Micro-enterprises’ behavioral responses to changes in tax burden: Evidence from a survey experiment

Last registered on June 18, 2026
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Pre-Trial

Trial Information

General Information

Title
Micro-enterprises’ behavioral responses to changes in tax burden: Evidence from a survey experiment
RCT ID
AEARCTR-0018914
Initial registration date
June 12, 2026

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 18, 2026, 9:25 AM EDT

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

Locations

Country
Italy
Region
Autonomous Province of Trento

Primary Investigator

Name
Annalisa Tassi
Affiliation
FBK-IRVAPP
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Other Primary Investigator(s)

PI Name
Alessio Tomelleri
PI Affiliation
FBK-IRVAPP
Contact Investigator
PI Name
Sergiu Burlacu
PI Affiliation
FBK-IRVAPP
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Additional Trial Information

Status
On going
Start date
2026-05-26
End date
2026-12-31
Keywords
Behavior, Firms & Productivity, Labor, Other
Additional Keywords
Business taxes, tax incidence, firm behavior, investment, labor supply, labor demand, micro-enterprises, tax literacy
JEL code(s)
D22, H00, H22, H25, J22, J23
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Micro-enterprises account for a large share of employment and value added, yet their behavioral responses to taxation are poorly understood. Existing evidence focuses mainly on large firms’ ex post responses observed in administrative data, while much less is known about intended behavioral adjustments, especially among very small firms with limited managerial capacity and tax literacy. Moreover, existing studies (e.g., Kennedy et al., 2024; Duan and Moon, 2025; Giroud and Rauh, 2019; Risch, 2024; Suarez Serrato and Zidar, 2016) largely focus on one or few margins of adjustment to a change in tax burden (e.g., consider only effects on consumer prices), disregarding other contemporaneous strategic reactions (e.g., investments, labor costs).
This study aims to elicit how micro-entrepreneurs say they would react to a permanent increase or decrease in their overall tax burden, through a between-subject vignette study implemented within a survey to microenterprises in the Trentino Region, Italy. We further examine how these stated responses vary with tax literacy, tax regime, and firm or owner characteristics.
The closest study to ours is Winter et al. (2025) which implements a vignette study in Germany aimed at understanding the overall incidence of business taxes. First, we provide a replication of their study in the case of Italian microenterprises. Additionally, we create a novel tax literacy index which we exploit to understand heterogeneity in intended behavioral responses. Further, as a share of microenterprises is subject to a simplified tax regime, the eligibility to which depends on strict cost and revenue thresholds, we can understand whether responses are bound by tax regime. Finally, since many microenterprises do not have employees, we aim to understand if the microentrepreneur would increase or decrease his labor supply in response to the different scenarios.
Understanding these mechanisms is relevant for: the design of micro and small-business tax policies; assessing (unintended) pass-through effects on investment, prices, and labor inputs; interpreting heterogeneous and asymmetric responses to tax reforms among micro- enterprises.

REFERENCES
Duan, Yige, and Terry Moon. 2025. “Impacts of Corporate Tax Cuts on Firms and Workers: Evidence from Small Businesses.” SSRN Scholarly Paper 4301243
Giroud, Xavier, and Joshua Rauh. 2019. “State Taxation and the Reallocation of Business Activity: Evidence from Establishment-Level Data.” Journal of Political Economy, 127(3): 1262–1316.
Kennedy, Patrick J., Christine Dobridge, Paul Landefeld, and Jake Mortenson. 2024. “The Efficiency-Equity Tradeoff of the Corporate Income Tax: Evidence from the Tax Cuts and Jobs Act.” Working Paper
Risch, Max. 2024. “Does Taxing Business Owners Affect Employees? Evidence from a Change in the Top Marginal Tax Rate.” The Quarterly Journal of Economics, 139(1): 637–692
Suarez Serrato, Juan Carlos, and Owen Zidar. 2016. “Who Benefits from State Corporate Tax Cuts? A Local Labor Markets Approach with Heterogeneous Firms.” American Economic Review, 106(9): 2582–2624
Winter, R., Doerrenberg, P., Eble, F., Rostam-Afschar, D., & Voget, J. (2025). The Asymmetric Incidence of Business Taxes: Survey Evidence from German Firms. IZA Working Paper No. 17983
External Link(s)

Registration Citation

Citation
Burlacu, Sergiu, Annalisa Tassi and Alessio Tomelleri. 2026. "Micro-enterprises’ behavioral responses to changes in tax burden: Evidence from a survey experiment." AEA RCT Registry. June 18. https://doi.org/10.1257/rct.18914-1.0
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Experimental Details

Interventions

Intervention(s)
This study investigates how micro-entrepreneurs adjust their intended business decisions in response to changes in their tax burden. The experiment is embedded in an online survey administered to micro-enterprises in the Autonomous Province of Trento, Italy.

Objectives
1. Estimate the causal effect of an exogenous tax-change scenario (increase vs decrease) on intended firm-level behavioral responses. Identify which adjustment margins (prices, investment, labor costs, own working time, input costs) are most salient.
2. Analyze heterogeneity in responses by: assessed tax literacy, self-reported tax literacy, self-reported tax regime, firm characteristics (sector, presence of employees, dimension, firm age), and owner characteristics (sex, level of education, age group).

