【免费】论文研究-基于DEA-Malmquist指数的玉米生产效率分析：以河南省为例_DEA-Malmquist

DEA-Malmquist指数法

惠普过滤器方法

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Journal of Agricultural Chemistry and Environment, 2018, 7, 176-187

http://www.scirp.org/journal/jacen

ISSN Online: 2325-744X

ISSN Print: 2325-7458

DOI:

10.4236/jacen.2018.74015 Nov. 28, 2018 176 Journal of Agricultural Chemistry and Environment

Analysis of Maize Production Efficiency Based

on DEA-Malmquist Indexes: A Case Study of

Henan Province

Bingjun Li, Xiaoxiao Zhu

College of Information and Management Science, Henan Agricultural University, Zhengzhou, China

Abstract

In order to improve the production efficiency of maize in Henan, China, the

HP (High-Pass) filter method is used to obtain the maize trend yield. Se-

condly, the Malmquist index method is used to analyze the changes of

TFP

(Total Factor Productivity) of maize in 18 cities in Henan Province in the past

11 years. Finally, the amount of slack in maize input and output is analyzed

The results show that the research and development level of advanced tech-

nology of maize production in Henan Province has been improved to some

extent in recent years; the advanced technology in various regions has not

been fully promoted and utilized;

there is a certain degree of relaxation in the

input of various elements of maize;

the resource allocation is unreasonable,

and there is a certain amount of space for saving.

Keywords

DEA-Malmquist Index Method, HP Filter Method, Henan Province, Maize

1. Introduction

Henan Province is located in the center of Huang-Huai Maize dominant indus-

trial belt, and its light and heat resources are abundant, forming the cultivation

system of wheat and maize cropping twice a year. Located in the continental

monsoon climate zone, Henan Province is an important grain producing area in

China. The summer maize planting area and output account for about 10% of

the country, but the summer maize yield is high and unstable. As a big grain

planting province, Henan planted 3316.86 thousand hectares of maize in 2016,

with a total yield of 17.5297 million tons. In fact, the yield per unit area of maize

in Henan Province is 5638 kg/ha in 2012 and decreased to 5285 kg/ha in 2016,

How to cite this paper:

Li, B.J. and Zhu,

.X. (2018)

Analysis of Maize Production

Efficiency Based on DEA

-Malmquist In-

dexes: A Case Study of Henan Province.

Journal of Agricultural Chemistry and

Environment

, 176-187.

https://doi.org/10.4236/jacen.2018.74015

Received:

October 29, 2018

Accepted:

November 25, 2018

Published:

November 28, 2018

8 by authors and

Scientific

Research Publishing Inc.

This work is licensed under the Creative

Commons Attribution International

License (CC BY

4.0).

http://creativecommons.org/licenses/by/4.0/

Open Access

B. J. Li, X. X. Zhu

DOI:

10.4236/jacen.2018.74015 177 Journal of Agricultural Chemistry and Environment

while the planting area of maize in 2012 is 3100 thousand hectares, and by 2016

it had increased to 3316.86 thousand hectares. The input of other controllable

elements is also in the state of growth; the input gradually increases and the

output decreases, which indicates that the production efficiency of maize in He-

nan Province is low, so it is necessary to adjust the input of production factors to

increase the yield of maize.

Data Envelopment Analysis (DEA), Malmquist Index Method, Stochastic

Frontier Analysis (SFA), and DEA-Tobit models are widely used in productivity

studies in the agricultural sector. Many scholars have studied the production ef-

ficiency of maize, and most scholars’ research mainly concentrates on the above

methods to study the maize production efficiency in the country or in some

provinces and cities, mainly the following parts.

For the study of maize production efficiency in China: Yang Guoqing

et al.

[1]

used the Malmquist index analysis method in DEA to analyze the growth of ma-

ize production efficiency in China’s main maize producing areas from the pers-

pective of time gradient and regional difference. Yan Yijun

et al.

[2] used the

stochastic frontier analysis (SFA) method to calculate the maize production effi-

ciency in 20 provinces and regions of China, and analyzed the output elasticity

of each input factor. Wang Jun

et al.

[3] analyzed the total factor productivity of

maize production in China’s core producing areas from 2001 to 2008 using Sto-

chastic Frontier Analysis (SFA) method. Liu Nian

et al.

