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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Optimizing Policymakers’ Loss Functions in Crisis Prediction: Before, Within or After?
Peter Sarlin, Gregor von Schweinitz
Macroeconomic Dynamics,
No. 1,
2021
Abstract
Recurring financial instabilities have led policymakers to rely on early-warning models to signal financial vulnerabilities. These models rely on ex-post optimization of signaling thresholds on crisis probabilities accounting for preferences between forecast errors, but come with the crucial drawback of unstable thresholds in recursive estimations. We propose two alternatives for threshold setting with similar or better out-of-sample performance: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. Given probabilistic model output, it is intuitive that a decision rule is independent of the data or model specification, as thresholds on probabilities represent a willingness to issue a false alarm vis-à-vis missing a crisis. We provide real-world and simulation evidence that this simplification results in stable thresholds, while keeping or improving on out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.
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Phillips Curve and Output Expectations: New Perspectives from the Euro Zone
Giuliana Passamani, Alessandro Sardone, Roberto Tamborini
DEM Working Papers,
No. 6,
2020
published in: Empirica
Abstract
When referring to the inflation trends over the last decade, economists speak of "puzzles": a “missing disinflation” puzzle in the aftermath of the Great Recession, and a ”missing inflation” one in the years of recovery to nowadays. To this, a specific "excess deflation" puzzle may be added during the post-crisis depression in the Euro Zone. The standard Phillips Curve model, in this context, has failed as the basic tool to produce reliable forecasts of future price developments, leading many scholars to consider this instrument to be no more adequate. The purpose of this paper is to contribute to this literature through the development of a newly specified Phillips Curve model, in which the inflation-expectation component is rationally related to the business cycle. The model is tested with the Euro Zone data 1999-2019 showing that inflation turns out to be consistently determined by output gaps and and experts' survey-based forecast errors, and that the puzzles can be explained by the interplay between these two variables.
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Asymmetric Investment Responses to Firm-specific Forecast Errors
Julian Berner, Manuel Buchholz, Lena Tonzer
Abstract
This paper analyses how firm-specific forecast errors derived from survey data of German manufacturing firms over 2007–2011 affect firms’ investment propensity. Understanding how forecast errors affect firm investment behaviour is key to mitigate economic downturns during and after crisis periods in which forecast errors tend to increase. Our findings reveal a negative impact of absolute forecast errors on investment. Strikingly, asymmetries arise depending on the size and direction of the forecast error. The investment propensity declines if the realised situation is worse than expected. However, firms do not adjust investment if the realised situation is better than expected suggesting that the uncertainty component of the forecast error counteracts positive effects of unexpectedly favorable business conditions. Given that the fraction of firms making positive forecast errors is higher after the peak of the recent financial crisis, this mechanism can be one explanation behind staggered economic growth and slow recovery following crises.
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How Forecast Accuracy Depends on Conditioning Assumptions
Carola Engelke, Katja Heinisch, Christoph Schult
IWH Discussion Papers,
No. 18,
2019
Abstract
This paper examines the extent to which errors in economic forecasts are driven by initial assumptions that prove to be incorrect ex post. Therefore, we construct a new data set comprising an unbalanced panel of annual forecasts from different institutions forecasting German GDP and the underlying assumptions. We explicitly control for different forecast horizons to proxy the information available at the release date. Over 75% of squared errors of the GDP forecast comove with the squared errors in their underlying assumptions. The root mean squared forecast error for GDP in our regression sample of 1.52% could be reduced to 1.13% by setting all assumption errors to zero. This implies that the accuracy of the assumptions is of great importance and that forecasters should reveal the framework of their assumptions in order to obtain useful policy recommendations based on economic forecasts.
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Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After?
Peter Sarlin, Gregor von Schweinitz
Abstract
Early-warning models most commonly optimize signaling thresholds on crisis probabilities. The expost threshold optimization is based upon a loss function accounting for preferences between forecast errors, but comes with two crucial drawbacks: unstable thresholds in recursive estimations and an in-sample overfit at the expense of out-of-sample performance. We propose two alternatives for threshold setting: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. Given probabilistic model output, it is intuitive that a decision rule is independent of the data or model specification, as thresholds on probabilities represent a willingness to issue a false alarm vis-à-vis missing a crisis. We provide simulated and real-world evidence that this simplification results in stable thresholds and improves out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.
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Asymmetric Investment Responses to Firm-specific Uncertainty
Julian Berner, Manuel Buchholz, Lena Tonzer
Abstract
This paper analyzes how firm-specific uncertainty affects firms’ propensity to invest. We measure firm-specific uncertainty as firms’ absolute forecast errors derived from survey data of German manufacturing firms over 2007–2011. In line with the literature, our empirical findings reveal a negative impact of firm-specific uncertainty on investment. However, further results show that the investment response is asymmetric, depending on the size and direction of the forecast error. The investment propensity declines significantly if the realized situation is worse than expected. However, firms do not adjust their investment if the realized situation is better than expected, which suggests that the uncertainty effect counteracts the positive effect due to unexpectedly favorable business conditions. This can be one explanation behind the phenomenon of slow recovery in the aftermath of financial crises. Additional results show that the forecast error is highly concurrent with an ex-ante measure of firm-specific uncertainty we obtain from the survey data. Furthermore, the effect of firm-specific uncertainty is enforced for firms that face a tighter financing situation.
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„Challenges for Forecasting – Structural Breaks, Revisions and Measurement Errors” 16th IWH-CIREQ Macroeconometric Workshop
Matthias Wieschemeyer
Wirtschaft im Wandel,
No. 1,
2016
Abstract
Am 7. und 8. Dezember 2015 fand am Leibniz-Institut für Wirtschaftsforschung Halle (IWH) zum 16. Mal der IWH-CIREQ Macroeconometric Workshop statt. Die in Kooperation mit dem Centre interuniversitaire de recherche en économie quantitative (CIREQ), Montréal, durchgeführte Veranstaltung beschäftigte sich dieses Mal mit zentralen Herausforderungen, denen sich die ökonomische Prognose zu stellen hat: Strukturbrüche in den Daten, statistische Revisionen und Fehler bei der Messung wichtiger Indikatoren.
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