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Record W2052705444 · doi:10.1080/00036840500427585

Market deregulation, trade liberalization and productive efficiency in Bangladesh agriculture: an empirical analysis

2006· article· en· W2052705444 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Economics · 2006
Typearticle
Languageen
FieldDecision Sciences
TopicEfficiency Analysis Using DEA
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsDeregulationEconomicsLiberalizationAgricultureProductive efficiencyFrontierAgricultural economicsFree tradeGovernment (linguistics)International economicsMacroeconomicsMarket economyProduction (economics)

Abstract

fetched live from OpenAlex

The impact of trade liberalization and of market deregulation in general, on the performance of agriculture remains contentious and empirical issue in the literature. Following the random coefficient frontier modelling framework, this paper attempts to contribute to this debate by computing the farm-specific productive efficiency indices in Bangladesh agriculture before and after reform. It also examines the impact of some farm-specific and policy variables on productive efficiency. The empirical results show that there are wide variations in productive efficiency across farms and regions and the average efficiency of all regions increased modestly by 8 percentage points from the pre-reform to post-reform period. The efficiency differentials are largely explained by farm size, infrastructure, households' off-farm income and the reduction of government anti-agricultural bias in relation to trade and domestic policies. The implication of these results suggests the need for further policy reform to augment productive efficiency.

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.

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)0.002
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 score0.587
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
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 head0.025
GPT teacher head0.292
Teacher spread0.268 · 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