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2021/2022  BA-BHAAV6008U  Forecasting in Business and Economics

English Title
Forecasting in Business and Economics

Course information

Language English
Course ECTS 7.5 ECTS
Type Elective
Level Bachelor
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 120
Study board
Study Board for BSc in Economics and Business Administration
Course coordinator
  • Natalia Khorunzhina - Department of Economics (ECON)
Main academic disciplines
  • Economics
Teaching methods
  • Blended learning
Last updated on 15-02-2021

Relevant links

Learning objectives
Upon the end of the course, the students will be able to:
  • Understand various important concepts of forecasting in the areas of economics and business,
  • Understand different approaches to modeling trend, seasonality and persistence,
  • Use the analytical tools that econometricians employ to analyze data
  • Tailor-make models for their applications and use them to produce forecasts in economics and business,
  • Use packaged computer programs for the forecasting purpose, and
  • Complete basic programming tasks using programming language R.
Course prerequisites
Forecasting of time series requires the use of econometric models. The course assumes familiarity and completed bachelor courses in economics, basic econometrics and regression analysis. However, the necessary econometrics will be reviewed.
Prerequisites for registering for the exam (activities during the teaching period)
Number of compulsory activities which must be approved (see section 13 of the Programme Regulations): 2
Compulsory home assignments
In order to qualify for the exam, each student has to submit:
Assignment 1: Midterm project of maximum 5 pages based on data of their own choice.
Assignment 2: Everyone who handed in Assignment 1 has to read and give written feedback to two fellow student's midterm project assigned randomly.
Forecasting in Business and Economics:
Exam ECTS 7,5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 15 pages
Assignment type Written assignment
Duration Written product to be submitted on specified date and time.
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
Course content, structure and pedagogical approach

Accurate forecasting of future events and their outcomes is a crucial input into a successful business or economic planning process. Forecasting is used to answer important questions, such as: How much profit will the business make? How much demand will there be for a product or service? How much will it cost to produce the product or offer the service? How much money will the company need to borrow? When and how will borrowed funds be repaid? Businesses must understand and use forecasting in order to answer these important questions. This course provides an introduction to the application of various forecasting techniques.
This course aims to introduce quantitative methods and techniques for time series modeling, analysis, and forecasting.  Emphasis will also be put on the applications in economic and business related areas.  Computing is an integral part of this course, therefore all students are expected to do data analysis, modeling and forecasting with computer programming software.
The focus of the course is to use past data to predict the future.  The key concept is that there is an underlying process that gives rise to the data.  Using statistical properties of that process, we can develop forecasts. Forecasting methodology will be presented in a lecture format in the first part of each class meeting. The application, however, is the centerpiece of the presentation. In the second part of the class meeting, students will work on in-class applications. 
We will start with simple models that are widely used in business and progress to modern methods that are used by professional forecasters and economists. We will be studying basic components of time-series data, such as trend, seasonal, and cyclical components, as well as basic model specification techniques, such as moving average and auto regressions, used in the forecasting of time-series. 
All forecasting methods will be illustrated with detailed real world applications designed to mimic typical forecasting situations. The course uses applications not simply to illustrate the methods but also drive home an important lesson, the limitations of forecasting, by presenting truly realistic examples in which not everything works perfectly! Examples of the applications include, but not limited to, forecasting retail sales, hotel occupancy, fishery output, consumer loan requests, predicting expansion of fast food chain stores, modeling and forecasting macroeconomic activity indices such as Gross Domestic Product, unemployment and inflation, modeling development of a small open economy, forecasting New York Stock Exchange index and currency exchange rates and many other applications.

The course’s development of personal competences: 
During the course, students will develop theoretical, empirical and programming skills necessary for handling the time series analysis, models and forecasts.


Description of the teaching methods
Lectures and exercises in computer labs.

Students are expected to write a small mid-term paper, and complete one peer-to-peer feedback assignment and write a 15-page final exam individual paper as an examination requirement. The students will be assessed by the research paper based on the individual forecasting project with actual economic and business data.
Feedback during the teaching period
Office Hours
Student workload
Preparation / exam 170 hours
Classes 36 hours
Expected literature

Diebold, F. X. Elements of Forecasting, 4th Ed. (Mason, OH: Cengage Publishing, 2007).

Last updated on 15-02-2021