Working Paper: NBER ID: w16657
Authors: James D. Hamilton; Michael T. Owyang
Abstract: This paper develops a framework for inferring common Markov-switching components in a panel data set with large cross-section and time-series dimensions. We apply the framework to studying similarities and differences across U.S. states in the timing of business cycles. We hypothesize that there exists a small number of cluster designations, with individual states in a given cluster sharing certain business cycle characteristics. We find that although oil-producing and agricultural states can sometimes experience a separate recession from the rest of the United States, for the most part, differences across states appear to be a matter of timing, with some states entering recession or recovering before others.
Keywords: Regional Business Cycles; Markov-Switching; Bayesian Methods
JEL Codes: E32
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| idiosyncratic shocks and differences in industrial composition (L16) | observed comovements (F29) |
| state-level business cycle experiences (E32) | national trends (J11) |
| timing of recessions (E32) | regional economic dynamics (R11) |
| common recessions (F44) | dynamics of state employment growth (J69) |
| correlation of employment growth rates and state-level characteristics (J69) | cluster membership (C38) |