Making it less taxing: Using email reminders to improve tax compliance amongst businesses

Last registered on May 09, 2017

View Trial History

Pre-Trial

Trial Information

General Information

Title

Making it less taxing: Using email reminders to improve tax compliance amongst businesses

RCT ID

AEARCTR-0002201

Initial registration date

May 08, 2017

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

May 09, 2017, 11:45 AM EDT

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

Locations

Country

Australia

Region

Primary Investigator

Name

Michael Hiscox

Affiliation

Harvard University

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

In development

Start date

2017-04-27

End date

2017-07-31

Keywords

Governance

Additional Keywords

compliance, tax, business, reminder

JEL code(s)

D03 (Behavioural Microeconomics: underlying principles); D73 (Bureaucracy • Administrative Processes in Public Organizations • Corruption); D22 (Firm Behavior: Empirical Analysis); D53 (Financial Markets)

Secondary IDs

Abstract

The Deferred GST scheme allows businesses to defer the payment of GST on taxable imports which is beneficial for their cash flows. In order to remain on the scheme businesses must continue to meet all of their tax obligations. This includes lodging a monthly activity statement and being up to date on any payments due to the Australian Taxation Office (ATO).

At any given time, a proportion of businesses on the scheme are non compliant. Addressing this non-compliance creates additional work for the ATO and leads to higher levels of outstanding tax debt.
This trial will test the effectiveness of an email sent to non-compliant businesses reminding them to fulfil their tax obligations and highlighting the penalties of continued non-compliance. A successful intervention would increase business compliance and bring forward business tax payments.

External Link(s)

Registration Citation

Citation

Hiscox, Michael. 2017. "Making it less taxing: Using email reminders to improve tax compliance amongst businesses ." AEA RCT Registry. May 09. https://doi.org/10.1257/rct.2201-1.0

Former Citation

Hiscox, Michael. 2017. "Making it less taxing: Using email reminders to improve tax compliance amongst businesses ." AEA RCT Registry. May 09. https://www.socialscienceregistry.org/trials/2201/history/17471

Sponsors & Partners

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Experimental Details

Interventions

Intervention(s)

Businesses in the treatment groups will receive an email reminding them to fulfil their tax obligations and highlighting the penalties of continued non-compliance.

Intervention Start Date

2017-04-27

Intervention End Date

2017-07-31

Primary Outcomes

Primary Outcomes (end points)

Primary: (1) Proportion of businesses that become compliant (2) Payments made to tax office
Secondary: (1) Level of interaction (phone calls) with tax office (2) Changes in client account balances

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

This will be a ‘three arm trial’ involving two treatment groups and a control group.

Experimental Design Details

A sample of non-compliant businesses will be taken on the day of the trial launch. Some businesses will be excluded based on criteria relating to their lodgement method, relationship with the tax office and duration of non-compliance. Businesses will be randomly allocated to receive the email. Outcome measures for compliance will be measured on a daily basis throughout the trial. This process will be repeated until a sample of at least 1,200 businesses is achieved.

Randomization Method

Randomization will be done by a computer algorithm. Businesses will first be matched into triplets exhibiting similar characteristics. Randomisation will then be applied to each triplet so that one business is assigned to each of the treatment groups and one is assigned to the control group.

Randomization Unit

Individual businesses

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

N/A

Sample size: planned number of observations

At least 1,200 businesses

Sample size (or number of clusters) by treatment arms

Minimum of 400 in each treatment group and 400 in the control group.

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

For the outcome measure of proportion of businesses that become compliant, assuming alpha = 0.05 and power = 0.8 the study is powered to detect a 10% increase in compliance.

Supporting Documents and Materials

IRB