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Jun. 2007, Volume 6, No.6 (Serial No.48)
China-USA Business Review, ISSN1537-1514, USA
Analysis on economic growth variances and convergences
of county economy in China
XU Hong-fan
(School of Management, Wuhan University of Technology, Wuhan 430070, China)
Abstract: In this paper, the economic structure of county development in China is reflected in seven terms:
capital input, labor input, geographical position, industrial structure, and level of agricultural development, level
of urbanization and public expenditure with the method of cluster analysis, which categorizes Chinese counties
into three different area classifications according to the economic characteristics. The first classification of county
economic variance covers not only the  -divergence, but also the club convergence apparently. The second
classification covers the  -divergence, but not the club convergence. The third classification apparently covers
the  -divergence, yet the club convergence as well.
Key words: county economy; cluster analysis; panel data; growth convergence
1. Introduction
Various parts in China possessed variant accelerations of economic growth during the period of reform.
Especially since the 1990s, the variances have been significantly enlarged. Consequently, this type of disparity
among regions has begun to draw the attention of Chinese government, while the scholars both at home and
aboard also conducted investigations on this issue. CAI Fang and DU Yang (2000), SHEN Kun-rong & MA Jun
(2002), according to the geographical locations, divided China into three parts: the East, the Middle and the West,
to research on the issue of convergence conditionally. LIU Qiang (2001) discovered that the convergence system
emphasized by the new classical theory did not exist among provinces in China. LIN Yi-fu (2003) concluded that
what existed among provinces in China was not the absolute convergence, but the conditional convergence. XU
Xian-xiang (2004) researched on the economic growth in Chinese cities, discovering that the convergence systems
mentioned in both the new classical growth theory and the new modern growth theory coexisted on the aspect of
Chinese cities.
In all the existing documents on convergence, the researches are merely on the nations or regions (provincial
regions), neglecting the situations inside the subjects investigated. County economy, as a peculiar colony, is the
regional economy in the unit of administration, county, and possesses the prominent position in China. It is the
regional foundation and basic construction of the national economy. Whether county economy possesses variant
characteristics of economic growth from the aspects of nations and provincial regions has never occurred in any
scholar’s research so far. On the other hand, numerous documents simply divided China into three parts as the
East, the Middle, and the West when researching on regional convergence, which reveals several major problems.

This paper is supported by the Hunan Soft Science Research Program (No. 2007ZK3022).
XU Hong-fan, Ph.D. candidate of Department of Management Science and Engineering, School of Management, Wuhan
University of Technology; research field: regional economy.
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Analysis on economic growth variances and convergences of county economy in China
First, the division has not formed a unified standard. More importantly, this way of division does not show the
similarity of economic structure among the provinces and towns. Finally, the existing researches mostly employ
cross-section data whose estimate might be inaccurate, while the panel analysis is both consistent with the
conclusion of new classical growth theory and accurate in estimate. Based on these, the paper employs the cluster
analysis on the basis of panel data to categorize Chinese counties into variant area classifications according to
economic characteristics and research on the convergence effect of regional economic growth in Chinese counties.
2. Selection of specimens
According to the purpose of research, this paper employs the method of division to take the administrative
county as the basic regional unit. The administration of Chinese counties has diverse forms, including district,
town, county, autonomous county, special administrative region and forested area. The counties involved in this
paper do not include district, for it is generally a subdivision of prefecture-level city and its economic behavior is
essentially a type of urban economic behavior which is significantly variant from the economic behaviors of other
county administrative regions, therefore, they cannot be compared on the same aspect. And the counties involved
do include town, because under the present condition in China, most economic behaviors of towns are still
characterized by agricultural economic development, and are generally close to the connotation of county
economy investigated.
The source of all data employed in this paper is from Annals of County Economy in China, Annals of County
Social Economy in China and china-county.org.
3. Division of regions
According to CAI Fang (2000), XU He-lian and LAI Ming-yong (2003), the regional economic structure is
reflected in seven terms: capital input, labor input, geographical position, industrial structure, level of agricultural
development, level of urbanization and public expenditure.
