地方政府的雾霾治理政策作用机制——政策工具、空间关联和门槛效应

doi:10.18402/resci.2021.01.04

摘要/Abstract

摘要：

雾霾治理作为“污染防治攻坚战”的重要内容,地方政府作为环境治理的核心主体,有效提升地方政府环境政策的治霾效果具有重要意义。从政府环境治理的政策工具差异、空间关联和门槛效应的3个视角出发,本文提出了地方政府环境治理降低雾霾污染的3个理论假说,并基于中国2003—2016年30个省（市、区）和2007—2016年217个城市数据,利用动态空间面板和动态面板门槛计量方法对相关理论假说进行检验。结果表明：①政策工具方面,多数类型的地方政府环境治理政策工具对雾霾污染均存在不同程度的抑制作用,具体来看,地方政府的环保立法和环保投资降低雾霾污染的效果更显著,而地方政府环保执法对雾霾污染的抑制作用不甚显著。②空间关联方面,周边地区不同类型的地方政府环境治理政策对本地雾霾污染的影响也存在较大差异,其中,邻近地区环保立法通过环保政策的协调成本上升加剧了本地雾霾污染;邻近地区的环保执法虽能降低本地雾霾污染,但效果却不显著;而邻近地区的环保投资通过雾霾治理的空间外溢能显著降低本地雾霾污染。③门槛效应方面,地方政府环境治理对雾霾污染的影响存在比较显著的门槛效应,当地区科技水平或城镇化水平较高时,地方政府环境治理能够有效地降低雾霾污染,反之则加剧雾霾污染。本文将政府环境治理细分为环保立法、执法与投资3种政策工具,细化了政府环境治理行为对雾霾污染的作用机制,为政府更进一步完善环境治理体系提供了科学依据。

关键词: 地方政府, 环境治理, 雾霾污染, 政策工具, 空间关联, 门槛效应

Abstract:

Smog pollution reduction is an important part of the “tough battle for pollution prevention and control”. As the key actor of environmental governance, local governments should play a key role in improving the effectiveness of their environmental policies for smog control. Based on the data of 30 provinces (municipalities, autonomous regions) in China’s mainland from 2003 to 2016 and the data of 217 cities from 2007 to 2016, this study used dynamic spatial panels and dynamic panel threshold measurement methods to test relevant theoretical hypotheses. The results show that: (1) Different types of measures of the local governments for environmental governance have various degrees of success on smog pollution control. Specifically, environmental protection legislation and environmental protection investment of local governments have more significant effects in reducing smog pollution, while local governments’ environmental law enforcement has little effect on the suppression of smog pollution. (2) In terms of spatial correlation, the impact of different measures of local government environmental governance in neighboring areas on local smog pollution is also different. Environmental legislation of neighboring regions has increased local smog pollution through the escalation of coordination costs. Although government environmental law enforcement can reduce smog pollution, the effect is not significant; while environmental protection investment in neighboring areas can significantly reduce local smog pollution through the spatial spillover of smog pollution control. (3) The impact of local government environmental governance on smog pollution has a significant threshold effect. When the level of regional technological development or urbanization is high, local government environmental governance can effectively reduce smog pollution, and vice versa. This study divided government environmental governance into three measures: environmental legislation, law enforcement, and investment. This article detailed the mechanism of government environmental governance actions on smog pollution control, and provided a scientific basis for the government to further improve the environmental governance system and win the war of blue sky defense.

Key words: local government, environmental governance, smog pollution, policy tools, spatial correlation, threshold effects

李子豪, 袁丙兵. 地方政府的雾霾治理政策作用机制——政策工具、空间关联和门槛效应[J]. 资源科学, 2021, 43(1): 40-56.

LI Zihao, YUAN Bingbing. Environmental policy mechanism of local governments in the treatment of haze pollution：Policy tools, spatial correlations and threshold effects[J]. Resources Science, 2021, 43(1): 40-56.

