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 actually casually determines a certain outcome.

Organised by Wageningen School of Social Sciences (WASS)

Mon 14 February 2022 until Fri 8 April 2022

Duration Registration deadline: 31 January 2022


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


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. Of course if restrictions change, we may have to move the course online.

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. Write a pre-analysis plan including power analysis

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.
● Each Friday, Q&A to help students apply the material of the week in their own research design.
● Students will receive feedback on their research design from one of the teachers for further improvement after the course.


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
14-2 15.00 hrs Lecture 1 Karlijn
16-2 15.00 hrs Lecture 2 Karlijn
17-2 15.00 hrs Q&A Karlijn
Week 2: Causal inference in rondomized experiments
21-2 15.00 hrs Lecture 3 Mark
22-2 11.30 hrs Question hour Stata assigment: Simulation Mark
23-2 11.30 hrs Lecture 4 Mark
24-2 15.00 hrs Q&A Mark
Week 3: Avanced randomized designs
28-2 15.00 hrs Lecture 5 Maarten
2-3 15.00 hrs Lecture 6 Maarten
4-3 14.00 hrs Q&A: Application to student's research design Maarten
Week 4: Quasi-experimental methods I
7-3 15.00 hrs Deadline Stata Assignment 1: Simulation Via Brightspace
7-3 15.00 hrs Lecture 7 Robert
9-3 15.00 hrs Lecture 8 Robert
11-3 15.00 hrs Q&A: Application to student's research design Robert
Week 5: Quasi-experimental methods II
14-3 15.00 hrs Lecture 9 Elena
15-3 Question hour Stata assignment Elena, Robert
16-3 15.00 hrs Lecture 10 Elena
18-3 15.00 hrs Q&A: Application to student's research design Elena
Week 6: Power, ethics, and pre-analysis plans
21-3 15.00 hrs Lecture 11 Karlijn, Maarten
22-3 Question hour Stata assignment: Power
22-3 15.00 hrs Lecture 12 Karlijn, Maarten
24-3 15.00 hrs Q&A: Application to student's research design Karlijn, Maarten
Week 7: Self study
4-4 15.00 hrs Deadline Stata Assignment 3: Power Via Brightspace
7-4 15.00 Q&A Optional Via Brightspace
8-4 14.00 hrs Written 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.