To Örebro University

oru.seÖrebro University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
Identifying Useful Indicators for Nowcasting GDP in Sweden
Örebro University, Örebro University School of Business. Unit of Statistics.ORCID iD: 0000-0003-0203-4688
Örebro University, Örebro University School of Business. Unit of Statistics.ORCID iD: 0000-0002-1395-9427
Örebro University, Örebro University School of Business. Unit of Statistics.
2025 (English)Report (Other academic)
Abstract [en]

This paper focuses on identifying useful indicators for nowcasting GDP in Sweden. We analyze 35 monthly indicators spanning the period from 1993 to 2023. Additionally, we evaluate the group-wise performance of these indicators. The analysis is conducted using mixed-data sampling (MIDAS) and mixed-frequency VAR models in both individual and pooled setups forn owcasting. While the primary focus is on nowcasting, we also assess the performance of the indicators for backcasting and forecasting. For nowcasting, we identify 16 indicators in the individual setup and 23 indicators in the pooled setup that outperform the benchmark. Group-wise, indicators belonging to the survey, interest & exchange rates, and public finance groups exhibit strong performance in the individual setup. Notably, in the pooled setup, the output, survey, price, interest & exchange rates, and public finance groups demonstrate strong performance.

Place, publisher, year, edition, pages
Örebro: Örebro University School of Business , 2025. , p. 26
Series
Working Papers, School of Business, ISSN 1403-0586 ; 4/2025
Keywords [en]
Nowcasting, Swedish GDP, MIDAS, Mixed-frequency VAR
National Category
Economics Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:oru:diva-119368OAI: oai:DiVA.org:oru-119368DiVA, id: diva2:1938734
Available from: 2025-02-19 Created: 2025-02-19 Last updated: 2025-09-15Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Free full text

Authority records

Karlsson, SuneMazur, StepanRaftab, Mariya

Search in DiVA

By author/editor
Karlsson, SuneMazur, StepanRaftab, Mariya
By organisation
Örebro University School of Business
EconomicsProbability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 48 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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