R&D profitability, intensity and market-to-book: evidence from Australia
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.
Bibliographic record
Abstract
Purpose The purpose of this paper is to assess the financial disclosure vis-á-vis economic reality of research and development (R&D) expensed by Australian firms under the pre-2005 Australian generally accepted accounting principles (A-GAAP) regime via the lens of market-to-book. Design/methodology/approach The authors estimated firms' R&D profit rate, measured R&D revenue intensity and modelled the impacts of these and related economic factors, via economic and financial disclosure channels, on market-to-book using data for 1988-2004. Findings R&D, on average, was profit neutral and had undetectable impacts on market-to-book whether via equity valuation or financial disclosure. Research limitations/implications Market-to-book's information content is best viewed as conditional on the reference disclosure regime. Australian firms' typically at best minimal R&D profitability is an international anomaly. Data limitations in terms of the generating process and availability mean that R&D's impact on market-to-book via financial reporting is not definitively determined. Practical implications Restrictive rules on the capitalization of intangible asset-related expenditures under A-GAAP apparently did not adversely impact market-to-book's economic information. AIFRS's more permissive rule risks compromising market-to-book's reliability in such a role. Originality/value For Australia, the paper is anticipated to be the first to estimate the profit rate of R&D, measure the intensity of R&D, and model R&D's influence on the market-to-book ratio. It develops a framework for the economic and financial reporting impacts of investments on a key indicator of firms' financial standing and contributes to the debate on identifiable intangibles' disclosure.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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.
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