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Record W3122888805 · doi:10.2308/accr.2005.80.1.85

What Determines Residual Income?

2005· article· en· W3122888805 on OpenAlex

Why this work is in the frame

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

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Accounting Review · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEconomic rentResidual income valuationEconomicsPassive incomeValuation (finance)Explanatory powerReturn on equityEquity (law)Market valueResidualMarket powerAccountingMonetary economicsFinancial economicsLabour economicsMicroeconomicsMarket economyGross incomeFinanceEquity capital marketsMonopolyProfitability index

Abstract

fetched live from OpenAlex

This paper investigates the determinants of residual income scaled by book value of equity, i.e., abnormal return on equity (ROE), by analyzing the impact of value-creation (economic rents) and value-recording (conservative accounting) processes on abnormal ROE. I rely on economic theories to characterize economic rents and develop an empirical measure—the conservative accounting factor—to capture the effect of conservative accounting. As expected, industry abnormal ROE increases with industry concentration, industry-level barriers to entry, and industry conservative accounting factors. Also as expected, the difference between firm and industry abnormal ROE increases with market share, firm size, firm-level barriers to entry, and firm conservative accounting factors. Integrating these determinants into the residual income valuation model significantly increases its explanatory power for the variation in the market-to-book ratio.

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.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.053
GPT teacher head0.338
Teacher spread0.285 · 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