A micro data approach to the identification of credit crunches

This paper 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 credit 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 banks' refinancing costs, which are also likely to affect the supply of loans, we derive a credit crunch indicator, which measures that part of the shift in the willingness to lend that is neither explained by firm-specific factors nor by refinancing costs. -- credit crunch ; loan supply ; surveys ; nonlinear binary outcome panel-data models