@article {Rottmann:2013:0003-6846:2423,
title = "A micro data approach to the identification of credit crunches",
journal = "Applied Economics",
parent_itemid = "infobike://routledg/raef",
publishercode ="routledg",
year = "2013",
volume = "45",
number = "17",
publication date ="2013-06-01T00:00:00",
pages = "2423-2441",
itemtype = "ARTICLE",
issn = "0003-6846",
eissn = "1466-4283",
url = "https://www.ingentaconnect.com/content/routledg/raef/2013/00000045/00000017/art00010",
doi = "doi:10.1080/00036846.2012.665604",
keyword = "surveys, G21, nonlinear binary outcome panel-data models, E51, E44, credit crunch, loan supply, C23",
author = "Rottmann, Horst and Wollmersh{\"a}user, Timo",
abstract = "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.",
}