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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Das IWH auf der ASSA-Jahrestagung 2020 in San Diego
Das IWH auf der ASSA-Jahrestagung 2020 in San Diego Die American Economic Association (AEA) organisiert vom 3. bis 5. Januar 2020 die jährlich stattfindende ASSA-Tagung in San…
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Does IFRS Information on Tax Loss Carryforwards and Negative Performance Improve Predictions of Earnings and Cash Flows?
Sandra Dreher, Sebastian Eichfelder, Felix Noth
Journal of Business Economics,
January
2024
Abstract
We analyze the usefulness of accounting information on tax loss carryforwards and negative performance to predict earnings and cash flows. We use hand-collected information on tax loss carryforwards and corresponding deferred taxes from the International Financial Reporting Standards tax footnotes for listed firms from Germany. Our out-of-sample tests show that considering accounting information on tax loss carryforwards does not enhance performance forecasts and typically even worsens predictions. The most likely explanation is model overfitting. Besides, common forecasting approaches that deal with negative performance are prone to prediction errors. We provide a simple empirical specification to account for that problem.
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Conditional Macroeconomic Survey Forecasts: Revisions and Errors
Alexander Glas, Katja Heinisch
Journal of International Money and Finance,
November
2023
Abstract
Using data from the European Central Bank's Survey of Professional Forecasters and ECB/Eurosystem staff projections, we analyze the role of ex-ante conditioning variables for macroeconomic forecasts. In particular, we test to which extent the updating and ex-post performance of predictions for inflation, real GDP growth and unemployment are related to beliefs about future oil prices, exchange rates, interest rates and wage growth. While oil price and exchange rate predictions are updated more frequently than macroeconomic forecasts, the opposite is true for interest rate and wage growth expectations. Beliefs about future inflation are closely associated with oil price expectations, whereas expected interest rates are related to predictions of output growth and unemployment. Exchange rate predictions also matter for macroeconomic forecasts, albeit less so than the other variables. With regard to forecast errors, wage growth and GDP growth closely comove, but only during the period when interest rates are at the effective zero lower bound.
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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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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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Projekte
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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The IWH Forecasting Dashboard – From Forecasts to Evaluation and Comparison
Katja Heinisch, Christoph Behrens, Jörg Döpke, Alexander Foltas, Ulrich Fritsche, Tim Köhler, Karsten Müller, Johannes Puckelwald, Hannes Reichmayr
IWH Technical Reports,
Nr. 1,
2023
Abstract
The paper describes the “Halle Institute for Economic Research (IWH) Forecasting Dashboard (ForDas)”. This tool aims at providing, on a non-commercial basis, historical and actual macroeconomic forecast data for the Germany economy to researchers and interested audiences. The database renders it possible to directly compare forecast quality across selected institutions and over time. It is partly based on data collected in the DFG-funded project “Macroeconomic Forecasts in Great Crises”.
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Firm-specific Forecast Errors and Asymmetric Investment Propensity
Manuel Buchholz, Lena Tonzer, Julian Berner
Economic Inquiry,
Nr. 2,
2022
Abstract
This paper analyzes how firm-specific forecast errors derived from survey data of German manufacturing firms over 2007–2011 relate to firms' investment propensity. Our findings reveal that asymmetries arise depending on the size and direction of the forecast error. The investment propensity declines if the realized situation is worse than expected. However, firms do not adjust investment if the realized situation is better than expected suggesting that the uncertainty component of the forecast error counteracts good surprises of unexpectedly favorable business conditions. This asymmetric mechanism can be one explanation behind slow recovery following crises.
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