Step by Step ‒ A Quarterly Evaluation of EU Commission's GDP Forecasts
Katja Heinisch
IWH Discussion Papers,
No. 22,
2024
Abstract
The European Commission’s growth forecasts play a crucial role in shaping policies and provide a benchmark for many (national) forecasters. The annual forecasts are built on quarterly estimates, which do not receive much attention and are hardly known. Therefore, this paper provides a comprehensive analysis of multi-period ahead quarterly GDP growth forecasts for the European Union (EU), euro area, and several EU member states with respect to first-release and current-release data. Forecast revisions and forecast errors are analyzed, and the results show that the forecasts are not systematically biased. However, GDP forecasts for several member states tend to be overestimated at short-time horizons. Furthermore, the final forecast revision in the current quarter is generally downward biased for almost all countries. Overall, the differences in mean forecast errors are minor when using real-time data or pseudo-real-time data and these differences do not significantly impact the overall assessment of the forecasts’ quality. Additionally, the forecast performance varies across countries, with smaller countries and Central and Eastern European countries (CEECs) experiencing larger forecast errors. The paper provides evidence that there is still potential for improvement in forecasting techniques both for nowcasts but also forecasts up to eight quarters ahead. In the latter case, the performance of the mean forecast tends to be superior for many countries.
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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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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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Media Response
Media Response November 2024 Steffen Müller: Firmaer er oftere i problemer in: Flensborg Avis, 22.11.2024 Steffen Müller: Zahl der Insolvenzen steigt in: Süddeutsche.de,…
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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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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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IWH Forecasting Dashboard
IWH Forecasting Dashboard The objective of the IWH Forecasting Dashboard (ForDas) is to provide a platform for macroeconomic forecasts from various institutions for the German…
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Firm-specific Forecast Errors and Asymmetric Investment Propensity
Manuel Buchholz, Lena Tonzer, Julian Berner
Economic Inquiry,
No. 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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Inflation Puzzles, the Phillips Curve and Output Expectations: New Perspectives from the Euro Zone
Alessandro Sardone, Roberto Tamborini, Giuliana Passamani
Empirica,
February
2022
Abstract
Confidence in the Phillips Curve (PC) as predictor of inflation developments along the business cycle has been shaken by recent “inflation puzzles” in advanced countries, such as the “missing disinflation” in the aftermath of the Great Recession and the “missing inflation” in the years of recovery, to which the Euro-Zone “excess deflation” during the post-crisis depression may be added. This paper proposes a newly specified Phillips Curve model, in which expected inflation, instead of being treated as an exogenous explanatory variable of actual inflation, is endogenized. The idea is simply that if the PC is used to foresee inflation, then its expectational component should in some way be the result of agents using the PC itself. As a consequence, the truly independent explanatory variables of inflation turn out to be the output gaps and the related forecast errors by agents, with notable empirical consequences. The model is tested with the Euro-Zone data 1999–2019 showing that it may provide a consistent explanation of the “inflation puzzles” by disentangling the structural component from the expectational effects of the PC.
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Conditional Macroeconomic Forecasts: Disagreement, Revisions and Forecast Errors
Alexander Glas, Katja Heinisch
IWH Discussion Papers,
No. 7,
2021
Abstract
Using data from the European Central Bank‘s Survey of Professional Forecasters, we analyse the role of ex-ante conditioning variables for macroeconomic forecasts. In particular, we test to which extent the heterogeneity, updating and ex-post performance of predictions for inflation, real GDP growth and the unemployment rate are related to assumptions about future oil prices, exchange rates, interest rates and wage growth. Our findings indicate that inflation forecasts are closely associated with oil price expectations, whereas expected interest rates are used primarily to predict output growth and unemployment. Expectations about exchange rates and wage growth also matter for macroeconomic forecasts, albeit less so than oil prices and interest rates. We show that survey participants can considerably improve forecast accuracy for macroeconomic outcomes by reducing prediction errors for external conditions. Our results contribute to a better understanding of the expectation formation process of experts.
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