A previous version of this working paper was originally published in May 2012.
The authors employ Markov-switching Bayesian vector autoregressions (MS-BVARs) to gather evidence about the hypothesis on a long annual U.S. sample running from 1890 to 2010. The sample covers several episodes useful for understanding U.S. economic and financial history, which generate variation in the data that aids in identifying credit supply and demand shocks. They identify these shocks within MS-BVARs by tying credit supply and demand movements to inside money and its intertemporal price. The model space is limited to stochastic volatility (SV) in the errors of the MS-BVARs. Of the 15 MS-BVARs estimated, the data favor a MS-BVAR in which economic and financial crises and non-crisis business cycle regimes recur throughout the long annual sample. The best-fitting MS-BVAR also isolates SV regimes in which shocks to inside money dominate aggregate fluctuations.