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A micro data approach to the identification of credit crunches

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This article presents a micro data approach to the identification of credit crunches. Using a survey among German firms which regularly queries the firms' assessment of the current willingness of banks to extend credit, we estimate the probability of a restrictive loan supply policy by time taking into account the creditworthiness of borrowers. Creditworthiness is approximated by firm-specific factors, e.g. the firms' assessment of their current business situation and their business expectations. After controlling for the return on the banks' risk-free investment alternative, which is also likely to affect the supply of loans, we derive a credit crunch indicator, which measures that part of the shift in the loan supply that is neither explained by firm-specific factors nor by the opportunity costs of providing risky loans.
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Keywords: C23; E44; E51; G21; credit crunch; loan supply; nonlinear binary outcome panel-data models; surveys

Document Type: Research Article

Affiliations: 1: Amberg–Weiden University of Applied Sciences, Hetzenrichter Weg 1592637 Weiden, Germany 2: Ifo Institute – Leibniz Institute for Economic Research at the University of Munich, Poschingerstr. 581679 München, Germany

Publication date: 2013-06-01

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