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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Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one...
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Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one...
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ENTRANCES
ENTRANCES Energy Transitions from Coal and Carbon: Effects on Societies ...
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Evaluation of the InvKG and the federal STARK programme
Evaluation of the InvKG and the federal STARK programme InvKG = Coal Regions ...
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When there were almost no flats in Halle yet ... Brigitte Loose about IWH's...
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Research Clusters
Three Research Clusters ...
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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
Low Carbon Economy,
No. 1,
2023
Abstract
Climate change is increasingly evident, and the design of effective climate adaptation policies is important for regional and sectoral economic growth. We propose different modelling approaches to quantify the socio-economic impacts of climate change on three vulnerable countries (Kazakhstan, Georgia, and Vietnam) and design specific adaptations. We use a Dynamic General Equilibrium (DGE) model for Vietnam and an economy-energy-emission (E3) model for the other two countries. Our simulations until 2050 show that selected adaptation measures, in particular in the agricultural sector, have positive implications for GDP. However, some adaptation measures can even increase greenhouse gas emissions. Focusing on GDP alone can lead to welfare-reducing policy decisions.
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