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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Media Response
Media Response March 2025 IWH: Ökonomen heben Prognosen an in: Fuldaer Zeitung, 14.03.2025 IWH: Institute sehen kaum Wirtschaftswachstum in: Handelsblatt, 14.03.2025 IWH: Führende…
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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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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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Teaching
Teaching Within the framework of its cooperations with both German and foreign universities IWH researchers are actively committed to teaching by offering academic courses. These…
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Tracking Weekly State-Level Economic Conditions
Christiane Baumeister, Danilo Leiva-León, Eric Sims
Review of Economics and Statistics,
No. 2,
2024
Abstract
This paper develops a novel dataset of weekly economic conditions indices for the 50 U.S. states going back to 1987 based on mixed-frequency dynamic factor models with weekly, monthly, and quarterly variables that cover multiple dimensions of state economies. We find considerable cross-state heterogeneity in the length, depth, and timing of business cycles. We illustrate the usefulness of these state-level indices for quantifying the main contributors to the economic collapse caused by the COVID-19 pandemic and for evaluating the effectiveness of the Paycheck Protection Program. We also propose an aggregate indicator that gauges the overall weakness of the U.S. economy.
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Flight to Safety: How Economic Downturns Affect Talent Flows to Startups
Shai B. Bernstein, Richard R. Townsend, Ting Xu
Review of Financial Studies,
No. 3,
2024
Abstract
Using proprietary data from AngelList Talent, we study how startup job seekers’ search and application behavior changed during the COVID-19 downturn. We find that workers shifted their searches and applications away from less-established startups and toward more-established ones, even within the same individual over time. At the firm level, this shift was not offset by an influx of new job seekers. Less-established startups experienced a relative decline in the quantity and quality of applications, ultimately affecting their hiring. Our findings uncover a flight-to-safety channel in the labor market that may amplify the procyclical nature of entrepreneurial activities.
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Gender Equality & Anti-Discrimination
Equal Opportunities at IWH IWH commits to actively promoting equal opportunities for men and women, going beyond already existing guidelines. In 2013, 2016, 2019, and again 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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