Economics, Macroeconomic Forecasting, Second Cycle, 7.5 credits

Learning outcomes

Upon completion of the course, the students are expected to

• show broad knowledge concerning forecasting within the main fields of the course
• be able to discuss central problems regarding modelling, forecasting and forecast evaluation
• be able to analyse and critically evaluate time series and forecasting models
• within the assigned time be able to conduct empirical analysis of economic data based on relevant quantitative methods and motivate the choices of both data and methods and
• be able to discuss, with a scientific approach, questions within the field of macroeconomic forecasting.

Content

During the course, the students will work with relevant tools within the field of macroeconomic forecasting. The focus is on objective methods based on statistical models and concepts. This includes:

• ARIMA modelling
• VAR models
• Cointegration
• Models for time-varying volatility
• Point, interval and density forecasts
• Forecast evaluation

Examinations and grades

Written Examination, 5 credits (Code: A001)
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Assignments, 2.5 credits (Code: A002)
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

According to the Higher Education Ordinance, Chapter 6, Section 18, a grade is to be awarded on the completion of a course, unless otherwise prescribed by the university. The university may determine which grading system is to be used. The grade must be determined by a teacher specifically nominated by the university (the examiner).

In accordance with university regulations on grading systems for first and second-cycle courses and study programmes (Vice-Chancellor’s decision ORU 2018/00929), one of the following grades is to be used: fail (U), pass (G) or pass with distinction (VG). For courses included in an international master’s programme (60 or 120 credits) or offered to the university’s incoming exchange students, the A to F grading scale is to be used. The vice-chancellor, or a person appointed by them, may decide on exceptions from this provision for a specific course, if there are special grounds for doing so.

The grades used on this course are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Comments on grades

To obtain a passing grade for the course as a whole, a minimum of grade E is required for all components on the course. To arrive at a course grade, the grades awarded for each examination assignment, grades A-E, are first converted to the numerical values 5-1. An average value is then calculated, also taking into account the number of credits for each examination assignment in relation to the total number of credits for the course. The course grade is thus awarded by means of a weighted average of the examination assignments included on the course.

Modes of assessment

Written Examination, 5 credits (Code: A001)
Written Assignments, 2.5 credits (Code: A002)

For students with a documented disability, the university may approve applications for adapted or other modes of assessment.

For further information, see the university's local examination regulations.

Specific entry requirements

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 B" from the Swedish Upper Secondary School.

For further information, see the university's admission regulations.

Other provisions

The course will be given in English.

The course overlaps with Statistics, Time Series Analysis, Second cycle, 5 credits and these courses cannot be used together in a degree.

Students who have been admitted to and registered on a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted (see, the university's admission regulations (in Swedish)). After that, the right to receive tuition and/or supervision expires.

Reading list and other learning resources

Required Reading

Kirchgässner, G. and Wolters, J. (latest edition)
Introduction to modern time series analysis

Additional reading

Diebold, Francis X. (latest edition)
Elements of Forecasting

Additions and Comments

Apart from the main textbook, a number of articles and other material will be used during the course (maximum 100 pages).