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WHAT DO WE KNOW ABOUT STOCK REPURCHASES?

2000· article· en· W2029249721 on OpenAlexaboutno aff
Gustavo Grullon, David L. Ikenberry

Bibliographic record

VenueJournal of applied corporate finance · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsDividendEarningsBusinessMonetary economicsStock (firearms)Profitability indexShareholderRetained earningsCapital (architecture)Capital expenditureFinanceFinancial systemEconomicsCorporate governance

Abstract

fetched live from OpenAlex

Stock repurchases by U.S. companies experienced a remarkable surge in the 1980s and ‘90s. Indeed, in 1998, the total value of all stock repurchased by U.S. companies exceeded for the first time the total amount paid out as cash dividends. And the U.S. repurchase movement has gone global in the past few years, spreading not only to Canada and the U.K., but also to countries like Japan and Germany, where such transactions were prohibited until recently. Why are companies buying back their stock in such amounts? After dismissing the popular argument that stock repurchases boost earnings per share, the authors argue that repurchases serve to add value in two main ways: (1) they provide managers with a tax‐efficient means of returning excess capital to shareholders and (2) they allow managers to “signal” to investors their view that the firm is undervalued. Returning excess capital is value‐adding for two reasons: First, it helps prevent companies from pursuing growth and size at the expense of profitability and value. Second, by returning capital to investors, repurchases (like dividends) play the critically important economic function of allowing investors to channel their investment from mature or declining sectors of the economy to more promising ones. But if stock repurchases and dividends serve the same basic economic function, why are repurchases growing more rapidly? Part of the explanation is that, because repurchases are taxed as capital gains and dividends as ordinary income, repurchases are a more tax‐efficient way of distributing excess capital. But perhaps even more important than their tax treatment is the flexibility that (at least) open market repurchases provide corporate managers‐flexibility to make small adjustments in capital structure, to exploit (or correct) perceived undervaluation of the firm's shares, and possibly even to increase the liquidity of the stock, which could be particularly valuable in bear markets. For U.S. regulators, the growth in open market stock repurchases raises some interesting issues. Perhaps most important, companies are not required to (and rarely do) furnish their investors with details about a given program's structure, execution method, number of shares repurchased, or even its duration. Policy regulators (and corporate executives as well) should consider some of the benefits provided by other systems, notably Canada's, which provide greater transparency and more guidelines for the repurchase process.

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)0.005
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.050
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.005
Science and technology studies0.0010.005
Scholarly communication0.0070.017
Open science0.0020.001
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0140.005

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 head0.020
GPT teacher head0.214
Teacher spread0.194 · 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 designNot applicable
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

Citations304
Published2000
Admission routes1
Has abstractyes

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