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Record W2139379567

Financial Constraints and the Incentive for Tax Planning

2013· article· en· W2139379567 on OpenAlexaff
Alexander Edwards, Casey M. Schwab, Terry Shevlin

Bibliographic record

VenueSSRN Electronic Journal · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFinanceMonetary economicsEconomicsBusinessTax avoidanceAccrualTax reformIncentiveDouble taxationPublic economicsMicroeconomics
DOInot available

Abstract

fetched live from OpenAlex

In this study, we investigate the association between financial constraints, at both the macroeconomic and firm-specific level, and one potentially significant source of internal funds available to firms – cash savings generated through tax planning. In equilibrium a firm will undertake tax avoidance strategies if the marginal benefit (i.e., reduction in taxes payable) exceeds the marginal costs. Assuming the cost of implementing tax avoidance strategies does not increase for financially constrained firms, this suggests that firms will increase tax avoidance as access to external funds becomes more costly. Measuring financial constraints based on both macroeconomic measures (change in GDP and bank lending tightening) and firm-specific measures (a financial distress indicator based on the Altman Z-score and the decile ranking of the Whited and Wu 2006 financial constraint index), we find that firms facing financial constraints exhibit lower cash effective tax rates. Understanding how financial constraints affect tax avoidance and the interplay between macroeconomic forces and firm-level tax avoidance behavior is important as legislators look for ways to reduce the federal deficit.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.208
Teacher spread0.199 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations38
Published2013
Admission routes1
Has abstractyes

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