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Record W2954497595 · doi:10.1504/ejim.2020.10017198

Riding the storm out: the short- and long-term effects of export promotion on firm performance during an economic downturn

2018· article· en· W2954497595 on OpenAlexaff
Joan Freixanet, Iya Churakova, Josep Rialp Criado, Hsin‐Chen Lin

Bibliographic record

VenueEuropean J of International Management · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPromotion (chess)RecessionBusinessExport performanceTerm (time)International economicsEconomicsInternational tradePolitical sciencePoliticsMacroeconomics

Abstract

fetched live from OpenAlex

This study evaluates the short- and long-term impact of export promotion by focusing on a Spanish program to support beginning exporters. Based on the observations of 1884 firms over the period of 2005-2014, the findings demonstrate that the program had a positive impact on participants' export and economic performance, and the effects were persistent. The paper concludes that focusing export promotion towards SMEs and beginning exporters and ensuring a balanced mix of various forms of assistance are critical to the effectiveness and lasting effects of export promotion. It also shows that, during the recent great trade collapse starting in 2008, firms using this type of assistance outperformed firms in the control group and the national average regarding both export growth and survival rates. These results are encouraging regarding the countercyclical potential of export promotion. The findings have significant implications for scholars, managers and policymakers.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.332

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 studies0.0000.000
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 head0.040
GPT teacher head0.222
Teacher spread0.183 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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