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黄金科学技术 ›› 2023, Vol. 31 ›› Issue (4): 646-658.doi: 10.11872/j.issn.1005-2518.2023.04.030

• 采选技术与矿山管理 • 上一篇    下一篇

“一带一路”背景下巴基斯坦矿业投资环境风险评价与预测

郑明贵1,2(),王馨悦2(),顾东明2,张研博2   

  1. 1.江西理工大学巴基斯坦研究中心,江西 赣州 341000
    2.江西理工大学经济管理学院,江西 赣州 341000
  • 收稿日期:2023-02-22 修回日期:2023-05-28 出版日期:2023-08-30 发布日期:2023-09-20
  • 通讯作者: 王馨悦 E-mail:mgz268@sina.com;wxy1073090801@163.com
  • 作者简介:郑明贵(1978-),男,安徽颍上人,博士,教授,博士生导师,从事资源经济与管理方面的研究工作。mgz268@sina.com
  • 基金资助:
    国家社会科学基金西部项目“中国战略性矿产资源产业链供应链安全稳定战略研究(2025-2060)”(22XGL003);江西理工大学巴基斯坦研究中心2022年度招标课题(WYBY-2022LX001)

Environmental Risk Assessment and Prediction of Mining Investment in Pakistan Under the Background of the Belt and Road

Minggui ZHENG1,2(),Xinyue WANG2(),Dongming GU2,Yanbo ZHANG2   

  1. 1.Center for Pakistani Studies, Jiangxi University of Science and Technology, Ganzhou 341000, Jiangxi, China
    2.School of Economics and Management, Jiangxi University of Science and Technology, Ganzhou 341000, Jiangxi, China
  • Received:2023-02-22 Revised:2023-05-28 Online:2023-08-30 Published:2023-09-20
  • Contact: Xinyue WANG E-mail:mgz268@sina.com;wxy1073090801@163.com

摘要:

巴基斯坦矿产资源丰富,是我国“全天候战略合作伙伴”和重要的矿业投资国家之一。本文从政治法律、经济金融、资源开采、社会文化和基础设施5个风险层面出发,通过构建巴基斯坦矿业投资环境风险评价指标体系,采用改进的CRITIC法确定指标权重,再利用TOPSIS法集结指标信息,最后结合深度学习模型对巴基斯坦矿业投资环境进行评价和预测。研究结果表明:(1)逆全球化风险、资源丰富度、社会稳定、环境规制、信用风险和腐败风险是巴基斯坦矿业投资环境的主要影响因素;(2)2000—2022年巴基斯坦矿业投资环境评分总体呈螺旋上升态势,风险等级降低到中等风险后呈稳定状态。各一级指标中除基础设施风险评分总体呈动态下降趋势外,政治法律风险、经济金融风险、社会文化风险以及资源开采风险评分均呈波动上升趋势;(3)2023—2033年巴基斯坦矿业投资环境由中等风险降为较低风险水平,稳中向好。

关键词: 巴基斯坦, 矿业投资环境, 风险评价, CRITIC法, TOPSIS法

Abstract:

Pakistan is rich in mineral resources and is one of China’s “all-weather strategic partners” and an important mining investment country.Based on the five risk levels of politics and law,economy and finance,resource extraction,social culture and infrastructure,this paper constructs a mining investment environmental risk evaluation index system in Pakistan from a dynamic perspective.The weight of indicators is determined by the improved CRITIC method,and the index information is collected by the TOPSIS method to explore the possible risk factors of Pakistan’s mining investment environment,so that the evaluation results are more accurate,scientific and referenceable.The deep learning model was used to predict the mining investment environment in Pakistan from 2023 to 2033,which provides a reference for the risk prevention of Pakistan’s mining investment environment in the future.The results show that:(1)Anti-globalization risk,resource abundance,social stability,environmental regulation,credit risk and corruption risk sink are the main influencing factors of Pakistan’s mining investment environment.(2)From 2000 to 2022,Pakistan’s mining investment environment score generally showes a spiraling trend,and the risk level was stable after being reduced to medium risk.In addition to the overall dynamic downward trend of infrastructure risk scores,the political and legal risks,economic and financial risks,social and cultural risks and resource exploitation risk scores all show a fluctuating upward trend.(3)From 2023 to 2033,Pakistan’s mining investment environment will be reduced from medium risk to low risk level,stable and improving.

