BERGAMO
Dati Generali
Periodo di attività
Syllabus
Obiettivi Formativi
This course introduces students to the main theoretical and empirical tools used in applied data analysis and empirical research, with a specific focus on the identification and estimation of causal effects. The course is designed to help students understand how credible empirical evidence can be used to answer policy-relevant questions in economics and the social sciences.
A central objective of the course is to develop students’ ability to critically assess empirical research. Students will learn how to read and evaluate scientific articles, paying particular attention to the research question, the identification strategy, the data used, and the interpretation of empirical results. They will also begin to design and conduct their own empirical analyses using the methods discussed in class.
The course will focus on applied microeconometric tools for impact evaluation and causal inference. These methods will allow students to address questions such as: Does smoking cause cancer? Does an additional year of education increase future earnings? Does job training improve productivity? Does the minimum wage affect unemployment? Does an increase in police presence reduce crime?
By the end of the course, students will be able to formulate policy-relevant research questions, identify appropriate empirical strategies, collect and organize suitable data, and carry out basic empirical analyses using econometric software, with particular reference to Stata. More broadly, students will acquire the foundations needed to interpret empirical evidence and to develop independent applied research projects.
Prerequisiti
There are no specific prerequisites other than the requirements for admission to the programme, as indicated on the programme website: https://ls-eda.unibg.it/en.
However, students are strongly advised to have attended a course in Advanced Econometrics and to have a solid background in basic statistics, econometrics, and hypothesis testing.
Metodi didattici
The course combines traditional lectures with hands-on practical sessions. Lectures will introduce the main theoretical concepts, identification strategies, and empirical methods used in impact evaluation. Practical sessions will allow students to apply these methods to real or simulated data and to become familiar with their implementation using econometric software, particularly Stata.
Both lectures and practical sessions are designed to encourage active participation, critical thinking, and class discussion. Students will be invited to engage with empirical examples, discuss research designs, and interpret results in light of policy-relevant questions.
Verifica Apprendimento
The procedure and content of the exam will be the same for both attending and non-attending students.
Mode 1
This assessment mode is reserved for students who regularly and consistently attend the course lectures. The in-class workshops are an integral part of the course and are reserved for students who attend lectures on a regular basis. Participation in the in-class workshops alone is not sufficient to qualify for this assessment mode.
The detailed attendance requirements and the procedure for verifying attendance will be communicated at the beginning of the course. Students who do not meet the attendance requirements, or who do not take part in the required in-class activities, will be assessed according to Mode 2.
For students assessed under Mode 1, the final grade will be based on two components:
In-class group work – 40% of the final grade
- During the course, four dedicated in-class workshops will be organized. In each workshop, students will work in small groups on applied exercises, empirical applications, or research-design tasks related to the topics covered in class.
- The activities may involve the discussion of an empirical paper, the formulation of a research question, the identification of a suitable empirical strategy, the interpretation of empirical results, or the implementation of basic empirical analyses.
- The assessment will be based on the outputs produced during these in-class sessions. The aim is to evaluate students’ ability to apply the methods discussed in the course, work collaboratively, and critically assess empirical strategies in real time.
Written exam – 60% of the final grade
- The written exam will assess students’ individual understanding of the main concepts, methods, and applications covered in the course. It may include theoretical questions, interpretation of empirical results, discussion of identification strategies, and applied questions related to impact evaluation.
Mode 2 – Comprehensive written exam
Mode 2 is available to all students. It applies to non-attending students, to students who do not meet the requirements for Mode 1, and to attending students who prefer to be assessed entirely through a written exam.
Students assessed under Mode 2 will take a comprehensive written exam covering the entire course programme. The exam will be designed to evaluate both theoretical knowledge and the ability to apply empirical methods to policy-relevant questions.
The exam may include questions on causal inference, identification strategies, interpretation of empirical results, research design, and the critical evaluation of empirical studies. Compared with the written exam included in Mode 1, the Mode 2 exam will place greater weight on the independent mastery of the full syllabus, including all readings, methodological topics, and applied examples included in the course materials.
Students who choose Mode 2 will be assessed exclusively on the basis of the comprehensive written exam. In-class workshop activities, if attended, will not contribute to the final grade under this mode.
Students are required to indicate their preferred assessment mode by the end of the fourth week of classes. Students who do not communicate their choice by this deadline will be automatically assigned to Mode 2.
Contenuti
The course covers empirical strategies for addressing applied policy questions. Its main objective is to introduce students to the empirical tools used for counterfactual analysis and impact evaluation. The course will discuss the identification strategies and estimation techniques that are most relevant for estimating causal effects, with particular attention to applications based on observational data.
The course will cover the following topics:
- Review of basic econometric tools: OLS and panel data methods
- The ideal experiment: causal effects and the selection problem
- Matching and propensity score methods
- Randomized controlled trials
- From observational data to natural experiments: instrumental variables
- Difference-in-differences and synthetic control methods
- Regression discontinuity designs
- Quantile regressions
- Machine Learning and Causality
- Selected topics in impact evaluation
The emphasis will be on the practical implementation of each approach using Stata.
Altre informazioni
Most of the papers discussed in class will be available through the UniBG Online Library Services. Datasets, problem sets, additional readings, and other course materials will be made available on the course eLearning page.
Students are expected to check the eLearning page regularly for updates, materials, and announcements related to the course.