Unblocking big firms' tax collection: using nudges to encourage good behaviours in big firms

Last registered on September 17, 2024

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Pre-Trial

Trial Information

General Information

Title

Unblocking big firms' tax collection: using nudges to encourage good behaviours in big firms

RCT ID

AEARCTR-0012532

Initial registration date

September 16, 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, 1:54 PM EDT

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

Locations

Country

Colombia

Region

Primary Investigator

Name

Maria Alexandra Rizo Arango

Affiliation

Universidad de los Andes

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Luis Carlos Reyes

PI Affiliation

DIAN

Contact Investigator

PI Name

Daniel Eduardo Sandoval

PI Affiliation

Universidad de los Andes

Contact Investigator

Additional Trial Information

Status

Completed

Start date

2024-01-31

End date

2024-06-30

Keywords

Behavior, Firms & Productivity, Other

Additional Keywords

Tax compliance, big firms, development, tax bill, tax authority

JEL code(s)

H26, H25, C21, C33, D22

Secondary IDs

Prior work

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

Abstract

"The latest tax reform (Law 2277 of 2022) included changes in criminal offenses (sanctions) against tax evasion in the country. These modifications are outlined in Article 60 of the aforementioned law. It is the first time in Colombia that penalties for income and wealth tax evasion may lead to imprisonment.
This change can be used to identify shifts in taxpayers' behavior when filing their tax returns."

External Link(s)

Registration Citation

Citation

Reyes, Luis Carlos, Maria Alexandra Rizo Arango and Daniel Eduardo Sandoval. 2024. "Unblocking big firms' tax collection: using nudges to encourage good behaviours in big firms." AEA RCT Registry. September 17. https://doi.org/10.1257/rct.12532-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

In Colombia, there are 2536 Big Firms, which are companies or individuals contributing more than 60% of the revenue. The experiment will consist of four types of communications (treatment) will send to randomly selected samples within this population, stratify by sector. The communications differ in content, which is aimed at assessing the degree of response in the payment of their tax obligations. These communications will be dispatched between November 30, 2023, and February 1, 2024, on a one-time basis.

Intervention (Hidden)

Intervention Start Date

2024-01-31

Intervention End Date

2024-03-10

Primary Outcomes

Primary Outcomes (end points)

Income tax, wealth tax

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Tax compliance rate

Secondary Outcomes (explanation)

Percentage of taxpayers who declare and pay.

Experimental Design

Description of Treatments
Sample size
Communication delivery Method
Brief description of why this would affect Y

Experimental Design Details

Randomization Method

Randomization done in office by a computer

Randomization Unit

Cluster by sector?

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

A randomization test was carried out to obtain a sample of 500 signatures, eliminating the highest percentile in order to avoid unnecessary movements due to the fact that the values are very high, generating different behaviors in the sample.

Sample size: planned number of observations

We have 2536 Big Firms

Sample size (or number of clusters) by treatment arms

This sample of 500 signatures was randomly reorganized into four groups: three treatment groups and one control group.
1. Criminal with manual signature of the director
2. Minimum taxation with manual signature
3. Penalty with digital signature of the director
4. Control (80)

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

Supporting Documents and Materials

IRB