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safeguarding the national food security, promoting farmers' income, improving labor
productivity and promoting rural development(Yang, 2005; Zhang and Gao, 2009).
Seeking an optimal path for Chinese agricultural mechanization to develop continuously
and steadily, we have to consider the volatility of field production mechanization
development as well as the potential ability to grow in the future. At present, there are few
researches on the volatility of field production mechanization development. The level of
mechanical sowing and mechanical harvesting reflect the characteristics of field production
mechanization in China from different aspects. Considering that the low level of mechanical
sowing and mechanical harvesting as the main factor that leads to the low overall level of
Chinese agricultural mechanization, this article uses Hodrick-Prescott (HP) technique and
GM (1, 1) model to analyse the volatility and growth trend of field production
mechanization in China from 1973 to 2008 aiming to get the volatility feature and
development potential and provide theoretical basis for promoting agricultural
mechanization and developing modern agriculture.
2. The analysis of volatility of field production mechanization level based on
HP technique
2.1 Research methods and data
As shown in Fig 1, the development of mechanical sowing and mechanical harvesting can
be summarized as “growth in volatility” or “reduction in volatility”. They are the interact
results of two factors: long-term trends and short-term volatility. At present, the main
methodologies that used to analyse the volatility measurement of economic problems are
velocity method, residual method and HP technique. Compared with velocity method and
residual method, HP technique possesses the characteristics of perfect theory, using flexible
use and better fitting effect. Considering the complexity of field production mechanization
in China (the coexistence of growth and volatility), this article selected HP technique to
measure the volatility.
Since Hodrick and Prescott (1981) used HP technique to analyse the economic cycle, this
method has been used in other fields. The basic principle of HP technique is: assuming that
time series
T
C
Y
is combined by trend components
Y
and volatility components
Y
and
then the time series is:
T
C
YYY
(t=1, 2, 3,…, T)
(1)
t
t
t
where t is the sample size.
HP filter method is to estimate the least value of the following formula:
2
T
T
T
T
T
T
T
2
(
YY
)
[(
Y
Y
)
(
Y Y
)]
(2)
t
t
t
1
t
t
t
1
t
1
t
1
where the parameter λ is the penalty factor controlling the smoothness. And this parameter
requires to be given in advance. The greater the parameter λ is, the smoother the estimate
trend line is, whereas the bender. For annual data, the parameter λ mainly has two kinds of
value, 100 and 6.25. When using 6.25 to filter, the trend line reflects the volatility more
meticulously, and it can reflect the large scale change, as well as smaller annual ups and
downs. Here, λ=6.25 is used in HP filtering analysis.
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