Dr. Katja Heinisch

Dr. Katja Heinisch
Aktuelle Position

seit 1/13

Leiterin der Forschungsgruppe Ökonometrische Methoden für wirtschaftliche Prognosen und Simulationen

Leibniz-Institut für Wirtschaftsforschung Halle (IWH)

seit 9/09

Wissenschaftliche Mitarbeiterin der Abteilung Makroökonomik

Leibniz-Institut für Wirtschaftsforschung Halle (IWH)

Forschungsschwerpunkte

  • internationale Makroökonomik
  • angewandte Zeitreihenökonometrie, insb. Kurzfristprognose
  • strukturelle makroökonometrische Modelle

Katja Heinisch ist seit September 2009 wissenschaftliche Mitarbeiterin in der Abteilung Makroökonomik. Zu ihren Forschungsschwerpunkten zählen insbesondere Kurzfristprognosen und die ökonometrische Modellierung gesamtwirtschaftlicher Zusammenhänge.

Katja Heinisch studierte an der Technischen Universität Chemnitz und der Universität Straßburg. Sie promovierte an der Universität Osnabrück. Während ihrer Dissertationszeit absolvierte Katja Heinisch Forschungsaufenthalte an der Europäischen Zentralbank (EZB) und beim Internationalen Währungsfonds (IWF).

Ihr Kontakt

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

Publikationen

Neueste Publikationen

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Power Generation and Structural Change: Quantifying Economic Effects of the Coal Phase-out in Germany

Katja Heinisch Oliver Holtemöller Christoph Schult

in: Energy Economics, im Erscheinen

Abstract

In the fight against global warming, the reduction of greenhouse gas emissions is a major objective. In particular, a decrease in electricity generation by coal could contribute to reducing CO2 emissions. We study potential economic consequences of a coal phase-out in Germany, using a multi-region dynamic general equilibrium model. Four regional phase-out scenarios before the end of 2040 are simulated. We find that the worst case phase-out scenario would lead to an increase in the aggregate unemployment rate by about 0.13 [0.09 minimum; 0.18 maximum] percentage points from 2020 to 2040. The effect on regional unemployment rates varies between 0.18 [0.13; 0.22] and 1.07 [1.00; 1.13] percentage points in the lignite regions. A faster coal phase-out can lead to a faster recovery. The coal phase-out leads to migration from German lignite regions to German non-lignite regions and reduces the labour force in the lignite regions by 10,100 [6300; 12,300] people by 2040. A coal phase-out until 2035 is not worse in terms of welfare, consumption and employment compared to a coal-exit until 2040.

Publikation lesen

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(Since when) are East and West German Business Cycles Synchronised?

Stefan Gießler Katja Heinisch Oliver Holtemöller

in: Jahrbücher für Nationalökonomie und Statistik, im Erscheinen

Abstract

We analyze 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 we 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, synchronisation among East and West German business cycles seems to have become weaker again recently.

Publikation lesen

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Hohes öffentliches Defizit nicht nur wegen Corona – Mittelfristige Handlungsmöglichkeiten für den Staat

Andrej Drygalla Oliver Holtemöller Axel Lindner Matthias Wieschemeyer Götz Zeddies Katja Heinisch

in: Konjunktur aktuell, Nr. 4, 2020

Abstract

Nach der Mittelfristprojektion des IWH wird das Bruttoinlandsprodukt in Deutschland in den Jahren bis 2025 preisbereinigt um durchschnittlich ½% wachsen, und damit einen Prozentpunkt langsamer als im Zeitraum von 2013 bis 2019. Dies ist nicht nur auf den starken Einbruch im Jahr 2020 zurückzuführen, sondern auch darauf, dass die Erwerbsbevölkerung spürbar zurückgehen wird. Die Staatseinnahmen expandieren deutlich langsamer als in den vergangenen Jahren. Auch nach Überwindung der Pandemiekrise dürfte der Staatshaushalt im Fall unveränderter gesetzlicher Rahmenbedingungen ein strukturelles Defizit von etwa 2% relativ zum Bruttoinlandsprodukt aufweisen, und die Schuldenbremse würde weiter verletzt. Konsolidierungsmaßnahmen zur Rückführung dieser Defizitquote auf ½% würden die Produktion in Deutschland unter die Normalauslastung drücken. Mit Hilfe des finanzpolitischen Simulationsmodells des IWH kann gezeigt werden, dass dabei eine ausgabenseitige Konsolidierung die Produktion weniger belastet als eine einnahmenseitige. Es spricht, auch aus theoretischer Sicht, viel dafür, die Schuldenbremse zwar nicht abzuschaffen, aber ein Stück weit zu lockern.

Publikation lesen

 

Referierte Publikationen

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Power Generation and Structural Change: Quantifying Economic Effects of the Coal Phase-out in Germany

Katja Heinisch Oliver Holtemöller Christoph Schult

in: Energy Economics, im Erscheinen

Abstract

In the fight against global warming, the reduction of greenhouse gas emissions is a major objective. In particular, a decrease in electricity generation by coal could contribute to reducing CO2 emissions. We study potential economic consequences of a coal phase-out in Germany, using a multi-region dynamic general equilibrium model. Four regional phase-out scenarios before the end of 2040 are simulated. We find that the worst case phase-out scenario would lead to an increase in the aggregate unemployment rate by about 0.13 [0.09 minimum; 0.18 maximum] percentage points from 2020 to 2040. The effect on regional unemployment rates varies between 0.18 [0.13; 0.22] and 1.07 [1.00; 1.13] percentage points in the lignite regions. A faster coal phase-out can lead to a faster recovery. The coal phase-out leads to migration from German lignite regions to German non-lignite regions and reduces the labour force in the lignite regions by 10,100 [6300; 12,300] people by 2040. A coal phase-out until 2035 is not worse in terms of welfare, consumption and employment compared to a coal-exit until 2040.

Publikation lesen

cover_jahrbuecher-fuer-nationaloekonomie-und-statistik.jpg

(Since when) are East and West German Business Cycles Synchronised?

Stefan Gießler Katja Heinisch Oliver Holtemöller

in: Jahrbücher für Nationalökonomie und Statistik, im Erscheinen

Abstract

We analyze 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 we 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, synchronisation among East and West German business cycles seems to have become weaker again recently.

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

Arbeitspapiere

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How Forecast Accuracy Depends on Conditioning Assumptions

Carola Engelke Katja Heinisch Christoph Schult

in: IWH-Diskussionspapiere, 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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(Since When) Are East and West German Business Cycles Synchronised?

Stefan Gießler Katja Heinisch Oliver Holtemöller

in: IWH-Diskussionspapiere, Nr. 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.

Publikation lesen

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Outperforming IMF Forecasts by the Use of Leading Indicators

Katja Drechsel Sebastian Giesen Axel Lindner

in: IWH-Diskussionspapiere, Nr. 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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