Economic Outlook
Joint Economic Forecast Spring 2025 Geopolitical turn intensifies crisis – structural reforms even more urgent April 10, 2025 The German economy will continue to tread water in…
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People
People Doctoral Students PhD Representatives Alumni Supervisors Lecturers Coordinators Doctoral Students Afroza Alam (Supervisor: Reint Gropp ) Julian Andres Diaz Acosta…
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IWH FDI Micro Database
IWH FDI Micro Database The IWH FDI Micro Database (FDI = Foreign Direct Investment) comprises a total population of affiliates of multinational enterprises (MNEs) in selected…
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Seed Fund
Seed Fund Projects SEED 2021/01 I. Deposit Insurance and Depositor Behavior II. Access to Credit and the Environment Head of Project at IWH: Professor Reint Gropp Project Partner:…
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The Halle Spirit We provide independent research on economic topics that really matter and aim to enrich society with facts and evidence-based insights that facilitate better…
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27.03.2024 • 11/2024
East Germany's lead over West Germany in terms of growth is bound to shrink – Implications of the Joint Economic Forecast Spring 2024 for the East German economy
In 2023, the East German economy is expected to have expanded by 0.5%, while it shrank by 0.3% in Germany as a whole. The Halle Institute for Economic Research (IWH) forecasts an East German growth rate of 0.5% again for 2024, and a rate of 1.5% in 2025. The unemployment rate is expected to be 7.3% in 2024 and 7.1% in the following year.
Oliver Holtemöller
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Wirtschaft im Wandel
Wirtschaft im Wandel Die Zeitschrift „Wirtschaft im Wandel“ unterrichtet die breite Öffentlichkeit über aktuelle Themen der Wirtschaftsforschung. Sie stellt wirtschaftspolitisch…
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MICROPROD
MICROPROD Raising EU Productivity: Lessons from Improved Micro Data The goal of MICROPROD is to contribute to a greater understanding of the challenges brought about in Europe by…
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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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Green Transition
Green Transition Research and Policy Advice for Structural Change in the German Economy Dossier, 18.06.2024 Green Transition The green transition is a key topic of our time. In a…
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