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Last active May 25, 2020 08:40
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trendecon

trendecon: daily economic indicators based on Google searches

Project

During the Covid-19 pandemic, information about the economic and social situation has changed rapidly. Traditional indicators are not sufficiently frequent to monitor and forecast economic and social activity at high frequency. We use Google search trends to overcome this data gap and create meaningful indicators. We extract daily search data on keywords reflecting consumers' perception of the economic situation. The indicators are available at www.trendecon.org.

An accompanying R package contains the code to construct long daily time series from Google Trends for any keyword. Robustness of the series is achieved by querying Google multiple times. The queries are sampled at daily, weekly and monthly frequencies and then harmonized such that the long term trend is preserved. A more detailed methodological description is given on the website. We are currently summarizing these results in a research paper.

The project was initiated during the #versusvirus hackathon from April 3 to April 5. Since then, it was selected for additional funding from the hackathon and was cited in several media reports, such as at the NZZ, a major Swiss high-quality newspaper.

Content

  • trendecon: R package to construct long daily time series from Google Trends.
  • www.trendecon.org: Website with daily economic indicators based on Google searches in Switzerland.
  • Newspaper article: Article in Neue Zürcher Zeitung (in German).
  • Makronom article: Article in Makronom, a German online magazine for economic policy, by two of our contributors.
  • KOF article: Article in KOF Bulletin, monthly magazine of KOF Swiss Economic Institute, by two of our contributors.

Contributors

  • Angelica Becerra(Statistician and Programmer, ETH KOF)
  • Vera Z. Eichenauer(Economist, ETH KOF)
  • Ronald Indergand (Head of Short Term Economic Analyses, SECO)
  • Stefan Legge(Economist, University of St.Gallen)
  • Isabel Martinez(Economist, ETH KOF, formerly SGB)
  • Nina Mühlebach (Economist, ETH KOF)
  • Furkan Oguz (Economist, ETH KOF)
  • Christoph Sax(Economist and data scientist, cynkra)
  • Kristina Schuepbach (Economist, SGB and University of Bern)
  • Severin Thöni (Programmer, ETH KOF)
  • Uwe Thümmel(Economist, University of Zurich)
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