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Course 2016-2017 a.y.

20295 - MICROECONOMETRICS


CLMG - M - IM - MM - AFC - CLEFIN-FINANCE - CLELI - ACME - DES-ESS - EMIT - GIO
Department of Economics

Course taught in English


Go to class group/s: 31

CLMG (6 credits - II sem. - OP  |  SECS-P/05) - M (6 credits - II sem. - OP  |  SECS-P/05) - IM (6 credits - II sem. - OP  |  SECS-P/05) - MM (6 credits - II sem. - OP  |  SECS-P/05) - AFC (6 credits - II sem. - OP  |  SECS-P/05) - CLEFIN-FINANCE (6 credits - II sem. - OP  |  SECS-P/05) - CLELI (6 credits - II sem. - OP  |  SECS-P/05) - ACME (6 credits - II sem. - OP  |  SECS-P/05) - DES-ESS (6 credits - II sem. - OP  |  12 credits SECS-P/05) - EMIT (6 credits - II sem. - OP  |  SECS-P/05) - GIO (6 credits - II sem. - OP  |  SECS-P/05)
Course Director:
ENRICO RETTORE

Classes: 31 (II sem.)
Instructors:
Class 31: ENRICO RETTORE


Course Objectives
This course covers theoretical and empirical developments on Microeconometrics, with a focus on program evaluation. It provides students with basic skills to conduct rigorous estimation of the impact of governmental/aid agencies programs. Moreover, it conveys the theoretical background to test implications or assumptions of microeconomic models and to understand empirical applications in several applied fields, such as development, labor, health and education.

The course has an applied focus, but theoretical material is broadly covered. Estimation techniques and econometric theory are discussed during lecture; with each method being motivated by a series of empirical papers. The problem sets focus on helping students understand how these methods can be applied to real world data.


Course Content Summary
  • The course begins with a discussion about reduced form and structural form analysis, the counterfactual notion of causality and the differences between estimation and identification.
  • The main methodological part is devoted to the estimation of causal relationships, including experimental and non-experimental techniques (matching, instrumental variables, regression discontinuity and panel data).

Detailed Description of Assessment Methods
Grades
Problem sets (35%)
  • 4 problem sets.
  • All of them must be submitted.
  • Can be prepared and submitted in groups of 4 or 5 students.
  • They include theoretical questions similar to the ones in the final exam and applied questions with Real Data to solve in STATA.
Presentation (15%)
One presentation in Groups of 4/5 students. Students can choose one of the applied sections (Matching, IV, RDD, DID, Standard Errors) to present a paper of their choice (coordinated with me) that uses the discussed methodology.

Final Exam (50%)
  • Students are allowed to bring to the exam up to 3 sheets of paper (up to A4 size) written on the two sides with anything they want.
  • Dates: 9 Dec (for exchange students), 8 Jan (first round), 29 Jan (second round), 2 Sep (third round)


Textbooks
We will discuss material from the following textbooks (Most of the material in AP and IR is relevant for the course. We will cover only selected chapters of CT and W).
  • Angrist, J. and Pischke, J. (2009) Mostly Harmless Econometrics. Princeton University Press. [AP]
  • Imbens, G. and Rubin, D. (2015) Causal Inference for Statistics, Social and Biomedical Sciences. An Introduction. Cambridge University Press. [IR]
  • Cameron, Colin A. and Pravin K. Trivedi (2005) Microeconometrics. Methods and Applications. Cambridge University Press: New York. [CT]
  • Cameron, Colin A. and Pravin K. Trivedi (2009) Microeconometrics Using Stata. Stata Press.
  • Wooldridge, J. (2010) Econometric Analysis of Cross Section and Panel Data, MIT Press, 2nd Edition. [W]

Papers/Lecture Notes

For each topic, a list of recently published papers is provided (see below). Slides will be provided for each topic and posted online.

Prerequisites
A basic knowledge of econometrics is strongly recommended. Basic knowledge on the use of STATA or similar computer software is also recommended.
Last change 14/07/2016 10:39