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Record W1587608080

Can Foreign Aid Buy Investment? Appropriation Through Conflict

2009· preprint· en· W1587608080 on OpenAlexaff
David M. Bruner, Robert J. Oxoby

Bibliographic record

VenueRePEc: Research Papers in Economics · 2009
Typepreprint
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsForeign direct investmentProperty rightsAppropriationInvestment (military)IntuitionReturn on investmentMarket economyDeveloping countryEconomicsBusinessInternational economicsEconomic systemMonetary economicsEconomic growthPoliticsPolitical scienceMacroeconomicsProfit (economics)MicroeconomicsLaw
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT: The failure of foreign aid to promote growth in the developing world has received significant attention as evidence suggests that foreign aid does not translate into investment. This research has demonstrated that poor institutions in these developing economies (particularly with respect to property rights) results in an inability to fully appropriate the return to one’s investment, thereby serving as a prominent disincentive to investment. This paper presents an experimental test of a a 2-player, one-shot game of conflict in which we vary the strength of property rights. Our results suggest that stronger property rights reduce conflict and increase investment. In addition, we test the conventional wisdom that technological progress can increase the effectiveness of aid in stimulating investment. Contrary to intuition, we find technological progress has practically no effect on investment and that this failure to stimulate investment is largely due to deficiencies in property right institutions.

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)0.010
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0210.001

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 head0.064
GPT teacher head0.358
Teacher spread0.294 · 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
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

Citations2
Published2009
Admission routes1
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicInternational Development and AidFrench-language works237,207