Testing for profitability and contestability in banking: evidence from Austria

The paper investigates the determinants of banking profitability and banking market conditions in Austria. We conduct a panel econometric analysis which allows for testing the hypotheses which have become the most prominent in the literature on bank profitability: the structure–conduct–performance hypothesis, the efficient‐structure hypothesis and the relative market‐power hypothesis. Further, we test whether Austrian banking markets are, on average, contestable. A newly compiled dataset covering more than 700 Austrian banks ranging over the period from 1995 to 2002 is used to carry out these econometric analyses. The empirical findings support the view that the Austrian banks do exert, on average, some local market power. However, the gains in terms of excess profits are rather minor as a result of low deterrence powers of the incumbent banks.     

The wages of BMI: Bayesian analysis of a skewed treatment–response model with nonparametric endogeneity

We generalize the specifications used in previous studies of the effect of body mass index (BMI) on earnings by allowing the potentially endogenous BMI variable to enter the log wage equation nonparametrically. We introduce a Bayesian posterior simulator for fitting our model that permits a nonparametric treatment of the endogenous BMI variable, flexibly accommodates skew in the BMI distribution, and whose implementation requires only Gibbs steps. Using data from the 1970 British Cohort Study, our results indicate the presence of nonlinearities in the relationships between BMI and log wages that differ across men and women, and also suggest the importance of unobserved confounding for our sample of males. Copyright © 2008 John Wiley & Sons, Ltd.     

Interne Revision &; Controlling — Instrumente moderner Unternehmensführung in Kooperation

Ohne Zusammenfassung     

Credit Risk Models – Do They Deliver Their Promises? A Quantitative Assessment

We develop a framework to assess the statistical significance of expected default frequency calculated by credit risk models. This framework is then used to analyse the quality of two commercially available models that have become popular among practitioners: KMV Credit Monitor and RiskCalc from Moody's.
Using a unique database of expected default probability from both vendors, we study both the consistency of the prediction and its timeliness. We introduce the concept of cumulative accuracy profile (CAP) that allows to see in one curve the percentage of defaulting companies captured by the models one year in advance. We also use the Miller's information test to see if the models add information to the S&P rating.
The result of the analysis indicates that these models indeed add relevant information not accounted for by rating alone. Moreover, with respect to rating agencies, the models predict defaults more than ten months in advance on average.
(J.E.L.: C52).