Transparency and Forecasting: The Impact of Conditioning Assumptions on Forecast Accuracy
Katja Heinisch, Christoph Schult, Carola Stapper
Applied Economic Letters,
im Erscheinen
Abstract
This study investigates the impact of inaccurate assumptions on economic forecast precision. We construct a new dataset comprising an unbalanced panel of annual German GDP forecasts from various institutions, taking into account their underlying assumptions. We explicitly control for different forecast horizons to reflect the information available at the time of release. Our analysis reveals that approximately 75% of the variation in squared forecast errors can be attributed to the variation in squared errors of the initial assumptions. This finding emphasizes the importance of accurate assumptions in economic forecasting and suggests that forecasters should transparently disclose their assumptions to enhance the usefulness of their forecasts in shaping effective policy recommendations.
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Supply Chain Disruptions and Firm Outcomes
Michael Koetter, Huyen Nguyen, Sochima Uzonwanne
IWH Discussion Papers,
Nr. 3,
2025
Abstract
This paper examines how firms’ exposure to supply chain disruptions (SCD) affects firm outcomes in the European Union (EU). Exploiting heterogeneous responses to workplace closures imposed by sourcing countries during the pandemic as a shock to SCD, we provide empirical evidence that firms in industries relying more heavily on foreign inputs experience a significant decline in sales compared to other firms. We document that external finance, particularly bank financing, plays a critical role in mitigating the effects of SCD. Furthermore, we highlight the unique importance of bank loans for small and solvent firms. Our findings also indicate that highly diversified firms and those sourcing inputs from less distant partners are less vulnerable to SCD.
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The German Energy Crisis: A TENK-based Fiscal Policy Analysis
Alexandra Gutsch, Christoph Schult
IWH Discussion Papers,
Nr. 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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Chinesische Massenimporte und Wahlverhalten in Europa: Kann der Aufstieg der politischen Ränder durch Importschocks erklärt werden?
Annika Backes, Steffen Müller
Wirtschaft im Wandel,
Nr. 4,
2024
Abstract
Wir untersuchen die kurz- und langfristigen Auswirkungen eines starken Anstiegs chinesischer Importe auf Wahlergebnisse in Europa. Populistische sowie links- und rechtsextreme Parteien gewannen erst viele Jahre nach dem Höhepunkt des China-Schocks bedeutenden Zuwachs an Wählerstimmen. Wir zeigen, dass die Auswirkungen von Importschocks überwiegend zugunsten populistischer Parteien ausfallen. In geringerem Maße profitieren in der kurzen Frist zudem linksextreme Parteien, langfristig hingegen rechtsextreme Parteien. Die Effekte auf das Wahlverhalten sind jedoch moderat und wir schlussfolgern, dass Importschocks den Aufstieg der politischen Ränder nur in begrenztem Maße erklären können.
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Forecast Combination and Interpretability Using Random Subspace
Boris Kozyrev
IWH Discussion Papers,
Nr. 21,
2024
Abstract
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.
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Industry Mix, Local Labor Markets, and the Incidence of Trade Shocks
Steffen Müller, Jens Stegmaier, Moises Yi
Journal of Labor Economics,
Nr. 3,
2024
Abstract
We analyze how skill transferability and the local industry mix affect the adjustment costs of workers hit by a trade shock. Using German administrative data and novel measures of economic distance we construct an index of labor market absorptiveness that captures the degree to which workers from a particular industry are able to reallocate into other jobs. Among manufacturing workers, we find that the earnings loss associated with increased import exposure is much higher for those who live in the least absorptive regions. We conclude that the local industry composition plays an important role in the adjustment processes of workers.
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Import Shocks and Voting Behavior in Europe Revisited
Annika Backes, Steffen Müller
European Journal of Political Economy,
June
2024
Abstract
We provide first evidence for the long-run causal impact that Chinese imports to European regions had on voting outcomes and revisit earlier estimates of the short-run impact for a methodological reason. The fringes of the political spectrum gained ground many years after the China shock plateaued and, unlike an earlier study by Colantone and Stanig (2018b), we do not find any robust evidence for a short-run effect on far-right votes. Instead, far-left and populist parties gained in the short run. We identify persistent long-run effects of import shocks on voting. These effects are biased towards populism and, to a lesser extent, to the far-right.
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Advanced Technology Adoption: Determinants and Labor Market Effects of Robot Use
Verena Plümpe
Otto-von-Guericke-Universität Magdeburg, PhD Thesis,
2024
Abstract
The recent advances in automation technology, robotics in particular, have sparked a heated debate over the future of labor and human society at large. The ongoing process of robotization may engender profound impacts on various segments of the labor market. Given the far-reaching implications of robots, it is thus very important to understand the scale and scope of robot use and characteristics of robot users. However, the main challenge is the limited availability of robot data at the microeconomic level (Raj and Seamans, 2018). Due to the data constraint, the bulk of the existing literature relies on cross-country industry-level data from the International Federation of Robotics (IFR). The lack of micro-level robot data makes it difficult to paint a comprehensive picture of robotization in industrial settings, and perhaps more importantly, to assess how within-industry firm level heterogeneity manifests itself in robot use and adoption.
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Risky Oil: It's All in the Tails
Christiane Baumeister, Florian Huber, Massimiliano Marcellino
NBER Working Paper,
Nr. 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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23.04.2024 • 13/2024
Chinesische Massenimporte stärken extreme Parteien
Die Globalisierung hat den politischen Rändern in Europa Stimmenzuwächse beschert. Eine Studie des Leibniz-Instituts für Wirtschaftsforschung Halle (IWH) belegt erstmals Langzeitfolgen gestiegener chinesischer Importe in europäische Länder: Vor allem rechtsextreme und populistische Parteien konnten in nationalen Wahlen vom so genannten China-Schock profitieren.
Steffen Müller
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