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Record W4404360667 · doi:10.1093/ser/mwae045

Relative treatment of aliens: how level is the playing field for foreign firms in developing countries?

2024· article· en· W4404360667 on OpenAlexaff
Emma Aisbett, Carol McAusland, Lauge N. Skovgaard Poulsen

Bibliographic record

VenueSocio-Economic Review · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsField (mathematics)Level playing fieldDeveloping countryBusinessInternational tradeEconomicsEconomic growthMathematicsFinance

Abstract

fetched live from OpenAlex

Abstract This article provides the first systematic analysis of whether developing country governments treat foreign firms better, worse or the same as domestic firms. We use a novel econometric estimator to analyze the World Bank’s Enterprise Surveys. In contrast to the intuition in much of the literature on the political economy of foreign investment, we show that foreign firms are not treated worse by host state governments on average. Also, whereas governments in low-income countries treat all firms poorly, they treat foreign firms relatively better than comparable domestic firms. This contrasting pattern means that the findings of the large and growing literature on the cross-country causes and consequences of the absolute treatment of foreign firms cannot be transferred to the question of relative treatment. It also has important policy implications—for instance in the context of investment treaties, which grant extensive property right protections to foreign but not domestic investors.

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)0.008
metaresearch head score (Gemma)0.020
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 score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.004
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.077
GPT teacher head0.284
Teacher spread0.207 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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