In this paper we compare the predictive abilility of Stochastic Volatility (SV)models to that of volatility forecasts implied by option prices. We develop anSV model with implied volatility as an exogeneous var able in the varianceequation which facilitates the use of statistical tests for...

Accident costs are an important component of the external costs of traffic, a substantial part of whichis related to fatal accidents. The evaluation of fatal accident costs crucially depends on theavailability of an estimate for the economic value of a statistical life. The aim of the...

Various economic theories are available to explain the existence of credit and default cycles. There remains empirical ambiguity, however, as to whether or these cycles coincide. Recent papers_new suggest by their empirical research set-up that they do, or at least that defaults and credit...

This paper investigates business cycle relations among different economies in theEuro area. Cyclical dynamics are explicitly modelled as part of a time series model. Weintroduce mechanisms that allow for increasing or diminishing phase shifts and for time-varyingassociation patterns in different...

Banks provide risky loans to firms which have superior information regarding the quality of their projects. Due to asymmetric information the banks face the risk of adverse selection. Credit Value-at-Risk (CVaR) regulation counters the problem of low quality, i.e. high risk, loans and therefore...

The increasing availability of financial market data at intraday frequencies has not only led to the development of improved volatility measurements but has also inspired research into their potential value as an information source for volatility forecasting. In this paper we explore the...

In this paper we replace the Gaussian errors in the standard Gaussian, linear state space model with stochastic volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are ineffective, but that this problem can be removed by...

In this paper we employ techniques developed in spatial econometrics to analyse spatial patterns of technology diffusion, to detect clusters and to estimate theoretical models that incorporate space explicitly. These techniques correct for misspecifications resulting from the omission of spatial...

Economic problems such as large claims analysis in insurance and value-at-risk in finance, requireassessment of the probability P of extreme realizations Q. This paper provided a semi-parametricmethod for estimation of extreme (P, Q) combinations for data with heavy tails. We solve the...

We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...