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Can Germany’s economy stage an unexpected recovery?Steffen MüllerThe Economist, January 30, 2025
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.
Am 12. November 2024 hörte das Bundesverfassungsgericht Argumente zu einer Klage einiger FDP-Abgeordneter gegen den Solidaritätszuschlag. IWH-Präsident Reint Gropp war als Sachverständiger geladen und gibt in diesem Beitrag seine Einschätzung zur Thematik wieder.
Das Produktionspotenzial der deutschen Wirtschaft wächst mittelfristig (2023 bis 2029) mit einer jahresdurchschnittlichen Rate von 0,3% und damit deutlich schwächer als in den Jahren zuvor. Dies ist auf eine ungünstigere Entwicklung aller drei Faktoren (Arbeitsvolumen, Kapitalstock, totale Faktorproduktivität) zurückzuführen. Das potenzielle Wachstum wird insbesondere durch den Rückgang der durchschnittlichen Arbeitszeit gedämpft.
Zur Jahreswende dürfte die weltweite Produktion weiterhin in etwa so schnell wie in der Dekade vor der Pandemie expandieren. Die Konjunktur im Euroraum ist nur verhalten, und die Stagnation der deutschen Wirtschaft setzt sich fort. Die Industrie verliert an internationaler Wettbewerbsfähigkeit. Unternehmen und Verbraucher halten sich aufgrund unklarer wirtschaftspolitischer Aussichten mit ihren Ausgaben zurück. Das Bruttoinlandsprodukt dürfte im Jahr 2024 um 0,2% sinken und im Jahr 2025 um 0,4% expandieren.
Climate change and inequality are critical and interrelated defining issues for this century. Despite growing empirical evidence on the economic incidence of climate policies and impacts, mainstream model-based assessments are often silent on the interplay between climate change and economic inequality. For example, all the major model comparisons reviewed in IPCC neglect within-country inequalities. Here we fill this gap by presenting a model ensemble of eight large-scale Integrated Assessment Models belonging to different model paradigms and featuring economic heterogeneity. We study the distributional implications of Paris-aligned climate target of 1.5 degree and include different carbon revenue redistribution schemes. Moreover, we account for the economic inequalities resulting from residual and avoided climate impacts. We find that price-based climate policies without compensatory measures increase economic inequality in most countries and across models. However, revenue redistribution through equal per-capita transfers can offset this effect, leading to on average decrease in the Gini index by almost two points. When climate benefits are included, inequality is further reduced, but only in the long term. Around mid-century, the combination of dried-up carbon revenues and yet limited climate benefits leads to higher inequality under the Paris target than in the Reference scenario, indicating the need for further policy measures in the medium term.
Der deutsche Konjunkturmotor stottert weiter vor sich hin. Obwohl das Bruttoinlandsprodukt (BIP) im dritten Quartal 2024 um 0,2% zunahm, liegt es immer noch unter dem Niveau vom ersten Quartal 2024, da das zweite Quartal nach neuesten Zahlen weitaus schwächer ausgefallen ist als zuvor gemeldet (vgl. Abbildung 1). Der leichte Zuwachs im dritten Quartal dürfte dabei vor allem auf gestiegene staatliche und private Konsumausgaben zurückzuführen sein. In den Unternehmen ist die Stimmung weiterhin trüb und die wirtschaftspolitische Unsicherheit dürfte weiterhin hoch bleiben. Zudem belasten nach wie vor gestiegene Energie- und Lohnkosten die Investitionsbereitschaft der Unternehmen. Alles in allem dürfte das Bruttoinlandsprodukt (BIP) laut IWH-Flash-Indikator im vierten Quartal 2024 stagnieren. Für den Jahresbeginn 2025 deuten allerdings die Frühindikatoren auf eine Belebung der wirtschaftlichen Aktivitäten und einen Anstieg des BIP um 0,4% hin. Diese reflektieren jedoch noch nicht die jüngsten politischen Ereignisse in den USA und in Deutschland.
In a multi-sector and multi-region framework, this paper employs a dynamic general equilibrium model to analyze climate-resilient economic development (DGE-CRED) in Vietnam. We calibrate sector and region-specific damage functions and quantify climate variable impacts on productivity and capital formation for various shared socioeconomic pathways (SSPs 119, 245, and 585). Our results based on simulations and cost-benefit analyses reveal a projected 5 percent reduction in annual GDP by 2050 in the SSP 245 scenario. Adaptation measures for the dyke system are crucial to mitigate the consumption gap, but they alone cannot sufficiently address it. Climate-induced damages to agriculture and labor productivity are the primary drivers of consumption reductions, underscoring the need for focused adaptation measures in the agricultural sector and strategies to reduce labor intensity as vital policy considerations for Vietnam’s response to climate change.
This paper provides a comprehensive analysis of the forecastability of the real price of natural gas in the United States at the monthly frequency considering a universe of models that differ in their complexity and economic content. Our key finding is that considerable reductions in mean-squared prediction error relative to a random walk benchmark can be achieved in real time for forecast horizons of up to two years. A particularly promising model is a six-variable Bayesian vector autoregressive model that includes the fundamental determinants of the supply and demand for natural gas. To capture real-time data constraints of these and other predictor variables, we assemble a rich database of historical vintages from multiple sources. We also compare our model-based forecasts to readily available model-free forecasts provided by experts and futures markets. Given that no single forecasting method dominates all others, we explore the usefulness of pooling forecasts and find that combining forecasts from individual models selected in real time based on their most recent performance delivers the most accurate forecasts.
The European Commission’s growth forecasts play a crucial role in shaping policies and provide a benchmark for many (national) forecasters. The annual forecasts are built on quarterly estimates, which do not receive much attention and are hardly known. Therefore, this paper provides a comprehensive analysis of multi-period ahead quarterly GDP growth forecasts for the European Union (EU), euro area, and several EU member states with respect to first-release and current-release data. Forecast revisions and forecast errors are analyzed, and the results show that the forecasts are not systematically biased. However, GDP forecasts for several member states tend to be overestimated at short-time horizons. Furthermore, the final forecast revision in the current quarter is generally downward biased for almost all countries. Overall, the differences in mean forecast errors are minor when using real-time data or pseudo-real-time data and these differences do not significantly impact the overall assessment of the forecasts’ quality. Additionally, the forecast performance varies across countries, with smaller countries and Central and Eastern European countries (CEECs) experiencing larger forecast errors. The paper provides evidence that there is still potential for improvement in forecasting techniques both for nowcasts but also forecasts up to eight quarters ahead. In the latter case, the performance of the mean forecast tends to be superior for many countries.
This paper investigates forecast aggregation via the random subspace regressions method (RSM) and explores the potential link between RSM and the Shapley value decomposition (SVD) using the US GDP growth rates. This technique combination enables handling high-dimensional data and reveals the relative importance of each individual forecast. First, it is possible to enhance forecasting performance in certain practical instances by randomly selecting smaller subsets of individual forecasts and obtaining a new set of predictions based on a regression-based weighting scheme. The optimal value of selected individual forecasts is also empirically studied. Then, a connection between RSM and SVD is proposed, enabling the examination of each individual forecast’s contribution to the final prediction, even when there is a large number of forecasts. This approach is model-agnostic (can be applied to any set of predictions) and facilitates understanding of how the aggregated prediction is obtained based on individual forecasts, which is crucial for decision-makers.
