中国农业竞争力时空格局演化及其影响因素

doi:10.11821/dlxb202006014

Abstract

Abstract:

Based on the objective-weight value-assigning method, by means of establishing one comprehensive index system from four dimensions, namely natural endowment, flow input, output capacity and facilities' mechanism, this paper makes a series of experimental tests on the actual agricultural competitiveness within the 29 provincial-level areas of China from 2000 to 2016. And with application of spatial measurement model, it also makes a profound analysis upon spatio-temporal evolving rules and factors influencing China's agricultural competitiveness in hope for offering certain theoretical supports for formulating a series of targeted and differentiated agricultural competitiveness upgrading policies in the near future. The results of analysis show that: (1) China's agricultural competitiveness, featured by obvious spatial auto-correlation, is on the rise. The spatial spillover intensity presents an inverted "U-shaped" pattern. And the two sub-competitiveness indexes, namely flow input and output capacity, still keep on the upside. The overall resource endowment is relatively stable and the facilities' mechanism is witnessing a fluctuant increasing process. (2) The agricultural competitiveness in the central and western provinces continues to decline as that in the eastern provinces rises rapidly, which presents an apparent polarization. And the local-spatial clustering pattern is dominated by HH clustering mode and LL clustering mode with the characteristics of stronger stability and serious path dependency. (3) Multiple factors, including farmers' income, household-consuming level, economic basis, R&D input, planting structure and grain-variety selection, have direct effects on the spatio-temporal evolution of provincial agricultural competitiveness. At the same time, the above factors have indirect spillover effects on other provinces. (4) We should give full play of the current demonstration effect and diffusion effect brought by the agricultural competitiveness and related influencing factors to push future optimal allocation of agricultural resources, promote subsequent rational flow of the existing agricultural producing factors and plan finally-balanced development of agricultural competitiveness.

Key words: agricultural competitiveness, space-time evolution, influencing factor, spatial measurement model, China

WEI Suhao, LI Jing, LI Zeyi, ZONG Gang. Spatio-temporal evolution and its influencing factors of China's agricultural competitiveness[J].Acta Geographica Sinica, 2020, 75(6): 1287-1300.

Figures/Tables 8

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目标层	准则层	指标层	计算公式
农业竞争力评价	自然禀赋竞争力	土地资源禀赋(+)	总播种面积/年末常住人口数量
		水资源禀赋(+)	水资源总量/总播种面积
		自然灾害(-)	受灾面积/总播种面积
	流动投入要素竞争力	机械投入强度(+)	机械总动力/总播种面积
		化肥投入强度(o)	化肥投入总量/总播种面积
		农药投入强度(o)	农药投入总量/总播种面积
		农膜投入强度(+)	农膜投入总量/总播种面积
		农业用电投入强度(+)	农业用电量/总播种面积
	产出竞争力	劳动生产率(+)	第一产业产值/第一产业从业人员数量
		土地生产率(+)	粮食总产量/粮食播种面积
			蔬菜产量/蔬菜播种面积
			油料产量/油料播种面积
	设施与机制竞争力	有效灌溉面积占比(+)	有效灌溉面积/总耕地面积
		公路交通密度(+)	公路里程/行政面积
		财政支农力度(+)	财政支农资金/总播种面积

年份	Moran's I	p值	年份	Moran's I	年份	Moran's I	p值
2000	0.238	0.001	2006	0.462	2012	0.442	0.000
2001	0.248	0.003	2007	0.427	2013	0.254	0.001
2002	0.456	0.000	2008	0.433	2014	0.245	0.003
2003	0.203	0.005	2009	0.423	2015	0.221	0.007
2004	0.277	0.002	2010	0.443	2016	0.249	0.017
2005	0.423	0.000	2011	0.428

类型	2000年	2016年
H-H	北京、上海、天津、浙江、福建、新疆	北京、上海、天津、浙江、江苏、福建
L-H	河北、江西、江苏、安徽	河北、江西、安徽、新疆
L-L	辽宁、黑龙江、吉林、河南、山东、湖北、湖南、重庆、四川、贵州、云南、山西、甘肃、内蒙、陕西、宁夏	黑龙江、吉林、河南、山东、湖北、湖南、重庆、四川、贵州、云南、广西、山西、甘肃、内蒙、陕西、宁夏
H-L	青海、广东、广西	青海、广东、辽宁

模型	检验	结果	模型	检验	结果
SLM模型	Wald_spatial	27.661^***	SEM模型	Wald_spatial	41.304^***
SLM模型	LR_spatial	24.854^***	SEM模型	LR_spatial	38.060^***
SDM固定与随机效应模型	Hausman检验	11.237^***

变量	无固定	时期固定	空间固定	双固定	变量	无固定	时期固定	空间固定	双固定
-cons	1.791^* (1.84)				W×PCI	0.147^** (2.11)	0.314^*** (2.73)	0.123^* (1.86)	0.212^*** (3.03)
PCI	0.077^** (2.40)	0.314^*** (6.21)	0.078^** (2.56)	0.089^*** (2.96)	W×RCL	0.009 (0.17)	0.306 (0.89)	0.009 (0.21)	0.074 (1.48)
RCL	0.121^*** (5.54)	0.235^*** (5.96)	0.124^*** (5.62)	0.118^*** (5.32)	W×EDL	0.014 (1.50)	0.125^*** (6.18)	0.014 (1.36)	-0.004 (-0.29)
EDL	0.005 (0.86)	0.014^*** (4.35)	0.004 (0.60)	0.002 (0.39)	W×RDI	0.186^*** (4.08)	0.372^*** (6.31)	0.154^*** (3.97)	0.232^*** (5.27)
RDI	0.074^*** (3.69)	0.107^*** (4.68)	0.060^*** (3.81)	0.075^*** (4.00)	W×GSR	0.043^*** (2.94)	-0.066^*** (-5.05)	0.042^*** (3.06)	0.048^*** (2.82)
GSR	-0.033^*** (-4.17)	-0.064^*** (-9.02)	-0.029^*** (-3.75)	-0.026^*** (-3.37)	W×PPG	-0.028^* (-1.89)	0.001 (0.14)	-0.022 (-0.95)	0.002 (0.07)
PPG	0.051^*** (3.77)	-0.015^*** (-3.20)	0.055^*** (4.38)	0.057^*** (4.23)	rho	0.211^*** (3.42)	-0.044 (-0.58)	0.168^*** (2.87)	0.070 (1.08)
R²	0.748	0.933	0.645	0.517	Obs	493	493	493	493
LogL	451.898	682.340	357.587	338.463

Spatio-temporal evolution and its influencing factors of China's agricultural competitiveness

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变量	直接效应	间接效应	总效应	变量	直接效应	间接效应	总效应
PCI	0.313^*** (6.17)	0.308^*** (2.58)	0.621^*** (4.49)	RDI	0.108^*** (5.73)	0.370^*** (5.95)	0.478^*** (7.17)
RCL	0.235^*** (3.37)	-0.312 (-0.74)	-0.077^*** (-4.96)	GSR	-0.059^*** (-9.46)	-0.062^*** (-5.50)	-0.121^*** (-14.42)
EDL	0.103^* (1.84)	0.003^*** (5.81)	0.125^*** (5.20)	PPG	-0.012^*** (-3.13)	0.001 (0.22)	-0.011^*** (-3.78)

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