<trans-title>Characteristics of change and influencing factors of the technical efficiency of chemical fertilizer use for agricultural production in China</trans-title>

Pingping WANG; Yijun HAN; Yi ZHANG

doi:10.18402/resci.2020.09.11

Resources Science, Volume. 42, Issue 9, 1764(2020)

Characteristics of change and influencing factors of the technical efficiency of chemical fertilizer use for agricultural production in China

Pingping WANG¹, Yijun HAN², and Yi ZHANG^3、*

Author Affiliations

¹National School of Development, Peking University, Beijing 100871, China

²College of Economics and Management, China Agricultural University, Beijing 100083, China

³Institute of Scientific and Technical Information, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China

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Figures & Tables(10)

Fig. 1. China’s agricultural chemical fertilizer use technical efficiency and its average annual growth rate, 1991-2017

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Fig. 2. Technical efficiency of chemical fertilizer in different periods for various regions

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Fig. 3. Kernel density estimation of China’s agricultural chemical fertilizer use technical efficiency

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Table 1. The statistics of China's agricultural production input and output, 1991-2017

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Table 1. The statistics of China's agricultural production input and output, 1991-2017

	农业产出水平年度均值		农业投入产出的年均增长率/%
	1991	2017	1991—1997	1998—2014	2015—2017
农业总产值/亿元	113.57	440.50	7.19	4.79	3.32
劳动投入/万人	1211.90	932.70	-0.15	-1.01	-0.19
土地投入/千hm²	5304.81	5906.00	0.39	0.06	-1.40
化肥投入/万t	99.62	207.20	6.14	2.42	-1.63
机械投入/万kW	1042.97	3488.90	4.86	5.30	-2.43

Table 2. Tests of efficiency measurement model

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Table 2. Tests of efficiency measurement model

模型	Null hypothesis	log likelihood	LR test	${χ^{2}}_{0.05} (q + 1)$	结果
C-D函数	$β_{6}, \dots, β_{20} = 0$	780.35	504.32	26.30	拒绝
技术无进步	$β_{5}, β_{10}, β_{17}, \dots, β_{20}$	885.79	293.45	12.59	拒绝
技术非中性	$β_{17}, \dots, β_{20}$	1002.39	60.25	9.49	拒绝
时不变模型	$η$	588.26	888.51	5.99	拒绝

Table 3. Results of stochastic frontier function estimation

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Table 3. Results of stochastic frontier function estimation

变量	系数	标准误	变量	系数	标准误
常数项	2.517***	0.934	$\ln S \ln L$	0.185***	0.055
$\ln S$	0.198	0.174	$\ln S \ln F$	0.243***	0.040
$\ln C$	-0.014	0.170	$\ln L \ln C$	0.131***	0.049
$\ln L$	-0.585*	0.308	$\ln F \ln C$	-0.003	0.031
ln F	0.627***	0.173	$\ln L \ln F$	-0.210***	0.032
$T$	0.106***	0.010	$T \ln S$	-0.003	0.003
${(\ln S)}^{2}$	0.081***	0.030	$T \ln C$	0.001	0.002
${(\ln C)}^{2}$	0.031	0.020	$T \ln L$	-0.012***	0.003
${(\ln L)}^{2}$	-0.018	0.046	$T \ln F$	0.015***	0.002
${(\ln F)}^{2}$	-0.053***	0.016	$η$	-0.010***	0.001
$T^{2}$	-0.001***	0.000	$σ^{2}$	-0.956**	0.475
$\ln S \ln C$	-0.220***	0.037	log likelihood	1032.515

Table 4. Moran’s I index of chemical fertilizer use technical efficiency, 1991-2017

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Table 4. Moran’s I index of chemical fertilizer use technical efficiency, 1991-2017

