MétaCan
Menu
Back to cohort

Foreign direct investment and technology spillovers in Mexico: 20 years of NAFTA

2017· article· en· W2770166902 on OpenAlexaboutno aff
Enrique Blanco Armas, José Carlos Rodríguez

Bibliographic record

VenueJournal of technology management & innovation · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentAbsorptive capacityLiberalizationIndustrialisationTechnology gapInternational tradeIndigenousEconomicsInternational economicsEmerging marketsBusinessMarket economyIndustrial organization

Abstract

fetched live from OpenAlex

This article analyses the development of technology capabilities in the manufacturing sector of Mexico during the last two decades.It has been argued that the inclusion of Mexico in the North America Free Trade Agreement (NAFTA) in 1994 would be enough to catch up with Canada and the United States.In this regard, trade liberalisation and foreign direct investment (FDI) would have been two strategic tools to close the technology gap between Mexico and its commercial partners in North America.Yet, after twenty years of NAFTA, it has been demonstrated that many indigenous firms in Mexico must develop an absorptive capacity to benefit from FDI.This paper suggests that the debate on the Asian miracle in the 1990s could be an adequate theoretical framework to discuss technology development and industrialisation in the case of emerging economies.In fact, this debate reveals two alternative approaches to explain the development of technology capabilities: (i) the accumulation view of growth, and (ii) the assimilation view of growth.Therefore, the Asian miracle exemplifies how entrepreneurship, learning and a supporting innovation policy could be an adequate strategy to benefit from FDI and technology spillovers in the case of emerging economies.

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)0.001
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 score0.080
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
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 head0.014
GPT teacher head0.235
Teacher spread0.221 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of technology management & innovationSame topicGlobal Trade and CompetitivenessFrench-language works237,207