Econometric Tools for Macroeconomic Forecasting and Simulation

The aim of this research 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

05.2020 ‐ 04.2023

ENTRANCES: Energy Transitions from Coal and Carbon: Effects on Societies

European Commission

ENTRANCES aims at examining the effects of the coal phase-out in Europe. How does the phase-out transform society – and what can politics do about it?

IWH project page

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 883947.

Professor Dr Oliver Holtemöller
Dr Katja Heinisch

01.2018 ‐ 12.2023

EuropeAid (EU Framework Contract)

European Commission

Professor Dr Oliver Holtemöller

07.2016 ‐ 12.2018

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

Umweltbundesamt (UBA)

Dr Katja Heinisch

01.2017 ‐ 12.2017

Support to Sustainable Economic Development in Selected Regions of Uzbekistan

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Dr Andrej Drygalla

01.2017 ‐ 12.2017

Short-term Macroeconomic Forecasting Model in Ministry of Economic Development and Trade of Ukraine

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Dr Andrej Drygalla

01.2016 ‐ 12.2017

Development of analytical tools based on Input-Output table

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

The aim of the project was the development of an analytical tool to assess the gains and losses of possible state programs supporting the development of the private sector of the Tajik economy.

Dr Katja Heinisch

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

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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Coal Phase-out in Germany – Implications and Policies for Affected Regions

Pao-Yu Oei Hauke Hermann Philipp Herpich Oliver Holtemöller Benjamin Lünenburger Christoph Schult

in: Energy, April 2020

Abstract

The present study examines the consequences of the planned coal phase-out in Germany according to various phase-out pathways that differ in the ordering of power plant closures. Soft-linking an energy system model with an input-output model and a regional macroeconomic model simulates the socio-economic effects of the phase-out in the lignite regions, as well as in the rest of Germany. The combination of two economic models offers the advantage of considering the phase-out from different perspectives and thus assessing the robustness of the results. The model results show that the lignite coal regions will exhibit losses in output, income and population, but a faster phase-out would lead to a quicker recovery. Migration to other areas in Germany and demographic changes will partially compensate for increasing unemployment, but support from federal policy is also necessary to support structural change in these regions.

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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: German Economic Review, No. 4, 2019

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 surveys and financial 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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Expectation Formation, Financial Frictions, and Forecasting Performance of Dynamic Stochastic General Equilibrium Models

Oliver Holtemöller Christoph Schult

in: Historical Social Research, No. 2, Special Issue: Governing by Numbers 2019

Abstract

In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features, such as price and wage rigidities, contribute to forecasting performance. It turns out that neither alternative expectation formation behaviour nor financial frictions can systematically increase the forecasting performance of basic DSGE models. Financial frictions improve forecasts only during periods of financial crises. However, traditional price and wage rigidities systematically help to increase the forecasting performance.

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For How Long Do IMF Forecasts of World Economic Growth Stay Up-to-date?

Katja Heinisch Axel Lindner

in: Applied Economics Letters, No. 3, 2019

Abstract

This study analyses the performance of the International Monetary Fund (IMF) World Economic Outlook output forecasts for the world and for both the advanced economies and the emerging and developing economies. With a focus on the forecast for the current year and the next year, we examine the durability of IMF forecasts, looking at how much time has to pass so that IMF forecasts can be improved by using leading indicators with monthly updates. Using a real-time data set for GDP and for 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 as soon as the publication of the IMF’s Outlook is only a few months old. In particular, there is an obvious gain using leading indicators from January to March for the forecast of the current year.

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On DSGE Models

Lawrence J. Christiano Martin S. Eichenbaum Mathias Trabandt

in: Journal of Economic Perspectives, No. 3, 2018

Abstract

The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policymakers is how to assess the relative strength of those forces. Economists have a range of tools that can be used to make such assessments. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. We review the state of mainstream DSGE models before the financial crisis and the Great Recession. We then describe how DSGE models are estimated and evaluated. We address the question of why DSGE modelers—like most other economists and policymakers—failed to predict the financial crisis and the Great Recession, and how DSGE modelers responded to the financial crisis and its aftermath. We discuss how current DSGE models are actually used by policymakers. We then provide a brief response to some criticisms of DSGE models, with special emphasis on criticism by Joseph Stiglitz, and offer some concluding remarks.

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Working Papers

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Epidemics in the Neoclassical and New Keynesian Models

Martin S. Eichenbaum Sergio Rebelo Mathias Trabandt

in: NBER Working Paper, No. 27430, 2020

Abstract

We analyze the effects of an epidemic in three standard macroeconomic models. We find that the neoclassical model does not rationalize the positive comovement of consumption and investment observed in recessions associated with an epidemic. Introducing monopolistic competition into the neoclassical model remedies this shortcoming even when prices are completely flexible. Finally, sticky prices lead to a larger recession but do not fundamentally alter the predictions of the monopolistic competition model.

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Integrated Assessment of Epidemic and Economic Dynamics

Oliver Holtemöller

in: IWH Discussion Papers, No. 4, 2020

Abstract

In this paper, a simple integrated model for the joint assessment of epidemic and economic dynamics is developed. The model can be used to discuss mitigation policies like shutdown and testing. Since epidemics cause output losses due to a reduced labor force, temporarily reducing economic activity in order to prevent future losses can be welfare enhancing. Mitigation policies help to keep the number of people requiring intensive medical care below the capacity of the health system. The optimal policy is a mixture of temporary partial shutdown and intensive testing and isolation of infectious persons for an extended period of time.

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How Forecast Accuracy Depends on Conditioning Assumptions

Carola Engelke Katja Heinisch Christoph Schult

in: IWH Discussion Papers, No. 18, 2019

Abstract

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.

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(Since When) Are East and West German Business Cycles Synchronised?

Stefan Gießler Katja Heinisch Oliver Holtemöller

in: IWH Discussion Papers, No. 7, 2019

Abstract

This paper analyses whether and since when East and West German business cycles are synchronised. We investigate real GDP, unemployment rates and survey data as business cycle indicators and employ several empirical methods. Overall, we find that the regional business cycles have synchronised over time. GDP-based indicators and survey data show a higher degree of synchronisation than the indicators based on unemployment rates. However, recently synchronisation among East and West German business cycles seems to become weaker, in line with international evidence.

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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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