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Federal Reserve Bank of St. Louis
Working Papers
Metro Business Cycles
Maria A. Arias
Charles S. Gascon
David E. Rapach
Abstract

We construct monthly economic activity indices for the 50 largest U.S. metropolitan statistical areas (MSAs) beginning in 1990. Each index is derived from a dynamic factor model based on twelve underlying variables capturing various aspects of metro area economic activity. To accommodate mixed-frequency data and differences in data-publication lags, we estimate the dynamic factor model using a maximum- likelihood approach that allows for arbitrary patterns of missing data. Our indices highlight important similarities and differences in business cycles across MSAs. While a number of MSAs experience sizable recessions during the national recessions of the early 1990s and early 2000s, other MSAs escape recessions altogether during one or both of these periods. Nearly all MSAs suffer relatively deep recessions near the recent Great Recession, but we still find significant differences in the depth of recent metro recessions. We relate the severity of metro recessions to a variety of MSA characteristics and find that MSAs with less-educated populations and less elastic housing supplies experience significantly more severe recessions. After controlling for national economic activity, we also find significant evidence of dynamic spillover effects in economic activity across MSAs.


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Maria A. Arias & Charles S. Gascon & David E. Rapach, Metro Business Cycles, Federal Reserve Bank of St. Louis, Working Papers 2014-46, 11 Nov 2014, revised 09 May 2016.
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Keywords: Economic activity index; Metropolitan statistical area; Recession; Dynamic factor model; Latent variable; EM algorithm; Mixed regressive; spatial autoregressive model; Dynamic spillovers
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