Open Journal of Social Sciences, 2015, 3, 207-214
Published Online November 2015 in SciRes. http://www.scirp.org/journal/jss
http://dx.doi.org/10.4236/jss.2015.311025
How to cite this paper: Liu, Z.K. (2015) The Financial Capacity Assessment of Major Grain Producing Areas—Empirical
Analysis Based on Shandong Country Data. Open Journal of Social Sciences, 3, 207-214.
http://dx.doi.org/10.4236/jss.2015.311025
The Financial Capacity Assessment of Major
Grain Producing Areas—Empirical Analysis
Based on Shandong Country Data
Zhongkai Liu
School of Economics, Jinan University, Guangzhou, China
Received 19 October 2015; accepted 14 November 2015; published 17 November 2015
Copyright © 2015 by author and Scientific Research Publishing Inc.
This work is licensed under the Creative Commons Attribution International License (CC BY).
http://creativecommons.org/licenses/by/4.0/
Abstract
In this paper, starting at the definition of government financial capacity, building financial capaci-
ty evaluation system through factor analysis, and given that the fiscal capacity is unbalanced not
only between grain producing areas and non-grain producing areas, but also among grain pro-
ducing areas. Grain producing areas’ economic development level influences financial capacity.
Non-grain producing areas’ supply of public goods does not match with economic development
level. Then, some suggestions are submitted.
Keywords
Grain Producing Areas, Financial Capacity, Fiscal Capacity Equalization
1. Introduction and Literature Review
China totally has 13 major grain producing areas. Lili Gu and Qinghai Guo [1] had made profound analysis on the
evolution and development of major grain producing areas, thought that the major grain producing areas had three
characteristics: 1) the relatively concentrated on the space; 2) far distance from non-grain producing areas, and 3)
significant differences in grain commodity rates. Shandong province is a major grain producing province, due to
the different natural environment and city function orientation, major grain producing areas concentrated in the
county. On the one hand, major grain producing areas must strengthen the food production and need pay a lot of
money to maintain food security; on the other hand, it puts costs to develop economy in order to realize upgrading
of industrial structure and effe c tive supply of publ i c goods, so compa red t o the non-grain pr oduc i ng a re a s and grain
producing area s unde r great er f inanc ial stre ss. There fore, i t s financ ial capaci ty sta tus is worth expl ori ng.
To evaluate grain producing areas fiscal capacity, it must clearly connotate the “f iscal capacity” first. Western

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208
studied more about “the government capacity”, but the reference of “fiscal capacity” was relatively rare. There
was also no exact definition of “fiscal capacity”. Almond [2], John P. Coleman [3], R. T. Lenz [4] and Antony
Brown [5] all thought that fiscal capacity was a part of the government capacity; Buchanan [6] studied the im-
balance problem of fiscal capacity. He found that transfer payments from the central government to local gov-
ernment, to a certain extent, could change the fiscal capacity of a region. Other scholars, such as Tiebout [7],
Oates [8] and Musgrave [9], studied how to distribute financial problems. Domestic scholars have had con-
ducted extensive research on fiscal capability. Wenxing Li and Jiang Ying [10] argued that the local government
financial capacity was the local government raises money on the basis of public rights to provide public goods.
To meet the need of citizens, stable local public economy is reasonably redistributed. Xuejun Li and Shangxi
Liu [11], with a new perspective of analyzing financial capacity, thought that it was not a simple fin ancial scale,
but a multi-dimensional concept. It not only related to the government resources, but also related to the govern-
ment how to configure the resources of the financial system. It needed multi-angle analysis. They also put for-
ward three levels to evaluate fiscal capacity: standard fiscal capacity, realistic fiscal capacity and potential fiscal
capacity. Hongyou Lu and Zhilian Jia [12] argued that local fiscal capacity was the ability of local government
drawing resources and effective supply of public goods. In a word, the generally accepted concept of fiscal ca-
pacity which referred to cover the fiscal absorbing ability and configure ability was embodied in focus of local
government drawing financial resources, the allocation of resources and the effect from complete financial ac-
tivities.
