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,
Nr. 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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Medienecho
Medienecho November 2024 IWH: Manchmal wäre der Schlussstrich die angemessenere Lösung in: TextilWirtschaft, 21.11.2024 IWH: Existenzgefahr Nun droht eine Pleitewelle in: DVZ…
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Archiv
Medienecho-Archiv 2021 2020 2019 2018 2017 2016 Dezember 2021 IWH: Ausblick auf Wirtschaftsjahr 2022 in Sachsen mit Bezug auf IWH-Prognose zu Ostdeutschland: "Warum Sachsens…
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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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Das IWH auf der Jahrestagung des Vereins für Socialpolitik 2019 "30 Jahre Mauerfall" - Demokratie und Marktwirtschaft
IWH-BROWN-BAG-PANEL "Ost-West-Produktivitätslücke: Ursachen und Folgen" Ostdeutschlands Wirtschaft konnte anfänglich ihre Produktivität gegenüber den westdeutschen Verhältnissen…
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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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Unsere Projekte 07.2022 ‐ 12.2026 Evaluierung des InvKG und des Bundesprogrammes STARK Bundesministerium für Wirtschaft und Klimaschutz (BMWK) Im Auftrag des Bundesministeriums…
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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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Intuit QuickBooks Small Business Index: A New Employment Series for the US, Canada, and the UK
Ufuk Akcigit, Raman Chhina, Seyit Cilasun, Javier Miranda, Eren Ocakverdi, Nicolas Serrano-Velarde
IWH Discussion Papers,
Nr. 9,
2023
Abstract
Small and young businesses are essential for job creation, innovation, and economic growth. Even most of the superstar firms start their business life small and then grow over time. Small firms have less internal resources, which makes them more fragile and sensitive to macroeconomic conditions. This suggests the need for frequent and real-time monitoring of the small business sector’s health. Previously this was difficult due to a lack of appropriate data. This paper fills this important gap by developing a new Intuit QuickBooks Small Business Index that focuses on the smallest of small businesses with at most 9 workers in the US and the UK and at most 19 workers in Canada. The Index aggregates a sample of anonymous Quick- Books Online Payroll subscriber data (QBO Payroll sample) from 333,000 businesses in the US, 66,000 in Canada, and 25,000 in the UK. After comparing the QBO Payroll sample data to the official statistics, we remove the seasonal components and use a Flexible Least Squares method to calibrate the QBO Payroll sample data against official statistics. Finally, we use the estimated model and the QBO Payroll sample data to generate a near real-time index of economic activity. We show that the estimated model performs well both in-sample and out-of-sample. Additionally, we use this analysis for different regions and industries. Keywords:
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Evidence-based Support for Adaptation Policies in Emerging Economies
Maximilian Banning, Anett Großmann, Katja Heinisch, Frank Hohmann, Christian Lutz, Christoph Schult
IWH Studies,
Nr. 2,
2023
Abstract
In recent years, the impacts of climate change become increasingly evident, both in magnitude and frequency. The design and implementation of adequate climate adaptation policies play an important role in the macroeconomic policy discourse to assess the impact of climate change on regional and sectoral economic growth. We propose different modelling approaches to quantify the socio-economic impacts of climate change and design specific adaptations in three emerging market economies (Kazakhstan, Georgia and Vietnam) which belong to the areas that are heavily exposed to climate change. A Dynamic General Equilibrium (DGE) model has been used for Vietnam and economy-energy-emission (E3) models for the other two countries. Our modelling results show how different climate hazards impact the economy up to the year 2050. Adaptation measures in particular in the agricultural sector have positive implications for the gross domestic product (GDP). However, some adaptation measures can even increase greenhouse gas emissions. In addition, the focus on GDP as the main indicator to evaluate policy measures can produce welfare-reducing policy decisions.
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