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Christoph Schult

Christoph Schult
Current Position

since 7/16

Economist in the Department of Macroeconomics

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

Research Interests
  • dynamic macroeconomics
  • energy economics

Christoph Schult joined the Department of Macroeconomics as a doctoral student in July 2016. His research focuses on dynamic macroeconomics, forecasting and energy economics.

Christoph Schult received his bachelor's degree from Martin Luther University Halle-Wittenberg and his master's degree from Humboldt-Universität zu Berlin.

Your contact

Christoph Schult
Christoph Schult
Mitglied - Department Macroeconomics
Send Message +49 345 7753-806

Publications

Recent Publications

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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 Lünenburger Christoph Schult

in: Energy, 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.

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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

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

Christoph Schult Katja Heinisch Oliver Holtemöller

in: 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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Keywords

Coal Phase-out
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