First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Economics and Political Science
Course unit
ECM0013197, A.A. 2017/18

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course Second cycle degree in
EP2422, Degree course structure A.Y. 2017/18, A.Y. 2017/18
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Degree course track ECONOMICS [002PD]
Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination MICROECONOMETRICS
Department of reference Department of Economics and Management
Mandatory attendance No
Language of instruction English
Single Course unit The Course unit CANNOT be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Teacher in charge LORENZO ROCCO SECS-P/02

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses SECS-P/05 Econometrics 6.0

Mode of delivery (when and how)
Period Second semester
Year 1st Year
Teaching method frontal

Organisation of didactics
Type of hours Credits Hours of
Hours of
Individual study
Lecture 6.0 42 108.0 No turn

Start of activities 26/02/2018
End of activities 01/06/2018

Prerequisites: Students are required to have a good command of multivariate regression analysis and discrete choice models
Target skills and knowledge: The main focus will be on the problem of causal inference. Students will learn conditions and methods to identify causal effects and policy relevant parameters in microeconomic contexts.
Examination methods: The exam is composed of a written test (65 percent) and a short paper (35 percent) based on an individual project. To pass, both parts need to receive a positive evaluation.
Assessment criteria: Students will be evaluated on their ability of applying the concepts and tools learned in class to different contexts and situations. Moreover, precision, clarity and originality will be considered in the evaluation of the individual project.
Course unit contents: Definition of causal effects
Evaluation of causal effects in an experimental setting
Evaluation of causal effects in an observational setting
The problem of selection
Identification of causal effects by means of
1) Regression analysis and matching techniques
2) Instrumental Variables
3) Difference in Differences methods
4) Regression Discontinuity Design (sharp and fuzzy)
Introduction to the marginal treatment effect and the policy relevant treatment effects
Tutorials on using STATA for the microeconometric analysis.
Planned learning activities and teaching methods: lectures and tutorials
Additional notes about suggested reading: Course slides and additional material will be available on the course website
Textbooks (and optional supplementary readings)
  • Angrist J. and Pischke, Mostly Harmless Econometrics. --: Princeton University Press, 2009. Cerca nel catalogo
  • Cameron A.C. and Trivedi P.K., Microeconometrics using Stata. --: Stata Press, 2010. Cerca nel catalogo