Strengthening Fiscal Contracts Through Digital Town Halls in Freetown, Sierra Leone

Last registered on September 26, 2025

View Trial History

Pre-Trial

Trial Information

General Information

Title

Strengthening Fiscal Contracts Through Digital Town Halls in Freetown, Sierra Leone

RCT ID

AEARCTR-0016843

Initial registration date

September 22, 2025

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

September 26, 2025, 8:16 AM EDT

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

Locations

Country

Sierra Leone

Region

Freetown

Primary Investigator

Name

Kevin Grieco

Affiliation

Toulouse School of Economics - IAST

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Abou Bakarr Kamara

PI Affiliation

International Growth Centre

PI Name

Niccolò F. Meriggi

PI Affiliation

University of Oxford

PI Name

Wilson Prichard

PI Affiliation

University of Toronto

PI Name

Julian Michel

PI Affiliation

Hong Kong Babtist University

Additional Trial Information

Status

Completed

Start date

2020-09-01

End date

2022-03-31

Keywords

Governance

Additional Keywords

fiscal capacity, participatory budgeting, taxation, legitimacy, state building

JEL code(s)

H20, D72

Secondary IDs

EGAP Registration ID: 20220722AA & 20210820AA

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Building durable fiscal capacity requires that states obtain compliance with their taxes—a persistent challenge for states with low enforcement capacity. One promising option for governments in weak states is to raise voluntary compliance by enhancing governmental legitimacy. This study reports results from a participatory budgeting policy experiment in Sierra Leone designed to increase legitimacy and tax compliance by inviting public participation in local policy decision-making. In phone-based town halls, participants shared policy preferences with neighbors and local politicians and then voted for public services that were subsequently implemented. We find that the intervention durably increased participants’ perceptions of government legitimacy. However, contrary to influential models of tax compliance, we report a robust null effect on tax compliance behavior. Participants’ partisan affiliation strongly conditions the treatments’ effects on tax compliance and attitudes toward paying taxes: We find large, positive impacts among copartisans of the incumbent government but significant negative impacts among non copartisans. Our results highlight that the legitimacy gains of participatory interventions may not increase voluntary tax compliance when participation politicizes compliance.

External Link(s)

egap Registry (tax compliance pap)

egap Registry (legitimacy pap)

Registration Citation

Citation

Grieco, Kevin et al. 2025. "Strengthening Fiscal Contracts Through Digital Town Halls in Freetown, Sierra Leone." AEA RCT Registry. September 26. https://doi.org/10.1257/rct.16843-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

The intervention contained three components: (i) digital town halls, (ii) service delivery, (iii) notification calls about delivered services. For more details, see Section 3 of attached PAP.

i. Digital Town Halls (DTH): In this study, DTHs take the form of WhatsApp group chats. Participants were assigned to one of 58 chat groups, where the number of participants in each chat ranged from 17 to 37 (the median chat group size was 24). All participants in a given chat group own property in the same ward. The overarching goal of the DTH is for the group to deliberate and decide over how a budget of 15 million leones (about USD 1,500) should be spent in their ward. The budget allocated to the DTH does not come from FCC tax revenue given (1) the severity of the budget constraint the FCC faces and (2) that the expected increase in property tax revenue will be accrued after the DTHs have taken place. For these reasons, the funds to be decided on are taken from the project's research budget. However, this is not communicated to the DTH audience, allowing the Mayor and (FCC) political representatives to fully claim credit for the participatory budgeting opportunity, which further ensured buy-in to enable our research.

ii. Service Delivery:
Each participating ward received a service project—essentially a local public good both treated and control units in that ward could profit from. Construction began in most wards in October 2021, with the notable exception of one ward (Tengbeh Town) where the FCC needed to provide additional assurances over liability to the delivery company. By the end of 2021 all projects were completed, except the project in Tengbeh Town, which was completed in February of 2022.

iii. Service Delivery Notification Calls:
While our endline survey was conducted after all selected services were successfully delivered, we found it plausible that not all participants would be aware of the completed service project. To address this, we made notification calls on behalf of the FCC to all treated units, informing participants that the project chosen in the DTH had been successfully implemented. Note that by making these notification calls to treated units but not to the control group, we build the notification calls into our treatment.

Intervention (Hidden)

Intervention Start Date

2021-01-15

Intervention End Date

2022-03-02

Primary Outcomes

Primary Outcomes (end points)

Tax compliance (administrative records)

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

For secondary (mechanisms) outcomes related to tax compliance, See Section 5 attached document "dth_pap0722"
For secondary outcomes related to government legitimacy, See Section 4 attached document "20210820AA_PAP"

Secondary Outcomes (explanation)

Experimental Design

The unit of randomization is the property owner. To construct our sample frame we draw on FCC administrative records of the universe of taxable properties in Freetown, which contains a set of property characteristics and property owner contact information. To be eligible to participate in the Digital Town Hall a property owner must (i) own a property in one of the 30 study wards and (ii) have WhatsApp on their phone. We were able to complete baseline surveys with 3859 property owners that met this condition. To mitigate spillovers we drew a restricted sample from this set of property owners such that each property is at least 15 meters from the closest study property. The restricted sampling leaves us with final sample of 3619.

We assign treatment status using a matched-pair design, leveraging baseline data to match similar observations into groups of two. We create 1809 pairs and then assign one observation in each matched-pair to treatment and the other to control. We generate matched-pairs using the blockTools package in R. We use the Optimal Greedy (“opt-Greedy”) matching algorithm to find best matches along mahalanobis distance. We implement this randomization in R using the block ra function in the randomizr package.

Experimental Design Details

Randomization Method

Randomization is implemented in R using the block_ra function in the randomizr package.

Randomization Unit

individual property owner

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

not clustered design

Sample size: planned number of observations

3,618 property owners

Sample size (or number of clusters) by treatment arms

C: 1809
T: 1809

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Most of our outcomes of interest achieve 80% power with effects sizes at or less than .15 standard deviations. See Section 11 of attached pre-analysis plan for power simulations.

Supporting Documents and Materials

IRB