The present study examines the consequences of the planned coal phase-out in Germany according to various phase-out pathways that differ in the ordering of power plant closures. Soft-linking an energy system model with an input-output model and a regional macroeconomic model simulates the socio-economic effects of the phase-out in the lignite regions, as well as in the rest of Germany. The combination of two economic models offers the advantage of considering the phase-out from different perspectives and thus assessing the robustness of the results. The model results show that the lignite coal regions will exhibit losses in output, income and population, but a faster phase-out would lead to a quicker recovery. Migration to other areas in Germany and demographic changes will partially compensate for increasing unemployment, but support from federal policy is also necessary to support structural change in these regions.

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 are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.

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 surveys and financial data relative to industrial production and orders in Germany. Although we find evidence that forecast characteristics based on real‐time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator models. However, when obtaining the optimal combination of soft and hard data, the use of final release data may understate the role of survey information.

In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features, such as price and wage rigidities, contribute to forecasting performance. It turns out that neither alternative expectation formation behaviour nor financial frictions can systematically increase the forecasting performance of basic DSGE models. Financial frictions improve forecasts only during periods of financial crises. However, traditional price and wage rigidities systematically help to increase the forecasting performance.

This study analyses the performance of the International Monetary Fund (IMF) World Economic Outlook output forecasts for the world and for both the advanced economies and the emerging and developing economies. With a focus on the forecast for the current year and the next year, we examine the durability of IMF forecasts, looking at how much time has to pass so that IMF forecasts can be improved by using leading indicators with monthly updates. Using a real-time data set for GDP and for indicators, we find that some simple single-indicator forecasts on the basis of data that are available at higher frequency can significantly outperform the IMF forecasts as soon as the publication of the IMF’s Outlook is only a few months old. In particular, there is an obvious gain using leading indicators from January to March for the forecast of the current year.

In dem vorliegenden Aufsatz werden (a) Umfang und Struktur der vorhandenen Arbeitsplätze nach Geschlechtern in Ost- und Westdeutschland, (b) das geschlechtsspezifische Ausmaß der „Arbeitplatzlücke“ in beiden Großregionen sowie (c) die Ursachen für die – gemessen an Westdeutschland – höhere „Arbeitsplatzlücke“ in Ostdeutschland auf der Grundlage von Daten der Regionalen Volkswirtschaftlichen Gesamtrechnungen und der Bundesgentur für Arbeit untersucht. Die Analyse zeigt, dass im Jahr 2003 die „Arbeitsplatzausstattung“ je 1000 Erwerbsfähigen in Ostdeutschland fast genau so hoch war wie in Westdeutschland. Bei den Frauen lag sie sogar über dem westdeutschen Vergleichswert. Dennoch ist die Diskrepanz zwischen dem Arbeitsangebot und der Nachfrage bei den ostdeutschen Frauen und Männern erheblich größer. Dies ist zum einen auf strukturelle Ursachen und zum anderen auf die höhere Erwerbsneigung der ostdeutschen Frauen zurückzuführen, die insbesonde durch das tradierte Verhaltensmuster nach Erwerbsarbeit sowie die geringeren Haushalteinkommen in Ostdeutschland bedingt ist.