About fiscal capacity to measure; Qiang Li [13] used per capita fiscal expenditure and related indicators to
measure regional fiscal capacity gap; Xiangling Wu and Xiaoying Deng [14] used self-financing rate and gov-
ernment budgetary revenues accounted for the proportion of GDP to measure the financial capacity, while Han-
bo Liu, Gong Li and Yidan Xia [15] measured the country’s fiscal capacity by per capita fiscal income; Hon-
gyou Lu and Zhilian Jia set provincial government fiscal capacity evaluation index from fiscal absorbing ability
and the ability of public goods supply; Ran Guang, Luzhao Yang and Xu Kun [16] built a comprehensive evalu-
ation index system and measured county government financial capacity from aspects of the level of county
economy, county economy benefit and the county economy growth potential; Yanglin and Xiaoyan Yuan [17]
measured government fiscal capacity by a comprehensive evaluation index system, which was set up from as-
pects of the fiscal revenue, fiscal expenditure and self-sufficiency; as the deeper understanding of the fiscal ca-
pacity, a more comprehensive evaluation index system of fiscal capacity was gradually adopted.
To sum up, although domestic research on local fiscal capacity was more extensive, the research on fiscal ca-
pacity of major function area especially the study of the major grain producing areas was lacking. At the same
time, the major grain producing areas are located in the west of Shandong province, which is similar to most of
the major grain producing provinces located in China. So, fiscal capacity of the major grain producing areas in
Shandong province is studi ed. It has universal significance for constructing fiscal capacity of the national major
grain producing are a s.
In this paper, starting at the definition of government financial ability, I build financial capacity evaluation
system through factor analysis and select 25 producing counties in Shandong. In order to compare with non-
grain producing areas, I select 5 non-grain produ cing counties and use 18 indicators to evaluate Shandong grain
producing areas’ financial capacity, given that the fiscal capacity is unbalanced not only between grain produc-
ing areas and non-grain producing areas, but also among grain producing areas. Grain producing areas’ eco-
nomic development level influences financial capacity. Non-grain producing areas’ supply of public goods does
not match with economic development level. Then, some suggestions are submitted.
2. The Research Method and the Establishment of Evaluation Index System of
Fiscal Capacity
2.1. Factor Analysis Method
Factor analysis is an effective statistical analysis method. It can be easy get a few main factors to explain the
original variables, by extracting from more complex variables and samples, so as to find out a few random va-
riables, to describe the related or similar relationship between multiple variables or samples. The ultimate goal
partly reflects th e overall [18]. Government fiscal capacity is a complex, involving the multi-dimensional infor-
mation. Through factor ana lysis, it can reduce a few common factors. It also reflects the original information of
fiscal capacity. According to the factor score, an objective evaluation is ma d e . So its principal component analy-

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209
sis is chosen. The model is se t as: (j = 1, 2, and 3, ···, n, n is total number of original variables). X represents the
original variable, after the stand ard trea tment for Z, it can be in the form of a matrix for Z = AF + U. F calls pub-
lic factor, appears in each of the original variable linear expression; aji calls factor loading, U calls special fac-
tors, represents par ts of the original variables which cannot be explained by factors. M represents the number of
common factor of all variables.
2.2. The Evaluation Index System of Fiscal Capacity
Considering the principles of data availability, authoritative and operability, combine with major grain produc-
ing areas situation, which are less developed, with the large agricultural population, urbanization level is rela-
tively low, so from aspects of the financial revenue ability, potential growth ability, expenditure ability and
self-sufficiency ability, to establish the evaluation index system for major grain producing areas is more reality
(Table 1).
