Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations

TLDR

Instrumental variable methods rely on the assumption that unobserved individual gains do not influence participation, but when private information about program benefits affects enrollment, the standard IV justification breaks down. The study investigates how instrumental variables can estimate the mean effect of treatment on the treated, on randomly selected individuals, and the local average treatment effect, and explores the economic questions each parameter addresses. The authors develop these arguments for both continuous and discrete treatments, presenting several explicit economic models to illustrate the application of instrumental variables.

Abstract

This paper considers the use of instrumental variables to estimate the mean effect of treatment on the treated, the mean effect of treatment on randomly selected persons and the local average treatment effect. It examines what economic questions these parameters address. When responses to treatment vary, the standard argument justifying the use of instrumental variables fails unless person-specific responses to treatment do not influence decisions to participate in the program being evaluated. This requires that individual gains from the program that cannot be predicted from variables in outcome equations do not influence the decision of the persons being studied to participate in the program. In the likely case in which individuals possess and act on private information about gains from the program that cannot be fully predicted by variables in the outcome equation, instrumental variables methods do not estimate economically interesting evaluation parameters. Instrumental variable methods are extremely sensitive to assumptions about how people process information. These arguments are developed for both continuous and discrete treatment variables and several explicit economic models are presented.