Skip to content
naulon
Not checkedNot checked for notices yet.

Farmers’ Intentions to Lease Forestland: Evidence from Rural China

Xiaoyong Li, Giuseppe T. Cirella, Yali Wen and 1 more

Land · 2020

doi:10.3390/land9030078 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

In the last decade, despite considerable research developed for the forestland leasing market, little has been published in terms of econometric results on determinants of intentions and behaviors of Chinese farmers. With respect to leasing forestland, this study uses a Bayesian logit model to examine the factors that influence farmers’ intentions, using household data collected in one county in 2017. The results show that farmers’ past experience of leasing forestlands have significant impacts on their leasing intentions. Once farmers participated in leasing in or leasing out forestland in the last five years, it was shown that they will have stronger intentions of doing so in the future. Farmers will neither lease in or out forestland if the leasing profits are less than the profits originated from forestland management. As such, household head age, household population, proportion of income from nonfarm sources to total income, and security of rights to forestland use are significant factors in influencing farmers’ decisions on leasing in forestland. On the other hand, household head age and educational level, proportion of income from nonfarm sources to total income, and importance of forestland in terms of inheritance are significant factors in influencing farmers’ decisions on leasing it out. Results imply that institutional and market factors, which have impacts on transaction costs, are important for farmers in making decisions on forestland leases. Policy implications to reduce institutional intervention are discussed.

Abstract licence: CC BY

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.