The index of finance income ability mainly considered from factors of fiscal revenue sources, quantify po-
tential growth ability is relati v ely complex, need ed think of th e whole society; W hile f iscal exp enditure ab ility is
not only reflected on the expenditure scale, but also expenditure structure of the public service, in which the
most important are public health and education systems. Fangkun Xin [19] used the adult illiteracy rate (%) to
measure the quality of education, used the number of medical institution beds in every ten thousand people as
indicators to measure clinical outcomes, due to the availability of data from the county, we can use the propor-
tion (%) of livelihood expenditure in public expenditure and the number of primary teachers in every one thou-
sand people instead; And index of self-sufficiency ability reflects the ability of government how much indepen-
dent to raise revenue.
3. Empirical Research on the Fiscal Ability of Major Grain Producing Areas
3.1. Data Sources
According to annual output of grain in China, and with reference to the ministry of agriculture “the national
grain production counties “list in 2013, 25 counties in Shandong were selceted; In order to compare with non-
grain producing areas, five non-grain producing counties which are: Huangdao, Shizhong, Zhangdian, Laishan,
Table 1. The evaluation index system of fiscal capacity.
Target Level Indicators
fiscal capacity of major grain
producing areas
financial revenue ability
X1 GDP
X2 public budget income
X3 public budget revenues accounted for the proportion of GDP
X4 per capita public budget inc o me
X5 per capita net income of farmers
potential growth ability
X6 industrial gross output
X7 social consumer goods retail sales
X8 total exports
X9 the rural and urban residents ‘deposit balance
X10 Completed investment in fixed assets
X11 the financial institutions loan balance
X12 land area per capita
expenditure ability
X13 the public finance budget expendit ure
X14 per capita the budget expenditure
X15 the proportion of livelihood expenditure in public expenditure
X16 the number of primary teachers in every one thousand people
self-sufficiency ability X17 degree of fiscal self-financing
X18 tax accounted for the proportion of budget income

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210
Taishan were selected. 18 evaluation indexes all come from 2009-2014 “Shandong statistical yearbook”. Al-
though data index dimension is different, all are positive indicators.
3.2. The Empirical Analysis
First do Bartlett test and KMO test by SPSS20.0, the results show KMO = 0.862, which is bigger than 0.5, and
get significant probability of x2 statistics which is 0.000 ; the correlation betw een data is suitable f or factor anal-
ysis. And four comprehensive factors respectively explain the ability of the original information are 53.385%,
13.863%, 9.385% and 8.519%, the cumulative variance contribution rate is 85.152%; all eigenvalues are bigger
than 1. It shows that the 4 factors enough reflect the fiscal capacity of grain producing counties.
As is shown in Table 2, about interpretation total variance, the results showed KMO =0.862, is bigger than
0.5, and get significant probability of x2 statistics is 0.000; the correlation between data is suitable for factor
analysis. In order to make the relation between Zj and Fi more significant, make maximum swivel of variance
factor loading matrix A, component 1 has contributed 53.385% of fiscal capacity, in which the gross domestic
product (X1), industrial gross output (X6), total exports (X8), completed investment in fixed assets (X10) have
large load, it is associated with the level of economic development of grain producing areas, so we called de-
velopment factor. Component 2 has contributed 13.863% of fiscal capacity, public budget revenues accounted
for the proportion of GDP (X3), per capita public budget income (X4) and per capita the budget expenditure’s
(X14) load is bigger, reflect the government’s fiscal balance, we named fiscal balance factor; component 3 has
contributed 9.385% of fiscal capacity, in which social retail sales of consumer goods (X7), the rural and urban
residents deposit balance (X9), the financial institutions loan balance (X11), the proportion of livelihood ex-
penditure in public expenditure (X15) and the number of primary teachers in every one thousand people (X16)
load is bigger, reflect the level of public services and environmental factors, we named environmental factors;
component 4 has contributed 8.519% of fiscal capacity, including per capita public budget income (X4), per ca-
pita net income of farmers (X5), and degree of fiscal self-financing ‘s(X17) load is bigger, reflect the
self-sufficiency ability of curre nt state of the major grain producing areas, so we named self-f inan cing factor.
