Alumni
IWH Alumni The IWH maintains contact with its former employees worldwide. We involve our alumni in our work and keep them informed, for example, with a newsletter. We also plan…
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Macroeconomic Reports
Macroeconomic Reports Local and global: IWH regularly provides current economic data – be it about the state of the East German economy, the macroeconomic development in Germany…
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Forecasting Natural Gas Prices in Real Time
Christiane Baumeister, Florian Huber, Thomas K. Lee, Francesco Ravazzolo
NBER Working Paper,
No. 33156,
2024
Abstract
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.
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Research Clusters
Three Research Clusters Each IWH research group is assigned to a topic-oriented research cluster. The clusters are not separate organisational units, but rather bundle the…
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Forecast Combination and Interpretability Using Random Subspace
Boris Kozyrev
IWH Discussion Papers,
No. 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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Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one of the four research departments (Financial Markets – Laws, Regulations and Factor Markets –…
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Alumni
Alumni IWH provides guidance and support in job placement after graduation, including letters of recommendation and career advice. Graduates have found placements in academia…
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IWH Flash Indicator
IWH Flash Indicator The IWH Flash Indicator is a forecasting tool which provides early information on economic development. While the German Federal Statistical Office publishes…
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Ludwig (Interview)
About the CIA and a glass of red wine ... Professor Dr Udo Ludwig on the beginnings of our institute The core of the IWH founding team came from the Institute for Applied Economic…
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People
People Job Market Candidates Doctoral Students PhD Representatives Alumni Supervisors Lecturers Coordinators Job Market Candidates Tommaso Bighelli Job market paper: "The…
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