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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

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