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The Economics of Decoupled Farm Payments under Costly and Imperfect Enforcement

2002· article· en· W2080785942 on OpenAlexaffvenue
Konstantinos Giannakas, Murray Fulton

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsUniversity of Saskatchewan
FundersEuropean Commission
KeywordsEnforcementEconomicsInefficiencyPaymentPublic economicsWelfare economicsSubsidyMicroeconomicsFinancePolitical scienceMarket economy

Abstract

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This paper builds on the literature covering agricultural policy analysis under costly and imperfect enforcement by introducing enforcement costs and misrepresentation into the economic analysis of decoupled farm payments. Specifically, the paper examines the economic causes and consequences of cheating on a stylized decoupled area payment scheme. Policy design and implementation is modeled as a sequential game between a regulator who designs the policy, an agency responsible for policy enforcement, and farmers. Analytical results show that complete deterrence of cheating is not economically efficient when enforcement is costly. The introduction of enforcement costs and cheating changes the welfare effects and transfer efficiency of decoupled area payments, the level of government intervention that transfers a given surplus to producers, the socially optimal income redistribution, and the social welfare from intervention. While the transfer efficiency of the policy is positively related to the extent of farmer misrepresentation, the incorporation of enforcement costs and cheating results in decoupled payments being generally a less efficient means of income redistribution than is traditionally believed. Nevertheless, the analysis shows that decoupled payments remain superior to coupled subsidies as a means of farm income support. Les auteurs ajoutent à ce qui s'est déjàécrit sur l'analyse des politiques agricoles dans le contexte d'une application imparfaite et onéreuse en intégrant à l'analyse du découplage des paiements agricoles le coût d'une exécution forcée et des fausses déclarations. Plus précisément, l'article examine les causes et les répercussions économiques de la fraude dans le cadre d'un programme stylisé de découplage régional des paiements. l'élaboration et l'application des politiques ont été modélisées comme un jeu séquentiel entre l'organisme de réglementation, qui échafaude la politique, l'organisme chargé d'appliquer cette dernière et les agriculteurs. Les résultats indiquent que combattre la fraude n'est pas économique quand une application forcée de la politique est onéreuse. L'introduction des coûts d'exécution et de la fraude entraîne une modification de l'incidence du programme sur le bien‐être social et de l'efficacité du transfert des paiements découplés aux régions, du degré d'intervention du gouvernement débouchant sur la réalisation d'un certain excédent par les producteurs, de la redistribution socialement optimale des revenus et du bien‐être résultant de l'intervention. Bien que l'efficacité de transfert de la politique présente une corrélation positive avec l'importance des fausses déclarations faites par les producteurs, l'intégration du coût d'une application forcée et de la fraude indique que le découplage des paiements n'est pas aussi efficace qu'on le croyait pour ce qui est de redistribuer les revenus. Malgré cela, l'analyse révèle que le découplage assure un meilleur soutien du revenu que le couplage des subventions.

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 score0.810
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.163
Teacher spread0.138 · 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

Citations8
Published2002
Admission routes2
Has abstractyes

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