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Hochfrequenzdaten aus der Schifffahrt als Indikator für den deutschen Außenhandel
[Economic headlights: High-frequency data from shipping as an indicator of German foreign trade]

Author

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  • Saskia Meuchelböck

    (Institut für Weltwirtschaft)

  • Vincent Stamer

    (Institut für Weltwirtschaft)

Abstract

Die IfW Kiel Handelsindikatoren für die deutschen Warenexporte und -importe basieren auf hochfrequenten Schiffspositionsdaten und machen damit Informationen verfügbar, die bislang kaum in Konjunkturanalysen und -prognosen genutzt werden konnten. Sie zeichnen sich durch eine vergleichsweise hohe Prognosegüte aus und stellen eine wertvolle Ergänzung zu konventionellen Frühindikatoren dar. Aufgrund der nahezu tagesaktuellen Verfügbarkeit der Daten sind die IfW Kiel Handelsindikatoren insbesondere auch in Krisenzeiten nützlich, also wenn hohe Unsicherheit herrscht und traditionelle Indikatoren oft erst mit größerer Verzögerung Signale liefern - wie beispielsweise während der ersten Corona-Welle im Frühjahr des Jahres 2020.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Saskia Meuchelböck & Vincent Stamer, 2021. "Hochfrequenzdaten aus der Schifffahrt als Indikator für den deutschen Außenhandel [Economic headlights: High-frequency data from shipping as an indicator of German foreign trade]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 101(5), pages 403-404, May.
    • Handle: RePEc:spr:wirtsc:v:101:y:2021:i:5:d:10.1007_s10273-021-2926-1
    DOI: 10.1007/s10273-021-2926-1
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    References listed on IDEAS

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    1. Mr. Diego A. Cerdeiro & Andras Komaromi & Yang Liu & Mamoon Saeed, 2020. "World Seaborne Trade in Real Time: A Proof of Concept for Building AIS-based Nowcasts from Scratch," IMF Working Papers 2020/057, International Monetary Fund.
    2. Mr. Serkan Arslanalp & Mr. Marco Marini & Ms. Patrizia Tumbarello, 2019. "Big Data on Vessel Traffic: Nowcasting Trade Flows in Real Time," IMF Working Papers 2019/275, International Monetary Fund.
    3. Stamer, Vincent, 2021. "Thinking outside the container: A machine learning approach to forecasting trade flows," Kiel Working Papers 2179, Kiel Institute for the World Economy (IfW Kiel).
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