We propose a new approach to deal with structural breaks in time series models. The key contribution is an alternative dynamic stochastic specification for the model parameters which describes potential breaks. After a break new parameter values are generated from a so-called baseline prior...

In this paper, we evaluate the forecasting ability of 115 indicators to predict the housing prices and rents in 71 German cities. Above all, we are interested in whether the local business confidence indicators can allow substantially improving the forecasts, given the local nature of the...

Die Kaufpreise für Eigentumswohnungen sind seit Beginn des Jahres 2010 um durchschnittlich sechs Prozent gegenüber dem jeweiligen Vorjahresquartal gestiegen. Die Wachstumsraten der Mietpreise haben mit vier Prozent deutlich weniger zugenommen, liegen aber ebenfalls oberhalb der allgemeinen...

The role of the housing market in the everyday life of society is difficult to overestimate. The housing rents and prices directly affect standard of living of virtually every person. Housing loans constitute the largest liability of households and account for a large proportion of bank lending....

In this paper, we make multi-step forecasts of the annual growth rates of the real GDP for each of the 16 German Länder (states) simultaneously. Beside the usual panel data models, such as pooled and fixed-effects models, we apply panel models that explicitly account for spatial dependence...

This discussion paper led to a publication in the <A HREF="http://onlinelibrary.wiley.com/doi/10.1002/jae.2358/abstract"><I>Journal of Applied Econometrics</I></A>, 2014, 29, pages 693-712.<P> Many economic studies on inflation forecasting have found favorable results when inflation is modeled as a stationary process around a slowly time-varying trend. In contrast, the existing...</p></i></a>

Many economic studies on inflation forecasting have found favorable results when inflation is modeled as a stationary process around a slowly time-varying trend. In contrast, the existing studies on interest rate forecasting either treat yields as being stationary, without any shifting...

This article proposes a modified method for the construction of diffusion indexes in macroeconomic forecasting using principal component regres- sion. The method aims to maximize the amount of variance of the origi- nal predictor variables retained by the diffusion indexes, by matching the data...

Seasonality often accounts for the major part of quarterly or monthly movements in detrended macro-economic time series. In addition, business cycle nonlinearity is a prominent feature of many such series too. A forecaster can nowadays consider a wide variety of time series models which describe...

Nonlinear time series models have become fashionable tools to describe and forecast a variety of economic time series. A closer look at reported empirical studies, however, reveals that these models apparently fit well in-sample, but rarely show a substantial improvement in out-of-sample...