Ökonometrische Methoden für wirtschaftliche Prognosen und Simulationen

Der Forschungsschwerpunkt der Forschungsgruppe liegt in der Entwicklung ökonometrischer Methoden für Kurzfristprognosen (Reduzierte-Form-Modelle), für Regionalisierung und für Langfristprojektionen sowie für strukturelle Prognose- und Simulationsmodelle (DSGE-Modelle). Ferner erstellt sie ökonometrische Hintergrundanalysen für die Prognosetätigkeit der Forschungsgruppe Makroökonomische Analysen und Prognosen. Im Rahmen von Drittmittelprojekten wurden verschiedene makroökonomische Modelle, bspw. für die Volkswagen Financial Services AG oder im Rahmen von GIZ-Projekten für die Wirtschaftsministerien in Kirgistan und Tadschikistan sowie das Institut für makroökonomische Prognosen und Forschung (IFMR) in Usbekistan entwickelt.

IWH-Datenprojekt: IWH Real-time Database

Forschungscluster
Gesamtwirtschaftliche Dynamik und Stabilität

Ihr Kontakt

Dr. Katja Heinisch
Dr. Katja Heinisch
Mitglied - Abteilung Makroökonomik
Nachricht senden +49 345 7753-836

PROJEKTE

10.2019 ‐ 06.2022

An Klimawandel angepasste Wirtschaftsentwicklung

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Der Klimawandel wirkt sich stark auf das Wirtschaftswachstum und die Entwicklung eines Landes aus. Das erhöht den Bedarf an verlässlichen und realisierbaren Ansätzen, mit denen die Auswirkungen von Klimarisiken und potenzielle Anpassungsszenarien bewertet werden können. Die politischen Entscheidungsträger*innen in den Planungs- und Wirtschaftsministerien benötigen fundierte Prognosen, um entsprechende wirtschaftspolitische Instrumente zu konzipieren, zu finanzieren und aktiv gegenzusteuern. In den Pilotländern Kasachstan, Vietnam und Georgien werden Klimarisiken bei der makroökonomischen Modellierung berücksichtigt. Die Ergebnisse werden so in den Politikprozess integriert, dass angepasste Wirtschaftsplanungen entstehen können. Das IWH-Team ist verantwortlich für die makroökonomische Modellierung in Vietnam.

GIZ-Projektseite ansehen

Dr. Katja Heinisch

05.2020 ‐ 04.2023

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

Europäische Kommission

Ziel von ENTRANCES ist es, die Folgen des Kohleausstiegs in Europa zu untersuchen. Wie verändert der Kohleausstieg die Gesellschaft – und wie kann Politik darauf reagieren?

Projektseite ansehen

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-Rahmenvertrag)

Europäische Kommission

Professor Dr. Oliver Holtemöller

07.2016 ‐ 12.2018

Klimaschutz und Kohleausstieg: Politische Strategien und Maßnahmen bis 2030 und darüber hinaus

Umweltbundesamt (UBA)

Dr. Katja Heinisch

01.2017 ‐ 12.2017

Unterstützung einer nachhaltigen Wirtschaftsentwicklung in ausgewählten Regionen Usbekistans

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

Entwicklung eines analytischen Tools basierend auf einer Input-Output-Tabelle

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Das Ziel des Projektes war die Entwicklung eines Exceltools zur Wirkungsanalyse von Politikmaßnahmen in Tadschikistan basierend auf dem statischen Input-Output-Ansatz.

Dr. Katja Heinisch

11.2015 ‐ 12.2016

Beschäftigung und Entwicklung in der Republik Usbekistan

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Förderung einer nachhaltigen wirtschaftlichen Entwicklung in ausgewählten Regionen Usbekistans

Dr. Katja Heinisch

05.2016 ‐ 05.2016

Rahmenbedingungen und Finanzierungsmöglichkeiten für die Entwicklung des Privatsektors in Tadschikistan

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Dr. Katja Heinisch

02.2016 ‐ 04.2016

Makroökonomische Reformen und umwelt- und sozialverträgliches Wachstum in Vietnam

Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Dr. Katja Heinisch

Referierte Publikationen

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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 Lünenbürger 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.

Publikation lesen

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Nowcasting East German GDP Growth: a MIDAS Approach

João Carlos Claudio Katja Heinisch Oliver Holtemöller

in: Empirical Economics, Nr. 1, 2020

Abstract

Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.

Publikation lesen

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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, Nr. 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.

Publikation lesen

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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, Nr. 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.

Publikation lesen

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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, Nr. 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.

Publikation lesen

Arbeitspapiere

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Conditional Macroeconomic Forecasts: Disagreement, Revisions and Forecast Errors

Alexander Glas Katja Heinisch

in: IWH Discussion Papers, Nr. 7, 2021

Abstract

Using data from the European Central Bank‘s Survey of Professional Forecasters, we analyse the role of ex-ante conditioning variables for macroeconomic forecasts. In particular, we test to which extent the heterogeneity, updating and ex-post performance of predictions for inflation, real GDP growth and the unemployment rate are related to assumptions about future oil prices, exchange rates, interest rates and wage growth. Our findings indicate that inflation forecasts are closely associated with oil price expectations, whereas expected interest rates are used primarily to predict output growth and unemployment. Expectations about exchange rates and wage growth also matter for macroeconomic forecasts, albeit less so than oil prices and interest rates. We show that survey participants can considerably improve forecast accuracy for macroeconomic outcomes by reducing prediction errors for external conditions. Our results contribute to a better understanding of the expectation formation process of experts.

Publikation lesen

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Disentangling Covid-19, Economic Mobility, and Containment Policy Shocks

Annika Camehl Malte Rieth

in: IWH Discussion Papers, Nr. 2, 2021

Abstract

We study the dynamic impact of Covid-19, economic mobility, and containment policy shocks. We use Bayesian panel structural vector autoregressions with daily data for 44 countries, identified through sign and zero restrictions. Incidence and mobility shocks raise cases and deaths significantly for two months. Restrictive policy shocks lower mobility immediately, cases after one week, and deaths after three weeks. Non-pharmaceutical interventions explain half of the variation in mobility, cases, and deaths worldwide. These flattened the pandemic curve, while deepening the global mobility recession. The policy tradeoff is 1 p.p. less mobility per day for 9% fewer deaths after two months.

Publikation lesen

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Epidemics in the Neoclassical and New Keynesian Models

Martin S. Eichenbaum Sergio Rebelo Mathias Trabandt

in: NBER Working Paper, Nr. 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.

Publikation lesen

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Integrated Assessment of Epidemic and Economic Dynamics

Oliver Holtemöller

in: IWH Discussion Papers, Nr. 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.

Publikation lesen

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How Forecast Accuracy Depends on Conditioning Assumptions

Carola Engelke Katja Heinisch Christoph Schult

in: IWH Discussion Papers, Nr. 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.

Publikation lesen
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