黄河流域资源型城市转型效率及其影响因素

doi:10.18306/dlkxjz.2020.10.004

Abstract

Abstract:

Resource-based cities are widely distributed in the Yellow River Basin and face prominent problems. Improving urban efficiency and promoting the transformation of resource-based cities are an important way to achieve ecological protection and high-quality development in the Yellow River Basin. This study used the data envelopment analysis (DEA) model to evaluate the transformation efficiency of 41 resource-based cities in the Yellow River Basin from 2007 to 2017. It further carried out a panel regression analysis on the factors that influence the transformation efficiency of resource-based cities through the fixed effect model. The results show that: 1) Transformation efficiency of resource-based cities in the Yellow River Basin is not ideal. The number of cities with the best comprehensive efficiency reached 39.02% of all cities in 2017, but the gap in transformation efficiency has widened since 2015. 2) Scale efficiency is the main determining factor of comprehensive efficiency. The number of cities with the best scale efficiency increased first and then decreased, and the feature of decreasing returns to scale became increasingly more obvious, which indicates that there was a input redundancy in the transformation efficiency of some cities. 3) On the whole, per capita GDP, the proportion of government financial revenue in GDP, and the number of students in ordinary higher education institutions have a significant positive effect on the transformation efficiency of resource-based cities, while the proportion of the tertiary industry has a significant negative effect. With regard to different types of resource-based cities, the proportion of foreign-invested industrial enterprises has a significant positive effect on the transformation efficiency of coal-based cities, and the proportion of mining employees has a significant positive effect on the transformation efficiency of mature resource-based cities. The factors influencing the transformation efficiency of different cities are different.

Key words: resource-based cities, transformation efficiency, DEA model, high quality development, the Yellow River Basin

WANG Xiaonan, SUN Wei. Transformation efficiency of resource-based cities in the Yellow River Basin and its influencing factors[J].PROGRESS IN GEOGRAPHY, 2020, 39(10): 1643-1655.

Figures/Tables 13

Fig.1

Tab.1

Tab.2

Fig.2

Fig.3

Tab.3

Evaluation results of transformation efficiency of resource-based cities"

排名	2007年		2008年		2009年		2010年		2011年		2012年
排名	城市	效率	城市	效率	城市	效率	城市	效率	城市	效率	城市	效率
1	庆阳	0.666	武威	0.551	张掖	0.560	武威	0.661	张掖	0.663	张掖	0.685
2	张掖	0.612	张掖	0.550	武威	0.540	张掖	0.627	吕梁	0.657	吕梁	0.637
3	平凉	0.521	金昌	0.526	金昌	0.488	吕梁	0.537	陇南	0.623	晋城	0.599
20	朔州	0.198	濮阳	0.292	阳泉	0.286	东营	0.456	金昌	0.472	忻州	0.450
21	阳泉	0.190	晋城	0.289	淄博	0.285	延安	0.455	濮阳	0.468	濮阳	0.447
22	临汾	0.190	平顶山	0.285	平顶山	0.280	濮阳	0.447	忻州	0.463	渭南	0.442
39	榆林	0.094	洛阳	0.190	宝鸡	0.196	大同	0.301	大同	0.314	白银	0.357
40	包头	0.087	渭南	0.183	洛阳	0.178	石嘴山	0.297	洛阳	0.281	洛阳	0.315
41	洛阳	0.074	焦作	0.176	焦作	0.172	洛阳	0.276	武威	0.234	大同	0.310
平均值		0.241		0.306		0.304		0.440		0.466		0.465
排名	2013年		2014年		2015年		2016年		2017年
排名	城市	效率	城市	效率	城市	效率	城市	效率	城市	效率
1	张掖	0.690	张掖	0.654	张掖	0.656	张掖	0.653	庆阳	0.686
2	吕梁	0.616	吕梁	0.603	吕梁	0.584	吕梁	0.584	鹤壁	0.665
3	延安	0.585	延安	0.583	延安	0.581	延安	0.580	铜川	0.632
20	长治	0.459	东营	0.455	三门峡	0.448	三门峡	0.447	淄博	0.407
21	枣庄	0.457	渭南	0.452	渭南	0.447	渭南	0.447	渭南	0.407
22	武威	0.453	长治	0.451	乌海	0.440	乌海	0.437	金昌	0.406
39	阳泉	0.319	阳泉	0.310	大同	0.307	大同	0.307	大同	0.207
40	洛阳	0.314	大同	0.308	阳泉	0.294	阳泉	0.293	石嘴山	0.186
41	大同	0.305	洛阳	0.298	洛阳	0.277	洛阳	0.277	包头	0.185
平均值		0.462		0.452		0.446		0.444		0.404

