
Taking China’s recently developed Forest Right Mortgage System (FRMS) as an example, this paper examines the impact of the strength of farmers’ property rights on the intensity of credit restrictions imposed by lenders. Using the forest right mortgage policy documents we collected from eight key forestry counties (cities) in China’s southern collective forest regions and the corresponding data of 414 surveyed farmers in 24 villages, we quantify the exclusivity of farmers’ forest property rights and the extent of FRMS credit restrictions in the sampled regions, and explore whether and how the strength of farmers’ forest rights affect credit restrictions under FRMS. The results show that there exists a significant mediation effect of the forest rights exclusivity on credit restrictions intensity through its impact on the market value of forest rights. We further examine the relationship between each disaggregated forest right and the FRMS credit restrictions, and find that the strength of farmers’ forestland use rights, transfer rights and benefit rights are all statistically significant in increasing the market value of farmers’ forest right and thereby reducing the intensity of credit restrictions. Based on the analyses we also offer some policy suggestions.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 9 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
