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Course 2019-2020 a.y.

30337 - POLICY EVALUATION

BIG
Department of Social and Political Sciences

Course taught in English

Go to class group/s: 23

BIG (8 credits - II sem. - OB  |  6 credits SECS-P/06  |  2 credits SECS-S/01)
Course Director:
GIOVANNI ABBIATI

Classes: 23 (II sem.)
Instructors:
Class 23: GIOVANNI ABBIATI


Suggested background knowledge
PREREQUISITES

The exam code 30320 ‘Quantitative methods for social sciences - module 2 (Statistics)’ is a prerequisite of the exam code 30337 Policy evaluation


Mission & Content Summary
MISSION

Introducing the main tools used for data analysis and applied empirical research, focusing in particular on the estimation of causal relationships. The methods covered allow students to address questions that are relevant from a social, economic, and political perspective: Which are the economic returns of one additional year of schooling? Do democratic institutions promote economic development? Do longer prison sentences deter crimes? What are the economic costs of organized crime? What are the effects of immigration? These are just examples of the type of questions that motivate the use of empirical methods.

CONTENT SUMMARY
  • Review of descriptive statistics and the Ordinary Least Squares regression.
  • Correlation and causation.
  • The ideal experiment: the potential outcomes model, treatment effects, and the selection problem.
  • Randomized controlled trials.
  • Natural experiments.
  • Experiments with imperfect compliance and Instrumental Variable.
  • Regression discontinuity designs.
  • Exploiting variation over time: Panel, difference-in-differences, and synthetic control methods.

Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • Recognize interesting research questions.
  • Reproduce empirical analyses.
APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • Develop a research design.
  • Analyze data.

Teaching methods
  • Face-to-face lectures
  • Guest speaker's talks (in class or in distance)
  • Exercises (exercises, database, software etc.)
  • Group assignments
DETAILS

Students work in group on practical examples using the econometric software STATA.


Assessment methods
  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
  •     x
  • Group assignment (report, exercise, presentation, project work etc.)
  • x    
    ATTENDING STUDENTS

    The final grade is based on written final exam, group problem sets, and group presentation.

    • Problem sets: groups consisting of 3-4 students would be formed at the beginning of the course. This grouping is valid for both the group problem sets and the group presentation.
    • Group presentation: each group would present a research project proposal at the end of the course. The presentation format is an open seminar (about 20 min) with Q&As from other fellow students and instructors. A separate instruction for the presentation is provided.

    The final grade is determined as the maximum between:

    • The weighted average of the final written exam (60%), average grade in all problem sets (20%), and group presentation (20%).
    • Using this rule, problem sets and group presentations provide an insurance against having a bad day on the exam day.
    NOT ATTENDING STUDENTS

    The final grade is just grade received in the final exam.


    Teaching materials
    ATTENDING AND NOT ATTENDING STUDENTS

    All the material relevant for the final exam is covered in the slides used in class, which is posted on Bboard. Slides and your own notes should be your main reference, for this reason attendance in class is strongly recommended (though not imposed, see below for more on this). Below there is a list of additional reading materials. Neither the books nor the papers constitute material for the exam. You are, however, strongly encouraged to read them (skimming through the technical details), as the exam consists in interpreting the results of empirical analyses similar to those presented therein – though not the same ones.

    • Books:
      • J. ANGRIST, J.S. PISCHKE, Mastering Metrics, Princeton University Press, 2014.
      • J.H. STOCK,  M.W. WATSON, Introduction to Econometrics, Pearson, 2015.
    Last change 05/07/2019 16:09