Fiscal spending multiplier calculations have attracted considerable attention in the aftermath of the global financial crisis. Much of the current literature is based on VAR estimation methods and DSGE models. In line with the Keynesian literature we argue that many of these models probably underestimate the fiscal spending multiplier in recessions. The income-expenditure model of the fiscal spending multiplier can be seen as a good approximation under these circumstances. In its conventional form this model suffers from an underestimation of the multiplier due to an overestimation of the import intake of domestic absorption. In this article we apply input-output calculus to solve this problem. Multipliers thus derived are comparably high, ranging between 1.4 and 1.8 for many member states of the European Union. GDP drops due to budget consolidation might therefore be substantial in times of crisis.

In this paper we develop an open economy model explaining the joint determination of output, inflation, interest rates, unemployment and the exchange rate in a multi-country framework. Our model -- the Halle Economic Projection Model (HEPM) -- is closely related to studies published by Carabenciov et al. Our main contribution is that we model the Euro area countries separately. In doing so, we consider Germany, France, and Italy which represent together about 70 percent of Euro area GDP. The model combines core equations of the New-Keynesian standard DSGE model with empirically useful ad-hoc equations. We estimate this model using Bayesian techniques and evaluate the forecasting properties. Additionally, we provide an impulse response analysis and a historical shock decomposition.

The paper analyzes the forecasting performance of leading indicators for industrial production in Germany. We focus on single and pooled leading indicator models both before and during the financial crisis. Pairwise and joint significant tests are used to evaluate single indicator models as well as forecast combination methods. In addition, we investigate the stability of forecasting models during the most recent financial crisis.

This paper analyses the recession in 2008/2009 in Germany. This recession is very different from previous recessions in particular regarding their causes and magnitude. We show to what extent forecasters and forecasts based on leading indicators fail to detect the timing and the magnitude of the recession. This study shows that large forecast errors for both expert forecasts and forecasts based on leading indicators resulted during this recession which implies that the recession was very difficult to forecast. However, some leading indicators (survey data, risk spreads, stock prices) have indicated an economic downturn and hence, beat univariate time series models. Although the combination of individual forecasts provides an improvement compared to the benchmark model, the combined forecasts are worse than several individual models. A comparison of expert forecasts withthe best forecasts based on leading indicators shows only minor deviations. Overall, the range for an improvement of expert forecasts in the crisis compared to indicator forecasts is small.

We develop an evolutionary algorithm to estimate Threshold Vector Error Correction models (TVECM) with more than two cointegrated variables. Since disregarding a threshold in cointegration models renders standard approaches to the estimation of the cointegration vectors inefficient, TVECM necessitate a simultaneous estimation of the cointegration vector(s) and the threshold. As far as two cointegrated variables are considered, this is commonly achieved by a grid search. However, grid search quickly becomes computationally unfeasible if more than two variables are cointegrated. Therefore, the likelihood function has to be maximized using heuristic approaches. Depending on the precise problem structure the evolutionary approach developed in the present paper for this purpose saves 90 to 99 per cent of the computation time of a grid search.

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.