图/表 6

表1

表2

政策工具差异与空间溢出效应估计"

变量	解释变量：执法案件数(enf)		变量	解释变量：环保立法(law)		变量	解释变量：环保财政支出(inv)
变量	SDM模型	DSDM模型	变量	SDM模型	DSDM模型	变量	SDM模型	DSDM模型
smog_t-₁		0.092**	smog_t-₁		0.109***	smog_t-₁		0.103***
smog_t-₁		(2.56)	smog_t-₁		(2.78)	smog_t-₁		(2.67)
enf	0.163	0.246	law	-0.021***	-0.021***	inv	-0.464*	-0.458*
enf	(0.63)	(0.94)	law	(-3.28)	(-3.25)	inv	(-1.71)	(-1.66)
ey	-7.276**	-5.556**	ey	-2.821**	-2.954***	ey	-2.349*	-1.421*
ey	(-2.13)	(-2.06)	ey	(-2.45)	(-2.73)	ey	(-1.92)	(-1.73)
ey²	2.106**	1.581*	ey²	1.622*	1.896*	ey²	1.039*	1.219*
ey²	(2.42)	(1.74)	ey²	(1.69)	(1.84)	ey²	(1.74)	(1.77)
s	-0.037*	-0.029	s	-0.028	-0.043*	s	-0.155**	-0.149**
s	(-1.86)	(-1.63)	s	(-1.54)	(-1.96)	s	(-2.39)	(-2.10)
sci	-0.243*	-0.256*	sci	-0.225*	-0.203*	sci	-0.388**	-0.206
sci	(-1.88)	(-1.92)	sci	(-1.73)	(-1.70)	sci	(-1.99)	(-1.52)
urb	0.016	0.064*	urb	0.059*	0.066*	urb	0.130*	0.117*
urb	(1.08)	(1.68)	urb	(1.71)	(1.70)	urb	(1.74)	(1.66)
fdi	-0.040*	-0.065**	fdi	-0.017*	-0.015*	fdi	-0.071*	-0.070*
fdi	(-1.68)	(-2.16)	fdi	(-1.68)	(-1.67)	fdi	(-1.92)	(-1.87)
den	-0.002	-0.002	den	-0.006**	-0.005*	den	-0.013**	-0.015**
den	(-0.82)	(-0.60)	den	(-1.99)	(-1.74)	den	(-2.29)	(-2.13)
Wenf	-0.551	-0.635	Wlaw	0.043***	0.043***	Winv	-0.313*	-0.384*
Wenf	(-1.04)	(-1.19)	Wlaw	(3.79)	(3.81)	Winv	(-1.73)	(-1.77)
Wey	-0.474*	-0.463*	Wey	-0.968*	-0.892*	Wey	-0.586*	-0.443
Wey	(-1.77)	(-1.67)	Wey	(-1.86)	(-1.67)	Wey	(-1.65)	(-1.45)
Wey²	2.055*	1.600*	Wey²	0.406	0.609	Wey²	2.304	1.842
Wey²	(1.82)	(1.75)	Wey²	(1.29)	(1.43)	Wey²	(1.15)	(0.79)
Ws	-0.070	-0.074	Ws	-0.104*	-0.153**	Ws	-0.218**	-0.164*
Ws	(-1.07)	(-1.09)	Ws	(-1.80)	(-2.48)	Ws	(-2.11)	(-1.68)
Wsci	0.354	0.563*	Wsci	0.274	0.212	Wsci	0.441	0.506
Wsci	(1.46)	(1.68)	Wsci	(1.62)	(1.03)	Wsci	(0.64)	(1.22)
Wurb	-0.017	-0.014	Wurb	-0.069	-0.213**	Wurb	-0.507*	-0.435*
Wurb	(-0.30)	(-0.28)	Wurb	(-0.84)	(-2.22)	Wurb	(-1.93)	(-1.67)
Wfdi	0.044	0.175**	Wfdi	0.052	0.045	Wfdi	0.039	0.014
Wfdi	(0.58)	(1.97)	Wfdi	(0.77)	(0.77)	Wfdi	(0.37)	(0.12)
Wden	-0.010*	-0.005	Wden	-0.005	-0.004	Wden	-0.011	-0.013
Wden	(-1.77)	(-0.88)	Wden	(-0.73)	(-0.62)	Wden	(-1.12)	(-1.14)
ρ	0.779***	0.787***	ρ	0.590***	0.589***	ρ	0.559***	0.562***
ρ	(22.39)	(22.72)	ρ	(15.04)	(14.80)	ρ	(11.50)	(11.14)
R²	0.313	0.320	R²	0.337	0.355	R²	0.372	0.381
log L	-585.757	-888.657	log L	-888.657	-915.679	log L	-676.972	-607.577

