Open Journal of Social Sciences, 2014, 2, 25-29
Published Online July 2014 in SciRes. http://www.scirp.org/journal/jss
http://dx.doi.org/10.4236/jss.2014.27005
How to cite this paper: Zhang, L. and Wang, Y.H. (2014) Study on the Effects of Economic Growth to Farmland Conversion
in China. Open Journal of Social Sciences, 2, 25-29. http://dx.doi.org/10.4236/jss.2014.27005
Study on the Effects of Economic Growth to
Farmland Conversion in China
Li Zhang1, Yonghui Wang2
1School of Economics and Management Engineering, Beijing University of Civil Engineer and Architecture,
Beijing, China
2The Center for Housing Industrialization, Ministry of Housing and Urban-Rural Development of the People’s
Republic of China, Beijing, China
Received May 2014
Abstract
With the rapid development of Chinese economy and acceleration of urbanization, farmland con-
version trend is inevitable. In order to analyze the effects of economic growth to farmland conver-
sion in China, the author chooses the data of building occupied land area, per capita gross domes-
tic product, industrial structure, input-output ratio , consumption growth rate and urban and rural
income ratio and establishes a set of regression model with the aid of SPSS softw are . From the re-
sult of the model analysis, we can conclude that the impact of economic growth on farmland con-
version appears the inverted U curve. The rise of third industry and urban residents’ income will
stimulate the demand for farmland.
Keywords
Economic Growth, Farmland Conversion, Econometric Analysis
1. Introduction
Farmland conversion means to change farmland use and become the construction land of city residential, indus-
trial, service industry and infrastructure. With the rapid development of Chinese economy and acceleration of
urbanization, farmland conversion trend is inevitable. From 2004 to 2011, the area of land expropriation in-
creased from 196,000 hectares to 569,000 hectares, average annual growth of about 15%. Farmland conversion
improves the living level of millions of farmers, promotes the rapid development of industry, and makes a large
contribution to the economic development. But with the increase of population, the per capita arable land has
been from 1.59 acres in 1996 dropped to 1.35 acres in 2012, decreased by 15%. The contradiction between pop-
ulation and land became more and more glaring. In the new era of global sustainable development, protection of
cultivated land has become the primary task for the sustainable development of China’s land. Therefore, it is
necessary to strengthen the quantitative research on the problems of farmland conversion, find out the driving
force and influence factors of farmland conversion and set up the new mechanism of farmland conversion.

L. Zhang, Y. H. Wang
26
2. Select the Economic Growth Index
Since the reform and open policy in China, each economic indicator rate of rise has occupied the world leader,
economic output and economic quality ad the huge promotion. Economic growth emphasizes the raise of total
economic output, the expansion of economic scale, the growth of production efficiency, the increase of wealth
and the improvement of living standards. To measure the economic growth indicators include the index of eco-
nomic output and the index of economic structure. According to the study purpose and data characteristics, this
paper selects the following indicators to analyze the driving effects of economic growth to farmland conversion
through establishing econometric model.
2.1. Per Capita Gross Domestic Product
Gross domestic product is an aggregative indicator which reflects the level of socioeconomic development of a
country or a region. The per capita GDP reflects a nation’s economic strength. This paper selects per capita GDP
(X) to analyze the impact of Chinese economy to farmland conversion. In order to exclude the impact of infla-
tion, we convert it to 1978 as the base period of constant prices.
2.2. Industrial Struct ur e
In China, three industry contribution rate of GDP is from 41.6:41:17.3 in 1990 to 5.7:48.7:45.6 in 2012. The
pulling effect of first industry to GDP decreased gradually, and the pulling effect of third industry to GDP fast
rise. At present, second and third industries have become the core strength in Chinese economic growth. There-
fore, this paper selects the proportion of second industrial added value to GDP (C1) and the proportion of the
third industrial added value to GDP (C2), to analyze the influence of industrial structure to farmland conversion.
2.3. Input-Output Ratio
Input -output level is an important index to reflect the development of a dynamic economy, used to measure the
economic benefit of investment. This paper selects the proportion of fixed-asset investment to GDP (C3) to ana-
lyze the influence of input-output level to farmland conversion.
