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The purpose of this thesis is to investigate whether factor augmented vectorautoregression (FAVAR) models estimated using principal component analysis are able to improve monthly inflation rate forecasts for Sweden. We produce 42 forecasts for the period January 2012 to June 2015 and evaluate the forecasts by their root mean square errors as well as their ability to correctly predict the sign of t
