Dr Katja Heinisch

Dr Katja Heinisch
Current Position

since 1/13

Head of the Research Group Econometric Tools for Macroeconomic Forecasting and Simulation

Halle Institute for Economic Research (IWH) – Member of the Leibniz Association

since 9/09

Member of the Department Macroeconomics

Halle Institute for Economic Research (IWH) – Member of the Leibniz Association

Research Interests

  • international macroeconomics
  • applied time series econometrics and short-term forecasting
  • macroeconometric modeling

Katja Heinisch joined the Department of Macroeconomics in September 2009. Her research focuses on short-term forecasting and macroeconometric modelling.

Katja Heinisch earned a diploma from Chemnitz University of Technology and University of Strasbourg. She received her PhD from Osnabrück University. Katja Heinisch gained international research experience while working at the European Central Bank (ECB) and the International Monetary Fund (IMF).

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

Publications

Recent Publications

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IWH-Flash-Indikator III. Quartal und IV. Quartal 2021

Katja Heinisch Oliver Holtemöller Axel Lindner Birgit Schultz

in: IWH Flash Indicator, No. 3, 2021

Abstract

Zu Beginn des zweiten Quartals 2021 wurde die wirtschaftliche Erholung durch die dritte Corona-Welle gebremst. Dennoch stieg das Bruttoinlandsprodukt um 1,5%. Allerdings bestanden Angebotsrestriktionen für Dienstleistungen in einigen Bereichen fort. Weil die Corona-Impfquote mittlerweile recht weit vorangeschritten ist, könnten diese Restriktionen aufgehoben werden. Es gibt aber auch Hinweise, dass die Impfungen weniger wirksam sein könnten als erhofft. Außerdem nehmen die Infektionszahlen mit Verbreitung der Delta-Variante wieder zu, was die Aussichten für den Herbst erneut eintrübt. Zudem hemmen in der gewerblichen Wirtschaft weiterhin Lieferketten- und Beschaffungsprobleme, welche zu steigenden Einkaufs­preisen führen, die Produktion. Die Wirtschaft in Deutschland dürfte laut IWH-Flash-Indikator im dritten Quartal 2021 um 1,0% expandieren und im vierten Quartal um 0,1% leicht zurückgehen (vgl. Abbildung 1).

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Conditional Macroeconomic Forecasts: Disagreement, Revisions and Forecast Errors

Alexander Glas Katja Heinisch

in: IWH Discussion Papers, No. 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.

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IWH-Flash-Indikator II. Quartal und III. Quartal 2021

Katja Heinisch Oliver Holtemöller Axel Lindner Birgit Schultz

in: IWH Flash Indicator, No. 2, 2021

Abstract

Die hohen Infektionszahlen und der seit November 2020 immer wieder verlängerte Lockdown führten im ersten Quartal 2021 zu einem Rückgang des Bruttoinlandsprodukts um 1,7%. Insbesondere der private Konsum litt unter den strengen staatlichen Restriktionen. Hingegen liefen die Warenexporte gut und verhinderten einen stärkeren Einbruch der deutschen Wirtschaft. Nachdem bereits Ende des ersten Quartals in einigen Regionen Deutschlands begonnen wurde, die Restriktionen etwas zurückzunehmen, kam es aus Sorge vor einem weiteren Anwachsen der dritten Corona-Welle in der zweiten Aprilhälfte zu einer bundesweit regulierten Verschärfung der Lockdown-Regeln. Seit Anfang Mai gehen die Corona-Neuerkrankungen in Deutschland nun zurück. Das dürfte wohl neben einem saisonalen Effekt auch auf die endlich in Fahrt gekommene Impfkampagne zurückzuführen sein. Der Lockdown dürfte in absehbarer Zeit aufgehoben werden können. Insbesondere die private Konsumnachfrage dürfte davon profitieren und zusammen mit der robusten Nachfrage aus dem Ausland die Wirtschaftsleistung laut IWH-Flash-Indikator im zweiten Quartal 2021 um 2,1% und im dritten Quartal um 2,4% steigen lassen.

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Refereed Publications

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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, 2021

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.

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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, No. 1, 2021

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.

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Nowcasting East German GDP Growth: a MIDAS Approach

João Carlos Claudio Katja Heinisch Oliver Holtemöller

in: Empirical Economics, No. 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.

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Working Papers

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Conditional Macroeconomic Forecasts: Disagreement, Revisions and Forecast Errors

Alexander Glas Katja Heinisch

in: IWH Discussion Papers, No. 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.

read publication

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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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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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