In der Abteilung Makroökonomik werden kurz- und mittelfristige Schwankungen gesamtwirtschaftlicher Variablen (zum Beispiel des Bruttoinlandsprodukts, der Beschäftigung, der Preise und der Zinsen), die Wirkungen wirtschaftspolitischer Maßnahmen auf diese Größen und die institutionellen Rahmenbedingungen für Konjunktur und langfristiges Wirtschaftswachstum erforscht. Auf Basis dieser Forschung bietet die Abteilung wissenschaftlich fundierte und evidenzbasierte wirtschaftspolitische Beratung an.
Mit ihren etwa 20 Mitarbeiterinnen und Mitarbeitern kann die Abteilung ein breites Spektrum makroökonomischer Fragestellungen abdecken. Die Forschungsschwerpunkte liegen in der Entwicklung, Implementierung und Anwendung quantitativer makroökonomischer Modelle sowie in der Analyse der Interaktion von Finanzsystem und realwirtschaftlicher Entwicklung.
Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information
in: Econometrica, im Erscheinen
This paper makes the following original contributions to the literature. (i) We develop a simpler analytical characterization and numerical algorithm for Bayesian inference in structural vector autoregressions (VARs) that can be used for models that are overidentified, just‐identified, or underidentified. (ii) We analyze the asymptotic properties of Bayesian inference and show that in the underidentified case, the asymptotic posterior distribution of contemporaneous coefficients in an n‐variable VAR is confined to the set of values that orthogonalize the population variance–covariance matrix of ordinary least squares residuals, with the height of the posterior proportional to the height of the prior at any point within that set. For example, in a bivariate VAR for supply and demand identified solely by sign restrictions, if the population correlation between the VAR residuals is positive, then even if one has available an infinite sample of data, any inference about the demand elasticity is coming exclusively from the prior distribution. (iii) We provide analytical characterizations of the informative prior distributions for impulse‐response functions that are implicit in the traditional sign‐restriction approach to VARs, and we note, as a special case of result (ii), that the influence of these priors does not vanish asymptotically. (iv) We illustrate how Bayesian inference with informative priors can be both a strict generalization and an unambiguous improvement over frequentist inference in just‐identified models. (v) We propose that researchers need to explicitly acknowledge and defend the role of prior beliefs in influencing structural conclusions and we illustrate how this could be done using a simple model of the U.S. labor market.
Does Machine Learning Help us Predict Banking Crises?
in: Journal of Financial Stability, im ErscheinenPublikation lesen
Nowcasting East German GDP Growth: a MIDAS Approach
in: Empirical Economics, im Erscheinen
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.
Banks’ Funding Stress, Lending Supply and Consumption Expenditure
in: Journal of Money, Credit and Banking, im Erscheinen
We employ a unique identification strategy linking survey data on household consumption expenditure to bank‐level data to estimate the effects of bank funding stress on consumer credit and consumption expenditures. We show that households whose banks were more exposed to funding shocks report lower levels of nonmortgage liabilities. This, however, only translates into lower levels of consumption for low‐income households. Hence, adverse credit supply shocks are associated with significant heterogeneous effects.
The Appropriateness of the Macroeconomic Imbalance Procedure for Central and Eastern European Countries
in: Empirica, im Erscheinen
The European Commission’s Scoreboard of Macroeconomic Imbalances is a rare case of a publicly released early warning system. It was published first time in 2012 by the European Commission as a reaction to public debt crises in Europe. So far, the Macroeconomic Imbalance Procedure takes a one-size-fits-all approach with regard to the identification of thresholds. The experience of Central and Eastern European Countries during the global financial crisis and in the resulting public debt crises has been largely different from that of other European countries. This paper looks at the appropriateness of scoreboard of the Macroeconomic Imbalances Procedure of the European Commission for this group of catching-up countries. It is shown that while some of the indicators of the scoreboard are helpful to predict crises in the region, thresholds are in most cases set too narrow since it largely disregarded the specifics of catching-up economies, in particular higher and more volatile growth rates of various macroeconomic variables.
Drawing Conclusions from Structural Vector Autoregressions Identified on the Basis of Sign Restrictions
in: NBER Working Paper No. 26606, 2020
This paper discusses the problems associated with using information about the signs of certain magnitudes as a basis for drawing structural conclusions in vector autoregressions. We also review available tools to solve these problems. For illustration we use Dahlhaus and Vasishtha's (2019) study of the effects of a U.S. monetary contraction on capital flows to emerging markets. We explain why sign restrictions alone are not enough to allow us to answer the question and suggest alternative approaches that could be used.
Why is Unemployment so Countercyclical?
in: NBER Working Paper No. 26723, 2020
We argue that wage inertia plays a pivotal role in allowing empirically plausible variants of the standard search and matching model to account for the large countercyclical response of unemployment to shocks.
Flight from Safety: How a Change to the Deposit Insurance Limit Affects Households‘ Portfolio Allocation
in: IWH-Diskussionspapiere, Nr. 19, 2019
We study how an increase to the deposit insurance limit affects households‘ portfolio allocation by exogenously reducing uninsured deposit balances. Using unique data that identifies insured versus uninsured deposits, along with detailed information on Canadian households‘ portfolio holdings, we show that households respond by drawing down deposits and shifting towards mutual funds and stocks. These outflows amount to 2.8% of outstanding bank deposits. The empirical evidence, consistent with a standard portfolio choice model that is modified to accommodate uninsured deposits, indicates that more generous deposit insurance coverage results in nontrivial adjustments to household portfolios.
How Forecast Accuracy Depends on Conditioning Assumptions
in: IWH-Diskussionspapiere, Nr. 18, 2019
This paper examines the extent to which errors in economic forecasts are driven by initial assumptions that prove to be incorrect ex post. Therefore, we construct a new data set comprising an unbalanced panel of annual forecasts from different institutions forecasting German GDP and the underlying assumptions. We explicitly control for different forecast horizons to proxy the information available at the release date. Over 75% of squared errors of the GDP forecast comove with the squared errors in their underlying assumptions. The root mean squared forecast error for GDP in our regression sample of 1.52% could be reduced to 1.13% by setting all assumption errors to zero. This implies that the accuracy of the assumptions is of great importance and that forecasters should reveal the framework of their assumptions in order to obtain useful policy recommendations based on economic forecasts.
Power Generation and Structural Change: Quantifying Economic Effects of the Coal Phase-out in Germany
in: IWH-Diskussionspapiere, Nr. 16, 2019
In the fight against global warming, the reduction of greenhouse gas emissions is a major objective. In particular, a decrease in electricity generation by coal could contribute to reducing CO2 emissions. Using a multi-region dynamic general equilibrium model, this paper studies potential economic consequences of a coal phase-out in Germany. Different regional phase-out scenarios are simulated with varying timing structures. We find that a politically induced coal phase-out would lead to an increase in the national unemployment rate by about 0.10 percentage points from 2020 to 2040, depending on the specific scenario. The effect on regional unemployment rates varies between 0.18 to 1.07 percentage points in the lignite regions. However, a faster coal phase-out can lead to a faster recovery. The coal phase-out leads to migration from German lignite regions to German non-lignite regions and reduces the labour force in the lignite regions by 10,000 people by 2040.