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Record W2963165987 · doi:10.1177/0972150919850415

South–South Cooperation in South and East Asia: An Event Study of the China–Pakistan Economic Corridor

2019· article· en· W2963165987 on OpenAlexaff
Wing Him Yeung, Asad Aman

Bibliographic record

VenueGlobal Business Review · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBelt and Road Initiative
Canadian institutionsLakehead University
Fundersnot available
KeywordsChinaStock exchangeStock (firearms)Event studyStock marketSouth asiaBusinessExchange rateInternational economicsEconomicsEconomyDevelopment economicsGeographyFinanceAncient history

Abstract

fetched live from OpenAlex

South–South cooperation has been on the rise in recent years. One of the latest examples is the China–Pakistan Economic Corridor (CPEC) proposed by the Chinese and Pakistani governments in 2013. Using event study methodology, this article examines the impact of events and announcements associated with CPEC on the Pakistan Stock Exchange in Pakistan and the Shanghai Stock Exchange in China. The first key finding of this article is that the initial announcement associated with CPEC had stronger and positive short-term impact on the Pakistan Stock Exchange in comparison with the impact of subsequent CPEC events on the stock market. The second key finding is that the short-term impact of the CPEC initial announcement was stronger on the Pakistan Stock Exchange than on the Shanghai Stock Exchange, possibly due to the substantial difference in the size of the two economies. The empirical results of this article have important implications for investors, corporations and regulators to the Global South.

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 score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.258
Teacher spread0.231 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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