Spatial analysis of factors affecting fertilizer use efficiency in China: an empirical study based on geographical weighted regression model

Author(s):  
Xiuguang Bai ◽  
Tianwen Zhang ◽  
Shujuan Tian ◽  
Yanan Wang
Author(s):  
Xiuguang Bai ◽  
Tianwen Zhang ◽  
Shujuan Tian

Improving fertilizer use efficiency (FUE) is an effective means to reduce fertilizer use and environmental contamination. Few studies have considered the spatial effects of FUE and its determinants. This paper calculated the FUE of agricultural production by adopting panel data on 31 provinces in China from 2007 to 2017 using a stochastic frontier method with a heteroscedastic inefficiency term, and discussed the spatial characteristics. Further, the geographical weighted regression model (GWR) was employed to examine the spatial impact of factors on FUE and revealed the spatial dispersion and agglomeration effect. The results show that averaged FUE in China was 0.722, and had a significantly decreasing trend with a significant regional difference and spatial positive correlation in different provinces. The non-agricultural employment ratio was the leading factor for increasing FUE, and its degree of influence showed a decreasing trend from eastern to western China. The different agricultural industry development modes, crop planting patterns adjustment, labor transfer, and policy incentive systems for increasing the non-agricultural employment ratio should be developed for different regions. Farmers’ income had a negative impact on FUE, but the influence degree decreased annually. Education level had a negative impact on FUE and was relatively weak, but the influence degree was increasing. This should strengthen the exploration of a scientific and practical technical training system for farmers on fertilizer use while improving educational levels in different regions on the basis of local characteristics. The impact of disasters on FUE depended on their severity, and a combined weather and disaster forecasting mechanism should be developed.


2017 ◽  
Vol 81 (6) ◽  
pp. 1401-1412 ◽  
Author(s):  
K. F. Bronson ◽  
D. J. Hunsaker ◽  
J. Mon ◽  
P. Andrade-Sanchez ◽  
J. W. White ◽  
...  

2019 ◽  
Vol 53 (2) ◽  
pp. 127-133
Author(s):  
Eiichi KUSANO ◽  
Changbin YIN ◽  
Hsiaoping CHIEN

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