Does the Central Bank Respond to Credit Market Factors? A Bayesian DSGE Approach

44 Pages Posted: 12 Jun 2015 Last revised: 15 Jun 2015

See all articles by Paul Kitney

Paul Kitney

Centre for Applied Macroeconomic Analysis

Date Written: June 1, 2015


This paper estimates a version of a New Keynesian Dynamic Stochastic General Equilibrium model with financial frictions for the United States using Bayesian techniques. Various Henderson-McKibbin-Taylor style monetary policy rules are examined, which react to inflation, output and credit market factors including credit spreads, financial leverage and credit growth. The central question is whether the central bank responds to credit market factors in setting the policy interest rate, which is investigated using posterior odds tests. The paper explores whether there is evidence of stabilization, if indeed the central bank is responding to credit market factors. This is conducted using impulse response analysis and an examination of parameter posterior distributions. The most compelling result during the period under study is the US Fed responded to credit spreads in setting the policy rate. The empirical results also confirm that credit spreads offer stabilization benefits. This result is robust to variations in the policy rule. It is also found that while financial leverage improves model fit when included in the policy rule, the response is pro-cyclical, which would unlikely be a feature of stabilization policy. Finally, there is no evidence that the policy interest rate responded to credit growth.

Suggested Citation

Kitney, Paul, Does the Central Bank Respond to Credit Market Factors? A Bayesian DSGE Approach (June 1, 2015). CAMA Working Paper No. 21/2015. Available at SSRN: or

Paul Kitney (Contact Author)

Centre for Applied Macroeconomic Analysis ( email )

ANU College of Asia and the Pacific
Crawford School of Public Policy
Canberra, Australian Capital Territory 2601

HOME PAGE: http://

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
PlumX Metrics