Is deregulation of forest land use rights transactions associated with economic well-being and labor allocation of farm households? Empirical evidence in China

Hong, Yan-Zhen; Chang, Hung‐Hao; Dai, Yunchuan

doi:10.1016/j.landusepol.2018.02.013

Cited by 17 publications

(14 citation statements)

References 32 publications

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“…These results provide new insights into how labor migration affects households' forestland transfer decisions, and therefore complements the former conclusions that labor migration affects the transfer of forestland (e.g., Hong et al, 2018;X. Xu et al, 2013;Zhang, Kuuluvainen, Yang, et al, 2017).…”

Section: Discussionsupporting

confidence: 70%

“…Therefore, we considered the individual characteristics of the head of the household as the influencing factors. Following earlier studies (Hong et al, 2018;Zhang et al, 2020), basic indices such as age, education level, and village cadre were selected (Z. Liu et al, 2017).…”

Section: Selection and Definition Of The Model's Variablesmentioning

confidence: 99%

“…Regarding family characteristics, the number of household laborers (Deininger & Jin, 2005), the off‐farm income (Feng & Heerink, 2008), and land contract certificates (Wang et al, 2015; Zhang et al, 2019) are related to land transfers. Simultaneously, farmers' household resource endowments such as income diversities (R. Chen et al, 2014), the number of household laborers (D. Xu, Deng, Guo, et al, 2019), and household forestland areas (Hong et al, 2018) also affect the transfer of forestland. Interestingly, some scholars have also explored the long‐term effect of famine experience on land transfers (Deng et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Influence of rural labor migration behavior on the transfer of forestland

Xiao

Ning

Xie

et al. 2020

Natural Resource Modeling

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This study analyzes the influence mechanism of migration on farmers' forestland transfer behavior by using instrumental variable-Probit and instrumental variable-Tobit models based on survey data of 505 households in 50 villages in 10 sample counties in Jiangxi Province. The results show that the farmers' willingness to transfer forestland is generally not high, but there is a great difference in the influence of intra-county migration and outside-of-county migration on the transfer behavior of farmers. Outside-ofcounty migration promotes the renting out of forestland and inhibits renting it in, whereas intracounty migration does not affect either. In addition, households' human capital, forestland resource endowments, policy systems, and locational environment factors all have different degrees of influence on farmers' transfer behavior. According to the analysis, improving rural laborers' job skills through training can deepen the reform of collective forestland.

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Section: Discussionsupporting

confidence: 70%

Section: Selection and Definition Of The Model's Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Influence of rural labor migration behavior on the transfer of forestland

Xiao

Ning

Xie

et al. 2020

Natural Resource Modeling

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“…In addition, all research isolates, to some degree, farmers' leasing in and leasing out behaviors by employing two separate models. Similar research findings of factors affecting farmers' participation in forestland transactions have been examined by Hong et al [21]. Zhang et al [22] highlighted the effect of off-farm employment on forestland transfers in China using a simultaneous-equation Tobit model estimation verified that off-farm employment is endogenous to farmer' decision to lease their forestland.…”

Section: Introductionsupporting

confidence: 63%

“…As such, farmers performing as dominant actors, in leasing forestland usage rights, focalized on their leasing intentions formulates the practicality and significance of this study. The incorporation of this research with existing studies (i.e., investigating development of the forestland market based on studies of farmers' lease behaviors [19,21,22]) presents a more complete approach in predictive development of the forestland lease market in China. A conceptual model and econometric approach are presented in Section 2.…”

Section: Introductionmentioning

confidence: 99%

Farmers’ Intentions to Lease Forestland: Evidence from Rural China

Xiao-yong

Cirella

Wen

et al. 2020

Land

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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.

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