Technology and Local Tax Collection: Evidence from Ghana
Last registered on September 06, 2019


Trial Information
General Information
Technology and Local Tax Collection: Evidence from Ghana
Initial registration date
September 04, 2019
Last updated
September 06, 2019 1:52 PM EDT

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Primary Investigator
Harvard University
Other Primary Investigator(s)
PI Affiliation
University of Ghana
PI Affiliation
University of Ghana
PI Affiliation
UC San Diego
PI Affiliation
UC San Diego
Additional Trial Information
In development
Start date
End date
Secondary IDs
We study the impact of technology on the collection of property taxes across local governments in Ghana. The technology assists local tax collectors in finding the properties, but also allows improved monitoring of the collectors' activities in the field. At the same time, the technology creates a digital information trail for any payment received, and prints uniquely identifiable receipts as proof of payment. Our primary outcomes of interest are delivery of bills and payments by households.
External Link(s)
Registration Citation
Dzansi, James et al. 2019. "Technology and Local Tax Collection: Evidence from Ghana." AEA RCT Registry. September 06.
Experimental Details
The intervention provides technology equipment to assist tax collectors in the collection of local taxes (household property taxes and business property taxes). Collectors in the treatment group are assisted by point of sale (POS) devices, which help them locate the properties that they are assigned to collect taxes from. In addition, the POS device allows the collectors to provide detailed information to the household and businesses about the tax bill. Finally, the POS devices generate an electronic information trail when a (complete or partial) payment is made by the household. This electronic receipt is directly sent to the central finance officers, and is printed in the field and delivered to the household at the moment of payment. In the control group, the collectors are not assisted by technology. They have maps of the district to assist them in locating the households and properties that they are assigned to, and they produce hand written bills upon receiving payments for taxes due. The collection process in the control group is almost identical to the manual collection process that is currently implemented in most local governments around the country.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Our primary outcomes of interest are the share of bills that are successfully delivered, the share of households and properties from which any tax payment is collected, and the share of the due tax that is collected.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Each collection unit contains 150 households and businesses. Each tax collector is assigned to one collection unit, and has four weeks to complete the collection of taxes. We implement the intervention in two local governments - Madina and Konongo. There are 27 collection units included in the experiment in Madina, and 15 collection units included in Konongo.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
Local tax collector
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
42 local tax collectors
Sample size: planned number of observations
The primary data collected will be from 6,300 households and businesses
Sample size (or number of clusters) by treatment arms
The sample is equally split between the treatment and control groups in both local governments
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
UCSD Human Research Protections Program
IRB Approval Date
IRB Approval Number