The German Energy Crisis: A TENK-based Fiscal Policy Analysis
Alexandra Gutsch, Christoph Schult
IWH Discussion Papers,
No. 1,
2025
Abstract
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.
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Gemeinschaftsdiagnose Herbst 2024: Deutsche Wirtschaft im Umbruch
Geraldine Dany-Knedlik, Oliver Holtemöller, Stefan Kooths, Torsten Schmidt, Timo Wollmershäuser
Wirtschaftsdienst,
No. 10,
2024
Abstract
The German economy has stagnated for over two years, with a slow recovery anticipated in the coming quarters. However, growth is unlikely to reach pre-COVID-19 levels anytime soon. Decarbonisation, digitisation, demographic changes, and heightened competition from China are dampening growth prospects. GDP is projected to decline by 0.1 % in 2024, with increases of 0.8 % and 1.3 % in the subsequent years. Rising private consumption and improving foreign trade are expected to contribute positively to the economic upturn in Germany. Economic policy should prioritise reducing productivity barriers, facilitating structural changes, and lowering political uncertainty to support recovery.
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Deutsche Wirtschaft im Umbruch – Konjunktur und Wachstum schwach
Dienstleistungsauftrag des Bundesministeriums für Wirtschaft und Klimaschutz,
No. 2,
2024
Abstract
Die deutsche Wirtschaft tritt seit über zwei Jahren auf der Stelle. In den kommenden Quartalen dürfte eine langsame Erholung einsetzen. Aber an den Trend von vor der COVID-19-Pandemie wird das Wirtschaftswachstum auf absehbare Zeit nicht mehr anknüpfen können. Die Dekarbonisierung, die Digitalisierung, der demografische Wandel und wohl auch der stärkere Wettbewerb mit Unternehmen aus China haben strukturelle Anpassungsprozesse in Deutschland ausgelöst, die die Wachstumsaussichten für die deutsche Wirtschaft dämpfen.
Das Bruttoinlandsprodukt dürfte im Jahr 2024 um 0,1% sinken und in den kommenden beiden Jahren um 0,8% bzw. 1,3% zunehmen. Damit revidieren die Institute ihre Prognose vom Frühjahr 2024 leicht nach unten. Getragen wird die schmalspurige Erholung vom steigenden privaten Verbrauch, der von kräftigen Zuwächsen der real verfügbaren Einkommen angeregt wird. Das Anziehen der Konjunktur in wichtigen Absatzmärkten, wie den europäischen Nachbarländern, wird den deutschen Außenhandel stützen. Zusammen mit günstigeren Finanzierungsbedingungen kommt dies den Anlageinvestitionen zugute. Die Wirtschaftspolitik sollte Produktivitätshemmnisse abbauen, den Strukturwandel zulassen und die politische Unsicherheit verringern.
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Expectations, Infections, and Economic Activity
Martin S. Eichenbaum, Miguel Godinho de Matos, Francisco Lima, Sergio Rebelo, Mathias Trabandt
Journal of Political Economy,
No. 8,
2024
Abstract
The Covid epidemic had a large impact on economic activity. In contrast, the dramatic decline in mortality from infectious diseases over the past 120 years had a small economic impact. We argue that people's response to successive Covid waves helps reconcile these two findings. Our analysis uses a unique administrative data set with anonymized monthly expenditures at the individual level that covers the first three Covid waves. Consumer expenditures fell by about the same amount in the first and third waves, even though the risk of getting infected was larger in the third wave. We find that people had pessimistic prior beliefs about the case-fatality rates that converged over time to the true case-fatality rates. Using a model where Covid is endemic, we show that the impact of Covid is small when people know the true case-fatality rate but large when people have empirically-plausible pessimistic prior beliefs about the case-fatality rate. These results reconcile the large economic impact of Covid with the small effect of the secular decline in mortality from infectious diseases estimated in the literature.
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Risky Oil: It's All in the Tails
Christiane Baumeister, Florian Huber, Massimiliano Marcellino
NBER Working Paper,
No. 32524,
2024
Abstract
The substantial fluctuations in oil prices in the wake of the COVID-19 pandemic and the Russian invasion of Ukraine have highlighted the importance of tail events in the global market for crude oil which call for careful risk assessment. In this paper we focus on forecasting tail risks in the oil market by setting up a general empirical framework that allows for flexible predictive distributions of oil prices that can depart from normality. This model, based on Bayesian additive regression trees, remains agnostic on the functional form of the conditional mean relations and assumes that the shocks are driven by a stochastic volatility model. We show that our nonparametric approach improves in terms of tail forecasts upon three competing models: quantile regressions commonly used for studying tail events, the Bayesian VAR with stochastic volatility, and the simple random walk. We illustrate the practical relevance of our new approach by tracking the evolution of predictive densities during three recent economic and geopolitical crisis episodes, by developing consumer and producer distress indices that signal the build-up of upside and downside price risk, and by conducting a risk scenario analysis for 2024.
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COVID-19 and Political Preferences Through Stages of the Pandemic: The Case of the Czech Republic
Alena Bičáková, Štěpán Jurajda
CERGE-EI Working Paper,
No. 778,
2024
Abstract
We track the effects of the COVID-19 pandemic on political preferences through ‘high’ and ‘low’ phases of the pandemic. We ask about the effects of the health and the economic costs of the pandemic measured at both personal and municipality levels. Consistent with the literature, we estimate effects suggestive of political accountability of leaders during ‘high’ pandemic phases. However, we also find that the pandemic political accountability effects are mostly short-lived, and do not extend to the first post-pandemic elections.
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Board Announcements
Board Announcements 27.03.2025: IWH 1st Trial Evaluation on June 16, 2025 27.03.2025: IWH 2nd Trial Evaluation on October 13, 2025 27.03.2025: IWH Evaluation on November 5 and…
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Unions as Insurance: Workplace Unionization and Workers' Outcomes During COVID-19
Nils Braakmann, Boris Hirsch
Industrial Relations: A Journal of Economy and Society,
No. 2,
2024
Abstract
We investigate to what extent workplace unionization protects workers from external shocks by preventing involuntary job separations. Using the COVID-19 pandemic as a plausibly exogenous shock hitting the whole economy, we compare workers who worked in unionized and non-unionized workplaces directly before the pandemic in a difference-in-differences framework. We find that unionized workers were substantially more likely to remain working for their pre-COVID employer and to be in employment. This greater employment stability was not traded off against lower working hours or labor income.
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Media Response
Media Response March 2025 IWH: Ifo Dresden schließt 2027 in: Frankfurter Allgemeine Zeitung, 28.03.2025 Steffen Müller: Pleitewelle rollt: Es trifft auch viele namhafte…
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Forecasting Economic Activity Using a Neural Network in Uncertain Times: Monte Carlo Evidence and Application to the
German GDP
Oliver Holtemöller, Boris Kozyrev
IWH Discussion Papers,
No. 6,
2024
Abstract
In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an autoregressive benchmark model in many practically relevant cases. Then, we applied GRNN to forecast quarterly German GDP growth by extending univariate GRNN to multivariate and mixed-frequency settings. We could distinguish between “normal” times and situations where the time-series behavior is very different from “normal” times such as during the COVID-19 recession and recovery. GRNN was superior in terms of root mean forecast errors compared to an autoregressive model and to more sophisticated approaches such as dynamic factor models if applied appropriately.
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