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

Economist in the Department of 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 I. Quartal und II. Quartal 2021

Katja Heinisch Oliver Holtemöller Axel Lindner Birgit Schultz

in: IWH Flash Indicator, No. 1, 2021

Abstract

Seit November 2020 befindet sich Deutschland im Lockdown. Dadurch konnte sich der Erholungskurs der deutschen Wirtschaft im vierten Quartal nicht weiter fortsetzen, und das Bruttoinlandsprodukt (BIP) stagnierte mit 0,1% nahezu. Durch die Mitte Dezember weiter verschärften Eindämmungsmaßnahmen wird die wirtschaftliche Aktivität in vielen Branchen im laufenden Quartal erschwert oder gänzlich verhindert. Auch ein weiteres Sinken der Anzahl der Covid-19-Infizierten dürfte daran so schnell nichts ändern, da die Furcht vor hochinfektiösen Corona-Mutationen groß ist. Ebenfalls versprechen die mittlerweile zugelassenen Impfstoffe gegen Covid-19-Erkrankungen keine kurzfristige Verbesserung der Situation, da sie wohl frühestens in einigen Monaten für die breite Masse der Bevölkerung verfügbar sein werden. Aufgrund der robusten Nachfrage aus dem Ausland dürfte die Wirtschaftsleistung laut IWH-Flash-Indikator jedoch im ersten Quartal 2021 nur um 0,7% zurückgehen und im zweiten Quartal, wenn die Corona-Eindämmungsmaßnahmen langsam zurückgeführt werden sollten, um 1,5% steigen. (vgl. Abbildung 1).

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High public deficit not only because of Corona - Medium-term options for action for the state

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

in: Konjunktur aktuell, No. 4, 2020

Abstract

According to the IWH's medium-term projection, Germany's gross domestic product will grow by an average of ½% in price-adjusted terms in the years to 2025, which is 1 percentage point slower than in the period from 2013 to 2019. This is due not only to the sharp slump in 2020, but also to the fact that the labour force will decline noticeably. Government revenues will be expanding much more slowly than in previous years. Even after the pandemic crisis is overcome, the state budget is likely to have a structural deficit of about 2% relative to GDP if the legal framework remains unchanged, and the debt brake will continue to be violated. Consolidation measures to reduce this deficit ratio to ½ % would push production in Germany below the normal rate of capacity utilization. Simulations with the IWH fiscal policy model show that consolidation on the expenditure side would reduce production by less than consolidation on the revenue side. There is much to be said, also from a theoretical point of view, for not abolishing the debt brake, but for relaxing it to some extent.

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IWH-Flash-Indikator IV. Quartal 2020 und I. Quartal 2021

Katja Heinisch Oliver Holtemöller Axel Lindner Birgit Schultz

in: IWH Flash Indicator, No. 4, 2020

Abstract

Weil weitreichende Eindämmungsmaßnahmen gelockert wurden, war die deutsche Wirtschaft im Sommer 2020 auf Erholungskurs. Dazu hat auch die Wirtschaftspolitik entscheidend beigetragen. Nach dem pandemiebedingten Einbruch um 9,8% im zweiten Quartal stieg das Bruttoinlandsprodukt (BIP) im dritten Quartal um 8,2%. Im Vergleich zum vierten Quartal 2019 – dem letzten Quartal ohne Einfluss der Pandemie – beträgt der Rückgang noch 4%. Allerdings sind die Covid-19-Neuinfektionen im Herbst wieder stark gestiegen, und für den November wurden insbesondere für den privaten Bereich erneut erhebliche Einschränkungen erlassen. Für weite Teile der gewerblichen Wirtschaft gelten diese Einschränkungen aber nicht. Die Wirtschaftsleistung dürfte daher im vierten Quartal 2020 nicht so stark einbrechen wie in der ersten Jahreshälfte. Der IWH-Flash-Indikator für das Bruttoinlandsprodukt deutet auf einen Rückgang um 2,1% hin, gefolgt von einer Expansion um 5,0% im ersten Quartal 2021 (vgl. Abbildung 1)

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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, forthcoming

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, forthcoming

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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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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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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