The department of macroeconomics analyses economic fluctuations of important economic indicators as GDP, employment, and interest rates in the short and medium horizon, the impact of economic policy on these, and the institutional framework that determines long term growth and the business cycle. Founded on this research, the department offers policy advice.
Employing 20 experts, the department covers a wide range of macroeconomic issues. The research focuses on development, implementation and application of quantitative macroeconomic models and the analysis of the interaction between the financial markets and the real economy.
The out of sample performance of leading indicators for the German business cycle. Single vs combined forecasts
in: Journal of Business Cycle Measurement and Analysis , forthcomingread publication
Property networks of corporations as cause of abusive behaviour – A stock market analysis based on institutional economics
in: Applied Financial Economics Letters , forthcomingread publication
Continuity and Continuousness: The Chain of Ideas Linking Peirce’s Synechism with Veblen’s Cumulative Causation
in: Journal of Economic Issues , forthcomingread publication
Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment
in: Empirical Economics , forthcoming
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 Refugee Crisis and the Natural Rate of Output
in: Applied Economics Letters , forthcoming
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.
U.S. Monetary-Fiscal Regime Changes in the Presence of Endogenous Feedback in Policy Rules
in: IWH Discussion Papers , No. 15, 2017
We investigate U.S. monetary and fiscal policy regime interactions in a model, where regimes are determined by latent autoregressive policy factors with endogenous feedback. Policy regimes interact strongly: Shocks that switch one policy from active to passive tend to induce the other policy to switch from passive to active, consistently with existence of a unique equilibrium, though both policies are active and government debt grows rapidly in some periods. We observe relatively strong interactions between monetary and fiscal policy regimes after the recent financial crisis. Finally, latent policy regime factors exhibit patterns of correlation with macroeconomic time series, suggesting that policy regime change is endogenous.
Monetary Policy in an Oil-dependent Economy in the Presence of Multiple Shocks
in: IWH Discussion Papers , No. 14, 2017
Russian monetary policy has been challenged by large and continuous private capital outflows and a sharp drop in oil prices during 2014, with both ongoings having put a significant depreciation pressure on the ruble and having led the central bank to eventually give up its exchange rate management strategy. Against this background, this paper estimates a small open economy model for Russia, featuring an oil price sector and extended by a specification of the foreign exchange market to correctly account for systematic central bank interventions. We find that shocks to the oil price and private capital flows substantially affect domestic variables such as inflation, output and the exchange rate. Simulations of the model for the estimated actual strategy and five alternative regimes suggest that the vulnerability of the Russian economy to external shocks can substantially be lowered by adopting some form of an inflation targeting strategy. Foreign exchange intervention-based policy strategies to target the nominal exchange rate or the ruble price of oil, on the other hand, prove inferior to the policy in place.
Should Forecasters Use Real-time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence
in: IWH Discussion Papers , No. 5, 2017
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 survey 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.
Same, but Different: Testing Monetary Policy Shock Measures
in: IWH Discussion Papers , No. 9, 2017
In this study, we test whether three popular measures for monetary policy, that is, Romer and Romer (2004), Barakchian and Crowe (2013), and Gertler and Karadi (2015), constitute suitable proxy variables for monetary policy shocks. To this end, we employ different test statistics used in the literature to detect weak proxy variables. We find that the measure derived by Gertler and Karadi (2015) is the most suitable in this regard.
Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After?
in: ECB Working Paper Series , No. 2025, 2017
Early-warning models most commonly optimize signaling thresholds on crisis probabilities. The expost threshold optimization is based upon a loss function accounting for preferences between forecast errors, but comes with two crucial drawbacks: unstable thresholds in recursive estimations and an in-sample overfit at the expense of out-of-sample performance. We propose two alternatives for threshold setting: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. Given probabilistic model output, it is intuitive that a decision rule is independent of the data or model specification, as thresholds on probabilities represent a willingness to issue a false alarm vis-à-vis missing a crisis. We provide simulated and real-world evidence that this simplification results in stable thresholds and improves out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.