表2

表3

表4

表5

表6

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变量	单位	省（市、区）层面				地市层面
变量	单位	均值	最小值	最大值	标准差	均值	最小值	最大值	标准差
smog/SMOG	PM2.5/（μg/m3）	31.89	4.81	81.98	16.67	38.95	7.12	86.74	16.28
law/LAW	环保立法/件	27.22	0.00	208.00	29.84	3.79	0.00	110.00	9.01
enf	执法案件/（例/人）	0.53	0.01	5.95	0.62	-	-	-	-
inv/INV	环保占比/%	3.00	0.85	6.73	1.08	2.96	0.13	31.82	2.19
ey/EY	人均GDP/万元	1.19	0.28	3.18	0.64	1.39	0.27	8.37	0.86
sci/SCI	科学技术支出占比/%	1.53	0.22	7.20	1.31	1.64	0.07	20.68	1.44
s/S	二产占比/%	46.98	19.26	61.50	7.94	50.18	14.95	90.97	10.49
urb/URB	城镇化/%	50.48	13.89	89.60	14.58	52.53	7.08	100.00	18.81
fdi/FDI	外资存量占比/%	15.32	0.79	78.83	13.41	26.73	0.00	168.35	28.18
h/H	人力资本/%	8.64	6.04	12.30	0.99	1.24	0.40	4.48	0.52
den/DEN	人口密度/（人/km²）	436.84	7.40	3826.2	630.11	482.68	21.00	2648.00	336.65

变量	环保执法(enf)			环保立法(law)			环保投资(inv)
变量	(0, 0.530]	(0.530, 2.250]	(2.250, +∞)	(0, 0.360]	(0.360, 4.440]	(4.440, +∞)	(0, 1.530]	(1.530, 3.740]	(3.740, +∞)
smog_i,t-₁	0.149*	0.150*	0.038*	0.132	0.124	0.162*	-0.003	-0.095	-0.167
smog_i,t-₁	(1.67)	(1.69)	(1.72)	(1.44)	(1.34)	(1.72)	(-0.01)	(-0.36)	(-0.62)
gov	0.228	2.007***	-0.229	0.027***	-0.075*	-0.093*	-0.163	0.709	-1.018*
gov	(0.47)	(2.79)	(-1.42)	(3.05)	(-1.66)	(-1.76)	(-0.28)	(1.24)	(-1.70)
ey	-2.462*	-2.463*	-2.792	-2.155**	-2.289**	-1.539	-5.812*	-7.001*	-5.756*
ey	(-1.74)	(-1.76)	(-1.61)	(-2.49)	(-2.52)	(-1.35)	(-1.76)	(-1.92)	(-1.72)
ey²	0. 778*	0.778*	0.914	0. 605	0.666*	0.472	1.115	1.197	0.604
ey²	(1.75)	(1.75)	(0.89)	(1.61)	(1.66)	(1.47)	(1.56)	(1.60)	(0.30)
s	-0.136*	-0.137*	-0.127*	-0.193***	-0.192***	-0.207***	-0.206**	-0.212**	-0.203**
s	(-1.82)	(-1.82)	(-1.70)	(-2.68)	(-2.66)	(-2.86)	(-2.00)	(-2.08)	(-1.99)
fdi	-0.114*	-0.115*	-0.001	-0.056	-0.049	-0.071	-0.007	0.047	-0.087
fdi	(-1.72)	(-1.72)	(-0.91)	(-0.82)	(-0.71)	(-1.02)	(-0.03)	(0.23)	(-0.43)
den	-0.007*	-0.007*	-0.007*	-0.007*	-0.007*	-0.008**	-0.013	-0.014	-0.015
den	(-1.75)	(-1.75)	(-1.67)	(-1.81)	(-1.79)	(-2.00)	(-1.42)	(-1.46)	(-1.62)
AR(1)	-3.299	-3.321	-3.021	-3.335	-3.300	-3.277	-2.734	-2.712	-2.754
AR(1)	-[0.001]	[0.001]	[0.001]	[0.001]	[0.001]	[0.001]	[0.006]	[0.006]	[0.005]
AR(2)	2.564	2.632	2.441	2.776	2.744	2.667	2.230	2.225	2.327
AR(2)	[0.113]	[0.146]	[0.108]	[0.155]	[0.152]	[0.149]	[0.125]	[0.130]	[0.144]
Sargan	24.206	24.321	22.446	25.315	25.277	25.082	24.991	24.877	25.021
Sargan	[1.000]	[1.000]	[1.000]	[1.000]	[1.000]	[1.000]	[0.895]	[0.894]	[0.895]

