Economic valuation of social demand for key features of the Noir de Bigorre pork production chain

Abstract

Extensive farming systems produce for the society goods and services definable as public goods (biodiversity…), or having public good features (landscape attractiveness…). The provision of these public goods may not be guaranteed due to the lack of recognition of their values in markets and policies that ultimately can put in risk the future of these systems. Within TREASURE project, a choice experiment (CE) survey was applied to assess the social demand for relevant attributes of the Noir de Bigorre (NB) French regional pork chain producing Gascon local pig breed in extensive system with public good character. CE is an economic valuation method estimating the social demand for a given attribute or for combinations of them in management scenarios. Five relevant attributes of the NB chain and their current and potential levels in alternative management options were identified from focus groups: probability of existence of the breed in next 25 years, farm size, feedstuff origin, geographical availability of the products and type of selling places. A monetary attribute was included to assess the social demand for the previous attributes. A valuation questionnaire was administered to 418 individuals (365 through web-based survey, 53 face-to-face), half of them located in the South West of France, i.e. the production area of the NB chain. Results of the CE showed that the respondents had a distinctively urban profile, with no agricultural family background. Almost 40% of the respondents did not know or consume products from the NB chain. On average guaranteeing the survival of the breed achieved the highest willingness to pay (112.37 €/household/year). Respondents were willing to pay 42.35€ to maintain equal number of small and medium farms and 21.86€ to have feedstuff produced in the proximity of the farms. Geographical availability and selling places of products contributed to a lesser extent to shape their preferences. Funded by European Union's H2020 RIA program (grant agreement no. 634476).