Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/122088 
Erscheinungsjahr: 
2015
Schriftenreihe/Nr.: 
Working Paper No. 739
Verlag: 
Queen Mary University of London, School of Economics and Finance, London
Zusammenfassung: 
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.
Schlagwörter: 
Credit supply shocks
Proxy SVAR
Sign restrictions
Identification via heteroscedasticity
DSGE models
JEL: 
C15
C32
E32
Dokumentart: 
Working Paper

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