Bureaucratic Selection and Weberian Values
Lab-in-the-Field Evidence from Indonesia
Bibliographic Data
| ID | 10188717 |
|---|---|
| Authors | Nicholas Kuiper (0000-0001-5733-6400, Princeton University, corresponding author), Nicholas Kuipers |
| Year | 2024 |
| Volume | 88 |
| Issue | 1 |
| Pages | 000-000 |
| Publication date | 2024-12-12 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | The Journal of Politics (JOURNAL) |
| Journal identifiers | ISSN: 0022-3816 • E-ISSN: 1468-2508 |
| Publisher | University of Chicago Press (PUBLISHER • US) |
| DOI | 10.1086/734258 |
| OpenAlex | W4405311779 |
| Language | EN |
| Citations received | 1 |
| References cited | 34 |
The meritocratic recruitment of bureaucrats is thought to promote “Weberian” values through two distinct properties. The first concerns the use of examinations to sort aspirants on the basis of traits considered desirable for bureaucrats. The second relates to nondiscretionary selection, whereby recruits do not owe their position to a politician’s patronage, making them less likely to be captured. Using a lab-in-the-field experiment among aspirants to the Indonesian bureaucracy, I disentangle the relative importance of these mechanisms by manipulating how “public officials” are chosen from groups to perform tasks on behalf of others. I find no differences on tasks gauging commitment to Weberian values across public officials selected via the merit system or lotteries—although both perform better than those selected under patronage. Because both the merit system and lotteries are nondiscretionary, the results question examinations as the ideal tool for selecting bureaucrats
Bureaucracy · Field (mathematics · Political science · Politics · Selection (genetic algorithm · Artificial Intelligence · Computer Science · Corruption and Economic Development · Culture, Economy, and Development Studies · Law · Local Government Finance and Decentralization · Mathematics
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| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |