Determinants of heterogeneity in European credit ratings

In this study, we empirically analyze the determinants of heterogeneity in rating assessments across different segments of the European loan market. We conduct a benchmarking analysis using rating information on European corporate obligors from nine major Austrian banks that have a large share of foreign lending, particularly in the Central and Eastern European region. We provide evidence that, generally, overall heterogeneity among rating outcomes for foreign markets is higher than for domestic markets. Furthermore, we show that heterogeneity increases in transition economies and those markets where Austrian bank involvement is relatively low. Our evidence supports the hypothesis that heterogeneity in the assessment of credit risk is determined not only by the objective quality of information, which is deemed to be lower in transition economies, but also by the subjective access to information about obligors measured by the level of domestic bank involvement in the respective foreign market. Furthermore, we quantify potential effects on regulatory capital requirements.     

Recursive Nash bargaining over a productive asset

We propose an equilibrium concept (the recursive Nash bargaining solution) that describes the outcome of repeated negotiations between two rational agents under the assumptions that the state of the economic system under consideration changes according to the actions of the players and that neither party can make binding commitments to future behavior. This equilibrium is dynamically consistent but typically not Pareto-efficient. As an application, we compute the recursive Nash bargaining solution in a model of two heterogeneous agents bargaining over the use of a productive asset with constant gross rate of return and study how the time-preference rates and the elasticities of substitution affect the solution.     

Proportional Odds Models with High‐Dimensional Data Structure

The proportional odds model is the most widely used model when the response has ordered categories. In the case of high‐dimensional predictor structure, the common maximum likelihood approach typically fails when all predictors are included. A boosting technique pomBoost is proposed to fit the model by implicitly selecting the influential predictors. The approach distinguishes between metric and categorical predictors. In the case of categorical predictors, where each predictor relates to a set of parameters, the objective is to select simultaneously all the associated parameters. In addition, the approach distinguishes between nominal and ordinal predictors. In the case of ordinal predictors, the proposed technique uses the ordering of the ordinal predictors by penalizing the difference between the parameters of adjacent categories. The technique has also a provision to consider some mandatory predictors (if any) that must be part of the final sparse model. The performance of the proposed boosting algorithm is evaluated in a simulation study and applications with respect to mean squared error and prediction error. Hit rates and false alarm rates are used to judge the performance of pomBoost for selection of the relevant predictors.     

Decomposing desert and tangibility effects in a charitable giving experiment

Several papers have documented that when subjects play with standard laboratory “endowments” they make less self-interested choices than when they use money they have either earned through a laboratory task or brought from outside the lab. In the context of a charitable giving experiment we decompose this into two common artifacts of the laboratory: the intangibility of money (or experimental currency units) promised on a computer screen relative to cash in hand, and the distinct treatment of random “windfall” gains relative to earned money. While both effects are found to be significant in non-parametric tests, the former effect, which has been neglected in previous studies, has a stronger impact on total donations, while the latter effect has a greater impact on the probability of donating. These results have clear implications for experimental design, and also suggest that the availability of more abstract payment methods may increase other-regarding behavior in the field.     

The association between two random elements: A complete characterization and odds ratio models

For random elements X and Y (e.g. vectors) a complete characterization of their association is given in terms of an odds ratio function. The main result establishes for any odds ratio function and any pre-specified marginals the unique existence of a corresponding joint distribution (the joint density is obtained as a limit of an iterative procedure of marginal fittings). Restricting only the odds ratio function but not the marginals leads to semi-parmetric association models for which statistical inference is available for samples drawn conditionally on either X or Y. Log-bilinear association models for random vectors X and Y are introduced which generalize standard (regression) models by removing restrictions on the marginals. In particular, the logistic regression model is recognized as a log-bilinear association model. And the joint distribution of X and Y is shown to be multivariate normal if and only if both marginals are normal and the association is log-bilinear.Acknowledgements The author thanks both referees for their helpful comments which improved the first draft of the paper.     

FISCAL POLICY AND OPTIMAL TAXATION: EVIDENCE FROM A TAX SMOOTHING EXERCISE

Testing the tax smoothing hypothesis for the EU‐15, we hypothesise that the introduction of the 3%‐deficit rule of the Maastricht Treaty in 1993 may have inhibited tax smoothing as European Union (EU)‐member states are no longer capable of letting the deficit grow as much as implied by expected decreases in government expenditure. Our results show that for some countries this fiscal rule may have indeed changed the validity of the tax smoothing hypothesis, thus implying that EU accession has caused welfare losses.     

A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP

We derive forecast weights and uncertainty measures for assessing the roles of individual series in a dynamic factor model (DFM) for forecasting the euro area GDP from monthly indicators. The use of the Kalman smoother allows us to deal with publication lags when calculating the above measures. We find that surveys and financial data contain important information for the GDP forecasts beyond the monthly real activity measures. However, this is discovered only if their more timely publication is taken into account properly. Differences in publication lags play a very important role and should be considered in forecast evaluation.     

Privacy Is Precious: On the Attempt to Lift Anonymity on the Internet to Increase Revenue

We investigate the effect of a reduction of anonymity on consumers' purchase decisions (whether to buy, and if so how much to pay) at an online music store with Pay‐What‐You‐Want (PWYW)‐like pricing and in an Internet experiment mimicking the real world situation. Revealing the customer's name, e‐mail, and payment to the artist (seller) led to insignificantly higher payments, although it drastically reduced the number of customers purchasing. Overall, the regime led to a revenue loss of 25%. In the online experiment, revenue drops by 35%. These results suggest that the positive effect of reduced anonymity, previously established for donation or public goods contexts, does not extend to a consumption environment. Instead, the substantial opt‐out of customers is likely to be motivated by concerns about privacy.     

Administrative tradition and management reforms: a comparison of agency chief executive accountability in four Continental Rechtsstaat countries

This article investigates perceived accountability patterns of national agencies’ chief executives in four countries with a Rechtsstaat tradition and tests theoretical expectations about potential tensions between managerial reforms and administrative values using survey data (N = 453). All countries combine old and new forms of accountability requirements, while legal and financial accountability have not been replaced with results accountability. Switzerland and the Netherlands score highest on results accountability, though in combination with legal and financial accountability, which are dominant in Germany and Austria. Nation-specific characteristics seem more important for core values of public administration than generic characteristics of the Rechtsstaat model.