8th CompNet Annual Conference
From Micro to Macro: Market Power, Firms’ Heterogeneity and Investment 8th Annual Conference of CompNet, jointly organized with IMF, EIB, ENRI and IWH, March 18-19 2019, European…
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2nd FINPRO - Finance and Productivity Conference
2nd FINPRO - Finance and Productivity Conference A conference jointly organised by the Competitiveness Research Network (CompNet), the European Bank for Reconstruction and…
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7th CompNet Annual Conference
Economic Growth, Trade and Productivity Dispersion 7 th CompNet Annual Conference, June 21-22, 2018, Leopoldina, Halle (Saale), Germany The main target of this conference was to…
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Charts
Info Graphs Sometimes pictures say more than a thousand words. Therefore, we selected a few graphs to present our main topics visually. If you should have any questions or would…
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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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Research Data Centre
Research Data Centre (IWH-RDC) Direct link to our Data Offer The IWH Research Data Centre offers external researchers access to microdata and micro-aggregated data sets that…
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Declining Business Dynamism in Europe: The Role of Shocks, Market Power, and Technology
Filippo Biondi, Sergio Inferrera, Matthias Mertens, Javier Miranda
VoxEU CEPR,
2024
Abstract
We study changes in business dynamism in Europe after 2000 using novel micro-aggregated data that we collected for 19 European countries. In all countries, we document a broad-based decline in job reallocation rates that concerns most economic sectors and size classes. This decline is mainly driven by dynamics within sectors, size, and age classes rather than by compositional changes. Large and mature firms experience the strongest decline in job reallocation rates. Simultaneously, the employment shares of young firms decline. Consistent with US evidence, firms’ employment has become less responsive to productivity shocks. However, the dispersion of firms’ productivity shocks has decreased too. To enhance our understanding of these patterns, we derive and apply a novel firm-level framework that relates changes in firms’ sales, market power, wages, and production technology to firms’ responsiveness and job reallocation.
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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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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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