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Record W1521113526 · doi:10.3386/w13435

Institutions and Foreign Investment: China versus the World

2007· report· en· W1521113526 on OpenAlexaff
Joseph P. H. Fan, Randall Mørck, Lixin Colin Xu, Bernard Yeung

Bibliographic record

VenueNational Bureau of Economic Research · 2007
Typereport
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChinaForeign direct investmentInvestment (military)International tradeBusinessInternational economicsEconomicsPolitical scienceMacroeconomicsLawPolitics

Abstract

fetched live from OpenAlex

Weak institutions ought to deter foreign direction investment (FDI), and mass media stories highlight China's institutional deficiencies, yet China is now one of the world's largest FDI destinations. This incongruity characterizes China's paradoxical growth. Cross-country regressions show that China's FDI inflow is not exceptionally large, given the quality of its institutions and its economic track record. Institutions clearly determine a country's allure as an FDI destination, but standard measures of institutional quality can be problematic for countries undergoing rapid institutional development, and can usefully be augmented by economic track record measures. Deng Xiaoping's 1993 "southern tour" heralded sweeping reforms, and this regime shift is insufficiently reflected in commonly used measures of institutional quality. China's FDI inflow surge after these reforms resembles similar post-regime shift surges in the East Bloc, and so is also unexceptional. Recent arguments that China's FDI inflow is inefficiently large because weak institutions deter domestic investment while special initiatives attract FDI are thus either unsupported or not unique to China.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.401
GPT teacher head0.487
Teacher spread0.086 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2007
Admission routes1
Has abstractyes

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