区间	环保执法(enf)			环保立法(law)			环保投资(inv)
区间	(0, 45.760]	(45.760, 86.500]	(86.500, +∞)	(0, 68.710]	(68.710, 81.550]	(81.550, +∞)	(0, 67.370]	(67.370, 82.010]	(82.010, +∞)
smog_i,t-₁	0.154	0.157	0.159	0.199	0.203	0.205	0.332	0.256	0.210
smog_i,t-₁	(1.11)	(1.14)	(1.16)	(1.57)	(1.58)	(1.60)	(1.62)	(1.26)	(1.03)
gov	1.788	0.226	0.418	0.027***	-0.103*	-0.090*	-0.115	2.500***	-3.642**
gov	(1.22)	(0.58)	(1.05)	(2.71)	(-1.93)	(-1.79)	(-0.23)	(2.60)	(-2.57)
ey	-10.385**	-8.965**	-9.040**	-10.967***	-10.922***	-10.937***	-11.056*	-12.148**	-13.111**
ey	(-2.49)	(-2.13)	(-2.15)	(-2.81)	(-2.79)	(-2.82)	(-1.84)	(-2.05)	(-2.22)
ey²	2.157**	1.804*	1.817*	2.391**	2.383**	2.374**	2.363	2.483	2.494
ey²	(2.17)	(1.79)	(1.80)	(2.54)	(2.53)	(2.50)	(1.39)	(1.49)	(1.51)
s	-0.066	-0.074	-0.082*	-0.116	-0.119	-0.127	-0.168*	-0.137	-0.164*
s	(-1.36)	(-1.47)	(-1.95)	(-1.46)	(-1.47)	(-1.50)	(-1.69)	(-1.40)	(-1.63)
fdi	-0.079	-0.075	-0.078	-0.104	-0.107	-1.09	-0.260*	-0.210	-0.219
fdi	(-0.79)	(-0.76)	(-0.79)	(-1.13)	(-1.14)	(-1.16)	(-1.67)	(-1.30)	(-1.36)
den	-0.008*	-0.009**	-0.009**	-0.004	-0.004	-0.004	-0.039***	-0.036***	-0.037***
den	(-1.87)	(-2.04)	(-2.08)	(-0.93)	(-0.92)	(-0.95)	(-3.55)	(-3.37)	(-3.44)
AR(1)	-3.774	-3.558	-3.449	-3.472	-3.311	-3.287	-2.844	-2.920	-2.941
AR(1)	[0.001]	[0.001]	[0.001]	[0.001]	[0.001]	[0.001]	[0.004]	[0.004]	[0.004]
AR(2)	2.611	2.544	2.494	2.844	2.582	2.573	2.517	2.523	2.525
AR(2)	[0.167]	[0.157]	[0.150]	[0.164]	[0.160]	[0.153]	[0.170]	[0.174]	[0.178]
Sargan	23.822	22.882	22.772	26.022	23.774	23.463	26.233	26.821	26.833
Sargan	[1.000]	[1.000]	[1.000]	[1.000]	[1.000]	[1.000]	[0.914]	[0.923]	[0.925]