Key words: Pakistan, mining investment climate, risk assessment, CRITIC method, TOPSIS method

中图分类号: 

  • F426.1

表1

巴基斯坦矿业投资环境风险评价指标体系"

准则层指标层指标度量数据来源指标属性
政治法律风险矿业政策矿业投资政策感知指数Fraser研究所
腐败风险政府官员腐败情况WGI数据库
信用风险主权信用评级联合信用评级有限公司
环境规制环境可持续性政策和制度评级WGI数据库
经济金融风险经济发展水平人均GDPWDI数据库
物价风险按GDP平减指数衡量的通货膨胀WDI数据库
汇率风险人民币兑换美元汇率的标准差系数世界银行
逆全球化风险直接投资净流出/直接投资净流入WDI数据库、WTO数据库
资源开采风险资源丰富度矿产资源单位面积的蕴藏量USGS、WDI数据库
国内生产能力矿产在生产份额中所占的比例USGS数据库
储采比矿产开采年限USGS数据库
采选技术采选技术水平高低专家调查
社会文化风险社会稳定社会治安状态UNODC数据库
劳动力水平劳动力平均受教育年限WDI数据库
基尼系数贫富差距程度世界发展指数
基础设施风险交通便利度货柜码头吞吐量WDI数据库
网络覆盖程度互联网个人用户数/总人口WDI数据库
能源供应通电率世界银行

表2

巴基斯坦矿业投资环境风险评价指标权重"

准则层指标层

指标

变异性

指标

冲突性

信息量权重
政治法律风险矿业政策0.30815.8984.9000.056
腐败风险0.29517.1615.0660.058
信用风险0.27917.9915.0280.058
环境规制0.32718.8326.1540.071
经济金融风险经济发展水平0.23418.4664.3280.050
物价风险0.21319.3954.1310.047
汇率风险0.30514.1964.3230.050
逆全球化风险0.32421.7977.0600.081
资源开采风险资源丰富度0.31719.9856.3400.073
国内生产能力0.30913.6714.2250.048
储采比0.21219.9464.2300.048
采选技术0.30813.8554.2710.049
社会文化风险社会稳定0.29221.4936.2690.072
劳动力水平0.31414.0764.4240.051
基尼系数0.33813.5954.6020.053
基础设施风险交通便利度0.31713.6764.3340.050
网络覆盖程度0.29313.6744.0110.046
能源供应0.25114.2323.5730.041

表3

风险等级划分标准"

相对贴近度风险等级
0~0.2高风险
0.2~0.4较高风险
0.4~0.6中等风险
0.6~0.8较低风险
0.8~1.0低风险

表4

巴基斯坦矿业投资环境风险评价综合得分"

年份正理想解距离负理想解距离相对贴近度风险等级
20000.7700.4970.392较高风险
20010.7160.5320.426中等风险
20020.6710.5700.459中等风险
20030.7110.5340.429中等风险
20040.6420.5980.483中等风险
20050.6510.5630.464中等风险
20060.6050.5630.482中等风险
20070.5480.5860.517中等风险
20080.5930.5590.485中等风险
20090.5410.5780.517中等风险
20100.5150.5600.521中等风险
20110.5430.5380.497中等风险
20120.5590.6220.527中等风险
20130.5440.6310.537中等风险
20140.5270.6290.544中等风险
20150.4540.6480.588中等风险
20160.4790.6390.572中等风险
20170.5120.6100.544中等风险
20180.5190.6340.550中等风险
20190.5190.5820.528中等风险
20200.6110.6090.499中等风险
20210.5090.6710.569中等风险
20220.5200.6930.571中等风险

图1

风险评分"

图2

GAN模型预测流程"

图3

生成器和判别器的损失变化"

表5

3种模型预测结果对比"

模型RMSEMAPE
WGAN0.0326965420.483403340
LSTM0.0456634040.502774728
GRU0.0385634110.523065860

图4

WGAN模型预测结果对比"

图5

LSTM模型预测结果对比"

图6

GRU模型预测结果对比"

图7

2023—2033年巴基斯坦矿业投资风险预测"

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