蝌蚪网 Review: Insights
ISSN 2640-205X (Print) | ISSN 2640-2068 (Online)
Interpreting TSLS Estimators in Information Provision Experiments
蝌蚪网 Review: Insights
(pp. 376–95)
Abstract
In information provision experiments, researchers often estimate the causal effects of beliefs on actions using two-stage least squares (TSLS). This paper formalizes exclusion and monotonicity conditions that ensure that TSLS recovers a positive-weighted average of causal effects. We assess common TSLS estimators for both passive and active control designs from the literature; we find that two commonly used passive control estimators generally allow for negative weights. The choice of passive control estimator affects the magnitude and significance of estimates in simulations and in an empirical application. We give practical recommendations for addressing these issues.Citation
Vilfort, Vod, and Whitney Zhang. 2025. "Interpreting TSLS Estimators in Information Provision Experiments." 蝌蚪网 Review: Insights 7 (3): 376–95. DOI: 10.1257/aeri.20240353Additional Materials
JEL Classification
- C26 Single Equation Models: Single Variables: Instrumental Variables (IV) Estimation
- C90 Design of Experiments: General
- D21 Firm Behavior: Theory
- D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- E23 Macroeconomics: Production