25 Years IWH

Econometric Tools for Macroeconomic Forecasting

This research group belongs to the IWH Research Cluster Macroeconomic Dynamics and Stability. The aim of this group is to enhance research on, and development, implementation, evaluation, and application of quantitative macroeconometric models for forecasting and analysing aggregate economic fluctuations and developments. Research in this group contributes to the econometric foundation and the methodological improvements of the IWH forecasts. During the last years, the IWH has highly specialised in macroeconomic modelling, both for flash estimates and medium-term projections. Furthermore, this group conducts comprehensive empirical analysis and develops econometric tools that are used for third-party funded projects. In the last years, particular models have been developed for e.g. Volkswagen Financial Services AG and for GIZ. The research group contributed in particular on macroeconomic modelling for ministries in Kyrgyzstan and Tajikistan as well as for the institute of forecasting and macroeconomic research (IFMR) Uzbekistan.

IWH Data Project: IWH Real-time Database

Research Cluster
Macroeconomic Dynamics and Stability

Your contact

Dr Katja Heinisch
Dr Katja Heinisch
Mitglied - Department Macroeconomics
Send Message +49 345 7753-836

EXTERNAL FUNDING

11.2015 ‐ 12.2016

Employment and Development in the Republic of Uzbekistan

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Support to sustainable economic development in selected regions of Uzbekistan

Dr Katja Heinisch

05.2016 ‐ 05.2016

Framework and Finance for Private Sector Development in Tajikistan

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Dr Katja Heinisch

07.2016 ‐ 12.2017

Climate Protection and Coal Phaseout: Political Strategies and Measures up to 2030 and beyond

Umweltbundesamt (UBA)

Dr Katja Heinisch

02.2016 ‐ 04.2016

Macroeconomic Reforms and Green Growth - Assessment of economic modelling capacity in Vietnam

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Dr Katja Heinisch

Refereed Publications

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On DSGE Models

Lawrence J. Christiano Martin S. Eichenbaum Mathias Trabandt

in: Journal of Economic Perspectives , forthcoming

Abstract

Macroeconomic policy questions involve trade-o s between competing forces in the economy. The problem is how to assess the strength of those forces for the particular policy question at hand. DSGE models are the leading framework that macroeconomists have for dealing with this problem in an open and transparent manner. This paper reviews the state of DSGE models before the financial crisis and how DSGE modelers have responded to the crisis and its aftermath. In addition, we discuss the role of DSGE models in the policy process.

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Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment

Katja Heinisch Rolf Scheufele

in: Empirical Economics , forthcoming

Abstract

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.

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Should We Use Linearized Models To Calculate Fiscal Multipliers?

Jesper Lindé Mathias Trabandt

in: Journal of Applied Econometrics , forthcoming

Abstract

We calculate the magnitude of the government consumption multiplier in linearized and nonlinear solutions of a New Keynesian model at the zero lower bound. Importantly, the model is amended with real rigidities to simultaneously account for the macroeconomic evidence of a low Phillips curve slope and the microeconomic evidence of frequent price changes. We show that the nonlinear solution is associated with a much smaller multiplier than the linearized solution in long-lived liquidity traps, and pin down the key features in the model which account for the di¤erence. Our results caution against the common practice of using linearized models to calculate scal multipliers in long-lived liquidity traps.

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The European Refugee Crisis and the Natural Rate of Output

Katja Heinisch Klaus Wohlrabe

in: Applied Economics Letters , No. 16, 2017

Abstract

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.

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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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Working Papers

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Progressive Tax-like Effects of Inflation: Fact or Myth? The U.S. Post-war Experience

Matthias Wieschemeyer Bernd Süssmuth

in: IWH Discussion Papers , No. 33, 2017

Abstract

Inflation and earnings growth can push some tax payers into higher brackets in the absence of inflation-indexed schedules. Moreover, inflation may affect the composition of individuals’ income sources. As a result, depending on the relative tax burden of labour and capital, inflation may decrease or increase the difference between before-tax and after-tax income. However, whether some and if so which percentiles of the income distribution net benefit from inflation via taxation is a widely unexplored question. We make use of a novel dataset on U.S. pre-tax and post-tax income distribution series provided by Pike ty et al. (2018) for the years 1962 to 2014 to answer this question. To this end, we estimate local projections to quantify dynamic effects. We find that inflation shocks increase progressivity of taxation not only contemporaneously but also with some repercussion of several years after the shock. While particularly the bottom two quintiles gain in share, it is not the top but the fourth quintile that lastingly loses.

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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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Outperforming IMF Forecasts by the Use of Leading Indicators

Katja Drechsel Sebastian Giesen Axel Lindner

in: IWH Discussion Papers , No. 4, 2014

Abstract

This study analyzes the performance of the IMF World Economic Outlook forecasts for world output and the aggregates of both the advanced economies and the emerging and developing economies. With a focus on the forecast for the current and the next year, we examine whether IMF forecasts can be improved by using leading indicators with monthly updates. Using a real-time dataset for GDP and for the indicators we find that some simple single-indicator forecasts on the basis of data that are available at higher frequency can significantly outperform the IMF forecasts if the publication of the Outlook is only a few months old.

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Effects of Incorrect Specification on the Finite Sample Properties of Full and Limited Information Estimators in DSGE Models

Sebastian Giesen Rolf Scheufele

in: IWH Discussion Papers , No. 8, 2013

Abstract

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 parameters 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.

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