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FORECASTING WITH MIXED FREQUENCY DATA:MIDAS VERSUS STATE SPACE DYNAMIC FACTOR MODEL: AN APPLICATION TO FORECASTING SWEDISH GDP GROWTH
Örebro University, Orebro University School of Business, Örebro University, Sweden.
2013 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Most macroeconomic activity series such as Swedish GDP growth are collected quarterly while an important proportion of time series are recorded at a higher frequency. Thus, policy and business decision makers are often confront with the problems of forecasting and assessing current business and economy state via incomplete statistical data due to publication lags. In this paper, we survey a few general methods and examine different models for mixed frequency issues. We mainly compare mixed data sampling regression (MIDAS) and state space dynamic factor model (SS-DFM) by the comparison experiments forecasting Swedish GDP growth with various economic indicators. We find that single-indicator MIDAS is a wise choice when the explanatory variable is coincident with the target series; that an AR term enables MIDAS more promising since it considers autoregressive behaviour of the target series and makes the dynamic construction more flexible; that SS-DFM and M-MIDAS are the most outstanding models and M-MIDAS dominates undoubtedly at short horizons up to 6 months, whereas SS-DFM is more reliable at long predictive horizons. And finally we conclude that there is no perfect winner because each model can dominate in a special situation.

Place, publisher, year, edition, pages
2013. , 30 p.
Keyword [en]
mixed frequency data, MIDAS regression, state space model, dynamic factor model, Swedish GDP growth
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:oru:diva-29475ISRN: ORU-HHS/STA-AS-2013/0010--SEOAI: oai:DiVA.org:oru-29475DiVA: diva2:627732
Subject / course
Statistik
Uppsok
Social and Behavioural Science, Law
Supervisors
Examiners
Available from: 2013-08-09 Created: 2013-06-12 Last updated: 2013-08-09Bibliographically approved

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Orebro University School of Business, Örebro University, Sweden
Probability Theory and Statistics

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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