Abstract
This paper evaluates the roles of short- and long-term private and government interest rates and inside and outside money in the monetary transmission mechanism. With money and credit markets present, changes in monetary policy set off a chain of relative price and portfolio adjustments affecting output and prices. I study interest rate and money supply rules within this monetary transmission mechanism by estimating several Markov-switching Bayesian vector autoregressions (MS-BVARs) on a quarterly U.S. sample from 1960 to 2018. The best-fit MS-BVAR restricts MS to the impact and lag coefficients of the monetary policy and money demand regressions as well as to the stochastic volatilities (SVs) of the structural shocks. Estimates of this MS-BVAR yield evidence of a SV regime which coincides with NBER-dated recessions. This MS-BVAR also identifies a regime switch in the Fed’s interest rate rule and banks’ demand for outside money around the dot-com bust of 2000 and again from the 2007–2009 recession and financial crisis to the end of the sample. Counterfactual simulations show the 2007–2009 recession and financial crisis would have not been as deep and long-lasting if the fed funds rate had been as low as −8 % in 2009 and remained negative from 2010 through 2016.
Acknowledgment
This paper is based on the first chapter of my Ph.D. dissertation. I am thankful for my graduate advisor, Jim Nason, for his support. I am also grateful to my dissertation committee members, Ayse Kabukcuoglu-Dur, Doug Pearce, Mark Walker, and Xiaoyong Zheng for their comments and suggestions. I have also benefited from conversations with Mike Belongia, Saroj Bhattarai, John Conlon, Lee Craig, Andrew Glover, Josh Hendrickson, Ron Mau, Elmar Mertens, Chris Sims, Tao Zha, and the macroeconomics workshop and seminar participants at North Carolina State University, University of Mississippi, Towson University, and West Chester University. My thanks also go to the editor, Felipe Schwartzman, and an anonymous referee, whose comments and suggestions substantially improved the paper. Finally, I extend my thanks to the staff at the High Performance Computing (HPC) centers at the University of Mississippi and North Carolina State University as well as the Dynare development team for computing support. All remaining errors are my own. Supplement and Additional Results appendices are available at https://kennethmrich.com/research.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/bejm-2022-0072).
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