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Do IRS Audits Deter Corporate Tax Avoidance?

2012· article· en· 561 citations· W3123872135 on OpenAlex· 10.2308/accr-50187

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

Candidate categories
Insufficient payload (model declined to judge)
Consensus categories
Insufficient payload (model declined to judge)
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Not applicableConsensus signal: Not applicable
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.375
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.008

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Opus teacher head0.053
GPT teacher head0.253
Teacher spread
0.199 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

ABSTRACT We extend research on the determinants of corporate tax avoidance to include the role of Internal Revenue Service (IRS) monitoring. Our evidence from large samples implies that U.S. public firms undertake less aggressive tax positions when tax enforcement is stricter. Reflecting its first-order economic impact on firms, our coefficient estimates imply that raising the probability of an IRS audit from 19 percent (the 25th percentile in our data) to 37 percent (the 75th percentile) increases their cash effective tax rates, on average, by nearly two percentage points, which amounts to a 7 percent increase in cash effective tax rates. These results are robust to controlling for firm size and time, which determine our primary proxy for IRS enforcement, in different ways; specifying several alternative dependent and test variables; and confronting potential endogeneity with instrumental variables and panel data estimations, among other techniques. JEL Classifications: M40; G34; G32; H25.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

The record

Venue
The Accounting Review
Topic
Corporate Taxation and Avoidance
Field
Business, Management and Accounting
Canadian institutions
Memorial University of NewfoundlandUniversity of Saskatchewan
Funders
not available
Keywords
EndogeneityInstrumental variableProxy (statistics)EnforcementPercentileCorporate taxEconomicsEconometricsPanel dataTax revenueLeverage (statistics)Tax avoidanceRevenueBusinessAuditTax creditPublic economicsAccountingStatistics
Has abstract in OpenAlex
yes