What do VARs Tell Us about the Impact of a Credit Supply Shock?

Haroon Mumtaz, Gabor Pinter and Konstantinos Theodoridis

No 739, Working Papers from Queen Mary University of London, School of Economics and Finance

Abstract: This paper evaluates the performance of a variety of structural VAR models in estimating the impact of credit supply shocks. Using a Monte-Carlo experiment, we show that identification based on sign and quantity restrictions and via external instruments is effective in recovering the underlying shock. In contrast, identification based on recursive schemes and heteroscedasticity suffer from a number of biases. When applied to US data, the estimates from the best performing VAR models indicate, on average, that credit supply shocks that raise spreads by 10 basis points reduce GDP growth and inflation by 1% after one year. These shocks were important during the Great Recession, accounting for about half the decline in GDP growth.

Keywords: Credit supply shocks; Proxy SVAR; Sign restrictions; Identification via heteroscedasticity; DSGE models (search for similar items in EconPapers)
JEL-codes: C15 C32 E32 (search for similar items in EconPapers)
Date: 2015-03-02
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Citations: View citations in EconPapers (9)

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Related works:
Journal Article: WHAT DO VARS TELL US ABOUT THE IMPACT OF A CREDIT SUPPLY SHOCK? (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:qmw:qmwecw:739

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