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Record W3036622553 · doi:10.1142/s0219091520500137

Wealth Effects of Retail Store Closure Announcements

2020· article· en· W3036622553 on OpenAlexaff
Abdul‐Rahman Khokhar

Bibliographic record

VenueReview of Pacific Basin Financial Markets and Policies · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsCompetitor analysisStock priceBusinessStock (firearms)Closure (psychology)Sample (material)Event studyMonetary economicsFinancial economicsEconomicsMarketingMarket economy

Abstract

fetched live from OpenAlex

This is the first study, to the best of our knowledge, to use value- and equal-weighted portfolios of U.S. retail firms to examine the stock market reaction to strategic and nonliquidating store closure announcements. Using event study methodology for a sample of 174 hand-collected store closure announcements during the period 1980–2017, we find a negative and significant stock price reaction on the announcement date. Given the highly competitive nature of the retail industry, we further investigate the market reaction for the closest competitors using a matched sample of 157 competing firms. We report a positive, albeit less significant stock price reaction for competing retail firms on the announcement date. Finally, a cross-sectional analysis shows that the stock price reaction to store closure announcements is positively associated with firm size.

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.217
Teacher spread0.203 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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