Analysis on Priority Order and Influencing Factors of Forest Farmers Demand for Forest Reform Policy - A Case Study in Jiangxi, China
Humanities and Social Sciences
Volume 7, Issue 5, September 2019, Pages: 170-176
Received: Sep. 7, 2019; Accepted: Sep. 27, 2019; Published: Oct. 15, 2019
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Authors
Hui Xiao, Department of Economics and Management, Jiangxi Agricultural University, Nanchang, China
Fangting Xie, Institute of Rural Development, Jiangxi Agricultural University, Nanchang, China
Shubin Zhu, Institute of Rural Development, Jiangxi Agricultural University, Nanchang, China
Caiwang Ning, Department of Economics and Management, Jiangxi Agricultural University, Nanchang, China
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Abstract
This paper analyzed forest farmers’ priority demands for forest reform policies through average linkage clustering analysis and multinomial logistic regression model by applying survey data of 500 households in Jiangxi province. The results indicated that the subsidy policies is the most needed policies followed by the forestry science and technology service policy, and financial services. In addition multinomial logistic regression model analysis was used to study what factors influence farmers’priority demand for forest reform policies. The empirical results show that the age of head of household, the area of household forest land, whether forest farmers have participated in forest right mortgage loans and forest insurance significantly affect the demand of forest farmers for forest reform policy. Finally, some pertinent suggestions were put forward to promote the collective forest reform.
Keywords
Forest Reform Policies, Demand Priority, Influencing Factors
To cite this article
Hui Xiao, Fangting Xie, Shubin Zhu, Caiwang Ning, Analysis on Priority Order and Influencing Factors of Forest Farmers Demand for Forest Reform Policy - A Case Study in Jiangxi, China, Humanities and Social Sciences. Vol. 7, No. 5, 2019, pp. 170-176. doi: 10.11648/j.hss.20190705.14
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Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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