our recommendation is that one should wait until one extra quarter of GDP growth is reported or one extra fmonmonth of the monthly indicators released before making a call of a business cycle turning point. We introduce two new measures for dating business cycle turning points, which we call the “quarterly real-time GDP-based recession probability index” and the “monthly real-time multiple-indicator recession probability index” that incorporate these principles. Both indexes perform quite well in simulation with real-time data bases. We also discuss some of the potential complicating factors one might want to consider for such an analysis, such as the reduced volatility of output growth rates since 1984 and the changing cyclical behavior of employment. Although such refinements can improve the inference, we nevertheless recommend the simpler specifications which perform very well historically and may be more robust for recognizing future business cycle turning points of unknown character.

“A Comparison of the Real-Time Performance of Business Cycle Dating Methods,” with Jeremy Piger, Journal of Business Economics and Statistics, Vol. 26, No. 1,  42-49, 2008. (Download Repec or BC_RealTime)

Abstract: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 they been used in real time for the past 30 years. Both approaches accurately identified the NBER dated turning points in the sample in real time, with no instances of false positives. Further, both approaches, and especially the Markov-switching model, yielded significant improvement over the NBER in the speed with which business cycle troughs were identified. In addition to suggesting that business cycle dating rules are an informative tool to use alongside the traditional NBER analysis, these results provide formal evidence regarding the speed with which macroeconomic data reveals information about new business cycle phases.

“Identifying Business Cycle Turning Points in Real Time,” with Jeremy Piger, Federal Reserve Bank of Saint Louis Review, March/April, 47-62, 2003. (Download Repec or TPrealtime) 

Abstract: In this paper we take it as given that the NBER correctly identifies the dates of business cycle turning points. We then evaluate the real-time performance of the Markov-switching model in replicating the NBER’s business cycle dates. We apply the model to two datasets, growth in quarterly real gross domestic product (GDP) and growth in monthly economywide employment. We first confirm the result found elsewhere that the model is able to replicate the historical NBER business cycle dates fairly closely when estimated using all available data. Second, we evaluate the real-time performance of the model at dating business cycles over the past 40 years; this is accomplished by estimating the model on recursively increasing samples of data and evaluating the evidence for a new turning point at the end of each sample. 

"Nonstationarities and Markov Switching Models," with Y. Su, in Recent Advances in Estimating Nonlinear Models, Springer, 123-148, 2013. (Download) 

Abstract: This paper proposes a flexible model that allows for recent changes observed in the US business cycle in the last six decades. It proposes a Markov switching model with three Markov processes to characterize the dynamics of US output fluctuations. We consider the possibility that both the mean and the variance of growth rates of real GDP can have short run fluctuations in addition to the possibility of a long run permanent break. We find that, differently from several alternative specifications in the literature, the proposed flexible framework successfully represents all business cycle phases, including the Great Recession. In addition, we find that the volatility of US output fluctuations has both a long run pattern, characterized by a structural break in 1984, as well as business cycle dynamics, in which periods of high uncertainty are associated with NBER recessions.

"Business Cycle Monitoring with Structural Changes,” with Simon Potter, International Journal of Forecasting, Vol. 6, No. 4, 777-793, 2010. (Download Repec or MonitorBreaks).

Abstract: This paper examines the predictive content of coincident variables for monitoring U.S. recessions in the presence of instabilities. We propose several specifications of a probit model for classifying phases of the business cycle. We find strong evidence in favor of the ones that allow for the possibility that the economy has experienced recurrent breaks. The recession probabilities of these models provide a clearer classification of the business cycle into expansion and recession periods, and superior performance in the ability to correctly call recessions and to avoid false recession signals. Overall, the sensitivity, specificity, and accuracy of these models are far superior as well as their ability to timely signal recessions. The results indicate the importance of considering recurrent breaks for monitoring business cycles

“Increased Stabilization and the G7 Business Cycles” with Fang Dong, in Business Fluctuations and Cycles, ed. T. Nagakawa, 265-283, 2007. (Download StableG7 or here) 

Abstract: This paper models the G7 business cycle using a common factor model, which is used to investigate increased stabilization and its impact on business cycle phases. We find strong evidence of a decline in volatility in each of the G7 countries. We also find a break towards stability in their common business cycle. This reduction in volatility implies that recessions will be significantly less frequent in the future compared to the historical track.

“International Business Cycles: G7 and OECD Countries,” with Chengxuan Yu; Economic Review, Federal Reserve Bank of Atlanta, First Quarter, Vol. 91 No. 1, 43-54, 2006. (Download Repec or Bc_G7OECD)

Abstract: 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, we construct business cycle indicators for G7 countries and for an aggregate measure of output by twenty-nine member countries of the Organisation for Economic Co-operation and Development (OECD). The model yields probabilities of the current business cycle phase for each G7 country and for the aggregate OECD and G7 output measures and reveals a common cycle underlying the OECD countries that characterizes an international business cycle. The proposed filter sorts out minor contractions and estimates only major economic recessions and expansions, thereby minimizing the occurrence of false turning points. This feature is especially important for central banks that may want to adjust monetary policy only in the event of major recessions affecting a broad set of economic sectors.

