Causal Inference in Empirical Economics - 4 ECTS

We, as human beings, tend to attribute cause and effect to observations quite quickly, even if such a causal relationship does not really exist. Causal inference is the science of the study of causal relationships and gives us tools to study rigorously if an intervention, action, or treatment causally determines a certain outcome. The importance of causal inference has been increasing, and in fact two recent Nobel prizes in Economics, in 2019, and in 2021, were awarded for methods to study causality.

Organised by Wageningen School of Social Sciences (WASS)

Mon 5 September 2022 until Fri 28 October 2022

Duration Registration deadline: 22 August 2022


Dr. Elena Fumagalli, Dr. Karlijn Morsink (both Utrecht University) and Dr. Mark Treurniet (University of Groningen)


Causal inference is required to answer questions such as “What is the impact of social distancing on the spread of COVID-19?”, “What is the effect of minimum wages on employment?”, or “To what extent do increases in food prices increase conflict?” In this “Advanced Causal Inference” course five development economists from both Wageningen University (WUR) and Utrecht University (UU), will teach state-of-the-art causal inference methods for both experimental and quasi-experimental designs, and help students to apply these to their own research designs.

The course will be taught in hybrid form: each week there will be one physical lecture (either in Wageningen or in Utrecht) and the rest of the meetings will be online. Students that are staying abroad will be allowed to participate online if they participate actively.

Learning objectives
After successful completion of this course, participants are expected to be able to:

  1. Use economic theory to design a (quasi) experiment

  2. Apply and evaluate statistical techniques in terms of valid causal inference
  3. Appraise various experimental design choices
  4. Appraise various quasi-experimental methods
  5. Practice with programming simulations

Course entry requirements

● DEC-32806 Impact Assessment of Policies and Programmes at WUR or ECRMRS1 Econometric Methods 1 at UU or a similar course at another university, and
● YSS-34306 Advanced Econometrics at WUR or ECRMRS1 Econometric methods 2 + Research skills: Data handling at UU or a similar course at another university, and
● Being able to program in Stata.


● Lectures: The course material will be discussed in fourteen interactive lectures.
● Assignments: Students will replicate some empirical results from highly-cited papers by implementing estimation procedures in Stata.


● Question hours to discuss progress with Stata assignments.
● Weekly Q&A to help students with the material.


The student needs to pass each:
A. Three Stata assignments (pass/fail grading)
B. Written exam with open questions (minimum 5.5 to pass)

Tentative schedule

Week 1: From theory to design
6-9 9.30 Lecture 1 Karlijn
7-9 9.30 Lecture 2 Karlijn
8-9 9.30 Q&A Karlijn
Week 2: Causal inference in rondomized experiments
12-9 9.30 Lecture 3 Mark
13-9 9.30 Question hour Stata assigment: Simulation Mark
14-9 9.30 Lecture 4 Mark
15-9 9.30 Q&A Mark
Week 3: Avanced randomized designs
19-9 9.30 Lecture 5 Maarten
21-9 9.30 Lecture 6 Maarten
22-9 9.30 Q&A: Application to student's research design Maarten
TBD 9.30 Deadline Stata Assignment 1: Simulation
Week 4: Quasi-experimental methods I
27-9 9.30 Lecture 7 Robert
28-9 9.30 Lecture 8 Robert
29-9 9.30 Question hour Stata assignment: quasi Robert
Day 3 9.30 Q&A: Application to student's research design Robert
Week 5: Quasi-experimental methods II
4-10 9.30 Lecture 9 Elena
TBD Deadline Stata Assignment 1: quasi
5-10 9.30 Lecture 10 Elena
6-10 9.30 Q&A: Application to student's research design Elena
Week 6: Power, ethics, and pre-analysis plans
11-10 9.30 Lecture 11 Karlijn, Maarten
13-10 Question hour Stata assignment: Power
12-10 9.30 Lecture 12 Karlijn, Maarten
13-10 9.30 Q&A: Application to student's research design Karlijn, Maarten
Week 7: Self study
Deadline Stata Assignment 3: Power Via Brightspace
20-10 9.30 Q&A Optional Via Brightspace
Week 8: Exam
24-10 Take home-exam

Please find more programme details and readings in the course outline.

Course fee 

WGS PhDs with TSP, UU PhDs, UG PhDs, WU MSc, UU MSc € 0
a) All other PhD candidates b) Postdocs and staff of the above mentioned Graduate Schools € 650
All others € 975

Cancellation conditions:

The participants can cancel their registration free of charge 1 month before the course starts. A cancellation fee of 100% applies if a participant cancels his/her registration less than 1 month prior to the start of the course.

The organisers have the right to cancel the course no later than one month before the planned course start date in the case that the number of registrations does not reach the minimum.

The participants will be notified of any changes at their e-mail addresses.