年份	Moran’s I	P值	年份	Moran’s I	P值
1991	0.159	0.090	2005	0.197	0.051
1992	0.168	0.077	2006	0.190	0.058
1993	0.161	0.089	2007	0.207	0.042
1994	0.173	0.072	2008	0.206	0.043
1995	0.178	0.064	2009	0.209	0.041
1996	0.184	0.057	2010	0.190	0.058
1997	0.193	0.049	2011	0.192	0.057
1998	0.203	0.041	2012	0.223	0.031
1999	0.202	0.043	2013	0.223	0.031
2000	0.193	0.052	2014	0.219	0.034
2001	0.200	0.045	2015	0.225	0.030
2002	0.203	0.044	2016	0.231	0.027
2003	0.200	0.047	2017	0.246	0.020
2004	0.200	0.047

Table 5. Three spatial regression models

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Table 5. Three spatial regression models

变量	SAR	SEM	SDM
ln(Income)	-0.253***	-0.247***	-0.262***
	(0.030)	(0.030)	(0.030)
ln(Trlabor)	-0.387***	-0.369***	-0.374***
	(0.027)	(0.025)	(0.030)
ln(Pdisa)	0.002	0.003	0.002
	(0.007)	(0.007)	(0.007)
ln(Irrig)	0.314***	0.317***	0.277***
	(0.031)	(0.030)	(0.032)
ln(Citizen)	0.024***	0.022***	0.003
	(0.008)	(0.008)	(0.009)
ln(Struc)	0.106**	0.103**	0.088*
	(0.048)	(0.046)	(0.053)
ln(Rain)	-0.016	-0.017	-0.015
	(0.014)	(0.014)	(0.015)
ln(Temp)	0.054*	0.047	0.046
	(0.030)	(0.030)	(0.031)
w×ln(Income)			0.113**
			(0.056)
w×ln(Trlabor)			-0.078
			(0.061)
w×ln(Pdisa)			-0.002
			(0.013)
w×ln(Irrig)			0.088
			(0.069)
w×ln(Citizen)			-0.078***
			(0.020)
w×ln(Struc)			0.133
			(0.110)
w×ln(Rain)			-0.006
			(0.023)
w×ln(Temp)			-0.013
			(0.057)
rho	-0.152***		-0.146**
	(0.051)		(0.057)
lambda		-0.164***
		(0.057)
log likelihood	735.040	734.855	748.127
R²	0.157	0.157	0.186

Table 6. Regression results of the spatial Dubin model

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Table 6. Regression results of the spatial Dubin model

