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
Transferfunktionsmodeller modellering och prognoser av Sjötransportindex
Örebro University, Swedish Business School at Örebro University.
Örebro University, Swedish Business School at Örebro University.
2011 (Swedish)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesisAlternative title
 Transferfunktionsmodeller modellering och prognoser av Sjötransportindex (Swedish)
Abstract [en]

We have by Statistics Sweden (SCB) been given the task of using different dynamic regression models in order to forecast service price index for sea transport. The aim is to see whether these models provide better forecasts than those previously used. This essay aim to identify, estimate and evaluate the selected prediction models.

 

Through our data material we were given access to 28 sightings of sea transport index during the period of 2004 q1 to 2010 q4. We have chosen to evaluate three different transfer function models, one ARIMA model and one naive forecasting model. The input variables we decided to test in our transfer function models were the price of petroleum products, the port activity in Swedish ports and the lending rate of Swedish Central bank.

 

The results of our study suggest that transfer function models generally provide better models than the ARIMA model and the naive forecast model. Results also show that both the transfer function models and ARIMA model seem to provide better models than the naïve forecasting model.  The transfer function model that gave the lowest forecasting errors had interest rate as an input variable.

Place, publisher, year, edition, pages
2011. , 57 p.
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:oru:diva-15908ISRN: ORU-HHS/STA-AG-2011/0002--SEOAI: oai:DiVA.org:oru-15908DiVA: diva2:422953
Subject / course
Statistik
Uppsok
Social and Behavioural Science, Law
Supervisors
Examiners
Available from: 2011-08-12 Created: 2011-06-14 Last updated: 2017-10-17Bibliographically approved

Open Access in DiVA

fulltext(1311 kB)279 downloads
File information
File name FULLTEXT01.pdfFile size 1311 kBChecksum SHA-512
01ac4ed8ba58e91617b3767a77b9d836617dda2fb240830ea40a51a3fb5ef4eecf9734bdccee88f30ab85d785e71d4d1467fc434295a910191214c8e7e24c1ec
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Lundell, Love
By organisation
Swedish Business School at Örebro University
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar
Total: 279 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 162 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