Balancing Progressivity and Efficiency: A Survey Experiment to elicit Preferences

Last registered on September 17, 2024

View Trial History

Pre-Trial

Trial Information

General Information

Title

Balancing Progressivity and Efficiency: A Survey Experiment to elicit Preferences

RCT ID

AEARCTR-0013839

Initial registration date

September 13, 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, 1:47 PM EDT

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

Locations

Country

Brazil

Region

Country

Spain

Region

Country

United States of America

Region

Primary Investigator

Name

Pilar Sorribas-Navarro

Affiliation

Universitat de Barcelona

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Andreu Arenas

PI Affiliation

Ivàlua and University of Barcelona

Contact Investigator

PI Name

Dirk Foremny

PI Affiliation

University of Barcelona

Contact Investigator

Additional Trial Information

Status

In development

Start date

2024-09-16

End date

2024-09-21

Keywords

Behavior, Electoral, Firms & Productivity, Governance, Labor

Additional Keywords

Taxation, Development, Survey Experiment

JEL code(s)

H11; H21; H24; H31; H50

Secondary IDs

Prior work

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

Abstract

This study aims to estimate individuals' preferences regarding the progressivity and efficiency of the Personal Income Tax (PIT). Variations in PIT designs result in differing impacts on redistribution and efficiency. While more progressive taxes achieve higher redistribution, their effects on tax revenues and economic growth remain inconclusive. To address this, we employ an experimental conjoint survey design to elicit individual preferences for regarding this trade-off.

In this experiment, participants will be presented with pairs of proposals for the design of the personal income tax and will choose their preferred option. Each proposal will provide details on different dimensions of the proposal: progressivity (marginal tax rates across six income brackets), tax revenues generated, the budgetary implications, and impact on economic growth.

This research is conducted across three countries—Spain, the USA, and Brazil—each with distinct levels of inequality, development, and importance of the welfare state.

External Link(s)

Registration Citation

Citation

Arenas, Andreu, Dirk Foremny and Pilar Sorribas-Navarro. 2024. "Balancing Progressivity and Efficiency: A Survey Experiment to elicit Preferences." AEA RCT Registry. September 17. https://doi.org/10.1257/rct.13839-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2024-09-16

Intervention End Date

2024-09-21

Primary Outcomes

Primary Outcomes (end points)

1-Marginal Means
2-AMCEs
3-WTPs
4-Weights of the attributes

And variations of these outcomes, as explained in the pre-analysis plan.

Primary Outcomes (explanation)

1-Marginal means: estimate of E[y|X], where X are the attributes, and y are ratings and choices
2-AMCEs: average marginal component effects for progressivity, level of tax revenues, efficiency and individual tax burden
3-WTPs: ratio of AMCEs of progressivity, level of tax revenues, and efficiency over the AMCE of individual tax burden.
4-Weights of the attributes: ratio of each of the AMCEs over the sum of the absolute values of all AMCEs

These will be studied on average for each country and also individually, focusing on the distribution of preferences, and their correlates (both with other preferences and with individual characteristics and beliefs). This is explained in detail in the PAP.

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

This design is a conjoint analysis of preferences for tax policy. Alternatives of policy proposals are randomly chosen in pairs to participants, who rate them, and choose the most preferred one.

Experimental Design Details

Respondents rate and choose between pairs of alternatives of fiscal policy proposals. Each alternative features a tax schedule (i.e., marginal tax rates for different income brackets), the resulting change in income tax revenues, what the government will do with the change in revenues (i.e., changes in different types of spending), and the expected effect on economic growth.

The aim is to retrieves preferences for the various attributes and to understand how people trade-off efficiency, equity, and self-interest motives in preferences for fiscal policy.

Randomization Method

The data collection is done by Netquest, a market-research company with ample evidence in conjoint designs. They will randomize the conjoint profiles shown to the survey participants.

Randomization Unit

Randomization is at the individual level so that alternatives are orthogonal to individual characteristics.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

2000 individuals per country (Brazil, Spain, US)

Sample size: planned number of observations

2000 x 8 x 2 = 32000 for each country.

Sample size (or number of clusters) by treatment arms

Each alternative is randomly chosen over all possible combinations of the attributes with only one constraint: the exclusion of regressive income tax alternatives. The change in fiscal revenues approximately corresponds to the change in marginal tax rates.

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

Power calculations for AMCEs: For continuous or binary attributes, the statistical power for an effect size of 0.02 is 94%. The type S error is 9% and the type M errror is 1.21. For those attributes with 6 levels (the marginal tax rate for each bracket, or the various spending categories), the statistical power for an effect size of 0.03 is 88%. The type S error is 0% and the type M error is 1.13.

Supporting Documents and Materials

IRB