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林业科学 ›› 2016, Vol. 52 ›› Issue (6): 43-53.doi: 10.11707/j.1001-7488.20160606

• 论文与研究报告 • 上一篇    下一篇

序列林价及其在林木资源资产评估中的应用

谢哲根1, 韩国康2, 童红卫3, 徐军1, 葛文宁1, 何必庭3   

  1. 1. 浙江省森林资源监测中心 杭州 310020;
    2. 浙江省林业厅计划财务处 杭州 310020;
    3. 浙江省龙泉市林业局 龙泉 323700
  • 收稿日期:2015-10-30 修回日期:2016-03-07 出版日期:2016-06-25 发布日期:2016-07-04
  • 基金资助:
    浙江省人民政府与中国林业科学研究院林业科技合作项目"林权抵押贷款森林资源资产评估技术研究"(2014SY19)。

Sequential Forest Price and Its Application in Forest Resources Assets Appraisal

Xie Zhegen1, Han Guokang2, Tong Hongwei3, Xu Jun1, Ge Wenning1, He Biting3   

  1. 1. Forest Resources Monitoring Center of Zhejiang Province Hangzhou 310020;
    2. Planning and Finance Division of Zhejiang Forestry Department Hangzhou 310020;
    3. Forestry Bureau of Longquan City Longquan 323700
  • Received:2015-10-30 Revised:2016-03-07 Online:2016-06-25 Published:2016-07-04
  • Contact: 韩国康

摘要: [目的] 以浙江省龙泉市杉木用材林为例,建立科学、实用的林木资源资产评估模型,使之能够应用于非交易性森林资源资产业务中的小班林木资源资产评估实践,如林权抵押贷款、森林保险、林木生物资产核算等领域中的大批量小班的林木资源资产评估。[方法] 设定参照林分,引入生产函数理论,建立参照林分的生长模型;研究相邻年度林木价值关系,设计序列林价递推公式;分析林分林木资产价值主要影响因素,构建基于序列林价的小班林木资源资产评估模型,并对林木资产评估模型进行适用性检验,包括模型估算值与样本实际值的差异显著性检验和模型使用精度检验。建模过程中综合运用了递推算法、回归方法、仿真模拟方法。[结果] 编制杉木林参照林分序列林价表,该表能够客观反映出林木价值生长过程;拟合林价主要影响因素调整系数模型参数,给出小班集材路程调整系数经验模型,以及成熟林小班的林分平均胸径调整系数经验模型、单位面积蓄积量调整系数经验模型;应用小班林木资产评估模型进行龙泉市岩樟乡芭蕉村杉木用材林小班林木资源资产评估,计算得到杉木用材林小班林木资产明细表,经汇总得到各农户杉木用材林林木资产价值、全村杉木用材林林木资产价值;利用98个正常交易实例检验样本计算小班林木资产评估模型检验指标,总相对误差-0.16%、平均相对误差1.25%、平均相对误差绝对值8.97%,估计精度97.6%,全部检验指标均符合要求。[结论] 基于序列林价的小班林木资源资产评估模型结构化、直观、可理解,评估效果较好,能够适用于非交易性森林资源资产业务中的大批量小班的林木资源资产评估业务;引入生产函数理论,保证参照林分营林过程中投入与产出的匹配性;序列林价递推算法可以更好地研究林分完整生长过程中的序列林价变化规律,实现重置成本法、收益现值法、市场价倒算法3种方法的融合与相互验证;通过林龄价值系数可以实现参照林分序列林价更新、小班林木资产评估模型更新;建立林价主要影响因素调整系数回归模型,优于以往对影响因素作分级处理的简单做法。

关键词: 林木资源资产, 资产评估, 序列林价, 递推公式, 参照林分, 生产函数

Abstract: [Objective] The Chinese fir(Cunninghamia lanceolata) timber forest in Longquan county of Zhejiang Province was taken as an example to establish a scientific and practical model for appraisal of forest resources assets in order to make the model applicable to appraisal of sub-compartment forest resources, such as mortgage of forest rights, forest insurance, accounting of forest biological assets.[Method] A reference stand was set up and a growth model was developed for the reference stands using production function. The relation between forest prices of the adjacent years was analyzed and used to design the recursive formula for calculating the sequential forest prices. Main factors that influence forest asset value were identified and used to develop assets appraisal model for sub-compartment forest resources assets based on the sequential forest prices. Applicability tests were then conducted for the appraisal model, including significance test of difference between estimated and actual values and accuracy test of the estimation. The recursive algorithm, regression method, and simulation method were used in the process of modeling. [Result] A table of the sequential forest prices of the reference stand was compiled, which objectively reflects the rises of forest values. The adjustment coefficient model parameters of the main factors that influence the forest asset value were fitted. Then the adjustment coefficient empirical equation for sub-compartment skidding distance was given. To mature forest sub-compartment, the adjustment coefficient empirical equations for stand average DBH and stand stock volume per unit area were obtained. The appraisal model of forest resources assets was applied to all sub-compartment appraisal of Chinese fir timber forest in Bajiao village, Yanzhang township, Longquan county. As the outcome of this application example, the forest resources assets list of each sub-compartment was calculated by the appraisal model, the total amounts of the forest resources assets for each farmer household and for the whole village were obtained by summarizing up. The test sample of 98 normal trading examples was used to calculate the test index of the appraisal model, total relative error was -0.16%, mean relative error was 1.25%, absolute value of mean relative error was 8.97%, and estimation accuracy was 97.6%. All the test indicators conformed to the requirements. [Conclusion] The forest resources assets appraisal model based on sequential forest prices was structured, intuitive and understandable, and the evaluation result was satisfactory. The assets appraisal model can be applied in forest resources assets appraisal practices of large number of sub-compartment related to non-transaction forest resources assets appraisals. By using the theory of production function, the matching between input and output in the forest management process of the reference stand was ensured. By using recursive formula, the variation rule of the sequential forest prices in the whole stand growth process can be studied better, and the fusion and mutual verification of 3 methods, the replacement cost method, the income method and the market value method, was realized. By using the age value coefficient, the list of the sequential forest prices of the reference stand can be updated, and the sub-compartment forest resources assets appraisal model can be updated synchronously. The regression models of the main influencing factors of forest price were established, and were better than the simple grading method to deal with the influence factors previously.

Key words: Forest resource assets, assets appraisal, sequential forest prices, recursive formula, reference stand, production function

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