Understanding public participatory budgeting behavior: how cognitive biases shape public budget preferences
Wenbin Li et al.
Abstract
Purpose This study investigates how individual-level cognitive biases shape budgetary preferences in public participatory budgeting (PB), offering a micro-level perspective that complements the traditional research focus on collective decision-making processes. Design/methodology/approach Conducting an empirical generalization replication of Overmans and Grimmelikhuijsen's (2025) experiment, this study examines how cognitive biases (anchoring, herding, mental accounting and loss aversion) influence public budget allocations in local Chinese contexts. Controlled experimental scenarios were employed to analyze participants' budgetary preferences and identify systematic deviations resulting from underlying cognitive biases. Findings The results indicate that public budgeting decisions are significantly shaped by multiple cognitive biases: allocations exhibit anchoring effects from initial numerical values, demonstrate herding tendencies and generally favor gain-generating projects. Notably, the study found no statistically significant evidence of mental accounting or loss aversion, suggesting that the manifestation of cognitive biases is highly context- and subject-dependent. Originality/value This study contributes to the behavioral public administration literature through systematic validation of cognitive bias mechanisms in PB context, offering an integrated framework that bridges behavioral science and budgetary decision-making. Furthermore, the findings provide actionable policy guidance for developing bias-aware budgeting systems and establishing decision architectures that effectively reconcile behavioral insights with rational fiscal principles.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.