2.4. Consumption Growth Rate
The consumption level is the scale and level of domestic consumption and services. This paper selects the
growth rate of total retail sales of consumer goods (C4) to analyze the influence of consumption level to farm-
land conversion.
2.5. Urban and Rural Income Ratio
With the rapid economic growth, the income level of residents has been greatly improved, and the urban-rural
income gap is expanding. This paper selects the ratio of urban residents’ disposable income to rural households’
net income (C5) to analyze the influence of urban and rural income level to farmland conversion.
3. Econometric Analysis of Economic Growth to Farmland Conversion
3.1. Data Collecti on
This article collected building occupied land area and various economic indicators from the “China Land
Resources Statistics Yearbook” and “Chinese Statistical Yearbook” (see Table 1).
3.2. Model Construction
According to the classic environmental Kuznets curve, ref ers to the income and trade model and income, institu-
tional and policy model, this paper construct s the following multiple model set, as in [1]-[6]:
23
12 3
() ()LnYLnX LnXLnX αβ ββε =+++ +
23
123 4
() ()
i
LnYLnXLnXLnXC LnX αβ βββε =++++ +

L. Zhang, Y. H. Wang
27
Table 1. Basic data of economic growth and farmland conversion (from 1999 to 2011).
Yea r
Farmland
conversion area
(Hectare)
Per capita
GDP
(Yuan)
The rate of second
industry to GDP
(%)
The rate of third
industry to GDP
(%)
Input output
ratio
(%)
Consumption
growth rate
(%)
Urban and
rural income ratio
(%)
Y X C1 C2 C3 C4 C5
1999 60355.59 2039.20 45.76 37.77 33.29 6.80 2.65
2000 93583.74 2193.98 46.21 36.23 33.18 9.70 2.79
2001 110180.18 2358.67 47.54 34. 17 33.94 1 0.10 2.90
2002 137836.95 2555.77 47.54 32. 77 36.15 1 1.80 3.11
2003 275481.34 2794.80 47.18 32. 86 40.91 9.10 3.23
2004 167400.30 3058.23 46.57 33. 57 44.08 1 3.30 3.21
2005 252958.39 3384.18 46.57 33. 72 48.00 1 4.88 3.22
2006 288052.26 3792.09 43.45 34. 76 50.85 1 5.79 3.28
2007 274365.52 4306.37 41.79 33. 69 51.66 1 8.23 3.33
2008 270185.75 4697.13 41.34 31. 54 55.03 2 2.72 3.31
2009 413793.10 5104.67 42.83 32. 06 65.88 1 5.54 3.33
2010 374934.98 5610.56 43.79 30. 51 62.68 1 8.33 3.23
2011 410538.55 6103.11 43.55 29. 64 65.84 1 7.15 3.13
2
124 5
()
ii
LnYLnXLnXC LnXC αββββ ε =+ ++++
3
134 5
() ii LnYLnXLnXC LnXC αββββ ε =+ ++++
14 5ii
LnYLnXC LnXC αβββ ε =+ +++
With the aid of SPSS software, this paper establishes a set of regression model. Through goodness of fit test,
variable significant test, equation significant test, hetero ske dasticit y test, serial correlation test, multicollinearity
test and so on, we choose the optimal model as follows:
1) Model of per capita GDP and farmland conversion area
Model I:
2
102.919 26.7671.548()LnYLnX LnX=−+ −
(2.72)(2.884) (2.723)−−
20.881 45.4422.313R FDW= ==
2) Model of industrial structure and farmland conversion area
Model II:
()
2
1
126.535 32.9721.8850.012LnYLnXLnXC LnX=−+ −−
( )( )()
2.872.992.883( 2.034)− −−
2
0.881 30.8582.81R FDW= ==
Model III:
()
2
2
96.996 25.1591.5270.017LnYLnXLnXC LnX=−+ −+
()( )()
2.9033.0673.055(2.982)−−

L. Zhang, Y. H. Wang
28
2
0.908 40.47 2.701RF DW= ==
3) Model of input-output ratio and farmland conversion area
Model IV:
33
12.094 2.820.4260.048LnYLnXCCLnX=−++ −
()()( )
1.3812.4032.350( 2.337)−−
2
0.85725.067 1.927R FDW= ==
4) Model of consumption growth rate and farmland conversion area
Model V:
24
150.280 37.7892.171()0.008LnYLnXLnXC LnX=−+ −−
()( )()
5.015.1934.946( 3.373)− −−
20.942 65.5232.725R FDW= ==
5) Model of urban and rural income ratio
