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Should Forecasters Use Real‐time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence

Katja Heinisch, Rolf Scheufele
German Economic Review, forthcoming
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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IWH-Flash-Indikator I. Quartal und II. Quartal 2020

Katja Heinisch, Oliver Holtemöller, Axel Lindner, Birgit Schultz
One-off Publications, No. 1, 2020
Abstract
Das Bruttoinlandsprodukt in Deutschland hat im vierten Quartal, so wie vom IWH-Flash-Indikator im November angezeigt, lediglich stagniert. Für das erste und das zweite Quartal 2020 deutet der IWH-Flash-Indikator wieder auf eine Zunahme des Bruttoinlandsprodukts hin (vgl. Abbildung 1). Allerdings gehen in den Indikator keine Daten ein, die der chinesischen Corona-Epidemie Rechnung tragen.
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Nowcasting East German GDP Growth: a MIDAS Approach

João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
IWH Discussion Papers, No. 24, 2019
published in: Empirical Economics
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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Sinkendes Potenzialwachstum in Deutschland, beschleunigter Braunkohleausstieg und Klimapaket: Finanzpolitische Konsequenzen für die Jahre bis 2024

Andrej Drygalla, Katja Heinisch, Oliver Holtemöller, Axel Lindner, Christoph Schult, Matthias Wieschemeyer, Götz Zeddies
Konjunktur aktuell, No. 4, 2019
Abstract
Nach der Mittelfristprojektion des IWH wird das Bruttoinlandsprodukt in Deutschland in den Jahren bis 2024 preisbereinigt um durchschnittlich 1% wachsen; das nominale Bruttoinlandsprodukt wird um durchschnittlich 2¾% zunehmen. Die Durchschnittswerte verschleiern die Tatsache, dass das Wachstum gegen Ende des Projektionszeitraums aufgrund der dann rückläufigen Erwerbsbevölkerung spürbar zurückgehen wird. Dies wird sich auch bei den Staatseinnahmen niederschlagen. Allerdings wird die Bevölkerung nicht regional gleichverteilt zurückgehen. Strukturschwache Regionen dürften stärker betroffen sein. Die regionalen Effekte auf die Staatseinnahmen werden zwar durch Umverteilungsmechanismen abgefedert, aber nicht völlig ausgeglichen. Regionen mit schrumpfender Erwerbsbevölkerung müssen sich auf einen sinkenden finanziellen Spielraum einstellen. Der beschleunigte Braunkohleausstieg wird diesen Prozess verstärken, das Klimapaket der Bundesregierung hat hingegen vergleichsweise geringe Auswirkungen auf die öffentlichen Finanzen.
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Nowcasting East German GDP Growth: a MIDAS Approach

João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Empirical Economics, forthcoming
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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IWH-Flash-Indikator IV. Quartal 2019 und I. Quartal 2020

Katja Heinisch, Oliver Holtemöller, Axel Lindner, Birgit Schultz
One-off Publications, No. 4, 2019
Abstract
Die Produktion in Deutschland hat nach einem Rückgang um 0,2% im zweiten Quartal 2019 im dritten Quartal zwar um 0,1% zugelegt, doch, damit bleibt die Expansionsrate weiterhin unter der Potenzialwachstumsrate zurück, und die Konjunktur dürfte nach Berechnungen des Leibniz-Instituts für Wirtschaftsforschung Halle (IWH) auch in den nächsten beiden Quartalen schwach bleiben. Der IWH-Flash-Indikator, der exklusiv für die WirtschaftsWoche berechnet wird, deutet darauf hin, dass die Wirtschaft im vierten Quartal 2019 stagnieren und im ersten Quartal 2020 um lediglich 0,1% zulegen wird (vgl. Abbildung 1).
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IWH-Flash-Indikator III. Quartal und IV. Quartal 2019

Katja Heinisch
One-off Publications, No. 3, 2019
Abstract
Die deutsche Wirtschaft schrumpfte im zweiten Quartal 2019 um 0,1%, nachdem das Bruttoinlandsprodukt zu Jahresbeginn noch um 0,4% zugelegt hatte. Der aktuelle IWH-Flash-Indikator deutet darauf hin, dass die Konjunktur auch in den kommenden beiden Quartalen schwach bleiben wird. So dürfte die Wirtschaft im dritten Quartal 2019 stagnieren, für das vierte Quartal kann ein kleines Plus von 0,2% erwartet werden.
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How Forecast Accuracy Depends on Conditioning Assumptions

Carola Engelke, Katja Heinisch, Christoph Schult
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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Power Generation and Structural Change: Quantifying Economic Effects of the Coal Phase-out in Germany

Christoph Schult, Katja Heinisch, Oliver Holtemöller
IWH Discussion Papers, No. 16, 2019
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. Using a multi-region dynamic general equilibrium model, this paper studies potential economic consequences of a coal phase-out in Germany. Different regional phase-out scenarios are simulated with varying timing structures. We find that a politically induced coal phase-out would lead to an increase in the national unemployment rate by about 0.10 percentage points from 2020 to 2040, depending on the specific scenario. The effect on regional unemployment rates varies between 0.18 to 1.07 percentage points in the lignite regions. However, 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 10,000 people by 2040.
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Klimaschutz und Kohleausstieg: Politische Strategien und Maßnahmen bis 2030 und darüber hinaus

Pao-Yu Oei, Casimir Lorenz, Sophie Schmalz, Hanna Brauers, Philipp Herpich, Christian von Hirschhausen, Claudia Kemfert, Barbara Dröschel, Jan Hildebrand, Juri Horst, Uwe Klann, Patrick Matschoss, Michael Porzig, Irina Rau, Bernhard Wern, Hans-Ulrich Brautzsch, Gerhard Heimpold, Katja Heinisch, Oliver Holtemöller, Christoph Schult, Hauke Hermann, Dirk Heyen, Katja Schumacher, Cornelia Ziehm
Pao-Yu Oei et al., Klimaschutz und Kohleausstieg: Politische Strategien und Maßnahmen bis 2030 und darüber hinaus. Abschlussbericht. Climate Change 27/2019. Dessau-Roßlau: Umweltbundesamt, 2019
Abstract
The present study examines the socio-economic consequences of a climate policy-driven coal phase-out in Germany. A focus lies on the lignite industry – especially in the lignite regions. In a first step, the regions are spatially defined and described. Additional analysis is based on energy economic modelling. The model examines phase-out scenarios, which differ in the chosen criteria for the order of power plant closure (specific emissions or plant age). An input-output-model and a regional macroeconomic model build up on these phase-out pathways and examine the socio economic effects of the phase-out in the lignite regions as well as in the rest of Germany. The combination of both models offers the advantage to consider the phase-out from different perspective and hence derive different and more robust effects. The models show, on the one hand, that in an early phase-out the negative effects of structural change are visible earlier. On the other hand, recuperative effects can counteract the negative consequences according to the regional economic model. Furthermore, the structural change creates economic opportunities. Those opportunities are primarily diversified economic activities. Case studies show significant employment potentials for the lignite regions. New jobs in renewable energies and energetic optimization of buildings can already counteract the negative employment effects associated with the investigated structural change. The study concludes, describing accompanying political instruments that can support the regions on their way to master the challenges of the up-coming structural change.
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