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基于多尺度投入-产出表的中国对外贸易产业结构调整多目标优化
引用本文:姚黎明,徐忠雯.基于多尺度投入-产出表的中国对外贸易产业结构调整多目标优化[J].四川大学学报(自然科学版),2022,59(5):057001.
作者姓名:姚黎明  徐忠雯
作者单位:四川大学商学院,南京大学环境学院
基金项目:国家自然科学面上项目 (71771157); 四川省社会科学基金 ( 201726); 生态环境部基金 (2020QT017-K2020A003)
摘    要:出口贸易引发的资源流失风险是当今研究的热点. 本文动态地分析了出口贸易引起的资源流出变动及其影响因素, 并对2018-2022年中国地区出口贸易进行优化调整. 首先, 本文利用行业间投入-产出表和资源消耗数据计算中国各行业的直接和完全资源消耗系数; 其次, 利用结构分解模型挖掘出口导向的隐含资源流出量变动的主要原因; 随即, 将45个行业进行聚类分析, 探讨未来各行业的节约资源潜力和调整路径; 最后基于情景分析和多目标优化理论, 从出口贸易结构, 贸易额和技术发展视角对中国未来出口贸易进行模拟分析. 实证分析结果表明: (1) 直接消耗强度, 技术进步, 出口总量和出口结构等4个影响因素中, 出口额对资源流失风险的贡献率最大. 直接能源消耗强度有助于降低因出口导致的能源流出, 而完全消耗水资源强度的降低大大减少了资源流失风险, 符合现实; (2) 以2017 年为基准年, 利用多目标优化模型求解2018-2022年出口结构和出口量, 结果表明优化结果有利于降低资源流出量. 通过调整未来各行业资源消耗强度, 优化结果发现技术提升带来的资源节约优势逐渐增强, 本文认为, 为技术改善的资金(人员)投入的边际产出呈现逐渐增强效应.

关 键 词:多尺度投入-产出分析    隐含资源    结构分解法    出口结构    多目标优化
收稿时间:2022/3/2 0:00:00
修稿时间:2022/5/6 0:00:00

China's export trade industrial structure multi-objective optimization based on a multi-scale input-output analysis method
YAO Li-Ming and XU Zhong-Wen.China''s export trade industrial structure multi-objective optimization based on a multi-scale input-output analysis method[J].Journal of Sichuan University (Natural Science Edition),2022,59(5):057001.
Authors:YAO Li-Ming and XU Zhong-Wen
Institution:Business School, Sichuan University,,School of Environment, Nanjing University
Abstract:The risk of resource loss caused by exports is a hot topic nowadays. This paper focuses on resource flow, analyzes contribution rates of influencing factors to changes in resource flow dynamically, and then offers optimized export restructure strategies during the period from 2018 to 2022. In the analytic framework, firstly, the economic input-output table and energy-water consumption data are used to calculate the direct and complete consumption coefficients of water and energy; Secondly, to provide a reference for scenario definition and future export restructure, the authors use the structural decomposition analysis model to identify the main reasons for the variation of the resources flow. Besides, the authors use clustering analysis to identify sectoral water and energy consumption disparity and the potential for resource-saving. At last, this paper uses a bi-objective optimization model to optimize the export structure. The empirical analysis indicates that the volume of exports is found as the primary contributor to resource flow; direct energy consumption intensity helps to reduce energy outflow caused by export, while the reduction of total water consumption intensity greatly reduces the risk of resource loss, which is consistent with the reality. Cluster analysis offers the improving directions, and the optimization result shows that faced with the extension of export, reducing the energy-water coefficient helps to achieve resources conservation. Besides, this paper argues that the marginal output derived from technological improvement shows a gradually increasing effect.
Keywords:Multi-scale Input-Output analysis method  Embodied resources  Structural decomposition analysis  Export structure  Multi-objective optimization
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