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Economics, Macroeconomic Forecasting, Second Cycle

Utbildningsinformation från den publicerade källan. Utbildningen och dess tidsbundna tillfällen hålls åtskilda.

Utbildningsfakta

Kod: NA437A

Macroeconomic forecasting typically relies on time series data. This course intends to provide skills regarding time series econometrics and time series analysis in order to be able to model and forecast macroeconomic variables. During the course, we will cover both the fundamental univariate ARIMA model and the more advanced multivariate VAR model. Topics such as unit roots, cointegration and structural breaks will also be discussed. The focus of the course is objective forecasting methods but we will also touch upon judgemental forecasting, Finally, tools for forecast evaluation will be addressed. Additional information: The course overlaps with Statistics, Time Series Analysis, Second cycle, 5 credits and these courses cannot be used together in a degree.

Behörighet

75 credits of economics courses on the first cycle, as well as Statistics, Basic Course, 15 credits. Alternatively 75 credits of business administration courses on the first cycle, as well as Statistics, Basic Course, 15 credits, and Economics, Basic Course, 30 credits. Alternatively 75 credits of statistics courses on the first cycle, as well as Economics, Basic Course, 30 credits. In addition, the applicant must have completed an independent project of 15 credits in the main field of study as well as Statistics, Econometrics, Intermediate Course, 7.5 credits, and Statistics, Time Series Analysis and Forecasting, Intermediate Course, 7.5 credits or Economics, Financial econometrics 15 credits. The applicant must also have qualifications corresponding to the course English 6/ English level 2 from the Swedish Upper Secondary School.

Utbildningstillfällen

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Källa och uppdatering

Skolverket Susa-navet

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Visa källversion

Publiceringsversion: 8e217193-f5fa-4778-b085-a4521fd03e8d

Kontrollsumma: 1b0dc54c0fc8a359f83ba9dc8f9d468479ce432de4c03bce3b8b33dd67fe3f6c

Senast ändrad enligt källan: 2026-03-12T14:17:26