30337 - POLICY EVALUATION
Course taught in English
Go to class group/s: 23
Synchronous Blended: Lessons in synchronous mode in the classroom (for a maximum of one hour per credit in remote mode)
The exam code 30320 ‘Quantitative methods for social sciences - module 2 (Statistics)’ is a prerequisite of the exam code 30337 Policy evaluation
The course provides an introduction to the main tools used in data analysis and applied empirical research, with a focus on the identification of causal relationships. The methods covered in the course will enable students to investigate some of the most important policy issues facing modern governments and societies, and to assess quantitatively the effects of policy interventions implemented to tackle them. Examples of policy analysis that will be explored in the course are tax policy, social insurance, labor market policies and gender inequality.
- Review of basic statistics concepts and the ordinary least squares regression model
- Correlation and causality
- The potential outcomes framework, treatment effects, and the selection problem
- Omitted-variable bias
- Randomized controlled trials
- Natural experiments
- Experiments with imperfect compliance and the instrumental variable approach
- Regression discontinuity design
- Panel data, difference-in-differences and the synthetic control method
- Event studies
- Formulate policy-relevant research questions
- Interpret quantitative academic and policy empirical analyses
- Reproduce empirical analyses
- Develop an empirical research design
- Analyze data applying the main technical tools of applied empirical economics and policy evaluation
- Face-to-face lectures
- Exercises (exercises, database, software etc.)
- Group assignments
Students will work in team on problem sets and on empirical analyses of actual data using the econometric software package STATA.
The final grade is based on group work and a written final exam.
- Group problem sets: problem sets will be provided throughout the course. Students are expected to hand in written answers to the problem sets. The problem sets are intended to assess the students’ ability to apply the research methods covered in the course, by reproducing and/or developing empirical analyses. The exercises in the problem sets require the use of the econometric software STATA. The students’ ability to interpret the econometric results of their or other analyses will also be assessed
- Research project proposal: each group will present a research project proposal at the end of the course. The group research project proposal is intended to evaluate the students’ ability to formulate policy-relevant research questions and develop a research design suitable for answering those questions
- Written exam: The exam consists of a set of closed and/or open questions. It aims to assess students’ knowledge of the methods covered in the course, their advantages, disadvantages and suitability to answer specific research questions. It also tests the students’ ability to interpret the results of academic and/or policy empirical analyses similar to those examined during the course
The final grade is determined as the maximum between:
- the grade obtained in the final written exam
- a weighted average of the group research project proposal and the final written exam
For non-attending students, assessment is based on the final written exam, with the same content of the exam for attending students. The final grade is the grade obtained in the final written exam.
All the material relevant for the final exam is covered in the slides used in class, which are posted on Bboard. Slides and students' own notes will be the main reference for the exam. For this reason, attendance in class is strongly recommended. Additional reading materials are listed below. Further references to academic papers will be provided in the course syllabus. Neither the books nor the papers constitute material for the exam. Students are, however, strongly encouraged to read them, since the exam may require to interpret the results of empirical analyses similar to those presented therein.
- Angrist, J. and J. S. Pischke (2014). Mastering Metrics, Princeton University Press
Cunningham, S. (2021). Causal Inference: The Mixtape, Yale University Press
Stock J.H. and M.W. Watson (2015). Introduction to Econometrics, Pearson
Huntington-Klein, N. (2021). The Effect: An Introduction to Research Design and Causality, Chapman and Hall/CRC
- See list provided in the course syllabus