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Record W4411060569 · doi:10.3390/jrfm18060309

Does Economic Freedom Influence Economic Growth? Evidence from Latin America

2025· article· en· W4411060569 on OpenAlexvenueno aff
Vanessa Arce, Freddy Benjamín Naula Sigua

Bibliographic record

VenueJournal of risk and financial management · 2025
Typearticle
Languageen
FieldComputer Science
TopicEconomic Growth and Development
Canadian institutionsnot available
FundersUniversidad de Cuenca
KeywordsEconomic freedomLatin AmericansEconomicsDevelopment economicsPolitical scienceMarket economyLaw

Abstract

fetched live from OpenAlex

This paper investigates the relationship between economic freedom and economic growth in Latin America and the Caribbean over the period 1997–2023, using data from 14 countries. To capture the multidimensional nature of economic freedom, two widely recognized indices—Heritage and Fraser—are incorporated into an extended Solow-type growth model. The empirical strategy relies on a dynamic panel data approach using the Arellano–Bond estimator, which allows for the control of unobserved heterogeneity, autocorrelation, and potential reverse causality. Robustness is assessed through alternative model specifications and in-sample forecasting using rolling-window techniques and Theil’s U-statistic. The results reveal a negative and statistically significant relationship between economic growth and the Heritage Index, while the Fraser Index shows a positive but generally non-significant effect. These findings highlight the methodological sensitivity of the economic freedom–growth nexus and suggest that context-specific institutional factors may shape how liberalization policies translate into development outcomes. The study contributes to the literature by jointly evaluating the impact of both indices in a unified dynamic framework, providing new evidence for a region marked by institutional heterogeneity and growth volatility.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.195
Teacher spread0.191 · 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 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
Published2025
Admission routes1
Has abstractyes

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