As is shown in Table 3, about rotate component matrix, 18 evaluation indexes all come from 2009-2014
“Shandong statistical yearbo ok”. Although data index dimension is different, all ar e positive indicators. We g et
4principal factors to reflect the fiscal capacity of grain producing counties. In order to evaluate fiscal capacity
comprehensively, using the formula to calculate th e total score of 30 evaluation object, and give a rank:
V = 53.385% × F1 + 13.863% × F2 + 9.385% × F3 + 8.5 19 % × F4
3.3. The Result Analysis
3.3.1. Sequence Analysis
As is shown in Table 4, about financial ability composite score and ranking of 30 counties of Shandong prov-
ince, the overall fiscal capacity has a gradually de cline trend from the northeast coast to southwest inland. First
of all, combined with the geographical position and economic zone of various counties, we have a lateral overall
analysis on this phenomenon.
1) The Shandong peninsula blue economic zone. Main producing counties Pingdu, Laixi, Zhucheng, Gaomi,
Laizhou and non-main producing counties Huangdao, Laoshan, comprehensive financial capacity ranking top,
Table 2. Interpretation total variance.
Component
Initial eigenvalues Extraction sums of squared loading
Total % of variance contribution of variance
contribution of variance % Cumulative % Total % of variance Cumulative %
1 9.609 53.385 53,385 7435 41,306 41,306
2 2.495 13.863 67,248 2958 16,434 57,740
3 1.689 9.385 76,633 2813 15,629 73,329
4 1.353 8.519 85,152 1941 11,783 85,152
Extraction method: principal component analysis.

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Table 3. Rotate component matrix.
Evaluation index Principal factor
F1 F2 F3 F4
X1 0.958 −0.003 0.085 0.221
X2 0.914 0.249 0.236 0.141
X3 0.030 0.782 0.397 −0.261
X4 0.570 0.610 0.064 0.430
X5 0.493 0.398 0.115 0.669
X6 0.929 0.038 0.143 0.049
X7 0.643 0.024 0.578 0.335
X8 0.918 0.064 −0.168 0.031
X9 0.723 0.247 0.542 0.111
X10 0.926 0.129 0.064 0.167
X11 at the end of the financial institutions loan balance 0.420 0.326 0.786 0.038
X12 0.261 0.075 −0.710 −0.158
X13 0.891 0.258 0.234 −0.089
X14 0.587 0.671 0.007 0.257
X15 0.011 −0.882 0.770 −0.144
X16 0.336 0.382 0.794 −0.191
X17 0.344 0.327 0.287 0.634
X18 0.042 0.089 0.040 0.675
Extraction method: principal component analysis.
belongs to the body region of Shandong peninsula blue economic zone. It’s also the important part of the na-
tional marine development strategy and coordinated regional development strategy; located in the eastern coastal,
geographical position is superior. Relying on Qingdao leading economic radiation effect, the social economy
and the integration of urban and rural development is rapid, financial ability is stronger .
2) Central of traditional manufacture areas. Main producing counties Zouping, Tengzhou, Zhangqiu, Feicheng,
Daiyue, Qihe, Linyi and non-main producing counties Zhangdian, Taishan, Shizhong located in Shandong tradi-
tional central industrial zone, Jinan and Zibo as the l e a de r of thos e di s tricts, some c ount ie s in ri c h mineral res ourc e s ,
has a good foundation of industry, which are the gathering place of traditional coal production, smelting processing
and other manufacturing industries. With the adjustment and upgrade of industrial structure, financial capacity is
strengthening. However Jiyang, Pingyuan and Lingxian, the second industry is relatively backward, agriculture
contributi on is lim ite d, so t hey are restricted by economic developm ent level. Financial ability needs to improve.
