Content overview

Abstract

Survey methodology research sets out to answer questions regarding the effects of particular design decisions: do self-administered modes increase the reports of socially undesirable behavior? Does the use of incentives increase response rates? Does dependent interviewing decrease seam-effects? Do the employment rate estimates change with adding additional response categories like “maternity leave”? This course teaches the fundamental concepts behind the estimation of causal effects, including potential obstacles to causal inference, faulty measurement, spuriousness, specification errors, and other problems that can lead to inappropriate causal inferences. We will discuss the benefits and the difficulties of randomization in survey research in the first half of the class. The focus of the second half is on the design of observational studies and inferences from prediction. Real-world examples will be discussed, with an emphasis on examples from survey methodology. Students will come away with an understanding of how to estimate causal effects in both randomized and observational settings, with a particular focus on careful design of both types of studies.