Meta-analysis of consumers' willingness to pay for sustainable food products
Cita com:
hdl:2117/367537
Document typeConference lecture
Defense date2021
Rights accessOpen Access
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Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
There is a continuous increasing number of studies dealing with consumers’ willingness to pay (WTP) price premiums for sustainable food products. This research focused on a broad area of sustainable food products, including different sustainable attributes using a meta-analysis of 80 worldwide studies. Overall average WTP was estimated using the forest plot, showing the existence of a high level of heterogeneity. The publication bias was also verified using the funnel plot and Egger’s test. Finally, the subgroup analysis and meta-regression were applied to classify the source of heterogeneity. The results suggest that the overall WTP a premium for sustainability (in percentage terms) is 29.5% on average. Furthermore, gender, region, sustainable attributes and food categories influence the average WTP estimates and their heterogeneity. Results also indicate that the WTP estimate conducted by hypothetical approach is higher than non-hypothetical one due to hypothetical bias. Results also highlight that Asian WTP estimates, in percentage terms, are higher than those obtained in America and similar to those from Europe. In addition, positive WTP estimates are shown independent of the food categories, region or methods. This outcome denotes the presence of great market potential for sustainable products worldwide, which can provide a reference for relevant stakeholders to better understand market trends and the government to give more support to sustainable policies.
CitationLi, S.; Kallas, Z. Meta-analysis of consumers' willingness to pay for sustainable food products. A: International Conference of Agricultural Economists. "Proceedings of the ICAE - 31st International Conference of Agricultural Economists". 2021, p. 1-25.
Publisher versionhttps://iaae-agecon.org/page/31st-icae---virtual-2021
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Paper_18123_extendedabstract_91_0.pdf | Article conference | 790,1Kb | View/Open | |
ICAE 2021 meta analysis Shanshan Li.pdf | 1,057Mb | View/Open |