Cours

Causal Inference in Empirical Economics - 5 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.

Organisé par Wageningen School of Social Sciences (WASS)
Date

lun. 4 septembre 2023 jusqu'à ven. 20 octobre 2023

Durée Registration deadline: 21 August 2023

Lecturers

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

Introduction

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 fully 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. 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.

Activities

● 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.

Feedback

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

Examination

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

Tentative schedule

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

4 September 9.30-11.30 Lecture 1
6 September 9.30-11.30 Lecture 2
7 September 9.30-10.30 Q&A
11 September 9.30-11.30 Lecture 3
12 September 9.30-10.30 Question hour Stata assignment
13 September 9.30-11.30 Lecture 4
14 September 9.30-10.30 Q&A
18 September 9.30-11.30 Lecture 5
20 September 9.30-11.30 Lecture 6
21 September 9.30-10.30 Q&A
25 September 9.30-11.30 Lecture 7
27 September 9.30-11.30 Lecture 8
28 September 9.30-10.30 Q&A
2 October 9.30-11.30 Lecture 9
3 October 9.30-10.30 Question hour Stata assignment
4 October 9.30-11.30 Lecture 10
5 October 9.30-10.30 Q&A
9 October 9.30-11.30 Lecture 11
11 October 9.30-11.30 Lecture 12
12 October 9.30-11.30 Question hour Stata Assignmnet and Q&A
19 October 9.30-10.30 Q&A Optional
23 October all day Take-home exam

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.