Modeling the Relationship Between Economic Growth, Resource Consumption and Environment Pollution by System Dynamics Model

Abstract

�According to connotation and framework of sustainable development in urban economy -resource -environment, this study proposes a novel system dynamics model to deal with an issue of economy development in Chongqing of China restricted by depletion of resource and degradation of environment, by means of fundamental theory and methodology of system dynamics. Eight subsystems are involved in the model, which denote population, GDP, technology in production, labor input, capital input, renewable resource, nonrenewable resource and environment. To compare different policies with regard to their potential economy-resource-environment impacts, alternative scenarios are used by adjusting the parameters within the model and changing the specification of some variables. The results are elucidated as follows: the current economyresource -environment system of Chongqing is not sustainable; the substitution rate of technology for resource is low and environment pollution becomes serious as a function of increasing output; a way to realize sustainable development of Chongqing is to optimize its economic development mode. Key words: System dynamics model, economy, resource, environment, Chongqing in ChinaUrban economic growth is a complicated process that is mainly determined by interaction between resource depletion and environment pollution in space and time at different scales 1,2) . Modeling is a valuable way to understand such a process [3][4][5][6] . To date, a variety of approaches have been developed to model a spatial process of urban development, including potential models 7) , IPAT model and quantitative economics method 8) , system optimization and mathematical modeling thinking 9) , as well as spatial logistic regression 10) . These models can only forecast development change in the future. However, there still lacks of explicit models for dynamic growth of urban economy that can not only effectively trace urban development in the past, but also predict possible growth scenarios in the future so that some related urban planning policies can be examined.Recently, it has been of attractive interest to spread the applications of system dynamics (SD) models in urban development and integrated sustainable management systems [11][12][13][14] . In an international comprehensive view, studies on urban SD model can be summarized as three core issues.

Assessment and Forecast of Urban Sustainability Based on Dynamic Indicators

“…However, it is less to carry out dynamic assessment of urban ERE with future indicator values. In this paper, the essential indicators of urban sustainability based on the present research are used to carry out the further dynamic assessment of ERE sustainability in the difference development scenarios (current, resource, environment and technology development modes) [1]. The basic hierarchy of composing indicators into the urban sustainable development is shown in Table 1, in which hierarchies from top to down are defined as A, B and C layers, respectively.…”

Correlation Analysis between Economic Growth and Environmental Quality

“…Scholars around the world have made some attempts, such as input-output model [1][2][3], system dynamics model [4][5][6], Kuznets curve [7][8][9][10][11], ridge regression model [12][13][14][15], Vertical Auto-regression model [16][17][18][19], and computable general equilibrium assessment [20][21][22][23][24][25]. One of the most widely used methods is the Kuznets curve, which reflects the inverted U-shape between economy and environment.…”

资源型区域经济空间分异解析——以中原经济区为例

“…理论、 经济增长理论以及空间统计方法的指导下 [10] [11] 年末单位从业人员数 人均粮食产量 (县域农业水平) 矿业产值占工业产值比重 每万人专业技术人员数之和 地方财政支出占 GDP 比重 工业产值占 GDP 比重 非农人口占比 [12] 人口的聚集程度决定市场份额的大小 [13] 选取公路和铁路密度进行综合评价 通讯用户数占比 解释变量的弹性系数 冗余量 表 1 模型变量 理 信 息 中 心 [14] 和《中 国 县 域 统 计 年 鉴》 (2001 年 ， 2011 年) [15， 16] 等。 对中原经济区的经济增长的各项指标进行全 局回归分析得出， 资本、 矿业、 工业化、 城市化对区 域经济增长促进作用显著， 政府支出为负相关， 其 它因素作用不显著 [17] 的拟合度， 以满足对拟合度的无偏估计假设 [18] 。 (1) 空间权重矩阵设定。用地理加权回归方法 解释空间分异过程和结构， 其核心思想是选取适当 的空间权重矩阵 [19] 。为了体现出空间距离对于影响 程度的差异， 并结合实际应用， 本文选取截尾型双 平方函数体现距离的加权特征和对尾噪声的消除 [20] ， 将那些对回归参数估计影响微乎其微的数据点 截去不予计算， 公式如下：…”