Exchange rates typically exhibit time-varying patterns in both means andvariances. The histograms of such series indicate heavy tails. In thispaper we construct models which enable a decision-maker to analyze theimplications of such time series patterns for currency risk management.Our approach...

This paper deals with optimal window width choice in non-parametric lag- or spectral window estimation of the spectral density of a stationary zero-mean process. Several approaches are reviewed: the cross-validation based methods described by Hurvich (1985), Beltrao & Bloomfield (1987) and...

The paper compares the cointegration methods of Johansen and Bierens by means of simulations and a real world example. Drawing on the fact developed in a companion paper that the Johansen procedure has robustness properties against ARMA systems and the Bierens procedure is designed for ARMA...

This paper analyzes the higher-order properties of nested pseudo-likelihood (NPL) estimators and their practical implementation for parametric discrete Markov decision models in which the probability distribution is defined as a fixed point. We propose a new NPL estimator that can achieve...

It is argued that the observed return rates on capital at firm-level have an upward bias if firms are producing with unobserved intangible capital. Using EUKLEED, a comprehensive firm level data base for Germany, this theoretical preposition is proved empirically. Furthermore, making unobserved...

In systems of variables with a specified or already identified cointegrating rank, stationarity of component variates can be tested by a simple restriction test. The implied decision is often in conflict with the outcome of unit root tests on the same variables. Using a framework of Bayes...

Bivariate time series data often show strong relationships between the two components, while both individual variables can be approximated by random walks in the short run and are obviously bounded in the long run. Three model classes are considered for a time-series model selection problem:...

In this study we evaluate the forecast performance of model averaged forecasts based on the predictive likelihood carrying out a prior sensitivity analysis regarding Zellner's g prior. The main results are fourfold: First the predictive likelihood does always better than the traditionally...

Ciccone and Jarocínski (2010) show that inference in Bayesian model averaging (BMA) can be highly sensitive to small changes in the dependent variable. In particular they demonstrate that the importance of growth determinants in explaining growth varies tremendously over different revisions of...

This note proposes a generalized two-part model for fractional response variables that nests the one-part model proposed by Papke and Wooldridge (1996). Consequently, a Wald test allows to discriminate between these two competing models. A small scale Monte Carlo simulation demonstrates that the...