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.
Alternatives to GDP - Measuring the Impact of Natural Disasters using Panel Data
in: Journal of Economic and Social Measurement , No. 3, 2016
A frequent criticism of GDP states that events that obviously reduce welfare of people can nevertheless increase GDP per capita. We use data of natural disasters as quasi experiments to examine whether alternatives to GDP (Human Development Index, Progress Index, Index of Economic Well-Being and a Happiness Index) lead to more plausible responses to disasters. Applying a Differences-in-Differences approach and estimates from various panels of countries we find no noteworthy differences between the response of real GDP per capita and the responses of suggested alternative welfare measures to a natural disaster except for the Human Development Index.
Impulse Response Analysis in a Misspecified DSGE Model: A Comparison of Full and Limited Information Techniques
in: Applied Economics Letters , No. 3, 2016
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.
Global Food Prices and Monetary Policy in an Emerging Market Economy: The Case of India
in: Journal of Asian Economics , 2016
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.&nbsp;
Monetary-Fiscal Policy Interaction and Fiscal Inflation: A Tale of Three Countries
in: European Economic Review , 2016
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.
Mapping Potentials for Input-Output Based Innovation Flows in Industrial Clusters – An Application to Germany
in: Economic Systems Research , No. 4, 2016
Our paper pursues two aims: first, it presents an approach based on input–output innovation flow matrices to study intersectoral innovation flows within industrial clusters. Second, we apply this approach to the identification of structural weaknesses in East Germany relative to the western part of the country. The case of East Germany forms an interesting subject because while its convergence process after unification began promisingly in the first half of the 1990s, convergence has since slowed down. The existing gap can now be traced mainly to structural weaknesses in the East German economy, such as the absence of strong industrial cluster structures. With this in mind, we investigate whether East Germany does in fact reveal the abovementioned structural weaknesses. Does East Germany possess fewer industrial clusters? Are they less connected? Does East Germany lack specific clusters that are also important for the non-clustered part of the economy?
Bracket Creeps: Bane or Boon for the Stability of Numerical Budget Rules?
in: IWH Discussion Papers , No. 29, 2016
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.
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.
Why They Keep Missing: An Empirical Investigation of Rational Inattention of Rating Agencies
in: IWH Discussion Papers , No. 1, 2017
Sovereign ratings have frequently failed to predict crises. However, the literature has focused on explaining rating levels rather than the timing of rating announcements. We fill this gap by explicitly differentiating between a decision to assess a country and the actual rating decision. Thereby, we account for rational inattention of rating agencies that exists due to costs of reassessment. Exploiting information of rating announcements, we show that (i) the proposed differentiation significantly improves estimation; (ii) rating agencies consider many nonfundamental factors in their reassessment decision; (iii) markets only react to ratings providing new information; (iv) developed countries get preferential treatment.