Impacts of Land Fragmentation and Cropping System on the Productivity and Efficiency of Grain Producers in the North China Plain: Taking Cangxian County of Hebei Province as an Example

Xue WANG; Xiubin LI

doi:10.5814/j.issn.1674-764x.2020.06.005

Journal of Resources and Ecology, Volume. 11, Issue 6, 580(2020)

Impacts of Land Fragmentation and Cropping System on the Productivity and Efficiency of Grain Producers in the North China Plain: Taking Cangxian County of Hebei Province as an Example

Xue WANG^1、* and Xiubin LI^1,2

Author Affiliations

¹Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

²College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China

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Figures & Tables(5)

Fig. 1. Location of the case study area

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Fig. 2. Description of the technical efficiency (TE)

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Table 1.
Summary statistics of variables

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Table 1.
Summary statistics of variables

Variable	Description	Mean	S.D.	Min.	Max.
Grain output	Per hectare grain output of the household (kg ha^-1)	7371.00	3701.68	750.00	20250.00
Labor	Per hectare input of family labor (person-day ha^-1)	31.80	19.83	3.00	123.96
Seed	Per hectare cost of seed (yuan ha^-1)	1437.42	790.62	197.37	6800.00
Machinery	Per hectare cost of machinery (yuan ha^-1)	3340.38	766.44	900.00	4986.67
Fertilizer	Per hectare cost of fertilizer (yuan ha^-1)	4121.32	1572.53	900.00	10016.13
Pesticide	Per hectare cost of pesticide (yuan ha^-1)	209.51	231.46	6.00	2000.00
Irrigation	Per hectare cost of irrigation (yuan ha^-1)	518.39	484.88	30.00	3290.00
Irrigation users	Dummy (1=Used irrigation, 0=No)	0.73	0.45	0.00	1.00
Average_size	Total agricultural land area divided by number of plots (ha)	0.16	0.06	0.05	0.40
MCI	Multiple cropping index	1.55	0.37	1.00	2.00
Qland	Average quality of farmland weighted by area	2.01	0.68	1.00	4.00
Age	Age of household head (year)	56.92	10.55	24.00	87.00
Education	Education status of the household head (1=illiterate; 2=primary school; 3=junior middle school; 4=senior middle school; 5=college or above)	2.29	0.79	1.00	5.00
Ragrilabor	Ratio of agricultural labor to family size	0.49	0.25	0.10	1.00
Routlabor	Ratio of off-farm labor to total labor	0.35	0.28	0.00	0.83
Aincome	Average income per off-farm labor (×10⁴ yuan person^-1 yr^-1)	1.24	0.86	0.00	4.56

Table 2.
Parameter estimation results for the Cobb-Douglas production frontier and technical inefficiency models

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Table 2.
Parameter estimation results for the Cobb-Douglas production frontier and technical inefficiency models

Variables	Model 1		Model 2		Model 3		Model 4
Production frontier	Coef.	Std. Err.	Coef.	Std. Err.	Coef.	Std. Err.	Coef.	Std. Err.
ln(Labor)	0.197^***	0.040	0.213^***	0.039	0.167^***	0.042	0.175^***	0.041
ln(Seed)	0.122^***	0.032	0.128^***	0.031	0.098^***	0.030	0.104^***	0.029
ln(Machinery)	0.108	0.166	-0.107	0.161	-0.069	0.170	-0.090	0.167
ln(Fertilizer)	0.077	0.047	0.052	0.047	0.074	0.046	0.057	0.045
ln(Pesticide)	-0.020^**	0.009	-0.015^*	0.008	-0.018^**	0.004	-0.015^**	0.007
ln(Irrigation)	0.009^**	0.004	0.009^**	0.004	0.008^***	0.004	0.007^*	0.004
Average_size	-	-	0.926^***	0.224	-	-	0.757^***	0.225
MCI	-	-	-	-	0.241^***	0.052	0.229^***	0.051
Constant	7.120^***	0.450	7.012^***	0.409	7.363^***	0.441	7.326^***	0.429
Inefficiency predictors
Age	0.005^**	0.002	0.007^*	0.004	0.007^*	0.004	0.011	0.008
Education	-0.003	0.027	0.002	0.038	0.006	0.039	0.016	0.058
Ragrilabor	0.128	0.152	0.159	0.215	0.185	0.228	0.226	0.065
Routlabor	0.219^*	0.115	0.281^*	0.140	0.308^*	0.305	0.148	0.371
Aincome	-0.029	0.026	-0.024	0.035	-0.040	0.039	-0.034	0.055
Qland	0.150^***	0.038	0.195^***	0.068	0.211^***	0.075	0.283^**	0.137
Average_size	-1.521^***	0.493	-	-	-1.916^***	0.776	-	-
MCI	-0.293^***	0.092	-0.381^***	0.150	-	-	-	-
Constant	0.275	0.271	-0.276	0.493	-0.613	0.564	-1.638	1.246
Model diagnostics
${{\sigma }^{2}}=\sigma _{\mu }^{2}+\sigma _{v}^{2}$	0.077^***	0.016	0.100^***	0.032	0.107^***	0.035	0.148^**	0.071
$\gamma =\sigma _{\mu }^{2}/(\sigma _{\mu }^{2}+\sigma _{v}^{2})$	0.815^***	0.062	0.834^***	0.053	0.862^***	0.049	0.887^***	0.049
H0: No inefficiency component (Prob. ≤ z):
	0.000		0.000		0.000		0.000
Total number of observations	350		350		350		350

Table 3.
Technical efficiency (TE) scores
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Table 3.
Technical efficiency (TE) scores
Variables Model 1 Model 2 Model 3 Model 4
Mean 0.737 0.778 0.776 0.802
S. D. 0.135 0.128 0.130 0.124
Min. 0.330 0.352 0.369 0.352
Max. 0.965 0.967 0.966 0.967

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Xue WANG, Xiubin LI. Impacts of Land Fragmentation and Cropping System on the Productivity and Efficiency of Grain Producers in the North China Plain: Taking Cangxian County of Hebei Province as an Example[J]. Journal of Resources and Ecology, 2020, 11(6): 580

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Paper Information

Received: May. 11, 2020

Accepted: Jul. 30, 2020

Published Online: Apr. 23, 2021

The Author Email: WANG Xue (wangxue@igsnrr.ac.cn)

DOI:10.5814/j.issn.1674-764x.2020.06.005

Topics

Resource Economy

Research Articles

Table 1. Summary statistics of variables

Table 1. Summary statistics of variables

Table 2. Parameter estimation results for the Cobb-Douglas production frontier and technical inefficiency models

Table 2. Parameter estimation results for the Cobb-Douglas production frontier and technical inefficiency models

Table 3. Technical efficiency (TE) scores

Table 3. Technical efficiency (TE) scores

Table 1.
Summary statistics of variables

Table 1.
Summary statistics of variables

Table 2.
Parameter estimation results for the Cobb-Douglas production frontier and technical inefficiency models

Table 2.
Parameter estimation results for the Cobb-Douglas production frontier and technical inefficiency models

Table 3.
Technical efficiency (TE) scores

Table 3.
Technical efficiency (TE) scores