Credit Risk and the Finnish Economy

Petr Jakubík

Czech Economic Review, 2007, vol. 1, issue 3, 254-285

Abstract: The significance of credit risk models has increased with the introduction of the New Basel Accord, known as Basel II. The aim of this study is to examine default rate modeling. This paper follows two possible approaches to macro credit risk modeling, empirical models and a latent factor model based on Merton. We employ data over the time period from 1988 to 2003 for the Finnish economy, including time series of bankruptcy, numbers of firms and industry-specific data. Linear vector autoregressive models are used in the case of a dynamic empirical model. We examine how significant macroeconomic indicators determine the default rate in the whole economy and in industry-specific sectors. Since these models cannot provide microeconomic foundations, we employ a model with one latent factor, although multi-factor models are also considered. This estimation helps us to understand the relationships between credit risk and macroeconomic indicators. Both models can be used for default rate prediction or stres s testing by central authorities.

Keywords: banking; credit risk; latent factor model; default rate (search for similar items in EconPapers)
JEL-codes: G21 G28 G33 (search for similar items in EconPapers)
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://auco.fsv.cuni.cz/storage/24_2007_03_254.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fau:aucocz:au2007_254

Ordering information: This journal article can be ordered from
http://auco.cuni.cz/

Access Statistics for this article

More articles in Czech Economic Review from Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies Contact information at EDIRC.
Bibliographic data for series maintained by Lenka Stastna ().