Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany...

This paper discusses the forecasting performance of alternative factor models based on a large panel of quarterly time series for the German economy. One model extracts factors by static principal components analysis; the second model is based on dynamic principal components obtained using...

This paper discusses the forecasting performance of alternative factor models based on a large panel of quarterly time series for the german economy. One model extracts factors by static principals components analysis, the other is based on dynamic principal components obtained using frequency...

In this paper we investigate whether differences exist among forecasts using real-time or latest-available data to predict gross domestic product (GDP). We employ mixed-frequency models and real-time data to reassess the role of survey data relative to industrial production and orders in...

The world economy has been struck by Covid-19 the same way people are struck by a lightning, fast and without warning, leaving nations out to dry on little to no reserves on their crucial supply side. Consequently, over the past year, economies shrunk, production drastically diminished, and...

We evaluate the informational content of news-based sentiment indicators for forecasting the Gross Domestic Product (GDP) of the five major European economies. The sentiment indicators that we construct are aspect-based, in the sense that we consider only the text that is related to a specific...

Using quarterly data for the Federal Republic of Germany, we generate four-quarter-ahead forecasts for real GDP growth. Throughout the seventies and eighties, real M1 is still the best predictor. It clearly outperforms interest rate-based forecasts, and within this group short-run interest rates...

The importance of solar energy has been growing in recent years. This raises the need for efficient modelling and forecasting methods. The existing methods are predominantly based on weather predictions or forecast solar radiation, which is not easy to convert into production forecast. Instead...

In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an...