Eligible respondents are business owners or legal representatives of firms with fewer than 10 employees who are involved in financial and strategic decisions. Firms are randomly assigned, with equal probability, to one of two hypothetical scenarios: a permanent 10% increase or a permanent 10% decrease in the firm’s overall tax burden on business income. The unit of randomization is the firm. The primary outcomes are stated adjustments in prices, investment, labor costs and human-capital investment, own working time, and other input costs, measured using directional indicators and a seven-point qualitative intensity scale. We will estimate the average effect of the tax-increase scenario relative to the tax-decrease scenario and test whether responses are asymmetric across adjustment margins. We will also examine heterogeneity by assessed and self-reported tax literacy, tax regime, firm characteristics, and owner characteristics. The expected sample size is 1,500–2,000 micro-enterprises, with approximately equal allocation across the two experimental arms.
The intervention consists of a randomly assigned hypothetical vignette describing a permanent change in the firm’s overall tax burden:
Tax increase treatment: the firm is told that its total tax burden on business income increases permanently by 10%.
Tax decrease treatment: the firm is told that its total tax burden on business income decreases permanently by the same percentage (e.g. −10%).
The vignette explicitly states that:
• the change is permanent and not targeted to a specific firm,
• it applies to the firm’s income as a whole (not to a specific tax).
The wording does not refer to changes in demand, input, prices, competition regulation, or any other market conditions.
Immediately after the vignette, respondents are asked how they would adjust their behavior along several predefined margins or have the chance to include additional margins of adjustment.
Intervention Start Date
2026-05-26
Intervention End Date
2026-06-30

Primary Outcomes

Primary Outcomes (end points)
For each outcome, the main estimand is the difference in mean outcome between firms assigned to the tax-increase scenario and firms assigned to the tax-decrease scenario.
• Binary indicators capturing whether the firm would:
o Reduce, not change, or increase prices,
o Reduce, not change, or increase investment (tangible and intangible assets),
o Reduce, not change, or increase labor costs and human capital investment,
o Increase, not change, or decrease own working time,
o Cut, not change, or increment other (input) costs,
o Increase, not change, or decrease other margins they can specify.

• Intensity of intended changes (where elicited), we use a Likert scale with 7 levels going from “I would decrease this item by a lot” --- the middle element is “no change” --- up to “I would increase this item by a lot”.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Internal consistency between self-reported and assessed tax literacy. Heterogeneity by: (assessed and self-reported) tax literacy, tax regime, industry/sector, firm size, gender and educational level of the entrepreneur.

Symmetry/asymmetry of results based on treatment branch. Since we do not force a direction of the answer (i.e., we do not assume that microenterprises will increase the prices following a tax increase, they may also decide to decrease it) we can test for the asymmetry in the direction of the change and separately for the asymmetry in the intensity of change.
Given the richness of the data collected, we will report as exploratory a data-driven heterogeneity analysis following the latest methodological developments in the literature (e.g., Chernozhukov et al., 2018; Wager and Athey, 2018, Chernozhukov, Demirer, Duflo and Fernández-Val, 2020 etc.).

References
Chernozhukov, V., Fernández‐Val, I., & Luo, Y. (2018). The sorted effects method: discovering heterogeneous effects beyond their averages. Econometrica, 86(6), 1911-1938.
Chernozhukov, V., Demirer, M., Duflo, E., & Fernández-Val, I. (2020). Generic machine learning inference on heterogenous treatment effects in randomized experiments.
Wager, S., & Athey, S. (2018). Estimation and inference of heterogeneous treatment effects using random forests. Journal of the American Statistical Association, 113(523), 1228-1242.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Design: Survey-embedded randomized controlled experiment.
Assignment: Between-subjects design with equal probability of assignment to each scenario.
Blinding: Respondents are unaware of alternative scenarios and of the experimental nature of the survey. The treatment is inserted in the last part of the questionnaire.

Experimental Design Details
Not available
Randomization Method
Simple random assignment implemented by the survey software at the respondent level.
Randomization Unit
Unit of randomization: Firm (one respondent per firm).
Unit of measurement: Firm-level stated behavioral responses.
Stratification: The survey sample is stratified by sector and by whether or not the enterprise has employees. Additional stratification for treatment assignment is not possible.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1,500-2,000 microenterprises.
Sample size: planned number of observations
1,500-2,000 microenterprises.
Sample size (or number of clusters) by treatment arms
750-1000 per treatment arm (around 50% of the sample in each arm)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The study is powered to detect small-to-moderate differences in response probabilities between treatment arms (e.g. 5–10 percentage points). Assumptions: Balanced assignment across treatments. Binary outcomes with baseline probabilities between 0 and 1. Standard significance level (α = 0.05) and power (1 − β = 0.8). Final sample size requirements depend on the number of outcomes analyzed and the degree of planned heterogeneity analysis.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan