Designing and Conducting Social-scientific Experiments
Lecturer: Wojtek Przepiorka
Modallity: In presence
Week 1: 14 - 18 August 2023
Workshop Contents and Objectives
Are norm violations contagious? Are people with more acquaintances more successful at finding a job? Are sanctioning institutions effective in promoting human cooperation? Why are working mothers more penalised by employers than working fathers? Why do prisoners fight? Are generous people more trustworthy? Under what conditions are individuals subject to success-breeds-success dynamics? These questions are rather difficult to address by means of observational data. In recent years, researchers have addressed these and other fundamental questions using experiments.
This course covers the design, implementation, and analytic tools necessary for conducting social science experiments. Students will learn what research questions can be addressed using a wide range of experimental methods. After a brief recap of the counterfactual approach to causal inference and experimental designs (day 1), the course will cover the theoretical and practical aspects of designing and conducting survey experiments (day 2), laboratory experiments (day 3), online experiments (day 4), and field experiments (day 5).
The objective is to provide students with the theoretical foundations for designing, implementing, conducting and analyzing experiments, but also to learn the applied aspects of experimental social science. Each day is divided in three parts. In the morning, after a lecture introducing the topic (part 1), we will work through the implementation of different types of experiments using oTree (part 2). In the afternoon, students will develop and receive feedback on their own experimental projects as part of group assignments (part 3).
Basic knowledge of multiple regression analysis, a concrete idea for an experimental project, the willingness to learn basic commands in Python, and the willingness to work in groups.
Auspurg, K., & Hinz, T. (2015). Factorial Survey Experiments. Thousand Oaks (CA): Sage.
Druckman, J. N. (2022). Experimental Thinking: A Primer on Social Science Experiments. Cambridge: Cambridge University Press.
Gerber, A. S., & Green, D. P. (2012). Field Experiments: Design, Analysis, and Interpretation. New York: W. W. Norton & Company.
Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Boston: Houghton Mifflin.