Optimal Tax Administration with Cash-on-Hand Constraints

Last registered on September 17, 2024

Pre-Trial

Trial Information

General Information

Title
Optimal Tax Administration with Cash-on-Hand Constraints
RCT ID
AEARCTR-0014381
Initial registration date
September 17, 2024

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 17, 2024, 2:00 PM EDT

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

Locations

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Primary Investigator

Affiliation
University of Zurich

Other Primary Investigator(s)

PI Affiliation
University of California, Berkeley
PI Affiliation
World Bank
PI Affiliation
University College London

Additional Trial Information

Status
On going
Start date
2024-07-01
End date
2025-06-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
While public revenue is urgently needed in low-income countries, the welfare costs of taxation may be particularly high because of the variability of income, liquidity constraints and the lack of savings technologies. This project explores whether tax authorities in such settings can increase tax compliance while minimizing welfare losses by adapting tax administration to the existence of binding cash-on-hand constraints. In a randomized field experiment conducted in collaboration with the provincial tax authority of Kasaï Central, we explore three interventions seeking to relax cash-on-hand constraints: (1) timing collector visits when households are unconstrained; (2) helping households plan and save up for tax payment; and (3) allowing households to pay in installments. Although the development literature has demonstrated the importance of liquidity constraints in economic decision-making, this project will be the first to bring this insight into the public finance of developing countries and experimentally assess policy tools capable of relaxing these constraints.
External Link(s)

Registration Citation

Citation
Laroche, Arthur et al. 2024. "Optimal Tax Administration with Cash-on-Hand Constraints." AEA RCT Registry. September 17. https://doi.org/10.1257/rct.14381-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
We partner with the Provincial Government and tax authority of Kasaï-Central, DGRKAC, to conduct a randomized controlled trial at scale in the city of Kananga, Democratic Republic of Congo. The intervention covers the entire universe of properties, of which there are 106,111 assessable buildings in Kananga, according to latest property valuation campaign conducted by the Kasai Central's Tax Authority. The tax campaign is rolled out in three phases in the second half of 2024. Properties in Kananga will be randomly assigned to the following interventions.
First, in the timing intervention, property owners will be assigned to either choose a date to receive a tax collection visit (treatment) or receive a visit on a randomly chosen date (control). Owners who choose their date will be nudged to pick a day when their cash-on-hand constraints will be less likely to bind. If a property owner has the will to pay but is simply constrained by time-varying liquidity shocks, then this treatment will allow them to schedule the collection visit at the optimal time. Of course, this treatment will backfire if the owner has no intention to pay and indicates a day, for instance, when they know they will be out of town. By comparing compliance among owners across treatment groups, we will be able to ascertain whether this simple intervention allows tax authorities to better facilitate compliance.
Second, the tax authority will send out SMS messages to taxpayers to help them plan for upcoming tax collection visits. Owners assigned to the treatment group of this intervention will receive two messages --- 7 and 2 days before --- reminding them of the precise date of the collector visit. The intention is to help owners remember and plan for the visit, especially so they can save the sufficient funds to pay their property tax. Owners assigned to control will receive the same number and timing of messages but without mention of the date of the visit. Holding the receipt of messages from the tax authority constant helps to neutralize any enforcement impact of these messages. After all, hearing from the tax authority for the first time by SMS could lead owners to update their beliefs about the probability of enforcement. By comparing owners who receive treatment and control messages, we can isolate the importance of being able to plan and save up before the tax collection visit --- especially when visits are randomly chosen. We also expect that choosing the date of your visit may have a more pronounced effect when coupled with these SMS alerts.
Third, a subset of property owners will be randomly offered the chance to pay their property tax in installments of at least one third of the total liability. Breaking large lumpy payments into smaller units is a paradigmatic approach to relaxing liquidity constraints. Perhaps surprisingly, then, we know of no well-identified evidence on its impact on facilitating tax compliance. Owners assigned to the option of paying in installments will be informed of this possibility when they receive their property tax bill. Owners will be given the possibility to pay in two or three installments at most. Payments will not be tied to specific dates; owners can pay on any date they are visited by the collector (or they can pay at the tax ministry directly). There is no interest or higher cost associated with paying in installments. While paying in installments could help relax cash-on-hand constraints, it could also give owners an excuse to pay less than their full liability if they expect the tax authority not to enforce payment of the remaining amount due. It is thus an empirical question whether this intervention will raise tax compliance in a setting of low state capacity.
Fourth, independent of these three facilitation interventions, the tax authority will randomly include an enforcement message on a subset of tax bills. On control bills, property owners will only be informed of the payment deadline. On treatment bills, they will also be informed (i) of penalties that apply after the deadline, and (ii) that the household has been selected to receive a visit from a dedicated enforcement team. One concern with such interventions in developing countries is that tax authorities lack the capacity to honor these threats if owners fail to pay. This could make such enforcement messages dynamically inefficient, as taxpayers realize the government is making non-credible threats. Fortunately, the tax authority in Kananga has a separate enforcement phase during each tax campaign. Our team can help them ensure that any owner who received an enforcement message and is delinquent by the payment deadline does indeed receive an enforcement team visit. In addition, treatment households will receive an enforcement SMS message with information about penalties for non-compliant taxpayers. Similar interventions have been studied extensively in the public finance literature (e.g., Blumenthal et al., 2001; Pomeranz, 2015) and reliably boost tax compliance by a few percentage points. We use this intervention both to benchmark the impacts of other interventions and to compare welfare costs of “facilitated compliance” to “enforced compliance.”
Intervention Start Date
2024-08-12
Intervention End Date
2024-12-22

