State Paralysis: The Effect of Compliance Uncertainty on Government Effectiveness

Last registered on July 15, 2023
View Trial History

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
July 15, 2023, 5:26 PM EDT

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

Locations

Country
Brazil
Region

Primary Investigator

Name
Socorro Pardo Martinez
Affiliation
University of California, Davis
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Diana Moreira
PI Affiliation
University of California, Davis
Contact Investigator
PI Name
Joana Naritomi
PI Affiliation
London School of Economics
Contact Investigator
PI Name
Gustavo Fernandes
PI Affiliation
Fundação Getulio Vargas
Contact Investigator
PI Name
Daniel Faleiros
PI Affiliation
CONASEMS
PI Name
Blenda Pereira
PI Affiliation
CONASEMS

Additional Trial Information

Status
On going
Start date
2022-07-12
End date
2024-02-15
Keywords
Governance, Health
Additional Keywords
Enforcement, Budget Execution
JEL code(s)
D73, H41, I18, K42
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 begin by leveraging administrative data of local government accounts to establish a puzzling phenomenon: substantial shares of local budgets in Brazil are not spent despite clear needs for additional resources for public services. We also investigate how random audits, which might increase the salience of compliance uncertainty, affect public spending. Then, we leverage a collaboration with the Brazilian Council of Municipal Health Secretaries (CONASEMS) to conduct an experiment with municipal health secretaries in order to shed light on the impact of compliance uncertainty on secretaries’ choices. In the experiment, we offer valuable-to-the-public spending plans randomly varying the degree of compliance guarantees from the audit courts.
External Link(s)

Registration Citation

Citation
Faleiros, Daniel et al. 2023. "State Paralysis: The Effect of Compliance Uncertainty on Government Effectiveness." AEA RCT Registry. July 15. https://doi.org/10.1257/rct.9821-3.0
Sponsors & Partners

Partner

Name
CONASEMS
Type
government
URL
https://www.conasems.org.br/
Experimental Details

Interventions

Intervention(s)
We administer a survey experiment to local bureaucrats in the health sector that seeks to understand their demand for spending plans that facilitate the execution of resources. We will introduce exogenous variation in the degree of compliance uncertainty around spending rules that each plan entails by randomizing the content of the provided information. We vary the source of the public funds used by the plans since rules and oversight vary depending on the source of funding in Brazil. We also randomly assign information on whether the spending plan will be interpreted as compliant with the rules by the control agency. With these random variations we will be able to understand whether reducing compliance uncertainty increase the implementation of effective health interventions. And whether this mechanism distorts spending of public funds.
The survey experiment will be implemented in collaboration with CONASEMS, the Brazilian Council of Municipal Health Secretaries. We will administer it during CONASEMS conferences organized over time, starting the pilot at CONASEMS annual congress in July/2022. These events bring together local bureaucrats in the health sector from all over Brazil.
Intervention Start Date
2022-07-12
Intervention End Date
2024-02-15

Primary Outcomes

Primary Outcomes (end points)
​​Our outcome variable will be participants’ demand for different strategies to execute resources. Following a Becker-DeGroot-Marschak (BDM) procedure, we will elicit participants’ maximum willingness to pay to receive these strategies. This will inform us about the local health officials’ 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 some of the main problems that municipalities are dealing with in the health sector. We will present to health officials several initiatives that aim to overcome those challenges. These solutions will be presented along with a strategy to execute resources. We will use the Becker-DeGroot-Marschak (BDM) method to elicit participants’ demand for the proposed strategies.
In the first round, the sample will be randomized into treatment and control group. The treatment group will receive information increasing the guarantee that the control agency will approve the expenses once the strategy to execute resources is implemented. This treatment reduces the compliance uncertainty associated with budget execution. This variation will let us test whether reducing uncertainty over compliance with spending regulation increase the implementation of effective health interventions by local bureaucrats in the health sector.
In the second round, we will introduce variation in both the effectiveness of the proposed policy and the source of the public funds. We will test whether the compliance uncertainty raised by the execution of non-discretionary and more heavily regulated funds distorts public policy decisions as it makes local secretaries switch to safer but less effective public policies. We will also randomize in the second round the information on whether the spending plan will be interpreted as compliant with the rules by the control agency. With this variation, we will test whether the distortion can be explained by regulation risk.
Finally, to be able to interpret the magnitude of the willingness to pay by local bureaucrats, we will introduce variation in another relevant dimension for policy implementation, as a benchmark.
Experimental Design Details
Not available
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
400 individuals per event
Sample size (or number of clusters) by treatment arms
We will randomize the sample into four groups. It will vary the information they receive associated with the spending plan.
1. Non-discretionary funds and low regulation risk
2. Non-discretionary funds and high regulation risk
3. Discretionary funds and high regulation risk
4. Non-discretionary funds and high regulation risk + benchmark constraint
At the same time, each group will be randomized into an effective and less effective public policy.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
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_July2023_AEA.pdf

MD5: ac08dab21cd8968ff15aaa1334a84ef9

SHA1: bc05fb8ae9fa8ea56e9b1cdb6a337a68545f2da9

Uploaded At: July 15, 2023