{"id":50455,"date":"2026-02-09T10:27:01","date_gmt":"2026-02-09T09:27:01","guid":{"rendered":"https:\/\/www.h-its.org\/de\/?p=50455"},"modified":"2026-02-09T10:48:12","modified_gmt":"2026-02-09T09:48:12","slug":"neue-methode-macht-konjunkturprognosen-verstandlicher","status":"publish","type":"post","link":"https:\/\/www.h-its.org\/de\/2026\/02\/09\/neue-methode-macht-konjunkturprognosen-verstandlicher\/","title":{"rendered":"Neue Methode macht Konjunkturprognosen verst\u00e4ndlicher"},"content":{"rendered":"\n

Forschende des KIT und HITS entwickeln ein transparentes Verfahren, das die Unsicherheit wirtschaftlicher Prognosen sichtbar macht.<\/strong><\/p>\n\n\n\n

Politik, Wirtschaft und Gesellschaft interessieren sich daf\u00fcr, wie sich zentrale Wirtschaftsindikatoren entwickeln. Prognosen zu Wachstum und Inflation sind leicht verf\u00fcgbar, doch die Unsicherheit dahinter bleibt oft unklar. Das Karlsruher Institut f\u00fcr Technologie (KIT) zeigt gemeinsam mit dem Heidelberg Institute for Theoretical Studies (HITS), wie sich diese Unsicherheit unkompliziert messen l\u00e4sst<\/a>.<\/p>\n\n\n\n

Einfaches Verfahren statt komplexer Modelle<\/strong><\/p>\n\n\n

\n
\"\"
Prognoseintervalle f\u00fcr die G7-Staaten, die mit dem neuen Verfahren erstellt wurden. @Friederike Becker, KIT<\/figcaption><\/figure>\n<\/div>\n\n\n

Die Forschenden haben eine Methode entwickelt, die Prognoseintervalle f\u00fcr Wachstum und Inflation der f\u00fchrenden Industrienationen erstellt<\/a>. Damit k\u00f6nnen sie Aussagen wie \u201eMit einer Wahrscheinlichkeit von 80 Prozent wird die Inflation in Deutschland im Jahr 2026 zwischen 0,5 Prozent und 3 Prozent liegen\u201c treffen. Grundlage sind Punktprognosen des Internationalen W\u00e4hrungsfonds und eine Analyse fr\u00fcherer Prognosefehler.<\/p>\n\n\n\n

\u201eDas Verfahren ist transparent und leicht anzuwenden\u201c, sagt Friederike Becker, wissenschaftliche Mitarbeiterin am Institut f\u00fcr Statistik des KIT. Melanie Schienle, Professorin am KIT und Senior Researcher am HITS, erg\u00e4nzt: \u201eWir nutzen die Expertise des Internationalen W\u00e4hrungsfonds und erzielen Ergebnisse, die mit komplexen statistischen Modellen vergleichbar sind.\u201c<\/p>\n\n\n\n

Die Methode eignet sich f\u00fcr alle Arten von Punktprognosen, sofern Daten zu fr\u00fcheren Fehlern vorliegen. Sie ist interpretierbar, transparent und auch ohne statistisches Fachwissen nutzbar. Aktuelle Prognoseintervalle werden auf einer \u00f6ffentlich zug\u00e4nglichen Website bereitgestellt.<\/p>\n\n\n\n

Publikation<\/strong>:<\/p>\n\n\n\n

Friederike Becker, Fabian Kr\u00fcger, Melanie Schienle. Simple Macroeconomic Forecast Distributions for the G7 Economies. Ann. Appl. Stat. 19(4): 2878-2897.
https:\/\/doi.org\/10.1214\/25-AOAS2095<\/a><\/p>\n\n\n\n

Wissenschaftlicher Kontakt:<\/strong><\/p>\n\n\n\n

Prof. Dr. Melanie Schienle
Chair of Statistics and Econometrics, Institute of Statistics<\/a>, KIT
melanie schienle@kit edu<\/a><\/p>\n\n\n\n

Medienkontakt:<\/strong><\/p>\n\n\n\n

Angela Michel
Head of Communications
Heidelberg Institute for Theoretical Studies (HITS)
E-Mail: angela.michel@h-its.org<\/a>
www.h-its.org<\/a><\/p>\n\n\n\n

Dr. Joachim Hoffmann
Karlsruher Institut f\u00fcr Technologie (KIT)
E-Mail: joachim.hoffmann@kit.edu<\/a>
www.kit.edu<\/a><\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

Forschende des KIT und HITS entwickeln ein transparentes Verfahren, das die Unsicherheit wirtschaftlicher Prognosen sichtbar macht. 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