In this paper we used a data set constructed for a companion paper (Fritsche/Stephan, 2000) where we explored the leading indicator properties of different time series for the German business cycle. Now we test for the ability of different indicator series to forecast recessions by using a...

Since 1990 the Netherlands Bureau for Economic Policy Analysis (CPB) uses a leading indicator in preparing short-term forecasts for the Dutch economy. This paper describes some recent methodological innovations as well as the current structure and empirical results of the revised CPB leading...

We study the properties of generalized stochastic gradient (GSG) learning in forward-looking models. We examine how the conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which governs stability under least squares learning. SG...

The paper derives analytical transitions probabilities following an exogenous shock to the deterministic component in the conditional logit model. The solution draws on the postestimation distribution of the models stochastic component, identified on the basis of a direct utility maximization...

Assessing the migration potential and predicting future migration streams are among the most relevant, yet least well understood topics of migration research. The usual approach taken to address aggregate-level prediction problems is to fit ad hoc specifications to historical data, and to...

The economic forecasts for Germany in the period 2001 to 2003 grossly missed reality. Forecasters estimated an average annual growth rate of 1.6 per cent, but real GDP actually grew by only 0.3 per cent per annum. In 2003 the real GDP in Germany even shrank by 0.1 per cent. Forecasters tend to...

The recent introduction of the realized variance measure defined as the sum of the squared intra-daily returns stamped on some high frequency basis has spurred the research in the field of volatility modeling and forecasting into new directions. First, the realized variance is a much better...

In this paper we discuss the current state-of-the-art in estimating, evaluating, and selecting among non-linear forecasting models for economic and financial time series. We review theoretical and empirical issues, including predictive density, interval and point evaluation and model selection,...

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Forecasters and applied econometricians are often interested in comparing the predictive accuracy of nested competing models. A leading example of nestedness is when predictive ability is equated with ?out-of-sample Granger causality?. In particular, it is often of interest to assess whether...