This module will cover the fundamental methods for analysis of microeconomic data and equip students to keep up with recent developments in their research area. The lectures will introduce and sketch out the material but the deep understanding of the techniques and how they can be implemented will come from the students own work (through reading, problem sets, actual work with data and one on one support from the module convenor). The module will cover a core set of techniques but also be responsive to the specific needs of students. In particular we will try to cover in more depth those topics that students may need for their doctoral research.
This module is formulated to provide students with a rigorous and broad knowledge of econometric methods especially important for conducting empirical research in microeconomics.
Specific topics to be covered include:
• Identification and Estimation in Micro-econometrics
• Instrumental variable and natural experiments
• Sample Selection and Program Evaluation
• Partial Identification
• Advanced Panel data model
• Mixed models – clustering
• Discrete choice models
• Introduction to Structural Models
• Quantile Regression
• Dynamic Discrete choice models
Total contact hours: 24
Private study hours: 128
Total study hours: 150
Method of assessment
Journal Paper Replication Report (five thousand words) (50%)
Presentation (20 minutes) (50%)
- Cameron, A.C., and P.K. Trivedi, Microeconometrics, Methods and Applications, Cambridge, 2005
- Wooldridge, J.M., Econometric Analysis of Cross Sectional Panel Data, MIT Press, 2001
- A. C. Cameron and P. K. Trivedi: Microeconometrics Using Stata. College Station, TX: Stata Press, 2008.
See the library reading list for this module (Canterbury)
On successfully completing the module students will be able to:
- Read intelligently all empirical research (with a proper understanding of the underlying methodology of inference and identification strategy)
- Conduct empirical research suitable for publication in any economics or econometrics journal.
- Learn and understand new techniques not covered in the course with a view to implementing them in their own research
- Apply econometrics methods to micro data,
- Understand and explain their identification strategy in new circumstances
- Handle real data with confidence
- Understand the conditions under which particular estimators are appropriate
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Credit level 7. Undergraduate or postgraduate masters level module.
- ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
- The named convenor is the convenor for the current academic session.
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