收益法在农用地在价值评估中的应用与改进研究

发布时间：2018-06-04 21:55

本文选题：农用地价值评估 + 收益还原法　；参考：《重庆理工大学》2016年硕士论文

【摘要】：随着当今社会城镇化的不断发展,农用地受到越来越多的关注,农用地的价值评估的重要性也日益突显。评估方法的研究对于进一步完善农用地价值评估工作十分必要,其中使用最为频繁的一种方法是收益还原法。通过预测农用地的未来收益、选取合理的土地还原率及各类其他影响因素的参数,最终计算出农用地的价格现值。该方法在农用地中之所以比较适用,是因为它相对其他方法来说更为符合农用地的收益及投资情况。并且拥有相对坚实的理论基础作为支撑,包括土地收益理论和地租理论这两种理论。但是在实际的农用地价值评估案例中,收益还原法的使用仍然存在一些不足,尤其是关于农用地的未来收益的预测值的问题。通常情况下评估人员直接参考实际收益值的均值,这样较为粗略的预测方法会导致最终评估结果具有一定的偏差,其应用效果受到直接影响。因此,在农用地价值评估中,关于收益还原法的应用研究在当前看来尤为重要。全文的主要内容主要分为七个部分。第一部分概述了农用地价值评估的研究背景、研究意义以及本篇文章主要的研究内容,并且对农用地价值评估方面的研究方法和研究路径进行了简要的阐述。第二部分主要介绍了农用地价值评估的相关概念、理论基础以及国内外关于农用地价值方面的文献研究。第三部分对农用地的产权和价格以及二者之间的联系进行了一定的描述,分析了农用地价格的类型及各类影响因素。第四部分详细的分析了收益还原法的理论依据、适用条件和估价步骤,在研究现状的基础上提出了目前传统收益法存在的一些应用问题。第五部分介绍了灰色系统理论的内容及其在农用地价值评估中的适用性,利用灰色系统理论构建农用地价值评估模型来解决纯收益的计算问题,并对得出的计算结果进行最终的精度检验。第六部分是将构建的评估模型应用到农用地的实际案例中,计算并检验了评估结果的精确度,并将改进后的收益还原法与传统方法进行比较和分析。第七部分是对以上各部分内容的总结,并对农用地价值评估的未来发展予以期望。
[Abstract]:With the development of urbanization, more and more attention has been paid to agricultural land, and the value evaluation of agricultural land is becoming more and more important. The research of evaluation method is very necessary to further improve the evaluation of agricultural land value, among which the most frequently used method is the method of income reduction. The present value of agricultural land price is calculated by predicting the future income of agricultural land and selecting reasonable parameters of land reduction rate and other influencing factors. The reason why this method is more suitable in agricultural land is that it is more in line with the income and investment of agricultural land than other methods. And has a relatively solid theoretical basis as the support, including land income theory and rent theory of these two theories. However, in the actual case of agricultural land value evaluation, there are still some shortcomings in the use of the income reduction method, especially the problem of predicting the future income of agricultural land. Usually, the evaluator directly refers to the average of the actual income value, so the rough prediction method will lead to a certain deviation of the final evaluation result, and its application effect will be directly affected. Therefore, in the evaluation of agricultural land value, the research on the application of income reduction method is particularly important at present. The main content of this paper is divided into seven parts. The first part summarizes the research background, research significance and the main research content of the agricultural land value evaluation, and briefly expounds the research methods and research path of the agricultural land value evaluation. The second part mainly introduces the related concepts of agricultural land value evaluation, the theoretical basis and the domestic and foreign literature on agricultural land value research. The third part describes the property right and price of agricultural land and the relationship between them, and analyzes the types of agricultural land price and various influencing factors. In the fourth part, the theoretical basis, applicable conditions and valuation steps of the income reduction method are analyzed in detail. On the basis of the research status quo, some application problems of the traditional income method are put forward. The fifth part introduces the content of the grey system theory and its applicability in the evaluation of agricultural land value, using the grey system theory to construct the evaluation model of agricultural land value to solve the problem of net income calculation. Finally, the accuracy of the calculated results is tested. In the sixth part, the evaluation model is applied to the actual case of agricultural land, the accuracy of the evaluation results is calculated and tested, and the improved income reduction method is compared and analyzed with the traditional method. The seventh part is a summary of the above parts, and the future development of agricultural land value evaluation is expected.
【学位授予单位】：重庆理工大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：F301.3

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