中国工业经济增长与工业污染的内在关联机制测度

doi:10.18402/resci.2018.04.19

摘要/Abstract

摘要：

工业污染始终是人类工业化进程中面临的重要挑战,为解决中国工业污染与工业经济之间的协调问题,本文基于中国工业固体废物产生量增长率（solid_t）、工业废水排放量增长率（liquid_t）、工业废气排放量增长率（gas_t）和工业经济增长率（iav_t）构建“solid_t-iav_t”、“liquid_t-iav_t”和“gas_t-iav_t”三种“工业污染与工业经济”系统,运用非线性MS-VAR模型,测度中国工业经济增长与工业污染内在关联机制的周期性。研究结果表明：①“工业污染与工业经济”系统潜存着在“低速增长区制”和“快速增长区制”之间相互转移的结构性突变迹象,并且具有非线性周期变化特征;②“工业污染与工业经济”系统处于“低（快）速增长区制”时,solid_t与iav_t呈负（正）相关关系,liquid_t与iav_t呈正（负）相关关系,gas_t与iav_t呈正相关关系;③“solid_t-iav_t”系统和“gas_t-iav_t”系统处于“低（快）速增长区制”时的可能性大（小）、持续性强（弱）,“liquid_t-iav_t”系统处于“快（低）速增长区制”的可能性大（小）、持续性强（弱）。

关键词: 工业经济增长, 工业污染, 关联机制, 周期性, 中国

Abstract:

Industrial pollution is a serious problem in the process of human industrialization. In order to solve the problem in China, based on the industrial data of China’s solid waste output ( $soli d t$ ), waste water emission ( $liqui d t$ ), waste gas exhaust ( $ga s t$ ) and economic growth ( $ia v t$ ), we built an industrial pollution and industrial economic growth system, namely “ $soli d t - ia v t$ ”, “ $liqui d t - ia v t$ ” and “ $ga s t - ia v t$ ”. Under this system, we measure the cyclicity of associative mechanisms between industrial economic growth and industrial pollution with the model of nonlinear MS-VAR. We capture and portray the regime transmission process of the industrial pollution and industrial economic growth system to identity whether the system is in “low growth regime” or “fast growth regime”, so that the relationship between industrial pollution and industrial economic growth can be identified. We found that “industrial pollution and industrial economic growth” system exists a sign of structural mutation between “low growth regime” and “fast growth regime”, and the system has a nonlinear characteristic of cyclic change. With the regime transforming, the relationship between industrial pollution and industrial economy will also change. While “ $soli d t - ia v t$ ” system is in “low (fast) growth regime”, $soli d t$ and $ia v t$ are negatively (positively) related. Comparatively, $liqui d t$ and $ia v t$ are performing a negative (positive) relationship, when “ $liqui d t - ia v t$ ” system is in “fast (low) growth regime”. No matter “ $ga s t - ia v t$ ” system is in “low growth regime” or “fast growth regime”, the relationship between $ga s t$ and $ia v t$ is positive. What’s more, for the “ $soli d t - ia v t$ ” system and the “ $ga s t - ia v t$ ” system, the possibility and sustainability in “low (fast) growth regime” is higher (lower). However, with a higher (lower) probability and stronger (weaker) durability, “ $liqui d t - ia v t$ ”system tends to be in “fast (low) growth regime”.

Key words: industrial economic growth, industrial pollution, associative mechanism, cyclicity, China

隋建利, 刘碧莹, 刘金全. 中国工业经济增长与工业污染的内在关联机制测度[J]. 资源科学, 2018, 40(4): 862-873.

Jianli SUI, Biying LIU, Jinquan LIU. The intrinsic associative mechanism between industrial economic growth and industrial pollution in China[J]. Resources Science, 2018, 40(4): 862-873.