3) The western plains. Dongming, Juan Cheng and Dingtao located in Heze, Yanggu, Guanxian belongs to
Liaocheng city; Wenshang belongs to the city of Jining; Heze, Jining and Liaocheng belongs Huang-huai-hai
plain, in addition to the economic growth faster Dongchang and tourism developed Qufu, compared with the
eastern coastal economic region and central industrial zone these counties’ industrial foundation is weak, eco-
nomic development level is backward, food production has a long history. It is traditional agricultural area and
its fiscal capacity lag behind oth er distr ic ts.
4) Yimeng mountain area. Yimeng mountain area are not all mountains, plains, hills and mountains each ac-
counted for a third; Junan and Cangshan have the foundation of traditional agriculture. In recent years, t hey de-
pend on the development of logistics industry in Linyi, policy support to the old revolutionary base areas, there
is a breakthrough in economic development, and fiscal capacity increase steadily, but it still have obvious gap
compared to the east.

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212
Table 4. Score and rank of 30 counties fiscal capacity.
Rank Countries F1 F2 F3 F4 Score
1 Huangdao 4.547 −0.138 −1.087 −0.215 2.288
2 Zhaodian 0.687 −0.081 3.536 1.262 0.795
3 Pingdu 0.805 −0.038 −0.321 0.932 0.474
4 Zhouping 0.651 0.398 0.629 −0.164 0.447
5 Zhucheng 0.680 0.329 0.239 −0.051 0.427
6 Laizhou 0.367 1.083 −0.440 0.836 0.377
7 Tengzhou 0.476 −0.359 1.507 −0.092 0.338
8 Zhangqiu 0.337 −0.019 0.078 0.831 0.255
9 Dongchang −0.146 2.925 1.771 −2.840 0.251
10 Laixi 0.322 0.349 −0.818 0.741 0.207
11 Gaomi 0.214 0.062 −0.094 −0.002 0.114
12 Feicheng 0.081 −0.517 0.406 0.723 0.071
13 Laishan 0.053 3.407 −1.432 1.850 0.050
14 Qihe −0.184 −0.348 −0.849 0.208 −0.208
15 Daiyue −0.013 −0.521 −0.224 −1.281 −0.209
16 Taishan 0.337 −0.0196 0.078 0.831 −0.212
17 Lunan −0.204 −0.195 −0.333 −1.106 −0.262
18 Shizhong −0.322 0.561 0.804 −0.048 −0.294
19 Qufu −0.671 −0.597 0.093 1.151 −0.335
20 Linyi −0.359 −0.380 −0.611 −0.529 −0.347
21 Cangshan −0.282 −0.951 0.152 −1.064 −0.358
22 Jiyang −0.714 0.745 −1.094 0.203 −0.363
23 Dongming −0.473 −0.061 −0.204 −0.978 −0.364
24 Lingxian −0.294 −0.582 −0.863 −0.641 −0.373
25 Yanggu −0.568 −0.891 0.083 0.363 −0.388
26 Pingyuan −0.299 −0.517 −1.111 −0.733 −0.398
27 Guanxian −0.356 −0.696 −0.339 −0.955 −0.401
28 Wenshang −0.743 −0.893 −0.047 0.598 −0.474
29 Juancheng −0.680 −0.769 −0.105 −0.568 −0.528
30 Dingtao −0.862 −0.595 −0.264 −0.197 −0.584
Extraction method: principal component analysis.
3.3.2. Cluster Analysis
Evaluate financial capacity of the major grain producing areas, we must start from the extracted public factors,
combine with the reality, make deep analysis, thus to the four extracted common factors, using the set of con-
nection between hierarchical do the cluster analysis, because the comprehensive factor score sorting ignores the
personality and the common features of the financial ability of the various counties and cities, which contains in

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213
the explain factor, clustering analysis is a kind of supplement of sequence analysis, there is a big dif ference be-
tween opera tion resul t s a nd compre hensive rank.