Primary Outcomes

Primary Outcomes (end points)
Tax revenue, tax compliance, subjective and objective well-being
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
See analysis plan.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The aforementioned interventions will be cross-randomized at the property level. To summarize, properties are assigned to three cross-cutting interventions randomizing the timing of the visit (random or chosen), taxpayers’ ability to plan for the visit by alerting them of the visit date (alert or no alert), and allowing taxpayers to smooth out the tax payment by paying in installments (installment option or no installment option) as well as fourth treatment arm that randomizes deterrence messaging to serve as a benchmark for the other treatments.
To collect data about the intervention, independent enumerators will additionally conduct a baseline, midline, and endline survey.
Experimental Design Details
Not available
Randomization Method
Randomization is done by a computer.
Randomization Unit
Properties (where properties may contain multiple buildings each with their own property tax liability and bill)
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
67,266 properties
Sample size: planned number of observations
For our primary tax-related outcomes, we will use administrative data to evaluate the effect of the various treatment arms on compliance and wellbeing. For this analysis, we have the universe of 106,111 assessable buildings.
Sample size (or number of clusters) by treatment arms
Fully cross-randomized. By treatment arm:

Random timing: ~53,055 properties
Chosen timing: ~53,055 properties

Installments: ~53,055 properties
No installments: ~53,055 properties

Low enforcement: ~53,055 properties
High enforcement: ~53,055 properties

SMS General Alert: ~12,127 properties
SMS Date Alert: ~12,127 properties
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Power simulations conducted using past data collected in Kananga indicate that we are able to detect a minimum effect size of .8 percentage points in a bilateral comparison of treatment and control for a single intervention. When studying the interaction between two cross-randomized treatments, i.e., imagining 4 cells, we would be powered to detect a .15 percentage point difference.
IRB

Institutional Review Boards (IRBs)

IRB Name
“Raising Money for the State: Strengthening Tax Capacity in Lower-Income Countries while Minimizing the Burden on the Poor” – approval by the Human Subjects Committee of the Faculty of Economics, Business Administration and Information Technology at the University of Zurich
IRB Approval Date
2024-05-22
IRB Approval Number
OEC IRB # 2023-105.1