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Graduate econometrics II

academic year

Course teacher(s)

Paula Eugenia GOBBI (Coordinator) and Mattia Nardotto

ECTS credits


Language(s) of instruction


Course content

Applied micro-econometrics: a) Instrumental variables, Wald estimate, LATE, Two-Stage-Least Squares, Weak instruments; b) Difference-in-Differences, Difference-in-Difference-in-Differences, Serial correlation problem; c) Regression Discontinuity Design; d) clustering; e) Methods in panel data; f) Non-linear models and duration models. 2. Working with geographical data (raster files). 3. Structural Estimation: a) Introduction to Fortran programming; b) Minimum Distance Estimation and Generalized Method of Moments. Optimal Weighting Matrix; c) Estimation of Standard Errors with bootstrap.

Objectives (and/or specific learning outcomes)

The course should serve graduate students to reinforce their empirical skills, which will then be used in an empirical project and their thesis.


Required knowledge and skills

This class will discuss advanced empirical methods and the practical problems that researchers face when doing empirical research. The focus will be put on analyzing identification strategies that have been used in the empirical literature. We will cover empirical methodologies that are mostly used in micro-econometric analysis and structural papers.

Teaching methods and learning activities

The course consists of 24 hours of lectures, 2 hours each, and 24 hours of exercises. The exercises will be in Stata, and in R and Fortran for the last part of the course. An introductory class on how to program in Fortran will be given by the professor. The exercises will focus on reproducing empirical and structural seminal papers.

Contribution to the teaching profile

This course contributes to the following program learning objectives:
LO 1.2 - Assess the quality of an economic research produced by others
LO 1.3 - Identify and analyse an issue using the relevant analytical tools and methods
LO 2.1 - Adopt a scientific approach to data collection, research and analysis and communicate results with clear, structured and sophisticated arguments
LO 2.2 - Display critical thinking and develop autonomous learning strategies and techniques
LO 3.2 - Thorough and critical ability to use empirical and statistical tools in economics
LO 4.1 - Work and communicate effectively as part of a team in an international and multicultural environment

Course notes

  • Syllabus
  • Université virtuelle

Other information




Method(s) of evaluation

  • Other
  • written examination
  • Oral examination
  • Personal work

Since the class aims at being interactive, the evaluation rules will not be the same in the June and August session. In the June session 20% of the grade will be given to class participation from the presentation of papers related to a lecture topic. 30% of the grade will be given to a referee report on an NBER or CEPR discussion paper of 2017-2020. The final 50% of the grade will be on the reproduction of a paper. In the August sessions, there will also be an oral exam. The weights attached to class participation, the referee report, the reproduction exercise and the exam are 0.2, 0.2, 0.3 and 0.3 respectively

Language(s) of evaluation

  • english