Economic Sentiment: Disentangling Private Information from Public Knowledge
Katja Heinisch, Axel Lindner
IWH Discussion Papers,
Nr. 15,
2021
Abstract
This paper addresses a general problem with the use of surveys as source of information about the state of an economy: Answers to surveys are highly dependent on information that is publicly available, while only additional information that is not already publicly known has the potential to improve a professional forecast. We propose a simple procedure to disentangle the private information of agents from knowledge that is already publicly known for surveys that ask for general as well as for private prospects. Our results reveal the potential of our proposed technique for the usage of European Commissions‘ consumer surveys for economic forecasting for Germany.
Artikel Lesen
A Comparison of Monthly Global Indicators for Forecasting Growth
Christiane Baumeister, Pierre Guérin
International Journal of Forecasting,
Nr. 3,
2021
Abstract
This paper evaluates the predictive content of a set of alternative monthly indicators of global economic activity for nowcasting and forecasting quarterly world real GDP growth using mixed-frequency models. It shows that a recently proposed indicator that covers multiple dimensions of the global economy consistently produces substantial improvements in forecasting accuracy, while other monthly measures have more mixed success. Specifically, the best-performing model yields impressive gains with MSPE reductions of up to 34% at short horizons and up to 13% at long horizons relative to an autoregressive benchmark. The global economic conditions indicator also contains valuable information for assessing the current and future state of the economy for a set of individual countries and groups of countries. This indicator is used to track the evolution of the nowcasts for the U.S., the OECD area, and the world economy during the COVID-19 pandemic and the main factors that drive the nowcasts are quantified.
Artikel Lesen
Conditional Macroeconomic Forecasts: Disagreement, Revisions and Forecast Errors
Alexander Glas, Katja Heinisch
IWH Discussion Papers,
Nr. 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.
Artikel Lesen
Optimizing Policymakers’ Loss Functions in Crisis Prediction: Before, Within or After?
Peter Sarlin, Gregor von Schweinitz
Macroeconomic Dynamics,
Nr. 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.
Artikel Lesen
A Comparison of Monthly Global Indicators for Forecasting Growth
Christiane Baumeister, Pierre Guérin
Abstract
This paper evaluates the predictive content of a set of alternative monthly indicators of global economic activity for nowcasting and forecasting quarterly world GDP using mixed-frequency models. We find that a recently proposed indicator that covers multiple dimensions of the global economy consistently produces substantial improvements in forecast accuracy, while other monthly measures have more mixed success. This global economic conditions indicator contains valuable information also for assessing the current and future state of the economy for a set of individual countries and groups of countries. We use this indicator to track the evolution of the nowcasts for the US, the OECD area, and the world economy during the coronavirus pandemic and quantify the main factors driving the nowcasts.
Artikel Lesen
Phillips Curve and Output Expectations: New Perspectives from the Euro Zone
Giuliana Passamani, Alessandro Sardone, Roberto Tamborini
DEM Working Papers,
Nr. 6,
2020
publiziert 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.
Artikel Lesen
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.
Artikel Lesen
The Value of Firm Networks: A Natural Experiment on Board Connections
Ester Faia, Maximilian Mayer, Vincenzo Pezone
CEPR Discussion Papers,
Nr. 14591,
2020
Abstract
This paper presents causal evidence of the effects of boardroom networks on firm value and compensation policies. We exploit exogenous variation in network centrality arising from a ban on interlocking directorates of Italian financial and insurance companies. We leverage this shock to show that firms whose centrality in the network rises after the reform experience positive abnormal returns around the announcement date and are better hedged against shocks. Information dissemination plays a central role: results are driven by firms that have higher idiosyncratic volatility, low analyst coverage, and more uncertainty surrounding their earnings forecasts. Firms benefit more from boardroom centrality when they are more central in the input-output network, hence more susceptible to upstream shocks, when they are less central in the cross-ownership network, or when they have low profitability or low growth opportunities. Network centrality also results in higher directors' compensation, due to rent sharing and improved executives' outside option, and more similar compensation policies between connected firms.
Artikel Lesen
Nowcasting East German GDP Growth: a MIDAS Approach
João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Empirical Economics,
Nr. 1,
2020
Abstract
Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.
Artikel Lesen
