ECON50560 PhD Econometrics

Academic Year 2017/2018

This module provides students with a profound understanding of state-of-the-art econometric methods. The course places particular emphasis on methods of causal inference such as randomized experiments, fixed-effect regressions, difference-in-difference, matching, synthetic controls and regression discontinuity. In assignments and presentations, students will discuss the most recent developments in these methods and apply them using statistical software.

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Curricular information is subject to change

Learning Outcomes:

1) Develop a deep understanding of causal inference.
2) Apply state-of-the art methods to own research projects
3) Assess the implications of model assumptions using Monte Carlo simulations
4) Learn about the latest developments in econometrics

Student Effort Hours: 
Student Effort Type Hours
Lectures

24
Seminar (or Webinar)

24
Computer Aided Lab

24
Autonomous Student Learning

180
Total

252
 
Requirements, Exclusions and Recommendations

Not applicable to this module.



 
Description % of Final Grade Timing

Not recorded

Compensation

This module is not passable by compensation

Remediation