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POLICY EVALUATION
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POLICY EVALUATION
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Academic year 2024/2025
- Course ID
- SEM0189
- Teacher
- Ainoa Aparicio Fenoll (Lecturer)
- Year
- 2nd year
- Teaching period
- Second semester
- Type
- Related or integrative
- Credits/Recognition
- 6
- Course disciplinary sector (SSD)
- SECS-P/01 - economics
- Delivery
- Formal authority
- Language
- English
- Attendance
- Optional
- Type of examination
- Written
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Sommario del corso
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Course objectives
The course offers an overview of key tools used in data analysis and empirical research, emphasizing the identification of causal relationships. Students will learn methods that equip them to analyze major policy challenges confronting contemporary governments and societies, and to evaluate the quantitative impact of policy interventions aimed at addressing these issues. Topics of policy analysis covered in the course include anti-poverty interventions, labor market reforms, and gender inequality.
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Results of learning outcomes
By the end of the course, students will be able to:
- Formulate research questions relevant to policy
- Interpret quantitative analyses from academic and policy studies
- Replicate empirical analyses
- Develop an empirical research design
- Analyze data using key technical tools from applied empirical economics and policy evaluation
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Program
- Review of fundamental statistics and the Ordinary Least Squares (OLS) regression model
- Distinguishing correlation from causality
- The potential outcomes framework, treatment effects, and addressing selection bias
- Omitted variable bias
- Randomized controlled trials (RCTs)
- Natural experiments
- Experiments with imperfect compliance and the instrumental variable (IV) approach
- Regression discontinuity design (RDD)
- Panel data, difference-in-differences (DiD), and the synthetic control method
- Event studies
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Course delivery
- Face-to-face lectures
- Exercises (exercises, database, software etc.)
- Group assignments
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Learning assessment methods
- Written individual exam (traditional)
- Group assignment (project work and presentation)
Suggested readings and bibliography
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- Book
- Title:
- Mastering Metrics
- Year of publication:
- 2024
- Publisher:
- Princeton University Press
- Author:
- Angrist, J. and J. S. Pischke
- Required:
- No
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Other books:
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Cunningham, S. (2021). Causal Inference: The Mixtape, Yale University Press
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Stock J.H. and M.W. Watson (2015). Introduction to Econometrics, Pearson
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Huntington-Klein, N. (2021). The Effect: An Introduction to Research Design and Causality, Chapman and Hall/CRC
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