俄罗斯经济特区:潜在居民预测决策与居民生成过程建模

IF 0.7 Q3 ECONOMICS
Alexander E. Plesovskikh
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引用次数: 0

摘要

现代研究广泛讨论了经济特区在刺激俄罗斯经济增长和发展方面的作用,通过扩大高附加值经济高科技部门的生产,产生必要的投资流动,增加国家的创新潜力。本研究的目的是模拟产生居民的过程,并确定对参与俄罗斯联邦经济特区的公司的平均年增长率具有统计显著影响的数量因素。本文描述了使用分类方法(支持向量机、决策树、随机森林、朴素贝叶斯、k近邻、梯度增强)和回归方法(逻辑回归)预测潜在居民在经济特区境内开展业务的选择的现代方法。在实践中应用了一种现代分类算法——基于直方图的梯度增强分类树,该算法对于分析变量值缺失的大数据稳定,且不需要进行初步的样本变换。本文证实了组织所在地与其年底形成的财务结果之间存在正相关关系的假设。平均而言,在样本中,位于俄罗斯联邦组成实体中心附近的常驻公司在创造收入方面更为成功。关于俄罗斯联邦各区域的空间分异指标与描述产生居民和私人投资过程的指标之间存在密切关系的假设尚未得到充分证实。从实践的角度来看,研究结果可以应用于居民组织、潜在居民和经济特区管理公司。本研究的理论意义在于提出了潜在居民的二元选择模型,可以在未来的工作中进行扩展和推广。目前,为发展工业、高技术经济部门和生产高附加值产品创造条件,以增加俄罗斯经济的稳定性,一切必要的先决条件都已具备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Special Economic Zones of Russia: Forecasting Decisions of Potential Residents and Resident Generation Process Modeling
Modern studies widely discuss the role of special economic zones in stimulating the economic growth and development of Russia, generating the necessary investment flows and increasing the country's innovative potential by expanding production in high-tech sectors of the economy with high added value. The purpose of the study is to model the process of generating residents and to determine quantitative factors that have a statistically significant effect on the average annual growth rate of companies participating in special economic zones in the Russian Federation. The paper describes modern approaches to predicting the choice of potential residents to start doing business in the territory of the SEZ using classification approaches (Support Vector Machines, Decision Trees, Random Forest, Naive Bayes, K-Nearest Neighbor, Gradient Boosting) and regression approaches (logistic regression). A modern classification algorithm was applied in practice - Histogram-based Gradient Boosting Classification Tree, which is stable for analyzing large data with missing variable values and does not require preliminary sample transformation. The paper confirms the hypothesis that there is a positive relationship between the location of the organization and its financial result forming by the end of the year. On average, in the sample, resident companies located near the centers of the constituent entities of the Russian Federation are more successful in terms of generated revenue. The hypothesis that there is a strong relationship between indicators of spatial differentiation of the regions of the Russian Federation and indicators characterizing the process of generating residents and private investment has not been fully confirmed. From a practical point of view, the results of the study could be applied by both resident organizations, potential residents, and SEZ management companies. The theoretical significance of the study lies in the specification of the proposed binary choice model for potential residents, which can be expanded and generalized in future works. At present, there are all the necessary prerequisites for creating conditions for the development of industry, high-tech sectors of the economy and the production of high value-added products in order to increase the stability of the Russian economy.
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CiteScore
2.40
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