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Record W7116727247 · doi:10.1016/j.tncr.2025.200160

Trade policy uncertainty and agricultural exports: The mitigating roles of RTA and liberal democracies

2025· article· en· W7116727247 on OpenAlexvenueno aff
Jadhav Chakradhar, Adrija Ganguly, Rahul Nath Choudhury, Pravin Jadhav

Bibliographic record

VenueTransnational Corporation Review · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsQuantile regressionAgricultureCommercial policyContext (archaeology)Panel dataGeneral partnershipTrade barrierFree tradeRegression analysis

Abstract

fetched live from OpenAlex

In the context of heightened global uncertainty over economic and trade policies, this analysis examines how Trade Policy Uncertainty (TPU) impacts agricultural exports using two-way fixed effects and Panel Quantile Regression (PQR) methods. It studies the role of Regional Trade Agreements (RTAs) and liberal democracies in mitigating the effect of the TPU on agricultural exports. The analysis covers 15 Regional Comprehensive Economic Partnership (RCEP) countries from 1988 to 2023. The estimated results reveal that the lagged values of TPU specific to RCEP countries and the Global TPU exert negative and statistically significant effects on agricultural exports. The results of the panel quantile regression analysis reveal that the effects of the independent variables on agricultural exports are heterogeneous across different quantiles. The findings of this study suggest that regional trade agreements and higher levels of liberal democracy serve as mitigating factors, alleviating the adverse effects of trade policy uncertainty on agricultural exports. Based on these findings, our study significantly contributes to the empirical literature and offers valuable insights for policy making.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.308

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 communication0.0000.000
Open science0.0000.000
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 head0.037
GPT teacher head0.240
Teacher spread0.202 · 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
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
Published2025
Admission routes1
Has abstractyes

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