Information, Accountability, and Cumulative Learning

How do voters respond to new information about the performance of politicians. Do they reward those that perform well and punish the poor performers. Not much, according to this book. The book, edited together with Thad Dunning, Guy Grossman, Susan D. Hyde, Craig McIntosh, and Gareth Nellis combines evidence from 7 research sites, reporting the major results from egap's Metaketa I initiative, an effort to foster cumulative learning by coordinating pre-registered trials across a variety of settings.


Abstract (from Science Advances article)

Voters may be unable to hold politicians to account if they lack basic information about their representatives’ performance. Civil society groups and international donors therefore advocate using voter information campaigns to improve democratic accountability. Yet, are these campaigns effective? Limited replication, measurement heterogeneity, and publication biases may undermine the reliability of published research. We implemented a new approach to cumulative learning, coordinating the design of seven randomized controlled trials to be fielded in six countries by independent research teams. Uncommon for multisite trials in the social sciences, we jointly preregistered a meta-analysis of results in advance of seeing the data. We find no evidence overall that typical, nonpartisan voter information campaigns shape voter behavior, although exploratory and subgroup analyses suggest conditions under which informational campaigns could be more effective. Such null estimated effects are too seldom published, yet they can be critical for scientific progress and cumulative, policy-relevant learning.