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Record W1772563446 · doi:10.1111/1756-2171.12100

Building new plants or entering by acquisition? Firm heterogeneity and entry barriers in the U.S. cement industry

2015· article· en· W1772563446 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 RAND Journal of Economics · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsBank of Canada
FundersFundación Caja MadridUS-UK Fulbright CommissionNational Science Foundation
KeywordsIndustrial organizationBusinessPermissiveCementEconomicsMicroeconomics

Abstract

fetched live from OpenAlex

I estimate a model of entry for the cement industry that considers two options of expansion: building a plant or acquiring an incumbent. The model takes into account that there is a transfer of the buyer firm‐level characteristics to the acquired plants, which affects profits from the acquisition. Estimates show that a less‐permissive Reagan–Bush administration's merger policy would decrease the number of acquired plants by 71%, greenfield entry would increase by 9.2% and consumer surplus would decrease by 23.5%. Results suggest that regulators should be concerned about policies that negatively affect the efficient reallocation of assets between incumbents and entrants.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.262

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 communication0.0000.000
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 head0.060
GPT teacher head0.257
Teacher spread0.197 · 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