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B030596 - ELEMENTS OF POLICY EVALUATION METHODS
Main information
Teaching Language
Suggested readings
Teaching Methods
Type of Assessment
Course program
Academic Year 2021-22
Coorte 2020 - Second Cycle Degree in STATISTICS AND DATA SCIENCE
Course year
Second year - Second Semester
Belonging Department
Statistics, IT and its applications "G. Parenti" (DISIA)
Course Type
Single education field course
Scientific Area
SECS-S/01 - STATISTICS
Credits
6
Teaching Hours
48
Teaching Term
21/02/2022 ⇒ 31/05/2022
Attendance required
No
Type of Evaluation
Final Grade
Course program
show
Lectureship
Mutuality
Course teached as:
B029751 - POLICY EVALUATION METHODS
Second Cycle Degree in POLITICS, INSTITUTIONS AND MARKET
Curriculum ISTITUZIONI E MERCATI
B029751 - POLICY EVALUATION METHODS
Second Cycle Degree in POLITICS, INSTITUTIONS AND MARKET
Curriculum ISTITUZIONI E MERCATI
Teaching Language
English
Suggested readings (Search our library's catalogue)
Imbens G.W., Rubin D.B. (2015).
Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction.
Cambridge University Press
Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction.
Cambridge University Press
Teaching Methods
Theoretical lectures and practical labs
Type of Assessment
Final grades are based on the results obtained in three intermediate tests (a midterm test and two projects) and in the final oral exam.
Course program
1) Introduction to casual inference
2) Randomized experiments
- Methods based on randomization
- Regression models for randomized experiments
3) Observational studies
- Design: Unconfoundedness and Overlap; Propensity score; Subclassification, matching and trimming to assess and improve covariate balance
- Analysis: Methods based on Propensity Score; Sensitivity analysis to assess unconfoundedness
- Methods for non-binary treatments
4) Miscellanea
- Instrumental Variables
- Regression-discontinuity designs
- Difference-in-differences strategies
- Synthetic control methods
Each method will be illustrated using empirical analyses from various fields: economics (labor, population and development economics), social policy and other social sciences.
2) Randomized experiments
- Methods based on randomization
- Regression models for randomized experiments
3) Observational studies
- Design: Unconfoundedness and Overlap; Propensity score; Subclassification, matching and trimming to assess and improve covariate balance
- Analysis: Methods based on Propensity Score; Sensitivity analysis to assess unconfoundedness
- Methods for non-binary treatments
4) Miscellanea
- Instrumental Variables
- Regression-discontinuity designs
- Difference-in-differences strategies
- Synthetic control methods
Each method will be illustrated using empirical analyses from various fields: economics (labor, population and development economics), social policy and other social sciences.