[4] used the DEA-Malmquist

index method to measure the total factor productivity (TFP) of China’s maize

from 2002 to 2013. Based on DEA model, Malmquist index method and ESDA

analysis method, Zhang Lina

et al.

[5] analyzed the temporal and spatial charac-

teristics of the change of comprehensive technical efficiency and total factor

productivity of maize production in 20 major maize provinces (regions) of Chi-

na from 2005 to 2015.

Studies on maize production efficiency in individual provinces and cities:

Huang Yong [6] decomposed the Malmquist index and analyzed the internal

driving force of agricultural total factor productivity growth in Hubei Province.

Wang Zhidan

et al.

[7] used DEA-Malmquist index method to analyze the total

factor productivity (TFP) of maize and its composition change in Xinmin City,

Shenyang, Liaoning Province from 2013 to 2014 from the overall situation, dif-

ferent regions and different scale levels and analyzed the investment optimiza-

tion direction of maize production factors. Jiang Yubo

et al.

[8] took the modern

agricultural machinery cooperative in the core maize producing area of Heilong-

jiang Province as the research object and used the data envelopment analysis to

analyze the influencing factors of the typical samples production efficiency. Us-

ing the method of data envelopment analysis, Jiang Xiusheng

et al.

[9] analyzed

the technical efficiency of spring maize production in five main spring maize

production areas in North China from 2006 to 2014. Yang Chun

et al.

[10] used

DEA to analyze the production efficiency and inpu-output slack of Shanxi maize

from 1978 to 2011. Chen Suqiong

et al.

[11] analyzed the technical efficiency of

maize production of different types of labor transfer farmers in Liaoning Prov-

B. J. Li, X. X. Zhu

DOI:

10.4236/jacen.2018.74015 178 Journal of Agricultural Chemistry and Environment

ince. The results showed that there is no significant difference in the technical

efficiency of maize production among different types of labor transfer farmers.

Taking the three counties of Ganzhou, Linze and Gaotai in Zhangye City as ex-

amples, the DEA-Tobit model is used to analyze the production efficiency and

influencing factors of different types of farmers field maize [12]. On the basis of

using DEA to measure the production efficiency, Yang Xiao

et al.

improved the

simulation of redundant input elements based on the calculation results. On the

basis of using DEA to measure the production efficiency, Yang Xiao

et al.

[13]

improved the redundant input elements based on the calculation results. Qian

Jinxia [14] used maize per unit yield and meteorological data from 39 counties

(cities) in Shanxi Province from 1991 to 2000 to analyze the regional distribution

characteristics of maize climate resource utilization efficiency and maize climate

resource utilization efficiency in Shanxi Province. Liu Xiaoying

et al.

[15] stu-

died the utilization efficiency of light and heat resources of winter wheat and

summer maize in northern Henan. Wang Xueqiu [16] used correlation analysis

to analyze the relationship between the scale of maize management and produc-

tion efficiency in Jilin Province.

The above scholars have used the actual production as the output index of

maize, and the actual production of maize is affected by other factors, the actual

yield could not be used as the exact output corresponding to the input of each

element of maize. The analysis using actual production does not accurately re-

flect maize production efficiency. In this paper, the HP filter method is used to

process the yield data of maize, and the trend yield is obtained as the output in-

dex of maize. The Malmquist index method of DEA is used to study the growth

of maize TFP in 2006-2016 in various cities of Henan Province. The change of

total factor productivity of maize is decomposed into technical efficiency and

technological progress, and further decomposed into pure technical efficiency,

scale efficiency and technological progress. Then the influence of efficiency

change is analyzed concretely.

2. Theory and Method

2.1. DEA-Malmquist Index Method

Data Envelopment Analysis (DEA) is first proposed by A.Charnes and W. W.

Cooper [17] in the United States in 1978. The DEA model can be divided into

CCR model and BCC model. It is a systematic analysis method for the relative

effectiveness or benefit evaluation of the same type of units (departments) based

on multiple indicator inputs and multiple indicator outputs and the concept of

“relative efficiency”.

The Malmquist productivity index is first proposed by Swedish economist and

statistician Malmquist (1953) and can be used to investigate the variation of

production efficiency in different periods. The nonparametric Malmquist expo-

nent method based on data envelopment analysis defines the Malmquist expo-

nent by the distance function (distance function) and calculates the total factor

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