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Dr Christoph Schult

Dr 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 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. He got his PhD degree in 2021.

Your contact

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

Publications

Citations
183

Recent Publications

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Assumption Errors and Forecast Accuracy: A Partial Linear Instrumental Variable and Double Machine Learning Approach

Katja Heinisch Fabio Scaramella Christoph Schult

in: IWH Discussion Papers, No. 6, 2025

Abstract

<p>Accurate macroeconomic forecasts are essential for effective policy decisions, yet their precision depends on the accuracy of the underlying assumptions. This paper examines the extent to which assumption errors affect forecast accuracy, introducing the average squared assumption error (ASAE) as a valid instrument to address endogeneity. Using double/debiased machine learning (DML) techniques and partial linear instrumental variable (PLIV) models, we analyze GDP growth forecasts for Germany, conditioning on key exogenous variables such as oil price, exchange rate, and world trade. We find that traditional ordinary least squares (OLS) techniques systematically underestimate the influence of assumption errors, particularly with respect to world trade, while DML effectively mitigates endogeneity, reduces multicollinearity, and captures nonlinearities in the data. However, the effect of oil price assumption errors on GDP forecast errors remains ambiguous. These results underscore the importance of advanced econometric tools to improve the evaluation of macroeconomic forecasts.</p>

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Begleitende Evaluierung des Investitionsgesetzes Kohleregionen (InvKG) und des STARK-Bundesprogramms ‒ Zweiter Zwischenbericht vom 31.10.2024

Matthias Brachert Katja Heinisch Oliver Holtemöller Florian Kirsch Uwe Neumann Michael Rothgang Torsten Schmidt Christoph Schult Anna Solms Mirko Titze

in: IWH Studies, No. 1, 2025

Abstract

<p><strong>Gutachten im Auftrag des Bundesministeriums für Wirtschaft und Klimaschutz</strong></p> <p>Das Klimaschutzgesetz (KSG) sieht eine Reduktion der deutschen Treibhausgasemissionen bis zum Jahr 2030 um 65 Prozent gegenüber den Emissionen im Jahr 1990 vor. Der Ausstieg aus der thermischen Verwertung der Kohle (vor allem der Braunkohle) leistet einen substanziellen Beitrag zum Erreichen dieser Ziele. Der Kohleausstieg stellt die Braunkohlereviere (und die Standorte der Steinkohlekraftwerke) jedoch vor strukturpolitische Herausforderungen. Um den Strukturwandel in diesen Regionen aktiv zu gestalten, hat der Bundestag im August 2020 mit Zustimmung des Bundesrats das Strukturstärkungsgesetz Kohleregionen (StStG) beschlossen. Über dieses Gesetz stellt der Bund bis zum Jahr 2038 Finanzhilfen von 41,09 Mrd. Euro zur Verfügung. Im Fokus der Politikmaßnahmen stehen verschiedene Ziele, vor allem gesamtwirtschaftliche (Wertschöpfung, Wachstum, Steueraufkommen), wettbewerbliche (Produktivität), arbeitsmarktpolitische (Beschäftigung, Beschäftigungsstrukturen), verteilungspolitische (regionale Disparitäten) sowie klimapolitische (Treibhausgasreduzierung, Nachhaltigkeit). Die im StStG vorgesehenen strukturpolitischen Interventionen umfassen ein breites Maßnahmenbündel. Das Gesetz fordert eine begleitende wissenschaftliche Evaluierung des Gesetzes. Bei dem vorliegenden Bericht handelt es sich um das zweite Dokument in diesem Evaluierungszyklus. Der erste Bericht liegt seit Juni 2023 vor und präsentierte ein erstes Lagebild nach dem Start der im Rahmen des Investitionsgesetzes Kohleregionen (InvKG) und des STARK-Bundesprogramms geplanten Maßnahmen. Nachdem nunmehr zahlreiche Maßnahmen in die Umsetzung gehen, nimmt der Strukturwandel an Fahrt auf. Der aktuelle Bericht nimmt eine Aktualisierung vor und erweitert Aussagen zu deren möglichen Effekten. Auch für diesen Bericht bleibt zu berücksichtigen, dass viele der geplanten Maßnahmen noch nicht oder gerade erst begonnen haben, was bei einer fast zwanzigjährigen Laufzeit des Programms durchaus naheliegend ist. Die in diesem Bericht vorgelegten empirischen Analysen basieren auf dem Datenstand vom 30.06.2024, also fast vier Jahre nach Programmstart.</p>

