Harris, P, Lanfranco, B, Lu, B et al. (1 more author) (2020) Influence of Geographical Effects in Hedonic Pricing Models for Grass-Fed Cattle in Uruguay. Agriculture, 10 (7). 299. ISSN 2077-0472
Abstract
A series of non-spatial and spatial hedonic models of feeding and replacement cattle prices at video auctions in Uruguay (2002 to 2009) were specified with predictors measuring marketing conditions (e.g., steer price), cattle characteristics (e.g., breed) and agro-ecological factors (e.g., soil productivity, water characteristics, pasture condition, season). Results indicated that cattle prices produced under extensive production systems were influenced by all of predictor categories, confirming that found previously. Although many of the agro-ecological predictors were inherently spatial in nature, the incorporation of spatial effects into the estimation of the hedonic model itself, through either a spatially-autocorrelated error term or allowing the regression coefficients to vary spatially and at different scales, was able to provide greater insight into the cattle price process. Through the latter extension, using a multiscale geographically weighted regression, which was the most informative and most accurate model, relationships between cattle price and predictors operated at a mixture of global, regional, local and highly local spatial scales. This result is considered a key advance, where uncovering, interpreting, and utilizing such rich spatial information can help improve the geographical provenance of Uruguayan beef and is critically important for maintaining Uruguay’s status as a key exporter of beef with respect to the health and safety benefits of natural, open-sky, grass-fed production systems.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | beef cattle prices; spatial regression; multiscale; provenance; MGWR |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) |
Funding Information: | Funder Grant number NERC (Natural Environment Research Council) NE/S009124/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 Jul 2020 15:00 |
Last Modified: | 25 Jun 2023 22:21 |
Status: | Published |
Publisher: | MDPI |
Identification Number: | 10.3390/agriculture10070299 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:163301 |