Self-Efficacy and Citizen Engagement in Development: Experimental Evidence from Tanzania
Published online by Cambridge University Press: 29 January 2021
Recent studies of efforts to increase citizen engagement in local governance through information campaigns report mixed results. We consider whether low levels of self-efficacy beliefs limit engagement, especially among poor citizens in poor countries. Citizens may be caught in an “efficacy trap” which limits their realization of better public goods provision. We describe results from a series of experimental studies conducted with over 2,200 citizens in rural Tanzania, in which we compare the effects of standard information campaigns with Validated Participation (VP), an intervention designed to socially validate citizens’ participation. We implement a staged approach to experimental research, seeking to balance ethical and cost concerns about field experimentation. In our main analyses, we find that VP did not lead to increased levels of self-efficacy or more active citizen behaviors relative to standard informational treatments. Nonetheless, we find some promising evidence for VP in a follow-up qualitative study with teachers. We conclude by discussing lessons from this research and directions for future investigation of the possible role of self-efficacy traps in development.
- Research Article
- Journal of Experimental Political Science , Volume 9 , Issue 1 , Spring 2022 , pp. 46 - 63
- © The Author(s) 2021. Published by Cambridge University Press on behalf of The Experimental Research Section of the American Political Science Association
The data, code, and any additional materials required to replicate all analyses in this article are available at the Journal of Experimental Political Science Dataverse within the Harvard Dataverse Network, at: doi:10.7910/DVN/SLYEUJ (Zhou and Lieberman 2020). Our pre-analysis plans can be found at osf.io/jqzxp for Study 1 and osf.io/9xmjg for Study 2. This research received institutional review board (IRB) approval from MIT COUHES (#1603517857R001). We report no conflicts of interest. All errors and omissions are ours.
Authors contributed equally. Author order is randomized using randomizeauthor.shinyapps.io/shiny.