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The German Energy Crisis: A TENK-based Fiscal Policy Analysis

Alexandra Gutsch Christoph Schult

in: IWH Discussion Papers, No. 1, 2025

Abstract

<p>We study the aggregate, distributional, and welfare effects of fiscal policy responses to Germany’s energy crisis using a novel Ten-Agents New-Keynesian (TENK) model. The energy crisis, compounded by the COVID-19 pandemic, led to sharp increases in energy prices, inflation, and significant consumption disparities across households. Our model, calibrated to Germany’s income and consumption distribution, evaluates key policy interventions, including untargeted and targeted transfers, a value-added tax cut, energy tax reductions, and an energy cost brake. We find that untargeted transfers had the largest short-term aggregate impact, while targeted transfers were most cost-effective in supporting lower-income households. Other instruments, as the prominent energy cost brake, yielded comparably limited welfare gains. These results highlight the importance of targeted fiscal measures in addressing distributional effects and stabilizing consumption during economic crises.</p>

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Working Papers

cover_DP_2025-06.jpg

Assumption Errors and Forecast Accuracy: A Partial Linear Instrumental Variable and Double Machine Learning Approach

Katja Heinisch Fabio Scaramella Christoph Schult

in: IWH Discussion Papers, No. 6, 2025

Abstract

<p>Accurate macroeconomic forecasts are essential for effective policy decisions, yet their precision depends on the accuracy of the underlying assumptions. This paper examines the extent to which assumption errors affect forecast accuracy, introducing the average squared assumption error (ASAE) as a valid instrument to address endogeneity. Using double/debiased machine learning (DML) techniques and partial linear instrumental variable (PLIV) models, we analyze GDP growth forecasts for Germany, conditioning on key exogenous variables such as oil price, exchange rate, and world trade. We find that traditional ordinary least squares (OLS) techniques systematically underestimate the influence of assumption errors, particularly with respect to world trade, while DML effectively mitigates endogeneity, reduces multicollinearity, and captures nonlinearities in the data. However, the effect of oil price assumption errors on GDP forecast errors remains ambiguous. These results underscore the importance of advanced econometric tools to improve the evaluation of macroeconomic forecasts.</p>

read publication
cover_DP_2025-01.jpg

The German Energy Crisis: A TENK-based Fiscal Policy Analysis

Alexandra Gutsch Christoph Schult

in: IWH Discussion Papers, No. 1, 2025

Abstract

<p>We study the aggregate, distributional, and welfare effects of fiscal policy responses to Germany’s energy crisis using a novel Ten-Agents New-Keynesian (TENK) model. The energy crisis, compounded by the COVID-19 pandemic, led to sharp increases in energy prices, inflation, and significant consumption disparities across households. Our model, calibrated to Germany’s income and consumption distribution, evaluates key policy interventions, including untargeted and targeted transfers, a value-added tax cut, energy tax reductions, and an energy cost brake. We find that untargeted transfers had the largest short-term aggregate impact, while targeted transfers were most cost-effective in supporting lower-income households. Other instruments, as the prominent energy cost brake, yielded comparably limited welfare gains. These results highlight the importance of targeted fiscal measures in addressing distributional effects and stabilizing consumption during economic crises.</p>

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Is Risk the Fuel of the Business Cycle? Financial Frictions and Oil Market Disturbances

Christoph Schult

in: IWH Discussion Papers, No. 4, 2024

Abstract

I estimate a dynamic stochastic general equilibrium (DSGE) model for the United States that incorporates oil market shocks and risk shocks working through credit market frictions. The findings of this analysis indicate that risk shocks play a crucial role during the Great Recession and the Dot-Com bubble but not during other economic downturns. Credit market frictions do not amplify persistent oil market shocks. This result holds as long as entry and exit rates of entrepreneurs are independent of the business cycle.

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Topics

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