What Politicians Do Not Know Can Hurt You
The Effects of Information on Politicians' Spending Decisions
Bibliographic Data
| ID | 3762925 |
|---|---|
| Authors | Ryan Jablonski (0000-0002-7344-6738, London School of Economics and Political Science, corresponding author), Brigitte Seim (0000-0001-7963-4767, University of North Carolina at Chapel Hill, corresponding author) |
| Year | 2024 |
| Volume | 118 |
| Issue | 3 |
| Pages | 1497-1517 |
| Publication date | 2024-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | American Political Science Review (JOURNAL) |
| Journal identifiers | ISSN: 0003-0554 • E-ISSN: 1537-5943 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s0003055423001132 |
| OpenAlex | W4388724575 |
| Language | EN |
| Citations received | 3 |
| References cited | 38 |
Do well-informed politicians make more effective spending decisions? In experiments with 70% of all elected politicians in Malawi ($ N=460 $), we tested the effects of information on public spending. Specifically, we randomly provided information about school needs, foreign aid, and voting patterns prior to officials making real decisions about the allocation of spending. We show that these information interventions reduced inequalities in spending: treatment group politicians were more likely to spend in schools neglected by donors and in schools with greater need. Some information treatment effects were strongest in remote and less populated communities. These results suggest that information gaps partially explain inequalities in spending allocation and imply social welfare benefits from improving politicians' access to information about community needs
Business · Economics · Inequality · Information needs · Political science · Politics · Psychological intervention · Public economics · Public spending · Voting · Welfare · Fiscal Policy and Economic Growth · Local Government Finance and Decentralization · Psychology · Taxation and Compliance Studies
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| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |