Farmers’ Willingness to Participate in Payment‐for‐Environmental‐Services Programmes

Understanding farmers’ willingness to participate in agricultural payment‐for‐environmental‐services (PES) programmes is an essential precondition for designing effective and efficient programmes. Willingness to participate is typically examined via stated preference surveys using the standard hurdle model for whether and how much to participate. Among respondents who decline to participate, such analyses cannot distinguish between respondents who declined due to the payment level and those who were not interested at all. This paper applies a double hurdle model to incorporate a prior condition for whether a respondent is even willing to consider participating in the PES market. The model uses a unique stated preference survey permitting separation of the consideration and enrolment decisions of 1,700 farmers in Michigan, USA. The first hurdle probit model suggests that farmers’ willingness to consider PES chiefly depends on farm and farmer characteristics, while the second hurdle tobit model shows that decisions on whether and how much to enrol depend more on the payment offer and marginal benefit–cost criteria. This study provides fresh insights on facilitating farmer participation in PES programmes using tiered strategies that differ in costs of programme payment and administration.     

Semi‐Subsistence Farming: An Elusive Concept Posing Thorny Policy Questions

The massive expansion of semi‐subsistence farming in the European Union after the Eastern enlargements poses a real challenge to rural development. The problems of semi‐subsistence farms are low cash incomes and incidence of poverty, sub‐optimal use of land and labour, a lack of capital and poor contribution to rural growth. However, they play an important welfare function in some rural areas in Europe; they manage more than 11 million ha of agricultural land and deliver ecosystem services. The Common Agricultural Policy will have to accommodate this now widespread production system, through existing or new policy packages. Particularly important is support for commercialisation to incentivise and smooth the transition to commercial agriculture, and agri‐environmental payments to compensate the semi‐subsistence farmers for the provision of ecosystem services.     

Farmers' Preferences and Social Capital Regarding Agri‐environmental Schemes to Protect Birds

The steady decline of birds living in cereal steppe lands is a worrying situation that the European Common Agricultural Policy is attempting to remedy through the application of agri‐environmental schemes (AES). We assess farmers' preferences towards these AES, which call for a number of environmental practices to protect birds. Using a face‐to‐face survey in farming communities in Aragón (Spain), and through the estimation of an Ordered Logit model (OL), we assess the ranking of AES attributes, and obtain their economic valuation according to the farmers' preferences. We find that social factors are also important in determining farmers' decisions. In particular, the importance of social trust and expectation of compliance by other neighbours, encourage farmers to sign up to AES. These and other results may be used to design more effective AES and help to solve this important biodiversity problem.     

Willingness to Pay for Rural Landscape Improvements: Combining Mixed Logit and Random‐Effects Models

This paper reports the findings from a discrete‐choice experiment designed to estimate the economic benefits associated with rural landscape improvements in Ireland. Using a mixed logit model, the panel nature of the dataset is exploited to retrieve willingness‐to‐pay values for every individual in the sample. This departs from customary approaches in which the willingness‐to‐pay estimates are normally expressed as measures of central tendency of an a priori distribution. Random‐effects models for panel data are subsequently used to identify the determinants of the individual‐specific willingness‐to‐pay estimates. In comparison with the standard methods used to incorporate individual‐specific variables into the analysis of discrete‐choice experiments, the analytical approach outlined in this paper is shown to add considerable explanatory power to the welfare estimates.