Dynamic Effects of Credit Shocks in a Data-Rich Environment

The recent financial crisis and the ensuing global economic downturn suggests that financial variables can predict future economic conditions and play an important role in propagating economic fluctuations. In this paper we examine the dynamic effects and the propagation of credit shocks using a large data set of U.S. economic and financial indicators in a structural factor model. An identified credit shock, which can be interpreted as a unexpected deterioration of the credit market conditions, increases immediately the credit spreads, decreases the interest rates and causes large and persistent downturns in the activity of many economic sectors. In contrast to other recent papers, our approach does not rely on any constructed measure of credit market conditions from a large set of individual bond prices and financial series, and does not require any timing restrictions between the financial factors and the real economic activity. Moreover, our structural shock identification procedure gives an interpretation of the estimated factors.