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Record W3124317975

Productivity Gains from Services Liberalization in Europe

2011· preprint· en· W3124317975 on OpenAlexfundno aff
Jan Bena, Peter Ondko, Evangelia Vourvachaki

Bibliographic record

VenueASEP · 2011
Typepreprint
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsnot available
FundersDivision of Graduate EducationSocial Sciences and Humanities Research Council of CanadaAkademie Věd České RepublikyGrantová Agentura České RepublikyUniverzita Karlova v Praze
KeywordsLiberalizationProductivityHarmonizationEuropean commissionExploitBusinessInternational economicsInternational tradeIndustrial organizationEconomicsEuropean unionEconomic growthMarket economy
DOInot available

Abstract

fetched live from OpenAlex

As part of the Single Market Program the European Commission commanded the liberalization and regulatory harmonization of utilities, transport and telecommunication services. This paper investigates whether and how this process affected the productivity of European network firms. Exploiting the variation in the timing and degree of liberalization efforts across countries and industries, we find that liberalization increased firm-level productivity but had no reallocation impact. Based on our estimates, the average firm-level productivity gain from liberalization amounts to 38 percent of the average total within-firm productivity gain in network industries. The results underscore the growth-promoting role of liberalization efforts.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.245
Teacher spread0.219 · 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
Published2011
Admission routes1
Has abstractyes

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