Applied Econometrics I
| Code | School | Level | Credits | Semesters |
| ECON2032 | School of Economics | 2 | 20 | Autumn China |
- Code
- ECON2032
- School
- School of Economics
- Level
- 2
- Credits
- 20
- Semesters
- Autumn China
Summary
An introduction to the theory and practice of econometric methods, focusing on regression analysis and its application to economic situations. The module will pay particular attention to the principles of estimation and inference in the multiple regression model, and will rely on illustrations and intuition to develop understanding of the techniques and their interpretation. Students deepen their understanding of the material covered in the the lectures via a series of ‘hands-on’ computer exercises and classes using specialist econometric software (STATA) and a set of tutorials that will review worked examples.
Please note: This module is assessed at the end of Autumn semester. First sit/ Re-sit exams are scheduled normally in the summer and can take the same form as the missing/ failed component of the assessment (exam, essay etc.) or other form, as decided by the School.
Target Students
Year 3 Economics students
Classes
- One 2-hour lecture each week for 11 weeks
- One 1-hour computing each week for 6 weeks
Assessment
- 100% Exam 1 (2-hour): 2 hours written exam
Educational Aims
The main aims of this module are to:• Introduce students to the principles, uses and interpretation of regression analysis most commonly employed in applied economics using cross-section data;• Enable students to undertake empirical analyses using specialist econometric software.The module aims to enable the participants to develop:• Co-ordination with others through problem-based group work;• Digital capabilities through an ability to understand verbal, graphical, mathematical and econometric representation of ideas and analysis.Learning Outcomes
On completion of this module students should be able to:
• Demonstrate understanding of the assumptions, methods and data used in regression analysis.
• Interpret and manipulate the coefficients of multiple regressions and performance criteria.
• Conduct hypothesis testing on the coefficients of regression equations.
• Perform econometric analyses of their own using economic data.
Emphasised Learning outcomes are such that students will be able to:
Knowledge and Understanding:
A4 Demonstrate understanding of verbal, graphical, mathematical and econometric representation of economic ideas and analysis, including the relationship between them.
A5 Show understanding of relevant mathematical and statistical techniques.
Intellectual Skills:
B3 Be able to evaluate, analyse and present quantitative data.
Professional/Practical Skills:
C2 Understand the sources and content of economic data and evidence, as well as appropriate methods of analysis.
Transferable/Key Skills:
D1 Apply mathematical, statistical and graphical techniques in an appropriate manner.
D3 Use appropriate IT packages effectively.