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

Listed author(s):
  • Haroon Mumtaz

    ()

    (Queen Mary University of London)

  • Gabor Pinter

    (Bank of England)

  • Konstantinos Theodoridis

    (Bank of England)

This paper evaluates the performance of structural VAR models in estimating the impact of credit supply shocks. In a simple Monte-Carlo experiment, we generate data from a DSGE model that features bank lending and credit supply shocks and use SVARs to try and recover the impulse responses to these shocks. The experiment suggests that a proxy VAR that uses an instrumental variable procedure to estimate the impact of the credit shock performs well and is relatively robust to measurement error in the instrument. A structural VAR with sign restrictions also performs well under some circumstances. In contrast, VARs of the narrative variety, i.e. VAR models that include measures of the credit shock as endogenous variables are highly sensitive to ordering and measurement error. An application of the proxy VAR model and the VAR with sign restrictions to US data suggests, however, that the credit supply shock is hard to identify in practice.

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File URL: http://econ.qmul.ac.uk/research/workingpapers/2014/Items/docs/716.pdf
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Paper provided by Queen Mary University of London, School of Economics and Finance in its series Working Papers with number 716.

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Date of creation: Apr 2014
Handle: RePEc:qmw:qmwecw:wp716
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