Vilket gap-mått är bäst lämpat vid inflationsprognoser?-En empirisk studie
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2017-07-03
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Abstract
To forcast inflation is an important part of the Central bank’s role. The aim with this thesis is to study if the unemployment gap is a better measure than the GDP-gap when it comes to forcasting inflation. Our theoretical framework builds on the theory of the Phillipscurve and Okun’s law. We are using quarterly data from period 1993 to 2016. The GDP-gap is estimated with two different methods, the one-sided HP-filter and linear regression model. A directly forcast is used with a forcast horizon of one quarter, four quarters and eight quarters. The differences is marginal between the two methods, which makes it hard to draw a conclusion of which of the two methods are best suited. In our thesis, the unemployment-gap shows a generelly better result.
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inflation, BNP, arbetslöshet, prognostisering, autoregressivmodell, Phillipskurvan, Okuns lag, HP-filter, linjärregression, trend, gap-mått