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ADVANCED EMPIRICAL METHODS FOR ECONOMISTS
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ADVANCED EMPIRICAL METHODS FOR ECONOMISTS
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Academic year 2024/2025
- Course ID
- SEM0143
- Teacher
- Giovanni Mastrobuoni (Lecturer)
- Year
- 2nd year
- Teaching period
- First 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
- Prerequisites
- A good understanding of statistics and econometrics. Linear regressions, means, variances, Maximum likelihood, logit, probit, etc.
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Sommario del corso
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News
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Course objectives
This course covers the basics for doing sound empirical work at the postgraduate level. It is particularly aimed at students and researchers who plan on doing applied work for their thesis. The identification issue of causal relationship when analyzing experimental and non-experimental data represents the unifying topic of the course. We will cover the most common approaches to identify causal relationships: conditional independence assumption, matching, instrumental variables, random assignment, regression discontinuity, synthetic control approach, and difference-in-differences, two-way fixed effects models. I will discuss graphical methods to present the main evidence.
Empirical papers will serve as examples, and should give a taste about how to perform a convincing empirical analysis. The ideal experimental setting is often going to serve as a benchmark case. Empirical exercises using STATA with real data are going to be part of the module. Some tasks might involve replicating empirical results of published papers.
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Results of learning outcomes
At the end of the course students will have a broad understanding on how to perform sound empirical analysis.
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Program
We will cover the most common approaches to identify causal relationships: conditional independence assumption, matching, instrumental variables, random assignment, regression discontinuity, synthetic control approach, and difference-in-differences.
Extra topics may include non-parametric methods and text analysis.
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Course delivery
Most classes will be simple lectures but part of the course delivery may take place in the computer lab.
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Learning assessment methods
During the course students are are going to be asked to present research papers. There are going to be problem sets, a midterm exam and a final exam.
Suggested readings and bibliography
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