Explaining variables include respectively: (1) X1 refers to “the proportion of output value of the primary
industry in GDP”, reflecting the influencing function of the agricultural development to the county economic
development in China; (2) X2 refers to “the proportion of output value of the secondary industry in GDP”,
reflecting the level of industrialization and the influencing function of the industrial structure transformation to the
county economic development in China; (3) X3 refers to the proportion of public expenditure in GDP, measuring
the degree that the government intervention influences county economic development; (4) X4 refers to the
investment rate which is the proportion of accomplished investment quota of society-wide permanent assets in
GDP, roughly reflecting the influence of capital input on the variance of county economy; (5) X5 refers to the
urbanization rate which is reflected by the proportion of the town population in the total population of the county,
measuring the significant role that the development of urbanization plays in county economic development; (6)
X6 refers to the employment rate which is the proportion of the sum of rural employed personnel and year-end
post-operating employed personnel in the total population, measuring the degree of county labor input and the
significant role; (7) D1 and D2 refer to the regional dummy variables (D1 stands for counties in the Middle when
set 1, with other counties set 0; D2 stands for counties in the West when set 1, with other counties set 0); the
variables interpreted refer to the growth rate of logarithm of per capita GDP in various counties. The result is
inconsistent with the previous scholars’ results of the division of the East, Middle and West, and is more
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Analysis on economic growth variances and convergences of county economy in China
approximate to the economic structure of various counties and the antecedent condition of club constringency
(Barro, Robert J. & Salai, 1992).
4. Research on the convergence of county economy in China
4.1 Selection of models and terms
The research on convergence
generally
begins
with
the
Barro
regression
equation:
gi ,t ,t T     ln  yit    i ,t , and mostly employs the cross-section analysis. Islam (1995) pointed out
that the estimate of cross-section analysis was inaccurate, and proposed the adoption of penal analysis, which
could be both consistent with the conclusion of new classical growth theory (the equivalence of long-term growth
rate of each economy is the exogenic progress rate of technology) and accurate in estimate Islam also discovered
that the Barro regression equation and MRW analytical framework were able to deduce the regression equation of
penal analysis. Hereby the Barro regression equation is employed in this paper to analyze the convergence effect
of county economy in China.
4.2 Descriptive statistics
In the classical research on convergence, the  -convergence is generally measured by the dispersion
changes of regional per capita GDP logarithm. If the  value (or the dispersion) decreases as the time processes,
it implies that the  -convergence takes place, and the variance of regional economy has a decreasing tendency. If
the  value increases as the time processes, it implies that the  -divergence takes place, and the variance of
regional economy has a increasing tendency.
From Figure 1 to Figure 4, it can be seen that the regional variances, the first classification and the second
classification had slowly increased in the past 10 years, and the  -divergence took place; while the regional
variance of the third classification had continuously decreased in the past 10 years except 1993, and the
 -convergence took place.
0.3
0.3
0.25
0.25
0.2
0.2
0.15
0.15
0.1
0.1
0.05
0.05
Variance of national per capita GDP
20
03
20
01
19
99
19
97
19
95
19
93
19
91
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
Figure 1
19
89
0
0
Figure 2 Variance of county per capita
GDP of the first classification
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Analysis on economic growth variances and convergences of county economy in China
0.25
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
0.2
0.15
0.1
0.05
Figure 3
Figure 4
Variance of county per capita GDP of
the second classification
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
0
Variance of county per capita GDP of
the third classification
4.3 Examination and determination of models
Firstly what type of Panel Data Model is employed should be decided. Involved statistics are in Table 1 and
Table 2.
Table 1
Model test: S value
S1
S2
S3
7.3324
21.6420
28.2330
Table 2
Model test: F value
F1
0.59
the critical value on the significance level of 5% is 1.00
F2
4.26
the critical value on the significance level of 5% is 1.00
It is known from Table 2 that on the significance level of 5%, the hypothesis 2 is rejected, while the
hypothesis 1 is accepted, hence the variable intercept Panel Data Model is employed in the empirical research of
this paper.
