State Paralysis: The Effect of Compliance Uncertainty on Government Effectiveness

Last registered on August 08, 2025

Pre-Trial

Trial Information

General Information

Title
State Paralysis: The Effect of Compliance Uncertainty on Government Effectiveness
RCT ID
AEARCTR-0009821
Initial registration date
July 29, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
August 03, 2022, 2:42 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
August 08, 2025, 7:42 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
University of California, Davis

Other Primary Investigator(s)

PI Affiliation
University of California, Davis
PI Affiliation
London School of Economics
PI Affiliation
Fundação Getulio Vargas
PI Affiliation
CONASEMS
PI Affiliation
CONASEMS

Additional Trial Information

Status
Completed
Start date
2022-07-12
End date
2025-06-18
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Regulation and enforcement around the use of public funds can reduce corruption, but does it also alter incentives to spend? In this paper, we investigate whether compliance uncertainty around spending rules can stifle valuable-to-the-public spending and distort policy choice. We leverage administrative data and a collaboration with the Brazilian Council of Municipal Health Secretaries (CONASEMS, which organizes large conferences with municipal health heads responsible for managing, on average, a USD 1 million health budget. We first present three descriptive facts of the context consistent with the importance of compliance uncertainty for aggregate public spending. First, 20% of municipalities have experienced substantial incomplete spending for more than 10 years. Second, around one-fourth of the mayors are convicted with large penalties, even when there is no incidence of corruption. Lastly, regulation complexity is associated with incomplete spending (in the administrative data and a policymakers' perception in a survey). We then establish the causal link between compliance uncertainty and the spending decision, in a low-stakes lab-in-the-field experiment at CONASEMS conferences. We offer management support to implement a valuable public policy, namely a children's kit to reward parents who complete the vaccination scheme. We vary whether the children's kit includes "toys’’ (vs. "hygiene’’) items to be purchased with health earmarked funds. Preliminary evidence from the pilot shows that the toys policy bundle is perceived to be equally effective, but has a 20% reduced willingness to pay. Consistent with a risk-effectiveness trade-off, the toys policy bundle is perceived to have a higher risk.
External Link(s)

Registration Citation

Citation
Faleiros, Daniel et al. 2025. "State Paralysis: The Effect of Compliance Uncertainty on Government Effectiveness." AEA RCT Registry. August 08. https://doi.org/10.1257/rct.9821-4.0
Experimental Details

Interventions

Intervention(s)
We study the causal effect of compliance uncertainty on spending decisions in a lab-in-the-field experiment with municipal health heads, in partnership with the Brazilian Council of Municipal Health Secretaries (CONASEMS). We offer policymakers management support to implement a valuable public policy, namely a children's kit to reward parents who complete the vaccination scheme. Crucially, we introduce exogenous variation in the compliance uncertainty associated with the public policy while holding constant its perceived effectiveness. We vary whether the children's kit includes "toys’’ (vs. "hygiene’’) items to be purchased with health earmarked funds. With this random variation, we will be able to understand whether compliance uncertainty around the regulation of public funds alters incentives to spend and distorts policy choice.
The experiment will be implemented in collaboration with CONASEMS, the Brazilian Council of Municipal Health Secretaries. CONASEMS organizes a variety of conferences throughout the year, in which all Brazilian municipal health heads participate. We will administer it during the 2025 National Congress of CONASEMS in June 2025.
Intervention (Hidden)
Intervention Start Date
2022-07-12
Intervention End Date
2025-06-18

Primary Outcomes

Primary Outcomes (end points)
​​Our outcome variable will be participants’ demand for the proposed management support. Following a Becker-DeGroot-Marschak (BDM) procedure, we will elicit participants’ maximum willingness to pay to receive this support. This will inform us about the local health heads’ demand for compliance guarantees.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The survey experiment will first describe one of the main challenges that municipalities are dealing with in the health sector. We will present health officials with a valuable incentive public policy that aims to overcome this challenge. This initiative will be presented along with a proposal for management support to facilitate its implementation. We will use the Becker-DeGroot-Marschak (BDM) method to elicit participants’ demand for the proposed management support.
Our experiment introduces exogenous variation in the compliance uncertainty associated with budget execution by randomizing the components of the incentive policy. Specifically, the treatment version includes non-health sector items to be procured with funds earmarked for health. This variation will let us test whether compliance uncertainty around the regulation of public funds alters incentives to spend and distorts policy choice.
We also examine whether increasing the salience of the prosecution risk makes policymakers react more to compliance uncertainty. To do so, we randomize information about prosecution risk using data from the Federal Audit Court (TCU).
Finally, we assess how much policymakers value a proposal that helps reduce this uncertainty. To this end, we randomize the content of the management support proposal, with some participants receiving a version that includes additional risk-reduction components.
Experimental Design Details
Randomization Method
Randomization done on the spot by Qualtrics.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
None
Sample size: planned number of observations
700 individuals
Sample size (or number of clusters) by treatment arms
We do with three independent randomizations:
Randomization A: Compliance Uncertainty
Treatment A (High compliance uncertainty): 50%
Control A (Low compliance uncertainty): 50%
Randomization B: Salience of Prosecution Risk
Treatment B (Increased salience): 50%
Control B (No salience): 50%
Randomization C: Management Support with Risk-Reduction Components
Treatment C (With risk-reduction components): 30%
Control C (Without risk-reduction components): 70%
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
UC Davis IRB
IRB Approval Date
2023-05-05
IRB Approval Number
1936881-2
Analysis Plan

Analysis Plan Documents

PAP_June 2025_AEA.pdf

MD5: 51f3aea6a97a7d874ba607762b3ef149

SHA1: afd31d3884d7e9ce5fa05af509d2a64a7971b94a

Uploaded At: August 08, 2025

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials