Advanced Econometrics
Module Code: ECU44152/ECU44154
Module Name: Advanced Econometrics
- ECTS weighting: 10/5
- Semester/term taught: Semester 2
- Contact Hours: 22 hours of lectures and 4 hours of tutorials
- Module Personnel: Lecturer – Professor Alejandra Ramos
Module Learning Aims
The module learning aim is to provide students with a theoretical and applied toolbox of econometric techniques frequently used in applied microeconomics research.
Learning Outcomes
Upon successful completion, students will be able to:
- Derive and understand properties of different econometric models;
- Decide which approach is appropriate for a particular type of data and research question;
- Estimate econometric models using STATA;
- Correctly interpret the results;
- Replicate papers using the econometrics models discussed;
Module Content
Review
- Ordinary Least Squares
- Binary Choice Models
Maximum Likelihood estimation:
- Multinomial models
- Censoring, truncations, and selection
Casual Inference
- Instrumental variables
- Regression discontinuity designs
- Difference-in-differences
Extension: Structural Models*
Recommended Reading List
- Cameron, A. and Trivedi, P. (2005), Microeconometrics: Methods and Applications, Cambridge University Press. · Cunningham, S. (2017), Causal Inference: The Mixtape. (V. 1.7).
- Cameron, A. & Trivedi, P. (2008), Microeconometrics Using Stata, Stata Press.
- Angrist, J. and Pischke, J. (2009), Mostly Harmless Econometrics, Princeton University Press
Module Pre Requisite
JS Econometrics A/B
Assessment Details
10 ECTS students: There will be regular homework accounting for 60% of the overall grade, and group assignment (presentation plus replication exercise) accounting for 40% of the overall grade.
5 ECTS students: There will be regular homework accounting for 60% of the overall grade, and group assignment (presentation) accounting for 40% of the overall grade.
Module Website
Blackboard