Because the all-sample data are employed, theoretically it is more reasonable to select the models of fixed
effect; but they still need to be empirically examined. It is known that the primary hypothesis is rejected; hence it
is more appropriate to employ the fixed effect models. Besides, it is also proven in the result of B-P examination
that the fixed effect exists. Hereby the variable intercept model of fixed effect is employed to research on the
constringency of variance of county economic growth in China.
4.4 Conclusion
The method of cluster analysis is employed to categorize the 2714 specimens into variant area classifications
according to the economic characteristics. And the economic structure of county development in China is reflected
in seven terms: capital input, labor input, geographical position, industrial structure, level of agricultural
development, level of urbanization and public expenditure. The results of the cluster analysis include: the first
classification includes 908 counties whose level of urbanization and capital input are relatively high, and whose
proportion of the primary industry: agriculture in GDP is relatively small; the second classification includes 819
counties; the third classification includes 987 counties whose level of urbanization is relatively low, whose public
expenditure is relatively small and whose proportion of agriculture in industrial structure is much larger. The
result is inconsistent with the previous scholars’ results of the division of the East, Middle and West, and is more
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Analysis on economic growth variances and convergences of county economy in China
approximate to the economic structure of various counties and the antecedent condition of club constringency.
After that, the Panel Data Model is utilized to project an empirical research on the constringency of variances
in the development of county economy in China between 1989 and 2004. Firstly the Panel Data are examined to
determine the adoption of variable intercept models of fixed effect to research the constringency of variances in
the development of county economy in China. Finally the conclusions drawn include: (1) The  -divergence
exists in the county economic growth in China, and the county economy in China possesses a tendency of
radiation integrally in the process of absolute  test. (2) The first classification of county economic variance
covers not only the  -divergence, but also the club convergence apparently. (3) The second classification covers
the  -divergence, but not the club convergence. (4) The third classification apparently covers the  -divergence,
yet the club convergence as well.
References:
Barro, Robert J. & Salai. (1992). Convergence. Journal of Political Economy, 100, 223-251.
CAI Fang & DU Yang. (2000). Convergence and variances of regional economic growth in China. Economic Research, 10, 30-37.
Durlauf, Steven N. & Paul, A. Johnson. (1995). Multiple regimes and cross-country growth behavior. Journal of Applied
Econometrics, 10.
Isiam, N. (1995). Growth Empirics: A panel data approach. Quarterly Journal of Economics, 110, 1127-1170.
LIN Yi-fu & LIU Pei-lin. (2003). The strategy of economic development in china and the income variance among regions. Economic
Research, 3, 35-42.
LIU Qiang. (2001). An analysis of constringency of economic growth in China. Economic Research, 6, 15-19.
SHEN Kun-rong & MA Jun. (2002). The “Club Constringency” feature of economic growth in China and the research on its causes.
Economic Research, 1, 19-27.
WANG Xiao-lu & FAN Gang. (2004). The mobility tendency and influencing factors of regional variances in China. Economic
Research, 1, 33-44.
XU Xian-xiang. (2004). An analysis of convergence of urban economic growth in China. Economic Research, 5, 40-48.
(Edited by Rainbow Lee and Cara Wan)
(continued from Page 4)
The way of combining local government (land control and transfer) with finance institutions benefit to
control a wave of land price and speed up urban infrastructure. Specially the way can ensure the city land use and
space development orderly and sustainable if it bases on the city planning. That is to say, the way also creates the
conditions of carrying out the city planning.
Before the mode of Wuhu “government+land+finiance” put into practice, some pieces of lands which
belonged to some enterprises often exchanged underground. So the goal of the city planning can not be realized.
After the mode of Wuhu “government+land+finiance” putting into practice, the government controls large part of
city lands and can be transferred and sold in land market according to the city planning and function need. The
income from the land can be used for urban infrastructure and city development.
In a word, the Wuhu pattern based on the land, including city planning, land exploitation, lands impawning,
land income, government credit and finance operation, greatly speeds up the urban infrastructure construction and
city development, enhances the ability of attracting economic essentials like persons and capitals in short time.
Reference (omitted)
(Edited by Rainbow Lee and Cara Wan)
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