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Record W2993574303 · doi:10.1108/par-10-2018-0078

Managers’ stock-based compensation and disclosures of high proprietary cost information

2019· article· en· W2993574303 on OpenAlexaff
Luminiţa Enache, Jae Bum Kim

Bibliographic record

VenuePacific Accounting Review · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBusinessEquity (law)AccountingStock (firearms)Agency costExecutive compensationPrincipal–agent problemStock optionsActuarial scienceFinanceMarketingCorporate governanceShareholder

Abstract

fetched live from OpenAlex

Purpose The purpose of this study is to examine whether chief executive officers’ (CEOs’) stock-based compensation has any relationship with disclosure of high proprietary information. Design/methodology/approach Drawing on agency and proprietary cost theory, this study examines whether compensating CEOs based on equity value through the grants of stock option and restricted stock will affect different firms with high proprietary costs versus general costs of disclosures. The authors further explore the cross-sectional variation on the relationship between stock-based compensation and disclosures of high proprietary cost information. In particular, the authors examine certain circumstances under which stock-based compensation has a stronger effect in discouraging managers to make disclosures of product-related information. This study conducts an empirical investigation on the relationship by using hand-collected data on the product-related disclosures of biotechnology firms and by developing new disclosure indices to capture the product developments in the preclinical and clinical stages. Findings The authors find that on average, managers’ stock-based compensation does not have any significant relationship with the proxy of high proprietary disclosure index. More importantly, the authors find that managers with more equity-based compensation (in the total pay) make fewer disclosures of high proprietary cost information when they have a stronger need to protect such information. Specifically, the authors find a negative relationship between equity-based compensation and managers’ disclosure of high proprietary cost information when their firms’ product development is in early stage, when the corporate board mainly consists of directors with lack of sufficient knowledge on technology, and when firms are a leader in an industry in terms of market share. Research limitations/implications The authors acknowledge two limitations of the current study. First, the authors cannot completely rule out the possibility that the results are still subject to endogeneity issues such as reverse causality or omitted correlated variables even though the authors control for other important variables that affect disclosures and granting of stock-based compensation (including firm size, leverage, analyst following, institutional ownership and corporate governance) and use the lagged variable of stock-based compensation in the regression model. Second, given that the authors examine a small sample (only 10 per cent of firms in the biotechnology industry) due to the required hand-collection of product-related information, the generalizability of the results may be limited. Originality/value The study contributes to the literature in two important ways. First, the findings can add to the literature on the effect of stock-based compensation on managers’ disclosures. While previous studies suggest that compensating via stock options and restricted stocks can incentivize managers in enhancing firm disclosures in general (e.g. Nagar et al ., 2003), the authors provide evidence suggesting that it may not always be the case. When disclosing information involves high proprietary cost, stock-based compensation can sometimes motivate managers not to reveal information. The study also complements Erkens (2011), who finds that firms offer stock-based compensation to their managers as an attempt to prevent the leakage of research and development (R&D)-related information to competitors. Second, the study can contribute to the extant literature that examines the importance of proprietary costs on firms’ disclosure decisions. The authors attempt to respond to the call for more research in this area (Beyer et al., 2010) by focusing on one specific industry, the biotech industry and by using a novel proxy for the proprietary costs based on the stage of product development for a drug-related product in that industry. As it has been challenging for researchers to properly measure proprietary costs of disclosures, the setting of the biotech industry provides a particularly strong empirical identification to potentially pinpoint the proprietary costs.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.545

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 communication0.0000.002
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 head0.012
GPT teacher head0.203
Teacher spread0.191 · 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 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

Citations5
Published2019
Admission routes1
Has abstractyes

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