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.
Private Study: 128 hours
Contact Hours: 24 hours
Total: 150 hours
Optional module for students of the Ph.D. in Economics and PhD Agri-environmental economics.
Journal Paper Replication Report (five thousand words) (50%)*
Presentation (20 minutes) (50%)
*This element is pass compulsory and must be passed to achieve the learning outcomes of the module
Reassessment Instrument: 100% coursework
The University is committed to ensuring that core reading materials are in accessible electronic format in line with the Kent Inclusive Practices.
The most up to date reading list for each module can be found on the university's reading list pages.
See the library reading list for this module (Canterbury)
On successfully completing the module students will be able to:
1 Read intelligently all empirical research (with a proper understanding of the underlying methodology of inference and identification strategy), and
2 Conduct empirical research suitable for publication in any economics or econometrics journal
3 Learn and understand new techniques not covered in the course with a view to implementing them in their own research
4 Apply econometrics methods to micro data
5 Understand and explain their identification strategy in new circumstances
6 Handle real data with confidence
7 Understand the conditions under which particular estimators are appropriate.
University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. However, courses, services and other matters may be subject to change. Please read our full disclaimer.