变量	总体	1991—1997	1998—2014	2015—2017	东部	中部	西部
ln(Income)	-0.262***	0.109	-0.053**	-0.084**	-0.288***	0.201***	-0.175***
	(0.030)	(0.098)	(0.024)	(0.038)	(0.047)	(0.077)	(0.026)
ln(Trlabor)	-0.374***	-0.659***	-0.301***	0.196	-0.318***	-0.902***	-0.429***
	(0.030)	(0.091)	(0.030)	(0.135)	(0.067)	(0.065)	(0.030)
ln(Pdisa)	0.002	-0.019	0.002	0.003	0.002	0.000	-0.028***
	(0.007)	(0.015)	(0.004)	(0.003)	(0.008)	(0.013)	(0.008)
ln(Irrig)	0.277***	0.568***	0.026	0.342***	0.041	0.654***	0.040
	(0.032)	(0.126)	(0.025)	(0.032)	(0.053)	(0.049)	(0.040)
ln(Citizen)	0.003	0.010	0.005	0.014**	0.030***	-0.007	0.022**
	(0.009)	(0.018)	(0.006)	(0.007)	(0.010)	(0.011)	(0.010)
ln(Struc)	0.088*	0.472	0.079*	0.241***	-0.524***	-0.005	-0.319***
	(0.053)	(0.372)	(0.042)	(0.057)	(0.076)	(0.128)	(0.065)
ln(Rain)	-0.015	-0.018	0.008	0.048***	-0.048***	-0.043*	0.002
	(0.015)	(0.021)	(0.010)	(0.012)	(0.018)	(0.026)	(0.012)
ln(Temp)	0.046	0.084	-0.052**	-0.001	0.078	0.061	-0.021
	(0.031)	(0.054)	(0.021)	(0.106)	(0.075)	(0.059)	(0.019)
w×ln(Income)	0.113**	-0.423**	0.041	-0.081	0.658***	0.348***	-0.367***
	(0.056)	(0.166)	(0.044)	(0.086)	(0.048)	(0.105)	(0.055)
w×ln(Trlabor)	-0.078	0.216	-0.283***	0.415	-0.550***	0.337**	-0.468***
	(0.061)	(0.176)	(0.065)	(0.397)	(0.099)	(0.131)	(0.074)
w×ln(Pdisa)	-0.002	0.020	0.002	-0.005	0.012	0.042**	0.028**
	(0.013)	(0.032)	(0.009)	(0.010)	(0.012)	(0.017)	(0.014)
w×ln(Irrig)	0.088	-0.337	-0.091	0.056	-0.154*	0.367***	-0.090
	(0.069)	(0.290)	(0.058)	(0.118)	(0.081)	(0.076)	(0.089)
w×ln(Citizen)	-0.078***	0.020	-0.031**	0.014	0.019	-0.027	-0.011
	(0.020)	(0.046)	(0.014)	(0.018)	(0.015)	(0.017)	(0.024)
w×ln(Struc)	0.133	-0.077	-0.083	0.292**	0.363***	1.223***	-1.081***
	(0.110)	(0.703)	(0.087)	(0.123)	(0.103)	(0.321)	(0.137)
w×ln(Rain)	-0.006	0.020	-0.027*	0.103***	0.016	-0.031	-0.024
	(0.023)	(0.033)	(0.016)	(0.028)	(0.022)	(0.035)	(0.025)
w×ln(Temp)	-0.013	-0.009	0.021	0.251	0.070	-0.051	0.008
	(0.057)	(0.111)	(0.038)	(0.169)	(0.102)	(0.088)	(0.037)
rho	-0.146**	-0.130	0.109*	-0.120	0.109*	-0.319***	-0.304***
	(0.057)	(0.116)	(0.064)	(0.191)	(0.065)	(0.055)	(0.089)
log likelihood	748.1265	242.5672	794.9568	748.1265	337.1547	276.917	464.4569
R²	0.186	0.0032	0.181	0.31	0.2396	0.6648	0.3269

Table 7. Direct effect, indirect effect, and total effect of the Spatial Dubin Model

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Table 7. Direct effect, indirect effect, and total effect of the Spatial Dubin Model

	直接效应	间接效应	总效应
ln(Income)	-0.265***	0.138***	-0.127**
	(0.031)	(0.049)	(0.050)
ln(Translabor)	-0.375***	-0.021	-0.396***
	(0.030)	(0.052)	(0.045)
ln(Pdisa)	0.003	-0.003	0.000
	(0.007)	(0.012)	(0.012)
ln(Irrig)	0.276***	0.049	0.325***
	(0.031)	(0.066)	(0.068)
ln(Citizen)	0.005	-0.072***	-0.066***
	(0.008)	(0.018)	(0.023)
ln(Struc)	0.088	0.111	0.200**
	(0.054)	(0.105)	(0.087)
ln(Rain)	-0.015	-0.005	-0.020
	(0.015)	(0.021)	(0.020)
ln(Temp)	0.045	-0.016	0.029
	(0.030)	(0.055)	(0.051)

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Pingping WANG, Yijun HAN, Yi ZHANG. Characteristics of change and influencing factors of the technical efficiency of chemical fertilizer use for agricultural production in China[J]. Resources Science, 2020, 42(9): 1764

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Paper Information

Received: Oct. 15, 2019

Accepted: --

Published Online: Apr. 23, 2021

The Author Email: ZHANG Yi (zhangyihainan@163.com)

DOI:10.18402/resci.2020.09.11

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Resource Economy

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