Ebook Credit Market Shocks, Monetary Policy, and Economic Fluctuations

The current financial crisis and the contemporaneous contractions in output, investment, and employment indicate that credit markets disruptions have important effects on economic activity. Central banks round the world have responded with aggressive reductions in their interest rates what suggests that monetary authorities believe that they can partially offset these negative credit market shocks. In this paper I explore the importance of credit market shocks for economic fluctuations and I asses if monetary policy could stabilize shocks that originate in credit markets. To provide quantitative answers for the U.S. economy I use Bayesian maximum likelihood methods to estimate an extended version of the Bernanke, Gertler, Gilchrist (1999) (henceforth BGG) financial accelerator model using real and financial data.

Gilchrist, Yankov, and Zakrajmsek (2008) show that corporate bond spreads have significant predictive power for economic activity, which suggests important linkages between financial conditions and macroeconomic outcomes. In order to quantify these linkages a structural macroeconomic model that distinguishes between changes in credit supply and demand and that can account for general equilibrium feedback effects between developments in the financial and real sectors of the economy is required. Recent work by Elekdag, Justiniano, and Tchakarov (2006), Tovar (2006), Christiano, Motto, and Rostagno (2007), Christensen and Dib (2008), De Graeve (2008), and Queijo von Heideken (2008) seeks to quantify these mechanisms by estimating dynamic stochastic general equilibrium (DSGE) models that incorporate credit market imperfections through the financial accelerator mechanism described in Carlstrom and Fuerst (1997) and BGG.

Although details differ in terms of model estimation and shocks specification, all of these papers document an important role for financial factors in business cycles fluctuations. Queijo von Heideken (2008) for example, shows that the ability of a model with a rich array of real and nominal rigidities to fit both U.S. and the Euro area data improves significantly if one allows for the presence of a financial accelerator mechanism; and Christiano, Motto, and Rostagno (2007) demonstrate that shocks to the financial sector have played and important role in economic fluctuations over the past two decades, both in the United States and Europe. Queijo von Heideken (2008), however, estimate a structural model that is identified without reliance on financial data and that does not allow for shocks to the financial sector, whereas Christiano, Motto, and Rostagno (2007), though allowing for a wide variety of shocks to the financial sector, do not estimate the parameters governing the strength of the financial accelerator mechanism. To date, we are aware of no empirical work that seeks to estimate simultaneously the key parameters of the financial accelerator mechanism along with the shocks to the financial sector using financial market data. The present work fills this gap.