Behavioral responses to fiscal rules: evidence from Czech municipalities
Lucie Sedmihradská & Markéta Arltová
Abstract
Purpose The paper examines how the introduction of a debt rule affects local governments’ debt and savings management. The analysis explores anticipatory and compliance behavior driven by blame avoidance rather than direct financial sanctions in Czech municipalities before and after the introduction of the numerical debt rule in 2017. Design/methodology/approach The paper uses a sharp regression discontinuity design. The analysis focuses on 676 municipalities with debt ratios near the debt limit at 60% of average revenues and compares debt and saving management below and above the limit using data for 2015 to 2020. Hypotheses describing the pre-rule, anticipation and post-rule behavior are verified. Findings The paper finds that Czech municipalities adjusted their fiscal behavior in response to the introduction of the debt rule. Before the rule, no significant differences in debt or savings management were observed. After the rule’s announcement, municipalities slightly above the limit reduced savings, demonstrating anticipatory behavior. After the rule was enforced, municipalities just below the debt limit actively managed their debt and savings to avoid exceeding the debt limit. These behavioral changes confirm the influence of reputational concerns and blame avoidance, even in the absence of immediate sanctions. Originality/value It applies the behavioral model of the budgetary process to municipal finance and integrates blame avoidance theory and cognitive biases into the analysis of fiscal rule effects. It uses a sharp regression discontinuity design to evaluate responses to debt rule implementation. It shows that fiscal rules have impact even without immediate formal sanctions.
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.