Policymakers are increasingly turning to insights gained from the experimental method as a means to inform large scale public policies. Critics view this increased usage as premature, pointing to the fact that many experimentally-tested programs fail to deliver their promise at scale. Under this view, the experimental approach drives too much public policy. Yet, if policymakers could be more confident that the original research findings would be delivered at scale, even the staunchest critics would carve out a larger role for experiments to inform policy. Leveraging the economic framework of Al-Ubaydli et al. (2019), we put forward 12 simple proposals, spanning researchers, policymakers, funders, and stakeholders, which together tackle the most vexing scalability threats. The framework highlights that only after we deepen our understanding of the scale up problem will we be on solid ground to argue that scientific experiments should hold a more prominent place in the policymaker’s quiver.

More Research From These Scholars

BFI Working Paper Oct 21, 2019

Design and Analysis of Cluster-Randomized Field Experiments in Panel Data Settings

Bharat K. Chandar, Ali Hortaçsu, John List, Ian Muir, Jeffrey M. Wooldridge
Topics:  Employment & Wages
BFI Working Paper Aug 19, 2020

The $100 Million Nudge: Increasing Tax Compliance of Businesses and the Self-Employed using a Natural Field Experiment

Justin E. Holz, John List, Alejandro Zentner, Marvin Cardoza, Joaquin Zentner
Topics:  Fiscal Studies
BFI Working Paper Oct 21, 2019

The Drivers of Social Preferences: Evidence from a Nationwide Tipping Field Experiment

Bharat Chandar, Uri Gneezy, John List, Ian Muir
Topics:  Employment & Wages