IWH-Flash-Indikator II. und III. Quartal 2024
Katja Heinisch, Oliver Holtemöller, Axel Lindner, Birgit Schultz
IWH-Flash-Indikator,
No. 2,
2024
Abstract
Die deutsche Wirtschaft stagniert nun schon seit zwei Jahren. Auch zu Beginn des Jahres 2024 gab es mit einem leichten Plus von 0,2% keinen konjunkturellen Neustart. Vor allem war die Kauflaune der privaten Haushalte gedrückt, aber auch die Industrie kämpft weiter mit ungünstigen Rahmenbedingungen und einer schwachen Nachfrage. Hohe Zinsen und Energiepreise, aber auch strukturelle Probleme wie bürokratische Restriktionen fordern dabei ihren Tribut, wie nicht zuletzt an den steigenden Insolvenzzahlen zu sehen ist. Im internationalen Umfeld werden die Krisenherde und Spannungen nicht weniger, dennoch ist die Weltkonjunktur weiter aufwärtsgerichtet. Damit steigt bei den deutschen Unternehmen die Hoffnung, im Kielwasser mitziehen zu können. Alles in allem dürfte das Bruttoinlandsprodukt (BIP) laut IWH-Flash-Indikator im zweiten Quartal 2024 um 0,3% und im dritten Quartal 2024 um 0,1% steigen (vgl. Abbildung 1).
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Credit Supply Shocks: Financing Real Growth or Takeovers?
Tobias Berg, Daniel Streitz, Michael Wedow
Review of Corporate Finance Studies,
No. 2,
2024
Abstract
How do firms invest when financial constraints are relaxed? We document that firms affected by a large positive credit supply shock predominantly increase borrowing for transaction-based purposes. These treated firms have larger asset and employment growth rates; however, growth entirely stems from the increased takeover activity. Announcement returns indicate a low quality of the credit-supply-induced takeover activity. These results offer the possibility that credit-driven growth can simply reflect redistribution, rather than net gains in assets or employment.
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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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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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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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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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Economic Outlook
IWH Spring Forecast 2025 A Turning Point for the German Economy? March 13, 2025 The international political environment has fundamentally changed with looming trade wars and a…
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Homepage
A turning point for the German economy? The international political environment has fundamentally changed with looming trade wars and a deteriorating security situation in Europe.…
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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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