How off-farm work drives the intensity of rural households' investment in forest management: The case from Zhejiang, China

Zhu, Z. A.; Xu, Zhigang; Shen, Yueqin; Huang, Chenming; Zhang, Yaoqi

doi:10.1016/j.forpol.2018.04.006

Cited by 34 publications

(22 citation statements)

References 39 publications

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“…However, this study is based on a cross section of data and lacks a lagged variable to solve the endogeneity of independent variables. To solve the problem of endogeneity and the censoring of independent variables in cross data, some researchers have used the population of off-farm labor at the village level as a reasonable instrumental variable (Zhu et al, 2019). The instrumental variable must satisfy two conditions.…”

Section: Econometric Modelmentioning

confidence: 99%

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: Econometric Modelmentioning

confidence: 99%

Influence of rural labor migration behavior on the transfer of forestland

Xiao

Ning

Xie

et al. 2020

Natural Resource Modeling

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“…The characteristics of farmers mainly include the age [7][8] [32] , the number of afforestation experiences and the proportion of surrounding farmers participating in the division of labor. Woodland features mainly include the area of forestlands [7][8][10] [32] and the amount of forestry subsidies [13][28] [33] . As for farmers, the older they are, the lower their ability to accept new things and the less likely they are to participate in the division of labor.…”

Section: The Modelmentioning

confidence: 99%

Behavioral Ability and Division of Forestry Production of Households——Data From Fujian Province in China

2020

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Division of labor can increase labor productivity. Compared with the division of agricultural production, the division of forestry production has a typical positive externality. It is more scientific to study the division of labor in forestry production. Under the “Three Powers Separated” structure, the behavioral capacity of farmers has an important influence on the division of forestry production. This paper uses the survey data of farmers in Fujian Province to analyze the farmer’s forestry production division of labor behavior from three perspectives of the behavioral ability, the transaction ability and the disposal ability. The results show that the variable of “the contracting right is more important than the management right” in the measure exclusive ability and the difficulty in obtaining transaction information on forestlands to measure the trading capacity, both positively affects farmers’ participation in the division of forestry production. Meanwhile, whether has changed the use of forestlands negatively influences the division of the forestry production. This not only enriches the research results of the forestry production division of labor theory, but also provides a new perspective for promoting the development of the forestry production division of farmers, and thus provides a new source for improving the efficiency of forestry management. It helps promote the connection between small farmers and the development of modern forestry.

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“…Rural households generally have greater decision-making autonomy for labor input than monetary input (Zhu, Xu, Shen, Huang, & Zhang, 2019). Therefore, there may be differences in farmers' forestry investment between monetary decisions and labor decisions.…”

Section: Selection and Definition Of The Model Variablementioning

confidence: 99%

Labor off‐farm employment and household forest management investment in Jiangxi, China: A perspective from gender influence of rural labor

Xie

Kang

et al. 2019

Natural Resource Modeling

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That numerous rural laborers migrate to urban areas to find off-farm jobs has become an outstanding economic phenomenon in China. To examine the impact of rural labor off-farm employment on household forest management, we built binary logistic models and Tobit models by applying a sample survey data of 500 households in rural Jiangxi in 2018. Households' participation and investment in forest management were measured by their labor and cash input. The results indicated that more off-farm laborers in household would hold back their participation in cash input. In contrast, a higher rate of female off-farm employment encouraged household monetary input. And households with more female agricultural laborers were more likely to participate in labor input. Neither off-farm employment nor female offfarm employment significantly influences households' labor input. Off-farm employment of the householder negatively influenced labor and cash input. Policy factors, such as obtaining forestry subsidies and forestry

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How off-farm work drives the intensity of rural households' investment in forest management: The case from Zhejiang, China

Cited by 34 publications

References 39 publications

Influence of rural labor migration behavior on the transfer of forestland

Influence of rural labor migration behavior on the transfer of forestland

Behavioral Ability and Division of Forestry Production of Households——Data From Fujian Province in China

Labor off‐farm employment and household forest management investment in Jiangxi, China: A perspective from gender influence of rural labor

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