This module introduces students to applied econometrics using a general-purpose statistical software package (e.g., Stata or R), which is suitable for those intending to undertake postgraduate training in economics and/or becoming professional economists.
The module assumes a basic knowledge of statistics and quantitative methods and is designed for students who have followed Stage 1 modules in mathematics and statistics and who have taken relevant Stage 2 modules in econometrics.
What distinguishes this module is the adoption of the modern learning-by-doing approach to teaching econometrics, which emphasises the application of econometrics to real world problems. The focus is on understanding the theoretical aspects that are critical in applied work and the ability to correctly interpret empirical results.
Total contact hours: 31 hours
Private study hours: 119
Total study hours: 150
This module is compulsory for BSc Economics with Econometrics and BSc Financial Economics with Econometrics
This module is optional for all other Single and Joint Honours degree programmes in Economics.
This module is not available to students across other degree programmes in the University.
Main Assessment Methods:
*Temporary Assessment Methods 2022/23*
Problem Sets (10%)
Online Test 1 (7%)
Online Test 2 (13%)
Examination, 2 hours (70%)
Reassessment Instrument: 100% exam
C F Baum, Introduction to Modern Econometrics Using STATA, STATA Press, 2006
J M Wooldridge, Introductory Econometrics – A Modern Approach (5th ed), South-Western, 2013 (International Student Edition)
Kennedy, P., 2008, A Guide to Econometrics, 6th edition, Blackwell.
See the library reading list for this module (Canterbury)
On successfully completing the module you will be able to:
1. Understand and abstract the cross-section and panel properties of (micro) economic data
2. Synthesise and critically compare different (micro)econometric analyses of an economic issue
3. Demonstrate analytical skills that can be used to formulate and consider a range of econometric problems and issues
4. Practise the use of econometric concepts in relation to cross-section and panel data analyses.
5. Demonstrate critical understanding of statistical, graphical and numerical data analyses
6. Collate, examine and interpret cross-section and panel data in the context of economic theory and policy
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