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Tax Audits as Scarecrows: Evidence from a Large-Scale Field Experiment
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Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
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The 30 checked references that resolve
resolves10.1086/NTJ41788949
ESTIMATING THE DETERMINANTS OF TAXPAYER COMPLIANCE WITH EXPERIMENTAL DATA
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Do Audits Enhance Compliance? An Empirical Assessment of VAT Enforcement
resolves10.17310/ntj.2001.1.06
Do Normative Appeals Affect Tax Compliance? Evidence from a Controlled Experiment in Minnesota
resolves10.1111/0272-4332.00063
What Number is “Fifty‐Fifty”?: Redistributing Excessive 50% Responses in Elicited Probabilities
resolves10.1016/j.jebo.2015.04.002
Tax compliance and enforcement in the pampas evidence from a field experiment
resolves10.1016/j.jebo.2006.08.006
Why do people pay taxes? Prospect theory versus expected utility theory
resolves10.1016/j.jdeveco.2012.01.002
Beyond baseline and follow-up: The case for more T in experiments
resolves10.1016/j.jpubeco.2018.01.005
Ghostbusting in Detroit: Evidence on nonfilers from a controlled field experiment
resolves10.1257/aer.20130393
No Taxation without Information: Deterrence and Self-Enforcement in the Value Added Tax
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The Elasticity of Taxable Income with Respect to Marginal Tax Rates: A Critical Review
resolves10.1016/S0047-2727(99)00107-3
Taxpayer response to an increased probability of audit: evidence from a controlled experiment in Minnesota
resolves10.1111/j.0272-4332.2004.00433.x
Risk as Analysis and Risk as Feelings: Some Thoughts about Affect, Reason, Risk, and Rationality
The 21 references without a DOI — listed, not checked
no DOI — not checkedSocial Norms and the Enforcement of Laws
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no DOI — not checkedInflation Expectations, Learning, and Supermarket Prices: Evidence from Survey Experiments
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no DOI — not checkedUsing Salience and Influence to Narrow the Tax Gap
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no DOI — not checkedMy taxes are too darn high: Tax protests as revealed preferences for redistribution
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no DOI — not checkedDoes It Matter Who Writes the Check to the Government? The Economics of Tax Remittance
no DOI — not checkedTax Compliance and Enforcement
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no DOI — not checkedComprehensive Taxpayer Attitude Survey (CTAS) 2017 Executive Report. Publication 5296 (Rev. 3-2018) Catalog Number 71353Y, Department of Treasury
no DOI — not checkedThat is NOT the IRS Calling You! The Washington Post
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no DOI — not checkedDreadful Possibilities, Neglected Probabilities
no DOI — not checkedRetroactive VAT Amounts" correspond to VAT payments and withholdings submitted for liabilities incurred two or more months prior to payment (e.g., VAT payments made in
no DOI — not checkedTreatment effects are estimated using the difference-in-differences specification reported in equation (2), which compares treated firms that received different signals on p and ?. In all cases, we include an additional set of dummies for quintiles of the pre-treatment VAT payments, which are the groups from which we drew the sample of "similar firms" to calculate p and ? and the corresponding interactions with the time variable. The results are based on Poisson regressions with variables expressed in percentage terms, which means the coefficients can be interpreted directly as elasticities. Panel (a) presents the effect of providing different information regarding p and ? in the audit-statistics message. Panel (b) compares the two audit-threat messages, i.e., the 50% threat of audit vs. the 25% threat of audit
no DOI — not checkedTreatment effects are estimated using the difference-in-differences specification reported in equation (2), which compares treated firms that received different signals on p and ?. In all cases, we include an additional set of dummies for quintiles of the pre-treatment VAT payments, which are the groups from which we drew the sample of "similar firms" to calculate p and ? and the corresponding interactions with the time variable. The results are based on Poisson regressions with variables expressed in percentage terms, which means the coefficients can be interpreted directly as elasticities. Panel (a) presents the effect of providing different information regarding p and ? in the audit-statistics message. Panel (b) compares the two audit-threat messages, i.e., the 50% threat of audit vs. the 25% threat of audit
no DOI — not checkedStandard errors reported in parentheses are clustered at the firm level. Treatment effects are estimated using the difference-in-differences specification reported in equation (1), which compares treated firms to control firms and pre-treatment to post-treatment periods, using yearly aggregated variables
no DOI — not checkedAdditional details about the model are reported in the notes to Table 2 and Section 4. Column (1) shows results from the main specification, i.e., the first year post-treatment effect estimates reported in Table 2. Column (2) reports the effect of the audit-statistics message on firms whose prior beliefs about probability of being audited were below the signal (p) reported in the letter they received. Column (3) reports the results for firms whose prior beliefs were above the reported p. In both cases, the reference group is the baseline group. Column (4) reports estimates for firms that were audited at least once between
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