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.

We calculate the magnitude of the government consumption multiplier in linearized and nonlinear solutions of a New Keynesian model at the zero lower bound. Importantly, the model is amended with real rigidities to simultaneously account for the macroeconomic evidence of a low Phillips curve slope and the microeconomic evidence of frequent price changes. We show that the nonlinear solution is associated with a much smaller multiplier than the linearized solution in long‐lived liquidity traps, and pin down the key features in the model which account for the difference. Our results caution against the common practice of using linearized models to calculate fiscal multipliers in long‐lived liquidity traps.

The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policymakers is how to assess the relative strength of those forces. Economists have a range of tools that can be used to make such assessments. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. We review the state of mainstream DSGE models before the financial crisis and the Great Recession. We then describe how DSGE models are estimated and evaluated. We address the question of why DSGE modelers—like most other economists and policymakers—failed to predict the financial crisis and the Great Recession, and how DSGE modelers responded to the financial crisis and its aftermath. We discuss how current DSGE models are actually used by policymakers. We then provide a brief response to some criticisms of DSGE models, with special emphasis on criticism by Joseph Stiglitz, and offer some concluding remarks.

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.