Course code Ekon5083
Credit points 3
Economic Forecasting
Total Hours in Course81
Number of hours for lectures12
Number of hours for seminars and practical classes12
Independent study hours57
Date of course confirmation19.10.2011
Responsible UnitInstitute of Computer Systems and Data Science
Course developer
Irina Arhipova
Dr. sc. ing.
Course abstract
The subject of the economic forecasts course is the definition and optimal decision making of the following social-economic process problems: forecast methods of probabilistic situation, perspective tasks definition, development goals definition and analysis. The tasks of the economic forecast course are: analysis of the common tendencies of subjects, expert opinions about analyzing subject, the development path of the probabilistic subject, the problem situation analysis, the scientific decision evaluation. The main topics are related to expert forecast methods, statisticalforecastmethods.
Learning outcomes and their assessment
After completing the course student will have:Knowledge - is able to show the depth or extends knowledge and understanding of the forecasting methods, the perspective problem, development objectives and study, the optimal decision-making in the management of socio-economic development process; is able to apply knowledge of economic research related to the cross discipline fields.Skills – is able to independently use the theory, methods and problem-solving skills to carry out research of object nature, characteristics and trends, as well as inter-related objects correlative study of the relationship. Is able to forcefully explain and discuss the development path of the object under study, the realization date and a specific research problem situation.Competence – is able to independently formulate and critically analyze the research object development in master thesis using data processing application software, to make an optimal decision-making process ofsocio-economictasks.
Compulsory reading
1. Arhipova I., Bāliņa S. Statistika ekonomikā un biznesā. Risinājumi ar SPSS un Microsoft Excel. Macību līdzeklis. 2.izdevums. Rīga: Datorzinību centrs, 2006. 364 lpp.
2. Krastiņš O. Ekonometrija. Mācību grāmata augstskolām. Rīga: LR Centrālā statistikas pārvalde, 2003. 207 lpp. Ir LLU FB (~ 60 eks.)
3. Šķiltere D. Pieprasījuma prognozēšana: Mācību līdzeklis. Rīga: Latvijas Universitāte, 2001. 84 lpp. Ir LLU FB (1 eks.)
Further reading
1. Vasermanis E., Šķiltere D., Krasts J. Prognozēšanas metodes. Mācību līdzeklis. Rīga: Latvijas Universitāte, 2004. 129 lpp.
2. Yaffee Robert A., Monnie McGee. Introduction to Time series Analysis and Forecasting with applications of SAS and SPSS. San Diego etc.: Academic Press, 2000. 528.p.
3. Frolova L. u.c. Darba tirgus pieprasījuma izlgtermiņa ilgtermiņa prognozēšanas sistēmas izpēte un pilnveidošanas iespēju analīze. Rīga: LR LM,2007. 176 lpp.
Periodicals and other sources
1. Journal of business forecasting: methods and systems. Editor: Dr. Chaman L. Jain, St. John's University. ISSN: 0278-6087.
2. Journal of Forecasting. John Wiley & Sons, Inc. ISSN (printed): 0277-6693.