In this paper, we investigate whether there are benefits in disaggregating GDP into its components when nowcasting GDP. To answer this question, we conduct a realistic out-of-sample experiment that deals with the most prominent problems in short-term forecasting: mixed frequencies, ragged-edge data, asynchronous data releases and a large set of potential information. We compare a direct leading indicator-based GDP forecast with two bottom-up procedures—that is, forecasting GDP components from the production side or from the demand side. Generally, we find that the direct forecast performs relatively well. Among the disaggregated procedures, the production side seems to be better suited than the demand side to form a disaggregated GDP nowcast.

The European Commission follows a harmonized approach for calculating structural (potential) output for EU member states that takes into account labour as an important ingredient. This article shows how the recent huge migrants’ inflow to Europe affects trend output. Due to the fact that the immigrants immediately increase the working population but effectively do not enter the labour market, we illustrate that the potential output is potentially upward biased without any corrections. Taking Germany as an example, we find that the average medium-term potential growth rate is lower if the migration flow is modelled adequately compared to results based on the unadjusted European Commission procedure.

In this article, we examine the effect of estimation biases – introduced by model misspecification – on the impulse responses analysis for dynamic stochastic general equilibrium (DSGE) models. Thereby, we use full and limited information estimators to estimate a misspecified DSGE model and calculate impulse response functions (IRFs) based on the estimated structural parameters. It turns out that IRFs based on full information techniques can be unreliable under misspecification.

In this paper we analyze the small sample properties of full information and limited information estimators in a potentially misspecified DSGE model. Therefore, we conduct a simulation study based on a standard New Keynesian model including price and wage rigidities. We then study the effects of omitted variable problems on the structural parameter estimates of the model. We find that FIML performs superior when the model is correctly specified. In cases where some of the model characteristics are omitted, the performance of FIML is highly unreliable, whereas GMM estimates remain approximately unbiased and significance tests are mostly reliable.

This paper analyzes the role of common data problems when identifying structural breaks in small samples. Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown et al. (J R Stat Soc B 37:149–163, 1975) and Zeileis (Stat Pap 45(1):123–131, 2004), Nyblom (J Am Stat Assoc 84(405):223–230, 1989) and Hansen (J Policy Model 14(4):517–533, 1992), and Andrews et al. (J Econ 70(1):9–38, 1996). Power and size properties are derived using Monte Carlo simulations. We find that the Nyblom test is on par with the commonly used F type tests in a small sample in terms of power. While the Nyblom test’s power decreases if the structural break occurs close to the margin of the sample, it proves far more robust to nonnormal distributions of the error term that are found to matter strongly in small samples although being irrelevant asymptotically for all tests that are analyzed in this paper.

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.