Tab.3

Fig.4

Fig.5

Fig.6

Tab.4

Regression results of factors influencing the transformation efficiency of resource-based cities"

变量	固定效应模型
MIE	0.148
MIE	(1.11)
TI	-0.00260^***
TI	(-4.22)
FI	0.645
FI	(0.94)
ST	-0.356
ST	(-0.69)
SE	0.00000118^***
SE	(3.49)
PBR	0.613^*
PBR	(1.99)
PG	0.00000429^***
PG	(13.11)
$α 0$	0.195^***
$α 0$	(4.41)
N	451
R²	0.395
F	37.64

Tab.4

Tab.5

Regression results of factors influencing the transformation efficiency of cities with different resource types"

变量	煤炭型	石油型	金属矿型	非金属矿型	其他城市
MIE	0.199	0.471	-0.240	2.201	0.599
MIE	(1.31)	(0.79)	(-0.51)	(1.08)	(0.53)
TI	-0.00360^***	0.00114	-0.00575^***	0.00336	-0.00193
TI	(-4.35)	(0.37)	(-4.50)	(0.84)	(-0.82)
FI	2.570^**	0.997	1.317	1.963	2.793
FI	(2.73)	(0.36)	(0.81)	(0.22)	(1.24)
ST	1.476	-4.394	1.102	-0.130	-5.092
ST	(0.60)	(-0.91)	(0.45)	(-0.17)	(-0.41)
SE	0.00000304^***	0.00000382	-0.000000283	-0.000000337	-0.000000464
SE	(4.51)	(1.91)	(-0.39)	(-0.08)	(-0.70)
PBR	0.879	-2.010	0.836^*	-3.361	-0.946
PBR	(1.70)	(-1.17)	(2.27)	(-1.13)	(-0.43)
PG	0.00000387^***	0.00000511^***	0.00000879^***	0.0000134^*	0.0000114^*
PG	(9.87)	(5.30)	(6.47)	(2.08)	(2.68)
$α 0$	0.0586	0.0344	0.210^*	-0.0952	0.285
$α 0$	(0.75)	(0.10)	(2.56)	(-0.22)	(1.61)
N	231	55	88	33	44
R²	0.483	0.540	0.559	0.387	0.350
F	27.14	7.206	13.24	2.072	2.541

Tab.5

Tab.6

Regression results of factors influencing the transformation efficiency of cities with different developmental types"

变量	成长型	成熟型	衰退型	再生型
MIE	0.202	0.449^*	0.151	1.811
MIE	(0.44)	(2.19)	(0.65)	(1.80)
TI	0.00126	-0.00554^***	0.000707	-0.00329
TI	(0.76)	(-7.06)	(0.38)	(-1.87)
FI	3.392	0.778	0.377	-0.750
FI	(1.58)	(0.91)	(0.18)	(-0.46)
ST	-0.299	-1.513	-1.607	2.365
ST	(-0.43)	(-0.74)	(-0.48)	(0.50)
SE	0.00000231	0.000000979^*	0.00000255^*	0.00000210^**
SE	(1.22)	(2.57)	(2.38)	(3.23)
PBR	0.359	1.233^*	0.0574	1.311
PBR	(0.67)	(2.07)	(0.08)	(1.09)
PG	0.00000369^***	0.00000668^***	0.00000311^***	0.00000314^***
PG	(5.56)	(11.06)	(3.93)	(4.15)
$α 0$	0.0636	0.133	0.171	0.0408
$α 0$	(0.52)	(1.92)	(1.40)	(0.33)
N	88	220	77	66
R²	0.421	0.497	0.410	0.557
F	7.592	27.26	6.246	9.512

Tab.6

Fig.7

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	变量	变量符号	含义
被解释变量	转型效率	TE
解释变量	采矿业从业人员占比(%)	MIE	资源依赖
	第三产业比重(%)	TI	产业合理化
	外商投资工业企业占比(%)	FI	对外开放
	科学技术支出占比(%)	ST	创新投入
	普通高等学校在校学生数(人)	SE	创新过程
	政府财政收入占GDP的比重(%)	PBR	政府支持能力
	人均地区生产总值(万元)	PG	经济发展

Transformation efficiency of resource-based cities in the Yellow River Basin and its influencing factors

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类型	2007年	2008年	2009年	2010年	2011年	2012年	2013年	2014年	2015年	2016年	2017年
综合效率最优城市数	20	20	20	22	22	21	23	23	16	17	16
纯技术效率最优城市数	25	24	25	24	27	26	28	26	26	29	27
规模效率最优城市数	21	21	22	22	22	22	23	24	17	17	17

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