Macroeconomics

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.

Your contact

Professor Dr Oliver Holtemöller
Professor Dr Oliver Holtemöller
Leiter - Department Macroeconomics
Send Message +49 345 7753-800 Personal page

Refereed Publications

Alternatives to GDP - Measuring the Impact of Natural Disasters using Panel Data

Jörg Döpke Philip Maschke

in: Journal of Economic and Social Measurement , No. 3, 2016

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Impulse Response Analysis in a Misspecified DSGE Model: A Comparison of Full and Limited Information Techniques

Sebastian Giesen Rolf Scheufele

in: Applied Economics Letters , No. 3, 2016

Abstract

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.

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Global Food Prices and Monetary Policy in an Emerging Market Economy: The Case of India

Oliver Holtemöller Sushanta Mallick

in: Journal of Asian Economics , 2016

Abstract

This paper investigates a perception in the political debates as to what extent poor countries are affected by price movements in the global commodity markets. To test this perception, we use the case of India to establish in a standard SVAR model that global food prices influence aggregate prices and food prices in India. To further analyze these empirical results, we specify a small open economy New-Keynesian model including oil and food prices and estimate it using observed data over the period 1996Q2 to 2013Q2 by applying Bayesian estimation techniques. The results suggest that a big part of the variation in inflation in India is due to cost-push shocks and, mainly during the years 2008 and 2010, also to global food price shocks, after having controlled for exogenous rainfall shocks. We conclude that the inflationary supply shocks (cost-push, oil price, domestic food price and global food price shocks) are important contributors to inflation in India. Since the monetary authority responds to these supply shocks with a higher interest rate which tends to slow growth, this raises concerns about how such output losses can be prevented by reducing exposure to commodity price shocks. 

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Monetary-Fiscal Policy Interaction and Fiscal Inflation: A Tale of Three Countries

Martin Kliem Alexander Kriwoluzky Samad Sarferaz

in: European Economic Review , 2016

Abstract

We study the impact of the interaction between fiscal and monetary policy on the low-frequency relationship between the fiscal stance and inflation using cross-country data from 1965 to 1999. In a first step, we contrast the monetary–fiscal narrative for Germany, the U.S., and Italy with evidence obtained from simple regression models and a time-varying VAR. We find that the low-frequency relationship between the fiscal stance and inflation is low during periods of an independent central bank and responsible fiscal policy and more pronounced in times of non-responsible fiscal policy and accommodative monetary authorities. In a second step, we use an estimated DSGE model to interpret the low-frequency measure structurally and to illustrate the mechanisms through which fiscal actions affect inflation in the long run. The findings from the DSGE model suggest that switches in the monetary–fiscal policy interaction and accompanying variations in the propagation of structural shocks can well account for changes in the low-frequency relationship between the fiscal stance and inflation.

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Mapping Potentials for Input-Output Based Innovation Flows in Industrial Clusters – An Application to Germany

Mirko Titze Matthias Brachert Hans-Ulrich Brautzsch

in: Economic Systems Research , No. 4, 2016

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Working Papers

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Bracket Creeps: Bane or Boon for the Stability of Numerical Budget Rules?

Martin Altemeyer-Bartscher Götz Zeddies

in: IWH Discussion Papers , No. 29, 2016

Abstract

As taxpayers typically pay relatively low attention to a small inflation-induced bracket creep of the income tax, policy-makers tend to postpone its correction into the future. However, the fiscal illusion fades away and political pressure for a tax relief arises since after some years, the cumulative increase of the average tax rate exceeds a critical threshold. Using Germany as an example, this paper shows that bracket creeps can provoke revenue cycles in public budgets hindering governments‘ compliance with the numerical budget rules. An indexation of the tax tariff, which provides an automatic correction of the bracket creep could prevent such fluctuations and thus provides a favorable framework for the debt rule.

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Should Forecasters Use Real-time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence

Katja Heinisch Rolf Scheufele

in: IWH Discussion Papers , No. 5, 2017

Abstract

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.

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The European Refugee Crisis and the Natural Rate of Output

Katja Heinisch Klaus Wohlrabe

in: IWH Discussion Papers , No. 30, 2016

Abstract

The European Commission follows a harmonized approach for calculating structural (potential) output for EU member states that takes into account labor as an important ingredient. This paper 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 labor 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 modeled adequately compared to results based on the unadjusted European Commission procedure.

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Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After?

Peter Sarlin Gregor von Schweinitz

in: ECB Working Paper Series , No. 2025, 2017

Abstract

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.

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Why They Keep Missing: An Empirical Investigation of Rational Inattention of Rating Agencies

Gregor von Schweinitz Makram El-Shagi

in: IWH Discussion Papers , No. 1, 2017

Abstract

Although there is a wide consensus that rating agencies have frequently failed to predict major crises, the literature on sovereign ratings has so far mostly focused on explaining the rating level rather than explaining the timing of the rating decision. In this paper we aim to fill this gap in the literature. Moreover, we go beyond the previous literature by explicitly differentiating between a decision to assess a country and the actual rating decision. Thereby, we take rational inattention of rating agencies into account that should exist due to the cognitive and informational costs of a reassessment. Exploiting information of rating announcements, we can show that (i) the differentiation between the two decision processes significantly improves the model explaining rating decisions; (ii) rating agencies take many nonfundamental factors in their decision to reassess a country into account; (iii) markets only react to ratings if these ratings supply genuinely new information; and (iv) that developed country get preferential treatment.

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