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Record W3122093281

Productivity Spillovers from Competitive Reallocation: Evidence from Canadian Manufacturing Plants

2009· preprint· en· W3122093281 on OpenAlexaboutno aff
Guy Gellatly, John R. Baldwin

Bibliographic record

VenueRePEc: Research Papers in Economics · 2009
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsnot available
Fundersnot available
KeywordsProductivityFrontierExternalityMarket shareEconomicsEconomic geographyGeographyMicroeconomicsEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

This paper uses plant-level data on productivity growth and changes in market share over different periods during the 1970s, 1980s, and 1990s to investigate whether plants with declining market shares obtain productivity spillovers from more successful producers and whether the impact of spillovers is affected by the distance between plants. We are primarily interested in the extent to which productivity externalities moderate the centrifugal forces that separate growing plants from declining rivals because of the productivity advantages enjoyed by the former. The paper focuses on the productivity performance of plants with declining market shares as potential receivers of productivity spillovers. Two possible sources for these spillovers are examined rival plants operating at the technological frontier and rivals that are actively gaining market share. The analysis advances a model of the externality process in which the productivity of declining plants is influenced by (1) the economic distance of the declining plant from its technological frontier at the beginning of any period, (2) contemporaneous productivity gains in rival plants that are actively wresting market share away from decliners, and (3) the distance between rival plants. We evaluate the existence and magnitude of these sources of spillovers frontier plants and market-share gainers because of what they reveal about the types of productive information that struggling plants may be able to assimilate from rivals. Spillovers from the plants at the existing frontier are likely to reflect the established best practices of industry leaders; spillovers coming from market-share gainers involve new sources of productive knowledge that emerge as the frontier is actively being re-established. Our model also incorporates geographic information on the proximity of declining plants to both frontier plants and market-share gainers to test whether productivity spillovers are spatially circumscribed. The resu

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)0.005
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 score0.079
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.061
GPT teacher head0.284
Teacher spread0.223 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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