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Record W3125009392

Foreign Direct Investment Spillovers and the Absorption Capabilities of Domestic Firms in the Argentine Manufacturing Sector (1992-2001)

2004· preprint· en· W3125009392 on OpenAlexfundno aff
Daniel Chudnovsky, Andrés López, Gastón Rossi

Bibliographic record

VenueSan Andres Digital Repository (University of San Andrés) · 2004
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsRestructuringForeign direct investmentProductivityBusinessAbsorption capacityInternational economicsOrder (exchange)Investment (military)International tradeEconomicsEconomic growthMacroeconomicsFinance
DOInot available

Abstract

fetched live from OpenAlex

Argentina received large amounts of FDI inflows during the 90s. At the same time, deep structural reforms were introduced, forcing domestic firms to rapidly undertake restructuring processes in order to adapt to the new economic and institutional environment. This paper explores to what extent FDI helped or hindered those restructuring processes, analyzing whether positive (or negative) productivity spillovers arose from the increasing presence of TNCs affiliates. We found that TNCs affiliates have higher productivity levels than domestic firms and that the latter, on average, received neither positive nor negative horizontal and vertical (backward) spillovers from the growing presence of foreign firms in the local economy. However, we also found that domestic firms with high absorption capabilities reaped positive spillovers from TNCs presence while those with low absorption capabilities were more likely to receive negative spillovers. These findings suggest that those capabilities are key determinants of the possibilities of domestic firms to take advantage of incoming FDI flows into their countries.

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 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)0.000
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 score0.486
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.188
Teacher spread0.175 · 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 teacher head, 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

Citations7
Published2004
Admission routes1
Has abstractyes

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