Validating measurement approaches for sensitive topics with administrative tax data in Uganda

Last registered on November 01, 2023

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Pre-Trial

Trial Information

General Information

Title

Validating measurement approaches for sensitive topics with administrative tax data in Uganda

RCT ID

AEARCTR-0012298

Initial registration date

October 28, 2023

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

November 01, 2023, 4:10 PM EDT

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

Locations

Country

Uganda

Region

Kampala

Primary Investigator

Name

Yannick Markhof

Affiliation

United Nations University

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Stephan Dietrich

PI Affiliation

UNU-MERIT / Maastricht University

Contact Investigator

PI Name

Rose Camille Vincent

PI Affiliation

ETH Zurich

Contact Investigator

Additional Trial Information

Status

Completed

Start date

2023-09-15

End date

2023-10-21

Keywords

Behavior, Firms & Productivity

Additional Keywords

taxation

JEL code(s)

H25, H26

Secondary IDs

Prior work

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

Abstract

Our study will conduct a number of survey experiments to investigate the accuracy of different approaches widely used to estimate the prevalence of sensitive behavior in the social sciences.The context of the study is tax compliance in a sample of small- to mid-sized enterprises in Kampala, Uganda. By combining survey data with administrative tax records for the same firms, we assess the performance of different measurement approaches, benchmarked against the administrative data, within the same survey. This allows us to quantify measurement error in different self-reported measures of tax compliance and make recommendations for policy and research based on our findings.

External Link(s)

Registration Citation

Citation

Dietrich, Stephan, Yannick Markhof and Rose Camille Vincent. 2023. "Validating measurement approaches for sensitive topics with administrative tax data in Uganda." AEA RCT Registry. November 01. https://doi.org/10.1257/rct.12298-1.0

Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)

We conduct a number of survey experiments to collect self reported data on tax compliance among the firms in our sample.

Intervention Start Date

2023-09-15

Intervention End Date

2023-10-21

Primary Outcomes

Primary Outcomes (end points)

tax compliance

Primary Outcomes (explanation)

We will measure compliance with national business tax filing requirements as well as with municipal trade license requirements as our primary outcomes of interest.

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

We conduct a number of survey experiments to collect self reported data on tax compliance among the firms in our sample.

Experimental Design Details

We conduct a number of survey experiments to collect self reported data on tax compliance among the firms in our sample. We then link this survey data to administrative data on tax compliance for the same firms to validate the accuracy of different surveying techniques to elicit truthful answers to sensitive questions.

Randomization Method

Random assignment coded into survey tool through a random number generator.

Randomization Unit

Firm level randomization (unit of observation)

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

1500 firms

Sample size: planned number of observations

1500 firms

Sample size (or number of clusters) by treatment arms

Even split for each survey experiment and tax level. Expected sample sizes per experiment:

Experiment 1: List experiment
750 (URA), 750 (KCCA)

Experiment 2: Randomized Response
750 (URA), 750 (KCCA)

Experiment 3: Bayesian Truth Serum
750 (BTS), 750 (Control / Direct Questioning)

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

Supporting Documents and Materials

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IRB