Model VI:
25
6.33 0.027()0.161LnYLnXCLnX=++
( )( )()
10.579 3.609 2.355
2
0.905 58.4152.447
RF DW= ==
4. Conclusions
4.1. Effect of Total Economic Output to Farmland Conversion
From Model, we can find that the impact of economic growth on farmland conversion appeared the inverted U
curve . On early stage of economic growth, farmland conversion speed along with the improvement of per capita
GDP rapid increase. When economic growth reaches a certain level, people pay more and more attention to the
protection of land resources, farmland conversion rate will be decreased. According to the principle of extreme
values of derivative, when per capita GDP is 5500 Yuan, farmland conversion growth rate reached a maximum
value. So after 2011, protection of land resources will be gradually strengthen, farmland conversion speed will
be gradually slow down, the quality of farmland conversion will be optimized. Finally, we will realize the sus-
tainable development of society, economy and environment.
4.2. Effect of Economic Structure to Farmland Conversion
In order to analyze the impact of individual variables on land resources loss under fixing other control variables,
we calculate a derivative of logarithm of farmland conversion regression equation.
The formula is：
i
LnY
C
∂
∂
We can calculate the marginal change of farmland conversion (see Table 2).
1) Effect of industrial structure to farmland conversion
To some extent, up grading industrializa tion level will alleviate the speed of farmland conversion growth.
At first, the rise of third industry will stimulate the demand for farmland. In the future, when the develop-
ment of third industry entered the mature stage, it will gradually reduce the demand for farmland.
2) Effect of input-output ratio to farmland conversion
Although from 1999 to 2011, fixed asset investment maintained rapid growth, because of investment
structure optimization, it gradually reduces the demand for farmland.
3) Effect of consumption growth rate to farmland conversion

L. Zhang, Y. H. Wang
29
Table 2. The marginal change of farmland conversion.
Yea r
The rate of second
industry to GDP
The rate of third industry to
GDP
Input output
ratio
Consumption growth
rate
Urban and rural income
ratio
C1 C2 C3 C4 C5
−0.09144 0.129545 0.060225 −0.06096 1.22687
−0.09232 0.130789 0.056713 −0.06155 1.238649
−0.09319 0.13202 0.053239 −0.06 213 1.250302
−0.09415 0.133384 0.049386 −0.06277 1.263224
−0.09523 0.134904 0.045095 −0.06348 1.277618
−0.09631 0.136435 0.040771 −0.0642 1.29212
−0.09752 0.138157 0.035910 −0.06501 1.308426
−0.09889 0.140091 0.030447 −0.06593 1.326748
−0.10041 0.142253 0.024343 −0.06694 1.347224
−0.10146 0.14373 0.020174 −0.06 764 1.361208
−0.10245 0.145144 0.016180 −0.0683 1.374604
−0.10359 0.146751 0.011644 −0.06906 1.389817
−0.1046 0.148181 0.007605 −0.06973 1.403365
The effect of consumption growth rate to farmland conversion is very little. With the development of
economy, people’s actual consumption level has been greatly improved, consumption structure has also
changed, but from 1999 to 2011, the improvement of people’s consumption level did not increase the de-
mand for farmland.
4) Effect of urban and rural income ratio to farmland conversion
Because the income of urban residents increases more and more quickly, there is a great income gap be-
tween urban residents and rural residents. The increasing income of urban residents stimulates the demand for
farmland, so more and more farmland change into construction land.
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