Predictive ability of business cycle indicators under test: A case study for the Euro area industrial production

Carstensen, Kai; Wohlrabe, Klaus und Ziegler, Christina (2011): Predictive ability of business cycle indicators under test: A case study for the Euro area industrial production. In: Jahrbücher für Nationalökonomie und Statistik, Bd. 231, Nr. 1: S. 82-106

Abstract

In this paper we assess the information content of seven widely cited early indicators for the euro area with respect to forecasting area-wide industrial production. To this end, we use various tests that are designed to compare competing forecast models. In addition to the standard Diebold-Mariano test, we employ tests that account for specific problems typically encountered in forecast exercises. Specifically, we pay attention to nested model structures, we alleviate the problem of data snooping arising from multiple pairwise testing, and we analyze the structural stability in the relative forecast performance of one indicator compared to a benchmark model. Moreover, we consider loss functions that overweight forecast errors in booms and recessions to check whether a specific indicator that appears to be a good choice on average is also preferable in times of economic stress. We find that none of this indicators uniformly dominates all its competitors. The optimal choice rather depends on the specific forecast situation and the loss function of the user. For 1-month forecasts the business climate indicator of the European Commission and the OECD composite leading indicator generally work well, for 6-month forecasts the OECD composite leading indicator performs very good by all criteria, and for 12-month forecasts the FAZ-Euro indicator published by the Frankfurter Allgemeine Zeitung is the only one that can beat the benchmark AR(1) model.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Volkswirtschaft ; Volkswirtschaft > Lehrstühle > CESifo-Professur für Makroökonomie (aufgelöst)
• Themengebiete: 300 Sozialwissenschaften > 330 Wirtschaft
• Sprache: Englisch