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Record W1531848024

Measuring International Capital Mobility: A Review

2016· review· en· W1531848024 on OpenAlexaboutno aff
Jeffrey A. Frankel

Bibliographic record

VenueAmerican Economic Review · 2016
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsFinancial integrationCapital (architecture)EconomicsInvestment (military)International economicsLiberalizationArgument (complex analysis)Financial capitalDeveloping countryInternational tradePolitical scienceFinanceMarket economyEconomic growthFinancial marketHuman capitalGeography
DOInot available

Abstract

fetched live from OpenAlex

Many barriers to the international movement of capital across national boundaries have been dismantled over the course of the last 20 years. Financial integration was greatly enhanced by the removal of capital controls on the part of the United States, Germany, Canada, Switzerland, and the Netherlands after 1973; the recycling of surpluses to developing countries through the Euromarkets in the 1970's; the removal of capital controls in the United Kingdom and Japan beginning in 1979; financial integration among European Community countries, including France and Italy, in preparation for 1992; recent moves toward financial liberalization in smaller countries in the Pacific; and the steady process of technical and institutional innovation that has proceeded around the world. Some popular tests of international capital mobility, however, appear to show anomalous results. Martin Feldstein and Charles Horioka upset conventional wisdom in 1980 when they concluded that changes in countries' rates of national saving had very large effects on their rates of investment and interpreted this finding as evidence of low capital mobility. The argument

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0100.015
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.074
GPT teacher head0.309
Teacher spread0.235 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations347
Published2016
Admission routes1
Has abstractyes

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