In der vorliegenden Untersuchung betrachten wir die Grundgesamtheit der deutschen Unternehmen, von denen im Zeitraum 1956 bis 1998 Stamm- und stimmrechtslose Vorzugsaktien börsennotiert waren. Zwischen beiden Aktiengattungen besteht mit durchschnittlich 17,2 Prozentpunkten ein ökonomisch und...

This paper uses fractional integration and cointegration in order to model the DM/dollar and the yen/dollar real exchange rates in terms of both monetary and real factors, more specifically real interest rate and labour productivity differentials. We find that whilst the individual series may be...

In this note the unobserved component approach underlying the software package SEATS is compared with the Beveridge-Nelson type of decomposition for seasonal time series. The main strength of the SEATS approach lies in the appealing model formulation and the careful specification and adjustment...

We show in the paper that the decomposition proposed by Beveridge and Nelson (1981) for models that are integrated of order one can be generalized to seasonal Arima models by means of a partial fraction decomposition. Two equivalent algorithms are proposed to optimally (in the mean squared...

We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel. -- Factor Analysis ; Time Series ; Kernel...

We propose a nonparametric test for checking parametric hypotheses about the stationary density of weakly dependent observations. The test statistic is based on the L2-distance between a nonparametric and a smoothed version of a parametric estimate of the stationary density. It can be shown that...

We prove geometric ergodicity and absolute regularity of the nonparametric autoregressive bootstrap process. To this end, we revisit this problem for nonparametric autoregressive processes and give some quantitative conditions (i.e., with explicit constants) under which the mixing coefficients...

We develop a nonparametric estimation theory in a non-stationary environment, more precisely in the framework of null recurrent Markov chains. An essential tool is the split chain, which makes it possible to decompose the times series under consideration in independent and identical parts. A...

This paper discusses a methodology which uses time series cross sectional datafor the estimation of a time dependent regression function depending on explanatory variables and for the prediction of values of the dependent variable. The methodology assumes independent observations and is based on...

We propose a method of modeling panel time series data with both inter- and intra-individual correlation, and of fitting an autoregressive model to such data. Estimates are obtained by a conditional likelihood argument. If there are few observations in each series, the estimates can be...