Using Choice Experiments to Investigate the Policy Relevance of Heterogeneity in Farmer Agri-Environmental Contract Preferences

被引:130
作者
Broch, Stine Wamberg [1 ]
Vedel, Suzanne Elizabeth [1 ]
机构
[1] Univ Copenhagen, Forest & Landscape Denmark, Rolighedsvej 23, DK-1958 Frederiksberg C, Denmark
关键词
Afforestation; Contract preferences; Latent class; Participation; RPL; Regulation; Compensation; BIODIVERSITY CONSERVATION; MODELS; DESIGN; PARTICIPATION; SCHEMES; COMPENSATION; ACCEPTANCE; PAYMENTS; MARKET; RISK;
D O I
10.1007/s10640-011-9512-8
中图分类号
F [经济];
学科分类号
02 ;
摘要
Agri-environmental contracts are used to provide incentives for nature management on private land in, e.g. the European Union. The aim of this article is to investigate preference heterogeneity for agri-environmental contracts among farmers in order to discuss potential policy improvements utilising heterogeneity. We used a choice experiment to elicit farmers' stated preferences for afforestation contracts. Four attributes are investigated: purpose of afforestation, option of cancelling the contract, monitoring, and compensation level. All attributes present a potential conflict between farmers' and authorities' interests, which emphasises the importance of knowing how to handle these interests. A random parameter logit model shows that having the option to cancel the contract decreases farmers' required compensation level and monitoring increases it. Furthermore, farmers are willing to accept a lower compensation when the aim is to protect biodiversity and ground water relative to recreation. Latent class models with class probability variables reveal discrete heterogeneity and support a division into four groups with divergent preferences. For example, a group of farmers who already have forest areas does not find the option of cancelling the contract important, whereas another group relying on the farm for income requires higher compensation. The findings indicate potential for efficiency gains from targeting the contracts.
引用
收藏
页码:561 / 581
页数:21
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