CREFC ECONOMIC LETTER N o . 2002-01, March 20, 2002 Is the U.S. Recession Over Yet? Marcelle Chauvet Recent data indicate that the U.S. economy is already showing signs of breaking out of the 2001 recession. How and when will we know whether the recession is over? It seems that the market, economists, and politicians are waiting for a signal from the NBER Business Cycle Dating Committee. The NBER has been dating the U.S. expansions and recessions for the last fifty years. A decision about business cycle turning points is reached from a subjective consensus among the members of the Committee and it is generally accepted as the official dating of the U.S. business cycle. Although careful deliberations are applied to determine turning points, the NBER procedure can not be used to monitor business cycles on a current basis. Generally, the Committee meets months after a turning point has occurred, and a decision is only released when there is no doubt regarding the dating. This can only be achieved by examining a substantial amount of ex-post revised data. In fact, the NBER has announced in February 2002 that “the Committee will wait until a substantial period of expansion has elapsed before declaring that a turning point in the economy is a true trough, marking the end of a recession” (NBER 2002). Thus, the NBER dating procedure can not be used in real time. This raises some questions: • How can we assess whether a recession is over until the NBER announces its decision? • Are there models that can date business cycles in real time? Formal Probability Models for Dating Recessions Some analytic models that formalize the construction of economic indicators, and probabilistic frameworks to define and evaluate turning point forecasts have gained popularity in the last decades. The univariate Markov switching model proposed by Hamilton (1989) reproduces closely the NBER dating when applied to GDP growth. However, there are some problems in using GDP to assess current economic conditions. First, GDP is only available at the quarterly frequency, which implies a delay in real time chronology. Second, this series undergoes substantial and continuous revisions after its first release, which may compromise a real time assessment of turning points. In fact, the NBER Committee does not put much weight on GDP in their analysis due to these reasons. Instead, the NBER procedure is based on cyclical variation of several monthly variables that move together with business cycles, such as non- agricultural employment, personal income, manufacturing and trade sales, and industrial production, among others. The univariate Markov switching model can be extended to a multivariate dynamic factor model, as proposed in Diebold and Rudebusch (1995). This framework allows inclusion of several variables reflecting different sectors of the economy. Chauvet (1998) estimates a dynamic factor model with regime switching (DFMS) including the variables analyzed by the NBER at the monthly frequency. The model yields a monthly indicator of the U.S. business cycle and probabilities of recessions and expansions. These estimated probabilities can be used to obtain dates for the U.S. business cycle. The resulting chronology is highly correlated with the NBER dating ex-post and in real time. Thus, these formal analytic models can be used to monitor turning points and evaluate forecasts in real time, overcoming delays inherent in the NBER dating procedure. What do nonlinear probability models tell us about U.S. recessions? Since 1959 the U.S. economy has experienced seven recessions. Figure 1 shows the NBER recession dating (shaded area) and the ex-post probabilities of recessions (smoothed probabilities) obtained from the dynamic factor model with Markov switching (DFMS). These probabilities are -1.2 -0.8 -0.4 0.0 0.4 0.8 1.2 1 900 :1 20 10: 1 195 5:1