Influence of Geographical Effects in Hedonic Pricing Models for Grass-Fed Cattle in Uruguay

Paul Harris, Bruno Lanfranco, Binbin Lu and Alexis Comber
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Paul Harris: Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, Okehampton EX20 2SB, UK
Bruno Lanfranco: Instituto Nacional de Investigación Agropecuaria (INIA), INIA-Las Brujas, Canelones 90200, Uruguay
Binbin Lu: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Alexis Comber: School of Geography, University of Leeds, Leeds LS2 9JT, UK

Agriculture, 2020, vol. 10, issue 7, 1-17

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.

Keywords: beef cattle prices; spatial regression; multiscale; provenance; MGWR (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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