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Utländska avkastningskurvors prediktion av svensk ekonomisk tillväxt

Hedman, Fredrik LU and Skogsborg, Jacob (2019) NEKH02 20182
Department of Economics
Abstract
This thesis extends Chinn & Kucko`s (2015) article which examines if a country's yield curve can predict its economic growth. The results show that Sweden's yield curve is not a particularly good predictor of the Swedish industrial production growth. In order to develop the article, the purpose of this thesis is to determine if the German and US yield curves can be used in order to predict the Swedish future GDP growth. It uses two types of least-square regressions in order to achieve its purpose; the in-sample regression and the out-of-sample forecast. The in-sample regression uses all available data to calculate whether the yield curves has a significant impact on GDP growth. The out-of-sample forecast does a similar calculation but only... (More)
This thesis extends Chinn & Kucko`s (2015) article which examines if a country's yield curve can predict its economic growth. The results show that Sweden's yield curve is not a particularly good predictor of the Swedish industrial production growth. In order to develop the article, the purpose of this thesis is to determine if the German and US yield curves can be used in order to predict the Swedish future GDP growth. It uses two types of least-square regressions in order to achieve its purpose; the in-sample regression and the out-of-sample forecast. The in-sample regression uses all available data to calculate whether the yield curves has a significant impact on GDP growth. The out-of-sample forecast does a similar calculation but only uses data previous to the date from when the forecast begins. Results from the in-sample regressions shows that the Swedish yield curve has an insignificant impact on the Swedish GDP growth, while both foreign yield curves has a significant impact. Furthermore, the results from the out-of-sample forecast shows that the foreign yield curves are able to make fairly good forecasts of the Swedish GDP growth. On the other hand, the yield curves tend to lose predictability when the economy is in a state of shock or crisis. (Less)
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author
Hedman, Fredrik LU and Skogsborg, Jacob
supervisor
organization
alternative title
En studie om de tyska och amerikanska avkastningskurvorna kan användas för att prognostisera svensk BNP tillväxt
course
NEKH02 20182
year
type
M2 - Bachelor Degree
subject
language
Swedish
id
8968734
date added to LUP
2019-02-15 14:53:53
date last changed
2019-02-15 14:53:53
@misc{8968734,
  abstract     = {This thesis extends Chinn & Kucko`s (2015) article which examines if a country's yield curve can predict its economic growth. The results show that Sweden's yield curve is not a particularly good predictor of the Swedish industrial production growth. In order to develop the article, the purpose of this thesis is to determine if the German and US yield curves can be used in order to predict the Swedish future GDP growth. It uses two types of least-square regressions in order to achieve its purpose; the in-sample regression and the out-of-sample forecast. The in-sample regression uses all available data to calculate whether the yield curves has a significant impact on GDP growth. The out-of-sample forecast does a similar calculation but only uses data previous to the date from when the forecast begins. Results from the in-sample regressions shows that the Swedish yield curve has an insignificant impact on the Swedish GDP growth, while both foreign yield curves has a significant impact. Furthermore, the results from the out-of-sample forecast shows that the foreign yield curves are able to make fairly good forecasts of the Swedish GDP growth. On the other hand, the yield curves tend to lose predictability when the economy is in a state of shock or crisis.},
  author       = {Hedman, Fredrik and Skogsborg, Jacob},
  language     = {swe},
  note         = {Student Paper},
  title        = {Utländska avkastningskurvors prediktion av svensk ekonomisk tillväxt},
  year         = {2019},
}