Standard models of hierarchy assume that agents and middle managers are better informed than principals about how to implement a particular task. We estimate the value of the informational advantage held by supervisors (middle managers) when ministerial leadership (the principal) introduced a new monitoring technology aimed at improving the performance of agricultural extension agents (AEAs) in rural Paraguay. Our approach employs a novel experimental design that, before randomization of treatment, elicited from supervisors which AEAs they believed should be prioritized for treatment. We find that supervisors did have valuable information—they prioritized AEAs who would be more responsive to the monitoring treatment. We develop a model of monitoring under different allocation rules and rollout scales (i.e., the share of AEAs to receive treatment). We estimate marginal treatment effects (MTEs) to demonstrate that the value of information and the benefits to decentralizing treatment decisions depend crucially on the sophistication of the principal and on the scale of rollout.

Written with Fred Finan (UC Berkeley), Nicholas Li (UC Berkeley), and Laura Schechter (UW Madison)