In this paper, we construct the country-specific chronologies of the house price bubbles for 12 OECD countries over the period 1969:Q1 - 2010:Q2. These chronologies are obtained using a combination of a fundamental and a filter approaches. The resulting speculative bubble chronology is the one...

We examine various and different approaches for the prediction of economic crisis periods of US economy. We examine the traditional econometric discrete choice Logit and Probit models then a feed-forward neural network (FFNN) model and finally we apply an Adaptive Neuro-Fuzzy Inference System...

We estimate forward-looking Taylor rules on data from macroeconomic forecasts of three central banks (Bank of England, National Bank of Poland and Swiss National Bank) in order to determine the extent to which these banks are forward looking in their monetary policy decisions. We find that all...

When nontraded goods prices are accounted for consistently and genuine stock data on bilateral foreign asset holdings is employed, a modified sticky-price exchange rate model by far outperforms the benchmark random walk-model in empirically forecasting the D-mark/dollar parity out of sample....

Empirical evidence suggests that many macroeconomic and financial time series are subject to occasional structural breaks. In this paper we present analytical results quantifying the effects of such breaks on the correlation between the forecast and the realization and on the ability to forecast...

Autoregressive models are used routinely in forecasting and often lead to better performance than more complicated models. However, empirical evidence is also suggesting that the autoregressive representations of many macroeconomic and financial time series are likely to be subject to structural...

We consider the problem of forecasting time series with long memory when the memory parameter is subject to a structural break. By means of a large-scale Monte Carlo study we show that ignoring such a change in persistence leads to substantially reduced forecasting precision. The strength of...