"Maturing Capitalism and Stabilization: International Evidence,” with G. Popli in Journal of Business and Economics, Vol. 1, No. 12, 5-22, 2003. (Download or JBE)

Abstract: Recent literature has found that the U.S. business cycle has experienced a substantial decrease in volatility since the mid-1980s. An increased stability of business cycles has important policy implications since it affects the frequency, duration, and probabilities of future recessions and expansions. The findings are that the increased stabilization is widespread across many sectors of the U.S. economy. However, most authors have considered this as a recent phenomenon particular to the U.S., which narrows the search for potential causes. In this paper we go one step further and investigate whether this recent change is unique to the U.S. and a phenomenon particular to the 1980s alone or if this is part of a long run trend in volatility shared by several countries.  In particular, we examine whether maturing capitalism has engendered a continuous stabilization of business cycles in eleven industrialized countries over time. We do not try to quantify changes in volatility pre and post-War, which could be compromised by differences in the quality of the data.  Instead, we focus on examining structural changes in the long run trend of volatility in these countries.  Recursive stabilization tests are applied to examine breaks in the volatility of production in these countries, assuming that their dates are unknown. We find strong evidence of multiple structural breaks leading to more stability in these countries over time, and that the recent decrease in U.S. output volatility is part of a broader long-term trend shared by all industrialized countries studied. Since these breaks tend to be clustered for groups of countries, this makes it easier to investigate major common historical experiences that may explain changes in volatility.

"Markov Switching in Disaggregate Unemployment Rates,” with C.  Juhn and S. Potter, Empirical Economics, Vol. 27, No.2, 205-232, 2002.(Download Repec or MSunemployment). Reprint in: Advances in Markov Switching Models, ed. J.D. Hamilton and B. Raj. Studies in Empirical Economics. Physica-Verlag, 61-  88, 2002.

Abstract: We develop a dynamic factor model with Markov switching to examine secular and business cycle fluctuations in the U.S. unemployment rates. We extract the common dynamics amongst unemployment rates disaggregated for 7 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 that demographic adjustments can account for a great deal of secular changes in the unemployment rates, particularly the abrupt increase in the 1970s and 1980s and the subsequent decrease in the last 18 years.

"Employment and the Business Cycle," with Jeremy Piger, Manchester School, Vol 81, S2, 16-42, 2013. (Download Repec, Working Paper or Manchester )

Abstract: This paper investigates the differences in the cyclical dynamics in employment on non‐agricultural payroll (ENAP) and total civilian employment (TCE), and the implications for monitoring US business cycles in real time. We find that employment measures have diverged considerably around the last three recessions and subsequent recoveries. This significantly impacts identification of turning points. Models that use TCE are more in line with the National Bureau of Economic Research (NBER) recession dating, and deliver faster call of troughs in real time, whereas models that include ENAP series yield delays in signaling troughs, especially the most recent ones.

“Sunspots, Animal Spirits, and Economic Fluctuations,” with J.T. Guo, Macroeconomic Dynamics, Vol. 7, No. 1, February 2003. (Download SSRN or sunspots)

Abstract: Multiple-equilibria macroeconomic models suggest that consumers and investors' perceptions about the state of the economy may be important independent factors for business cycles. In this paper, we examine empirically the interrelations between waves of optimism and pessimism and subsequent economic fluctuations. We focus on the behavior of non-fundamental movements in the consumer sentiment index, as a proxy for consumers' sunspots, and in the business formation index, representing investors' animal spirits, around economic turning points. We find that bearish consumers and entrepreneurs were present before the onset of some U.S. economic downturns, sometimes even when the fundamentals were all very strong. In particular, our analysis shows that self-fulfilling pessimism may have played a nontrivial role for the 1969-70, the 1973-75, and the 1981-82 recessions. The results are robust to a range of alternative linear and nonlinear specifications. Our evidence provides some empirical support for the role of non-fundamental rational expectations in economic fluctuations.

“The Brazilian Business Cycle and Growth Cycle,” Brazilian Economic Journal (Revista Brasileira de Economia), Vol. 56 nº 1, 75-106, 2002. (Download BrazilBCGC or Repec )

Abstract: This paper uses several procedures to date and analyse the Brazilian business and growth cycles. In particular, a Markov switching model is fitted to quarterly and annual real production data. The smoothed probabilities of the Markov states are used as predictive rules to define different phases of cyclical fluctuations of real Brazilian economic activity. The results are compared with different non-parametric rules. All methods implemented yield similar dating and reveal asymmetries across the different states of the Brazilian business and growth cycles, in which slowdowns and recessions are short and abrupt, while high growth phases and expansions are longer and less steep. The resulting dating of the Brazilian economic cycles can be used as a reference point for construction and evaluation of the predictive performance of coincident, leading, or lagging indicators of economic activity. In addition, the filtered probabilities obtained from the Markov switching model allow early recognition of the transition to a new business cycle phase, which can be used, for example, for evaluation of the adequate strength and timing of countercyclical policies, for reassessment of projected sales or profits by businesses and investors, or for monitoring of inflation pressures.

Abstract: “Recent Changes in the U.S. Business Cycle,” with S. Potter, Manchester School, Vol. 69, No. 5, 481-508, 2001. (Download Repec , Working Paper or ChangesBC). 

The U.S. business cycle expansion that started in March 1991 was the longest on record (as of year 2000). This paper uses statistical techniques to examine whether that expansion was a one-time 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 considerably longer than the historical average.