Course Unit Page

  • Teacher Denni Tommasi

  • Credits 5

  • SSD SECS-P/05

  • Teaching Mode Traditional lectures

  • Language English

  • Campus of Bologna

  • Degree Programme Second cycle degree programme (LM) in Economics and Economic Policy (cod. 8420)

  • Teaching resources on Virtuale

  • Course Timetable from Sep 19, 2022 to Oct 24, 2022

Academic Year 2022/2023

Learning outcomes

We will build the statistical foundations for field experiments from the ground up. We will discuss the logic of randomized control trials (RCTs) conducted in real-world settings, their strengths and weaknesses compared to other methodologies, and the ways in which experimentation has been, and could be, used to investigate social phenomena. Students will learn how to interpret, design, and execute experiments.

Course contents

The course is targeted to students interested in understanding policy evaluations (i.e., public, health, labour, or development policies) as well as more business-oriented students interested in understanding business evaluations and A/B testing (i.e., useful for understanding user engagement and satisfaction of online features like a new feature or product).


The course is divided as follows:


Week 1: motivating examples of field experiments, potential outcomes framework, assumptions; ATEs, ITTs, LATEs; sampling distributions and randomization inference.


Week 2: blocking and covariate adjustment; balance checks; field experiments with one-sided noncompliance (failure-to-treat); field experiments with two-sided noncompliance (encouragement designs)


Week 3: peer effects; cluster designs; phase-in designs; determining optimal sample size; power calculations.


Week 4: sample attrition, interference between experimental units; heterogeneous treatment effects; mediation and causal mechanisms.


Week 5: Field experiments from A to Z: case studies and student presentations of the outline of the take home project, receiving feedback.


Gerber and Green (2012), “Field Experiments: Design, Analysis and Interpretation”.

Teaching methods

For each topic, we will first introduce the relevant statistical and econometric theory, and then move to Stata codes, examples and applications.

Assessment methods

Problem sets (20%): students will apply the concepts learnt in class through a set of applications using Stata.

Presentations (20%): students will be assigned a paper analysing the results of a field experiment and they will present it in class.

Take home exam (60%): students will be given a set of applied questions they need to answer within 7 days.

Teaching tools

Slides and Stata codes.

Office hours

See the website of Denni Tommasi