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Quasi-Real-Time Data of the Economic Tendency Survey
Konjunkturinstitutet, Stockholm, Sweden.
Statistiska centralbyrån, Stockholm, Sweden.
Konjunkturinstitutet, Stockholm, Sweden.
Örebro University, Orebro University School of Business, Örebro University, Sweden.ORCID iD: 0000-0002-4840-7649
2017 (English)In: Journal of Business Cycle Research, ISSN 2509-7962Article in journal (Refereed) In press
Abstract [en]

Survey data from businesses and households are widely used for forecasting and economic analysis. In Sweden, the most important survey of this kind is the Economic Tendency Survey of the National Institute of Economic Research. A shortcoming with this survey is that real-time data of it largely are unavailable. In this paper, we describe how two quasi-real-time data sets of this survey have been constructed – one monthly and one quarterly. The term “quasi-real-time data” refers to data which are not actual real-time data but have been created in order to provide a close approximation to real-time data. The data sets consist of monthly/quarterly vintages of the most important series of the survey, including the main confidence indicators. A natural usage of these data sets is evaluations of model-based forecasts and nowcasts. We illustrate this with an application to Swedish GDP growth. This shows that several of the studied indicators from the Economic Tendency Survey appear to have positive nowcast content for GDP growth.

Place, publisher, year, edition, pages
Springer, 2017.
Keyword [en]
Data revisions, Nowcasting
National Category
Economics
Research subject
Economics
Identifiers
URN: urn:nbn:se:oru:diva-57599OAI: oai:DiVA.org:oru-57599DiVA: diva2:1093959
Available from: 2017-05-08 Created: 2017-05-08 Last updated: 2017-05-11Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf