Forecasting

Recommended Prerequisites

Students attending this module should be familiar with basic economic, statistical and econometric terminology. Basic knowledge of statistics and econometrics is required. Familiarity with software (in special spreadsheets and econometrics packages) will be useful during classes and for solving exercises.

Teaching Methods

To acquire specific competencies: classes with both a lecture and a tutorial component; class discussion of forecasting exercises; homework; student forecasting projects. To develop generic competencies there is a “mixed evaluation regime“. This regime includes, besides the final exam, homework and exercises in classes, writing and presenting a forecasting project.  

Learning Outcomes

By the end of this unit, the student is expected to be able to:

- Recognise the need for knowing the source, the meaning and the characteristics of the data.

- Suggest and apply adequate transformations to the data.

- Implement different forecasting methods.

- Explain the advantages and disadvantages of different forecasting methods.

- Select, in face of the forecasting context, adequate forecasting methods.

Competencies:

1) Specific:

- Collect, analyse and treat the data required in the forecasting process.

- Present different forecasting methods, discussing their advantages and disadvantages.

- Use software to build and analyse forecasting models.

2) Generic:

- Analyse data.

- Solve problems.

- Use computer programs.

- Write and present reports.

- Plan work activities.

- Make decisions.

- Work in a team.   

Work Placement(s)

No

Syllabus

1. Introduction to the forecasting process.
2. Decomposition of economic time series.
3. Exponential smoothing.
4. Regression and forecasting.
5. Model selection.
6. Univariate models.
7. Multivariate models.
8. Other forecasting methods.   

Head Lecturer(s)

Pedro Miguel Avelino Bação

Assessment Methods

Assessment
Final exam 50% + Forecasting project and exercises solved in classes or at home 50%. Alternatively: Final Exam 100% : 100.0%

Bibliography

BOX, George ; JENKINS, Gwilym M. ; REINSEL, Gregory C. — Time series analysis : forecasting and control. 4th ed.. Hoboken : John Wiley & Sons, 2008. [BP 519.2 BOX]

GREENE, William H. — Econometric analysis. 7th ed.. Boston : Pearson, 2012. [BP 519.8 GRE]

HAMILTON, James D. - Time series analysis. Princeton : Princeton University Press, 1994. [BP 519.2 HAM]

HYNDMAN, Rob; George Athanasopoulos – Forecasting, prinsicples and practice, Otexts, 2014

MAKRIDAKIS, Spyros ; WHEELWRIGHT, Steven C. ; HYNDMAN, Rob J. — Forecasting : methods and applications. 3rd ed.. New York : John Wiley & Sons, 1998. [BP 519.8 MAK]

PINDYCK, Robert S. ; RUBINFELD, Daniel L. — Econometric models and economic forecasts. 4th ed.. Boston : Irwin/McGraw-Hill, 1998. [BP 519.8 PIN]