Half Day PM (1:30 p.m. – 5:30 p.m.)
This course provides a practical and example-driven guide to the design and analysis of natural experiments. The course will emphasize the role of qualitative inquiry in the discovery of natural experiments and use of case knowledge in the justification of these designs’ core assumptions. Natural experiments typically depend on a deep qualitative understanding of how causal factors are assigned to units in the population of interest. This qualitative understanding is critical for both discovery and analysis of natural experiments, but how precisely to incorporate this type of data into a concrete research project is often overlooked in standard methodological texts and courses. Questions that will be addressed include:
- What types of qualitative data are most useful for strengthening natural experiments?
- What makes the use of qualitative evidence in a given application convincing?
- How can qualitative evidence be effectively presented in the context of a research article?
- How can we raise standards for the use of qualitative data in the design and analysis of natural experiments?
The course will begin with a presentation of the basic causal model and assumptions often employed in the design of natural experiments, but the bulk of the course will be structured around a detailed examination of the nuts and bolts of recent political science examples. The course will integrate hands-on analysis of real data with the conceptual material. In addition to the analysis of the quantitative data typically presented research articles, we will also examine the raw qualitative data that is often used in the discovery and justification of natural experiments. These exercises will involve the examination of primary source documents, interview transcripts, and archival sources.
**All Short Courses will take place on Wednesday, August 30 at the APSA 2017 Annual Meeting in San Francisco, CA.**