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Record W4400308701 · doi:10.1093/ej/ueae062

The Rise of Pass-Throughs: an Empirical Investigation

2024· article· en· W4400308701 on OpenAlexaff
Sebastian Dyrda, Benjamin Pugsley

Bibliographic record

VenueThe Economic Journal · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEconomicsBusinessBusiness cycleLabour economicsPublic economicsMacroeconomics

Abstract

fetched live from OpenAlex

Abstract Almost half of all private employment in the United States is within businesses that do not pay corporate income tax. Instead, business income passes through to the owners’ individual income taxes. This pass-through share of employment has more than tripled since the early 1980s. Using comprehensive, confidential administrative data, this paper highlights five core findings underlying this growth: (1) the rise in pass-throughs is pervasive across industries and states; (2) the pass-through share converges unconditionally across both; (3) entrants’ organisational choices drive 60% of the rise; (4) shifts in firm and organisational dynamics following the 1986 Tax Reform Act show continued effects through the 2000s; (5) organisational forms exhibit high persistence with little life-cycle variation. Our study implies that tax or regulatory policy changes might take decades to manifest fully.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

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.

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

Opus teacher head0.037
GPT teacher head0.270
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

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