Spillover Effects of Tax Enforcement on Production Networks: Evidence from Paraguay

Last registered on June 13, 2025

Pre-Trial

Trial Information

General Information

Title
Spillover Effects of Tax Enforcement on Production Networks: Evidence from Paraguay
RCT ID
AEARCTR-0016101
Initial registration date
June 05, 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
June 13, 2025, 6:38 AM EDT

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

Locations

Region

Primary Investigator

Affiliation
Columbia University

Other Primary Investigator(s)

PI Affiliation
CREST
PI Affiliation
Inter-American Development Bank
PI Affiliation
Columbia University
PI Affiliation
Chicago Booth

Additional Trial Information

Status
On going
Start date
2024-12-02
End date
2025-07-11
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
Our project focuses on understanding how optimal targeting rules may change when enforcement activities have spillovers through production networks. The theoretical part of our project develops a tractable network model in which to study tax enforcement. The model-predicted optimal targeting rules will depend on a number of features of the production network and on a number of assumptions in the model. The experimental part of our project studies these questions empirically.

In partnership with Paraguay's tax authority, the Dirección Nacional de Ingresos Tributarios (DNIT), we are doing a series of three interlinked experiments. We developed a scalable tax enforcement intervention, building on the work of Carrillo et al (2017) in Ecuador. The first experiment studied the direct effects of the intervention on the targeted taxpayers. The second experiment is described in this pre-registration. The third experiment, planned for July/August 2025 will use the findings from the first two experiments and our theoretical model to derive and then experimentally test alternative tax enforcement targeting rules.
External Link(s)

Registration Citation

Citation
Best, Michael et al. 2025. "Spillover Effects of Tax Enforcement on Production Networks: Evidence from Paraguay." AEA RCT Registry. June 13. https://doi.org/10.1257/rct.16101-1.0
Sponsors & Partners

Sponsors

Partner

Experimental Details

Interventions

Intervention(s)
Our intervention is a modified version of the intervention studied by Carrillo et al (2017) in Ecuador. Among the eligible taxpayers, taxpayers were randomly selected to be sent a notice. The notice presents taxpayers with a summary by month of their reported sales, the purchases reported by their clients, and the discrepancies between them. The invoices underlying the purchases reported by clients are attached as an annex to back up the discrepancies. The notice then requests that the taxpayer file amendments of the relevant tax returns to address the inconsistencies.

We made two modifications to the notifications studied by Carrillo et al (2017). First, we strengthened the language used. Specifically, the notices emphasized that the request was for the taxpayer to file an amendment to their tax return in which they increase their reported sales to account for the discrepancy, but not make any other amendments to their return. This was intended to avoid taxpayers simultaneously increasing their reported purchases. Second, the notices were accompanied by greater follow-up and sanctions for non-response. In particular, auditors were assigned to follow up on each case. If the taxpayer responded but did not amend or amended only partially, the auditors reviewed the case and made a determination about whether to accept the partial response. If the taxpayer did not respond by the 10-day deadline, or responded unsatisfactorily, the auditor blocked the taxpayer's ID ("RUC"). Blocked IDs are not able to request more tax invoices, and are unable to perform a range of other processes with the tax authority (though they are still able to file and amend returns), potentially disrupting business activities for non-compliant taxpayers, especially larger ones that rely more on being able to issue tax invoices and have more complicated interactions with the tax authority.
Intervention (Hidden)
Intervention Start Date
2024-12-02
Intervention End Date
2025-06-01

Primary Outcomes

Primary Outcomes (end points)
Amendments: Do taxpayers amend their tax returns? If so, do they amend their reported sales? Reported purchases? Does this increase their tax liability and tax payments?
Tax returns: In their tax returns filed after the intervention, do taxpayers report different amounts of sales? Purchases? Does this increase their tax liability and tax payments?
Bilateral flows: Does the intervention change whom taxpayers report buying and selling from?
: Is the discrepancy between the taxpayer's VAT total reported sales and the sum of its buyers' bilateral purchase reports reduced by the intervention? Is the discrepancy between each of the taxpayer's bilateral sales reports and the corresponding bilateral purchase report by its buyer reduced by the intervention? Are the related discrepancies on the side of the taxpayer's purchases changed by the intervention?
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The randomization protocol is described in detail in the pre-analysis plan. In brief, the randomization occurs in two stages amongst the eligible pool of 62,344 taxpayers.

In stage 1 we select focal units and then randomly assign their clients and/or suppliers to treatment.
In stage 2 we focus on estimating the direct effect of the notices by focusing on anticliques: taxpayers who are not connected to other eligible taxpayers and who are not connected to any of the focal taxpayers from stage 1. In the anticliques we perform stratified random assignment to treatment, stratifying by size, degree, and baseline amendment propensity.

Full details of the procedure are available in the (public) pre-analysis plan included with this registration.
Experimental Design Details
Randomization Method
randomization done in an office on a computer.
Randomization Unit
firms.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
5,000 firms assigned to treatment out of 53,762 eligible firms (see PAP for eligibility description)
Sample size: planned number of observations
5,000 firms assigned to treatment out of 53,762 eligible firms (see PAP for eligibility description)
Sample size (or number of clusters) by treatment arms
53,762 eligible firms (see PAP for eligibility description)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
power calculations done by simulation as described in PAP of this and previous experiment.
IRB

Institutional Review Boards (IRBs)

IRB Name
Columbia University
IRB Approval Date
2020-02-04
IRB Approval Number
AAAS8400
Analysis Plan

Analysis Plan Documents

Pre-Analysis Plan

MD5: b1ffa89bc8c43c2c14034704a0f131e4

SHA1: 03b9dc49b0c180a5e97845f09c1f1845f89f1251

Uploaded At: June 05, 2025

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