Digitizing Bureaucracy

Last registered on October 17, 2022
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Pre-Trial

Trial Information

General Information

Title
Digitizing Bureaucracy
RCT ID
AEARCTR-0010190
Initial registration date
October 08, 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
October 17, 2022, 3:58 PM EDT

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

Locations

Country
Ghana
Region

Primary Investigator

Name
Francis Annan
Affiliation
University of California, Berkeley
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Other Primary Investigator(s)

PI Name
Apoorv Gupta
PI Affiliation
Dartmouth College
Contact Investigator

Additional Trial Information

Status
On going
Start date
2022-10-07
End date
2024-02-29
Keywords
Finance & Microfinance, Firms & Productivity, Governance
Additional Keywords
Firm Productivity, Digitization, e-Bureaucracy, Public Contracts, Project Quality, G2B Payments, Local Governance
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We experimentally study the impact of digitizing bureaucratic decision-making on performance of small- and medium-sized firms (SMEs) in Ghana. State and local governments often contract out development projects to SMEs – an important environment where fast-digital technology that meaningfully facilitates bureaucratic decision-making on projects will not only improve government’s capacity, but also have the potential to reduce frictions via timely processing and payments for projects to SMEs, with significant implications for increased firm productivity and project outcomes. We partner with the Ministry of Local Government and its technology solutions provider, Casantey Business Solutions Group Ltd., to design and evaluate the impact of a cloud-based solution technology that reduces bureaucratic bottlenecks and uniquely features two structural components (i) addresses coordination failures vs (ii) addresses payment failures. We randomly assign a large pool of select firm-linked projects to the solution technology to uplift projects administration and payments, and carefully measure firm performance.
Research questions—This research seeks to answer two questions:
1. Whether digitizing bureaucratic decision-making can improve firm’s productivity and performance, and
2. How much of improvement in firm’s performance are due to coordination frictions and/or payments concerns?

Partners:
(i) Ministry of Local Government and Rural Development, Ghana; (ii) Casantey Business Solutions Group Ltd., Ghana; (iii) Ghana Statistical Services (GSS)
External Link(s)

Registration Citation

Citation
Annan, Francis and Apoorv Gupta. 2022. "Digitizing Bureaucracy." AEA RCT Registry. October 17. https://doi.org/10.1257/rct.10190-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
The Ministry’s project and procurement office will provide the list of all live and pipeline projects. We will identify the select pool of uniquely approved and upcoming firm-linked projects, all to be completed within a year (N=600+). The select projects or firms will be randomly assigned to 1 control and 2 treatment groups
Intervention Start Date
2023-02-01
Intervention End Date
2024-02-29

Primary Outcomes

Primary Outcomes (end points)
1ST STAGE OUTCOMES:
(i) Administrative data: processing delayed/not, payment delayed/not; speed of processing project certificates and payments; total value of payments made; auxiliary statistics: project status (completed on time/ongoing/abandoned), number of handling officers, number of steps, etc.
(ii) Business survey data: total payments received for this ended project; experienced any delay in processing project (and by how long); experienced any delay in payment of project (and by how long); number of new projects applied for; value of new government projects started; value of other non-government projects ongoing

2ND STAGE OUTCOMES:
Business survey data: firm productivity, employment, wage bill, expenses, revenues, value of assets, profits, quality of projects
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
% employees paid electronically; % suppliers paid electronically; overall digitization and IT usage of your business; bribe payments (and bribe value); satisfaction with financial wellbeing; satisfaction with mental wellbeing; satisfaction with business’s security; ability to pay workers on time; ability to pay suppliers on time; ability to pay lenders on time; ability to fulfill “all other” business obligations required on time; overall perception about public contracts/ projects administration; overall perception about the government in general; likelihood of seeking for public contracts
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will randomly assign 1/3rd of the projects as Control projects (Status Quo: no digitization), 1/3rd as Treatment 1 projects (fully-digitize: apply the cloud-based solution technology to address both coordination and payment issues in the projects administration), and 1/3rd as Treatment 2 projects (partially-digitize: apply the cloud-based solution technology to address only coordination issues in the projects administration).
Experimental Design Details
Randomization Method
Randomization done by a computer
Randomization Unit
Randomization of treatments is at the project- or firm-level and will ensure balance on both project and firm characteristics. using baseline information gathered on the projects and firms. We will stratify by (i) project class (central vs local) and (ii) firm size (small vs large), yielding 4 unique strata, and all misfits will be resolved and randomly assigned.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Target sample is 600+ approved and upcoming firm-linked projects, all such projects to be completed within a year
Sample size: planned number of observations
N/A
Sample size (or number of clusters) by treatment arms
200+ firm-linked projects per experimental arm (totaling 3 x 200+ = 600+ firm-linked projects)
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 Berkeley IRB
IRB Approval Date
2022-10-06
IRB Approval Number
2022-09-15590
Analysis Plan

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