Finding Good Predictors for Inflation: A Bayesian Model Averaging Approach

We consider a Bayesian Model Averaging approach for the purpose of forecasting Swedish consumer price index inflation using a large set of potential indicators, comprising some 80 quarterly time series covering a wide spectrum of Swedish economic activity. The paper demonstrates how to efficiently and systematically evaluate (almost) all possible models that these indicators in combination can give rise to. The results, in terms of out-of-sample-performance, suggest that Bayesian Model Averaging is a useful alternative to other forecasting procedures, in particular recognizing the flexibility by which new information can be incorporated

Firm default and aggregate fluctuations

This paper studies the relation between macroeconomic fluctuations and corporate defaults while conditioning on industry affiliation and an extensive set of firm-specific factors. Using a logit approach on a panel data set for all incorporated Swedish businesses over 1990-2002, we find strong evidence for a substantial and stable impact of aggregate fluctuations. Macroeffects differ across industries in an economically intuitive way. Out-of-sample evaluations show our approach is superior to both models that exclude macro information and best fitting naive forecasting models. While firm-specific factors are useful in ranking firms’ relative riskiness, macroeconomic factors capture fluctuations in the absolute risk level.Business failures

Inflation, Exchange Rates and PPP in a Multivariate Panel Cointegration Model

New multivariate panel cointegration methods are used to analyze nominal exchange rates and prices in the four major economic powers in Europe, France, Germany, Italy and Great Britain for the post- Bretton Woods period. We test for PPP and find that the theoretical PPP relationship does not hold but there is a similar (1,-1.5,0.9 instead of 1,-1,1) relationship which is common for the investigated countries. Parametric bootstrap inference is used to deal with badly small sample sized tests.Long-run purchasing power parity, multivariate cointegration analysis, bootstrap inference.

Internal Ratings Systems, Implied Credit Risk and the Consistency of Banks Risk Classification Policies

Counterpart risk rating is at the heart of the banking business. In the new Basel II regulation, internal ratings have been given a central role. Although much research has been done on external ratings, much less is known about banks´ internal ratings. This paper presents new quantitative evidence on the consistency of internal ratings based on panel data from the complete business loan portfolios of two Swedish banks and a credit bureau over the period 1997-2000. We study rating class distributions, - transitions and default behavior and compute the credit loss distributions that each rating system implies by means of a semi-parametric Monte Carlo re-sampling method following Carey (1998). Our results reveal, for a portfolio with identical counterparts, substantial differences in the implied riskiness between banks. Such differences could translate into different amounts of required economic capital and create (new) incentives to securitize part of their loan portfolios or increase the riskiness of loans in certain rating classes. We also shed light on the quantitative importance of portfolio composition, portfolio size and the forecast horizon for loss distributions. For example, with common portfolio parameters, credit risk can be reduced by up to 40 percent by doubling the loan portfolio size. We also discuss the relation between loss distributions and the desirable level of insolvency risk

Growth, Savings, Financial Markets and Markov Switching Regimes

We report evidence that the relation between the financial sector share, private savings and growth in the United States 1948-1996 is characterized by several regime shifts. The finding is based on vector autoregressions on quarterly data that allow for Markov switching regimes. The evidence may be interpreted as support for a hypothesis that the relation between financial development and growth evolves in a stepwise fashion. Theoretical models where financial market extensions entail fixed costs imply such stepwise patterns. The estimated variable relations are roughly consistent with the patterns to be expected from such models, although our data do not admit definite conclusions. The timing of the shifts coincides with regulatory changes and changes in the financial market structure

Exploring Interactions between Real Activity and the Financial Stance

In this paper we empirically study interactions between real activity and the financial stance. Using aggregate data we examine a number of candidate measures of the financial stance of the economy. We find strong evidence for substantial spillover effects on aggregate activity from our preferred measure. Given this result, we use a large micro data-set for corporate firms to develop a macro-micro model of the interaction between the financial and real economy. This approach implies that the impulse responses of a given aggregate shock will depend on the portfolio structure of firms at any given point in time