| Unit name | Introduction to Business and Economic Forecasting |
|---|---|
| Unit code | ECONM2038 |
| Credit points | 15 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Dr. Crespo |
| Open unit status | Not open |
| Pre-requisites |
None. |
| Co-requisites |
None. |
| School/department | School of Economics, Finance and Management |
| Faculty | Faculty of Social Sciences and Law |
This unit follows on from the Autumn Term unit in Quantitative Methods. It will be a topics based unit and will normally cover stationary time series models and forecasting, non-stationarity, structural models and vector autoregressive models. The unit will also discuss data acquisition and data handling. This will enable students to be better prepared for dissertations which require the analysis of time series data. The techniques covered are widely used in Economics, Finance and Management and a knowledge of them will also enable students to be better able to apply them in their future work.
Students will learn how to estimate time series models and use them to make forecasts. Understand the concept of non-stationarity, its consequences and how to test for it. Learn how to estimate structural models and vector autoregressive models, and understand how to interpret the results.
Lectures and tutorials.
Formative assessment:
This consists of an assignment in which the student is given a data set to estimate a forecasting model for a particular economic variable. The assignment evaluates the familiarity of the student with the econometric techniques taught in the course. Word length: 2000 words.
Summative assessment:
A two-hour written exam (100%). Questions will be set that test understanding of key concepts such as stationary process, unit roots and Box-Jenkins Methodology. A theoretical model will be provided so that students can demonstrate their ability to derive key parameters and/or provide an interpretation of results derived from time series analysis.
