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Irrigation Development as an Instrument for Economic Growth in Saskatchewan: An Economic Impact Analysis

2017· dissertation· en· W2762166367 sur OpenAlexaboutno aff
Jillian Brown

Notice bibliographique

RevueUniversity Library - University of Saskatchewan (University of Saskatchewan) · 2017
Typedissertation
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueEconomic Growth and Productivity
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIrrigationEconomic analysisAgricultural economicsEnvironmental scienceWater resource managementEconomicsAgronomyBiology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Allocation decisions in Saskatchewan of water are needed because of the limited nature of the resource in the province. Timely allocation of water can impact crop production, and through that economic development in the province, which may result through the value of the improved crop production as well as the economic linkages within the economy. Irrigation can be seen as a tool for economic growth as it decreases the reliance on natural factors which are critical for crop production in the province. The provincial government has committed, among its various agricultural initiatives, to develop tools to reach economic development goals. A study of the economic importance of irrigation in Saskatchewan is important to understand its contribution provincially and regionally as a possible tool for this economic development. The economic impacts of irrigation extend beyond farm-level impacts and understanding how it contributes to the entire economy at a provincial and regional level is information needed by decision makers. The purpose of this study is to provide the contributions of the irrigation sector on the provincial and regional economy. The Saskatchewan Irrigation Impact Analyzer (SIIA) model was built as a part of this study. The SIIA was based on a regionalized rectangular input-output model of the irrigation sector. Base data for the model were obtained from Statistics Canada Transaction Tables for 2011. The model was regionalized into: The Lake Diefenbaker Development Area (LDDA) and the other regions of Saskatchewan. The original data for agriculture production were disaggregated into irrigated and dryland production, each further disaggregated to crop and livestock production sectors. The model was further augmented with an employment model. Two scenarios of irrigation development were tested in the study: First, irrigation development that occurred during 2011-2016; Second, new irrigation development through infill expansion. In addition, the marginal contribution of the irrigation activity on the lake Diefenbaker Development Area region was also undertaken, which required a survey of producers. The study found that the total economic impacts of irrigation development during 2011-2016, enabling an additional 8,472 acres of irrigated production, amounted to $200.83 million in output (sales) generating $86.60 million in GDP contributions at market prices. This resulted in 1,179 full-time equivalent (FTE) employment years and $62.48 million in household income contributions. These estimates are based on a simulation of irrigation over a twenty-year period. With respect to potential irrigation expansion, the study found that if the 32,250-remaining infill-acres (that have been identified as offering irrigation potential) were to be developed and under production for a twenty-year period, the total economic impacts to the province of Saskatchewan would be $603.70 million in output (sales) responsible for 2,908 FTE employment years. This would amount to $181.12 million in household income contributions and $240.89 million in gross domestic product (GDP) contributions at market prices, at 2011 dollars. The study also found that regionally, irrigation provides an impetus for economic development. During the 2011 year, the marginal contribution of irrigation production, over and above the alternative of dryland production, was created through purchases of higher amounts of farm inputs, as well as spending of additional household income. These two avenues resulted in total economic impacts of $116.53 million in output (sales) which generated $78.47 million in GDP contributions at market prices. In the region, $58.72 million in household income gains also were incurred as a result of the 1,323 FTE employment years generated. The study found the economic impacts of irrigation, currently and potentially, to be extensive in each scenario and offering considerable regional impacts over and above the dryland production alternatives.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,094
Score d'incertitude au seuil0,250

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0020,005
Études des sciences et des technologies0,0010,001
Communication savante0,0030,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,014
Tête enseignante GPT0,196
Écart entre enseignants0,182 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2017
Routes d'admission1
Résumé présentoui

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