Federal Reserve Bank of New York
Dynamic effects of credit shocks in a data-rich environment
We examine the dynamic effects of credit shocks using a large data set of U.S. economic and financial indicators in a structural factor model. An identified credit shock resulting in an unanticipated increase in credit spreads causes a large and persistent downturn in indicators of real economic activity, labor market conditions, expectations of future economic conditions, a gradual decline in aggregate price indices, and a decrease in short- and longer-term riskless interest rates. Our identification procedure, which imposes restrictions on the response of a small number of economic indicators, yields interpretable estimated factors, and allows us to perform counterfactual experiments. Such an experiment suggests that credit spread shocks have largely contributed to the deterioration in economic conditions during the Great Recession.
Cite this item
Jean Boivin & Marc Giannoni & Dalibor Stevanovic, Dynamic effects of credit shocks in a data-rich environment, Federal Reserve Bank of New York, Staff Reports 615, 2013, revised 01 Oct 2016.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
Keywords: credit shocks; FAVAR; structural factor analysis
This item with handle RePEc:fip:fednsr:615
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