变量	地理权重		经济权重		混合权重
SMOG_t-₁	0.050***	(4.48)	0.105***	(4.88)	0.035***	(2.63)
INV	-0.063*	(-1.74)	-0.074**	(-1.96)	-0.089***	(-2.75)
EY	1.168**	(2.11)	1.897*	(1.71)	1.052*	(1.76)
EY²	-0.139**	(-2.12)	-0.147	(-1.12)	-0.147**	(-2.02)
S	-0.024	(-1.48)	-0.060*	(-1.86)	-0.001	(-0.75)
SCI	-0.094*	(-1.85)	-0.297***	(-2.61)	-0.130**	(-1.96)
URB	0.019*	(1.73)	0.021*	(1.75)	0.024*	(1.90)
FDI	-0.008*	(-1.82)	-0.076***	(-4.71)	-0.004	(-1.38)
DEN	-0.002	(-1.51)	-0.001	(-1.16)	-0.003*	(-1.69)
WINV	-0.079	(-0.96)	-0.421**	(-2.37)	-0.215*	(-1.67)
WEY	-0.105	(-1.09)	-0.231	(-1.09)	-2.249*	(-1.83)
WEY²	0.017	(1.11)	0.371	(1.57)	0.285**	(2.00)
WS	-0.009	(-0.92)	-0.006*	(-1.90)	-0.004*	(-1.72)
WSCI	-0.357***	(-2.76)	-0.057	(-1.14)	-0.553***	(-3.11)
WURB	0.024	(0.78)	0.077	(1.43)	0.055*	(1.74)
WFDI	-0.018	(-0.93)	-0.010**	(-2.09)	-0.023**	(-2.28)
WDEN	0.010	(1.62)	0.006	(1.56)	0.007	(1.48)
ρ	0.977***	(139.82)	0.519**	(17.14)	0.955***	(94.65)
R²	0.360		0.308		0.373
log L	-404.673		-527.599		-428.164

科技支出区间	(0, 0.320]	(0.320, 1.200]	(1.200, +∞)	城镇化区间	(0, 71.880]	(71.880, 79.900]	(79.900, +∞)
SMOG_t-₁	1.572***	2.089***	2.006***	SMOG_t-₁	0.802***	0.742***	0.713**
SMOG_t-₁	(2.88)	(3.48)	(3.34)	SMOG_t-₁	(2.79)	(2.59)	(2.48)
INV	0.016	0.059**	-0.312***	INV	0.031	0.153***	-0.467**
INV	(1.28)	(2.39)	(-2.92)	INV	(1.38)	(4.51)	(-2.33)
EY	9.493*	14.381**	13.713**	EY	2.543*	1.985	1.754
EY	(1.81)	(2.50)	(2.38)	EY	(1.78)	(1.61)	(0.54)
EY²	-0.156	-0.883**	-0.837*	EY²	-0.006	-0.031	-0.045
EY²	(-1.25)	(-1.97)	(-1.87)	EY²	(-0.02)	(-0.11)	(-0.16)
S	0.068	-0.099**	-0.097**	S	-0.059	-0.088**	-0.087**
S	(1.50)	(-2.08)	(-2.02)	S	(-0.31)	(-2.27)	(-2.25)
FDI	-0.298**	-0.417***	-0.398***	FDI	-0.119*	-0.100	-0.095
FDI	(-2.31)	(-2.95)	(-2.81)	FDI	(-1.68)	(-1.42)	(-1.34)
DEN	-0.122***	-0.161***	-0.155***	DEN	-0.063***	-0.058**	-0.056**
DEN	(-2.90)	(-3.50)	(-3.36)	DEN	(-2.80)	(-2.60)	(-2.50)