Dodging the Taxman: Firm Misreporting and Limits to Tax Enforcement
Open accessAbstract
Reducing tax evasion is a priority for many governments. A growing literature argues that verifying taxpayer reports against third-party information is critical for tax collection. However, effectiveness can be limited when tax authorities face constraints to credible enforcement and taxpayers make offsetting adjustments on other margins. We exploit a policy intervention in which Ecuadorian firms were notified about detected revenue discrepancies. Most firms simply failed to respond. Firms that responded increased reported revenue, matching the discrepancy amount when provided. However, they also increased reported costs by 96 cents per dollar of revenue adjustment, resulting in minor increases in tax collection. (JEL D22, H25, H26, O23)
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Firms systematically misreport their revenues, costs, and wages to the authorities.
“there is a growing body of evidence to show that firms systematically misreport their revenues, costs, and wages to the authorities ( Pomeranz 2015; Carrillo, Pomeranz, and Singhal 2017; Kumler, Verhoogen, and Frías 2015 )”
From Identifying and Spurring High-Growth Entrepreneurship: Experimental Evidence from a Business Plan Competition (2017) · cites this paper as Carrillo, Pomeranz, and Singhal 2017
The paper’s revenue- and cost-discrepancy histograms (main text; page unavailable) show widespread differences between firms’ reports and third-party data, supporting the revenue and cost portions of the claim. The passages found do not address wage reporting, so they do not support that portion. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cited by
Sorted by citations
McKenzie, D. (2017) · American Economic Review · doi:10.1257/aer.20151404 · Cited by 333 · see citing works
Losing to Gain: Revenue Shortfalls and Fiscal Capacity in Brazil
Ferraz, C., Foremny, D., & Santini, J. F. (2024) · doi:10.3386/w32440 · Cited by 1 · see citing works
- Authors
- Carrillo, P., Pomeranz, D., & Singhal, M.
- Affiliations
- George Washington University (US)
- University of Zurich (CH)
- National Bureau of Economic Research (US)
- Venue
- American Economic Journal: Applied Economics
- Publisher
- American Economic Association
- Published
- 2017-04-01
- Volume
- 9
- Issue
- 2
- Pages
- 144-164
- ISSN
- 1945-7782 (ISSN-L)
- 1945-7790
- OpenAlex
- W3123306252
- Cited by
- 280
- References
- 0
- Citations by year
- 2026: 16 · 2025: 25 · 2024: 31 · 2023: 37 · 2022: 47 · 2021: 39 · 2020: 30 · 2019: 19 · 2018: 17 · 2017: 11 · 2016: 2 · 2015: 5 · 2014: 1
- FWCI
- 37.90
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- American Economic Journal Applied Economics (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Taxation and Compliance Studies
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic and Fiscal Studies
- Social Sciences › Business, Management and Accounting › Accounting › Corporate Taxation and Avoidance
- Keywords
- tax evasion, tax enforcement, misreporting, third-party verification, cost reporting, tax collection
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review