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Impact of delivering ‘green’ dairy products on farm in New Zealand

Wei Yang, Grant Rennie, Stewart Ledgard, Geoff Mercer and Gina Lucci

Agricultural Systems, 2020, vol. 178, issue C

Abstract: There has been an increasing demand for livestock products with credence attributes (CAs), such as environmental sustainability and high animal welfare standards. Although most livestock product CAs are strongly related to farm-level production processes, rarely have studies explored the issue from an on-farm perspective. Therefore, this paper aims to explore whether consumers' willingness-to-pay (WTP) a price premium could incentivise dairy farmers to deliver products with CAs in New Zealand. We first employed a meta-regression analysis to estimate WTP for CAs of dairy products, and then incorporated the WTP estimates into farm system models to estimate the economic and environmental (nitrogen and GHG losses) impacts for the farms. Data for the meta-regression models were sourced from a literature survey yielding 32 studies estimating WTP for CAs of dairy products. The results showed that price premium ranged from 5.3% to 47.5% for environmentally-friendly dairy products. Farm system (FARMAX), farm environmental (OVERSEER) and life cycle assessment (LCA) models were used to model the farm system changes required to deliver ‘green’ dairy by using data for the average Waikato dairy farm. The results showed that the economic and environmental outcomes varied over the predicted range in WTP as well as for different farm system scenarios. Findings of the study could help inform NZ farmers as to how to adjust their farm systems in response to market signals and thereby potentially gain a price premium.

Keywords: Meta-regression model; Credence attributes; Farm system modelling; Economic and environmental impact (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:agisys:v:178:y:2020:i:c:s0308521x19304093

DOI: 10.1016/j.agsy.2019.102747

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