Field Experiments

Course content

Recent years have seen an enormous increase and interest in research using experimental methods in the field to address questions across a broad range of topics in economics and management:

  • Does Uber surge pricing work to steer demand?
  • What is the impact of microloans on alleviating poverty?
  • Do people eat more vegetarian food when it is on top of the menu?
  • Do people work harder when you pay them more?

 

Rather than trying to find already available data (which is often not possible) and inferring causality with advanced econometric methods, field experiments randomly assign units of observations to treatment and control conditions to identify causal effects. While the idea is simple, the implementation brings other challenges.

 

The course will teach the students how to design, implement, and analyse field experiments – also known as randomized controlled trials (RCT). It will show the potential gains from using field experiments to test economic theory, make causal inference, and inform optimal policies, both in the public and private sector.

 

Students will acquire the tools to successfully conduct their own field experiments and learn to critically evaluate experimental findings from the academic literature. Students will also explore the many challenges to implementing RCTs in the field and the tools to address these issues in study design and analysis.

Learning outcome

After completing the course the student is expected to be able to:

 

Knowledge:

  • Discuss state-of-the-art empirical research in experimental economics conducted in the field.
  • Identify research or policy questions that can be answered using field experiments.

 

Skills:

  • Conduct power calculations for determening the correct sample size of an experiment.
  • Analyze experimental data using econometric tools.
  • Argue for optimal choice of outcome variables, sample size, clustering and randomization balancing.

 

Competencies:

  • Plan and develop a field experiment design, both conceptually for testing economic theory and practically.
  • Independently identify challenges that could arise when conducting an experiment and argue how to overcome them.
  • Initiate and participate in discussions of the implications of experimental results for policy makers or managements in the public and private sector.

The format of the course is a combination of lectures and individual student work. The first eleven lectures will present core concepts, methods, and empirical results. Lecture number 12, 13 and 14 will consist of student presentations applying and critically reflecting on the learning of the lectures.

Student participation in all lectures will be expected and encouraged. An active discussion in class is essential for effective learning.

Restrictions due to pandemic crisis:
The teaching in this course may be changed to be taught either fully or partly online due to a pandemic crisis like COVID-19. In case of changes and further information, please read the study messages in KUnet or the announcements in the course room on Absalon (for enrolled students).

The course will be based on a book, lecture slides, research papers, policy documents and survey articles. A detailed syllabus with required readings will be provided in Absalon the beginning of the course.

 

The following books and articles give an overview of the type of literature that will be used in class:

  • Main Book: Running Randomized Evaluations – A practical guide by Rachel Glennester and Kudaz Takavarasha ISBN-13: 978-0-691-15927-0
  • Harrison, Glenn and John A. List. 2004. "Field Experiments." Journal of Economic Literature, XLII: 1013-1059.
  • Athey, Susan, and Guido W. Imbens. "The econometrics of randomized experiments." Handbook of economic field experiments. Vol. 1. North-Holland, 2017. 73-140.
  • Banerjee, Abhijit, Rukmini Banerji, James Berry, Esther Duflo, Harini Kannan, Shobhini Mukerji, Marc Shotland, and Michael Walton. 2017. "From Proof of Concept to Scalable Policies: Challenges and Solutions, with an Application." Journal of Economic Perspectives, 31 (4): 73-102.
  • Card, David, Stefano Della Vigna & Ulrike Malmendier. 2011. The Role of Theory in Experiments. Journal of Economic Perspectives 25(3): 39–62.
  • List, John A., Sally Sadoff & Mathis Wagner (2011). So You Want to Run an Experiment, Now What? Some Simple Rules of Thumb for Optimal Experimental Design. Experimental Economics 14: 439–457.
  • Pomeranz, D. (2011). Impact Evaluation Methods: A Brief Introduction to Randomized Evaluations in Comparison with Other Methods.
  • Hauser, Oliver P., Elizabeth Linos, and Todd Rogers. "Innovation with field experiments: Studying organizational behaviors in actual organizations." Research in Organizational Behavior 37 (2017): 185-198.

It is recommended to have followed the course "Applied Econometric Policy Evaluation" at the study of Economics, University of Copenhagen, or equivalent before or at the same time as the course.

The student will benefit from having attended a course on behavioral economics such as "Science of Behavior Change", the summer school "Behavioral Experimental Economics" or "The Psychology of Choice" at the study of Economics, University of Copenhagen, or equivalent before taking Field Experiments.

Schedule:
3 hours lectures ones a week from week 6 to 20.

The overall schema can be seen at KUnet:
MSc in Economics => "courses and teaching" => "Planning and overview" => "Your timetable"
KA i Økonomi => "Kurser og undervisning" => "Planlægning og overblik" => "Dit skema"

Timetable and venue:
To see the time and location of lectures and exercise classes please press the link under "Timetable"/​"Se skema" at the right side of this page (F means Spring).

You can find the similar information in English at
https:/​/​skema.ku.dk/​ku2122/​uk/​module.htm
-Select Department: “2200-Økonomisk Institut” (and wait for respond)
-Select Module:: “2200-F22; [Name of course]”
-Select Report Type: “List – Weekdays”
-Select Period: “Forår/Spring – Week 5-30”
Press: “ View Timetable”

Please be aware:
- The schedule of the lectures and the exercise classes can be changed without the participants´ acceptance. If this happens you can see the new schedule in your personal timetable at KUnet, in the app myUCPH and through the links in the right side and the link above.
- It is the students´s own responsibility continuously throughout the study to stay informed about their study, their teaching, their schedule, their exams etc. through the curriculum of the study programme, the study pages at KUnet, student messages, the course description, the Digital Exam portal, Absalon, the personal schema at KUnet and myUCPH app etc.

Oral
Individual
Collective

 

The students receive oral collective feedback during the lectures.

Each student receives individual oral feedback on the mandatory presentations.

ECTS
7,5 ECTS
Type of assessment
Written assignment, 12 hours
individual take-home exam. It is not allowed to collaborate on the assignment with anyone.
The exam assignment is in English and must be answered in English.

__
Aid
All aids allowed

for the written assignment.

Information about allowed aids for the re-examination, please go to the section "Re-exam".

____

Marking scale
7-point grading scale
Censorship form
No external censorship
for the written exam.
An oral re-examination may be with external assessment.
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Criteria for exam assessment

Students are assessed on the extent to which they master the learning outcome for the course.

 

In order to obtain the top grade “12”, the student must with no or only a few minor weaknesses be able to demonstrate an excellent performance displaying a high level of command of all aspects of the relevant material and can make use of the knowledge, skills and competencies listed in the learning outcomes.

 

In order to obtain the passing grade “02”, the student must in a satisfactory way be able to demonstrate a minimal acceptable level of  the knowledge, skills and competencies listed in the learning outcomes.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 42
  • Preparation
  • 152
  • Exam
  • 12
  • English
  • 206