图/表 7

表2

1985—2014年中国“工业污染与工业经济”系统的增长区制划分及平滑概率均值"

“ $soli d t - ia v t$ ”系统					“ $liqui d t - ia v t$ ”系统				“ $ga s t - ia v t$ ”系统
低速增长区制			快速增长区制		低速增长区制		快速增长区制		低速增长区制			快速增长区制
时间区间		平滑概率均值	时间区间		平滑概率均值	时间区间	平滑概率均值	时间区间	平滑概率均值	时间区间	平滑概率均值	时间区间	平滑概率均值
1989—2002年	0.977 7		1985—1988年	0.902 7	1989—1993年	0.979 7	1985—1988年	0.970 3	1985—1999年	0.996 1		2000—2008年	0.968 6
2009年	1.000 0		2003—2008年	0.954 4	1996—1997年	0.996 3	1994—1995年	0.999 0	2009年	1.000 0		2010—2011年	1.000 0
2013—2014年	0.999 5		2010—2012年	0.855 0	1999年	0.876 7	1998年	1.000 0	2012—2014年	0.999 9
					2009年	0.999 5	2000—2008年	0.981 3
					2012—2014年	0.992 5	2010—2011年	0.935 8

表2

表1

MSMH (2) - VAR (1) 模型各均值和方差的估计结果"

参数	$soli d t - ia v t$ 系统估计值			$liqui d t - ia v t$ 系统估计值			$ga s t - ia v t$ 系统估计值
参数	$soli d t$		$ia v t$		$liqui d t$	$ia v t$	$ga s t$	$ia v t$
$μ 1$	0.040 7* (0.024 3)	0.111 9 (0.076 7)		-0.042 8*** (0.010 2)	0.114 8 (0.080 0)		0.027 0 (0.022 2)	0.102 9 (0.119 1)
$μ 2$	0.109 8*** (0.038 7)	0.207 7*** (0.065 5)		0.021 9* (0.012 1)	0.174 1** (0.075 6)		0.166 9*** (0.027 1)	0.192 3* (0.101 8)
$σ 1$	0.054 9	0.073 5		0.022 1	0.058 9		0.039 9	0.074 9
$σ 2$	0.108 0	0.026 3		0.030 2	0.054 3		0.068 3	0.030 7

表1

图1

图2

图3

表3

1985—2014年中国工业污染增长率与工业经济增长率在不同增长区制内的相关系数估计"

“ $soli d t - ia v t$ ”系统	低速增长区制			快速增长区制
“ $soli d t - ia v t$ ”系统	$soli d t$		$ia v t$	$soli d t$	$ia v t$
$soli d t$	1.000 0	-0.366 2		1.000 0	0.251 5
$ia v t$	-0.366 2	1.000 0		0.251 5	1.000 0
“ $liqui d t - ia v t$ ”系统	低速增长区制			快速增长区制
“ $liqui d t - ia v t$ ”系统	$liqui d t$		$ia v t$	$liqui d t$	$ia v t$
$liqui d t$	1.000 0	0.438 8		1.000 0	-0.197 4
$ia v t$	0.438 8	1.000 0		-0.197 4	1.000 0
“ $ga s t - ia v t$ ”系统	低速增长区制			快速增长区制
“ $ga s t - ia v t$ ”系统	$ga s t$		$ia v t$	$ga s t$	$ia v t$
$ga s t$	1.000 0	0.254 9		1.000 0	0.294 2
$ia v t$	0.254 9	1.000 0		0.294 2	1.000 0

表3

表4

1985—2014年中国“工业污染与工业经济”系统的区制转移概率矩阵以及区制属性"

“ $soli d t - ia v t$ ”系统	区制转移概率矩阵			区制属性
“ $soli d t - ia v t$ ”系统	低速增长区制		快速增长区制	样本数量	平均持续期
低速增长区制	0.843 1	0.156 9		17.8	6.37
快速增长区制	0.257 3	0.742 7		12.2	3.89
“ $liqui d t - ia v t$ ”系统	区制转移概率矩阵			区制属性
“ $liqui d t - ia v t$ ”系统	低速增长区制		快速增长区制	样本数量	平均持续期
低速增长区制	0.630 9	0.369 1		12.2	2.71
快速增长区制	0.268 6	0.731 4		17.8	3.72
“ $ga s t - ia v t$ ”系统	区制转移概率矩阵			区制属性
“ $ga s t - ia v t$ ”系统	低速增长区制		快速增长区制	样本数量	平均持续期
低速增长区制	0.891 4	0.108 6		19.2	9.20
快速增长区制	0.201 0	0.799 0		10.8	4.98

表4

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