1) The first category. Jiyang, Laixi, Laizhou and Laishan. Besides Jiyang in the central region, the others are
located in Shandong peninsula blue economic zone, comprehensive rank is different, but the structure of fiscal
capacity factor is similar, namely the fiscal balance factor and self-financing factor are prominent, shows four
counties have the ability to balance the budget, the self-sufficiency ability also performs well, but the environ-
mental factor score is low, manifests short supply of the public service, it need to improve social environment.
Laixi, Laizhou and Lai shan’s economic development level is higher than other areas, so financial ability
stronger than Jiyang, but they should focus on how to increase the financial input in livelihood, promote urban
and rural integration, improve capital construction and the level of public services; Jiyang’s economic is still
cannot be compare with the above three counties, it should improve the economic environment of the whole
county, attracting foreign investment, using radiation effect of Jinan, promote the development of urban and ru-
ral areas as a whole.
2) The second category. Huangdao, as a non-grain producing areas, ranked the first place, development factor
is prominent. In recent years, relying on Qingdao’s leading position, its economic growth is rapid, GDP in 2013
reached 212.4 billion, accounting for 25.5% of Qingdao, is one of the most developed areas in Shandong prov-
ince. But environ mental factor is smaller, not match with economic development level, it restricts economic de-
velopment potential. With the development of economy, the rapid increase of migrant workers, urban problems
such as environment pollution, traffic congestion, began to emerge, the urban and rural public services is imbal-
ance, environmental factor need to be improved.
3) The third category. Pingdu, Zhangqiu, Tengzhou, Zhucheng, Wenshang, Qufu, Feicheng, Yanggu, Zou ping,
Zhangdian, Taishan. In the structure of the county finance, environmental factor is bigger, but development fac-
tor, fiscal balance factor and self-financing factor are slightly low, but fiscal capacity of Zhangqiu, Pingdu,
which are increasing significantly, even more than the central district of Zaozhuang, they accurately positioning
of fiscal functions at the same time, put more money into the areas of the people’s livelihood, improve the effi-
ciency of the use of fiscal funds; Taishan, Qufu, Zhucheng, Zhangqiu and Pingdu’s tourism have developed, the
government attaches great importance to the infrastructure, increase investment in science and technology cul-
ture, also improve environmental factor. For the improvement of fiscal capacity, Tengzhou and Shizhong should
cling to coal industry upgrade and industry structure adjustment of Zaozhuang, improve the economic develop-
ment potential; Zhangqiu, Feicheng and Pingdu should rely on the good market location of Jinan, Taishan and
Qingdao, vigorously develop characteristic agricultural products (such as Zhangqiu shallot, Feicheng peach,
Pingdu daze moun tain grape), keep special developing way of green agriculture, extend the industrial chain, in-
crease added value of agricultural products. Wenshang and Yanggu financial ability is weak, in which develop-
ment factor, balance factor and environment factor at a lower level. Although based on weak fiscal revenue
sources, they should guarantee grain production firstly and put vigorously developing of the county ec onomy in
the top priority.
4) The fourth category. Daiyue, Cangshan, Junan, Qihe, Lingxian, Linyi, Pingyuan, Dongchang, Guanxian,
Dongming, Juancheng and Dingtao. Besides Dongchang outshines the fiscal balance factor and environment
factor, every other county four common factor is generally weak, especially in the development factor and
self-financing factor, composite scores were negative. This kind of country is mostly traditional agricultural
producti on in Shand o ng, especially the southwest of Shandong southwest, Dongming, Juancheng and Dingtao. It
has the weakest financial ability and needs to strengthen the construction of government financial ability in the
round. It is mainly limited by the economic development level. The shortage of the county financial resources
affects the supply of public services, and infrastructure is not perfect and not attractive to foreign investment and
becomes the bottleneck of restricting economic development in a vicious cycle of strife-torn.
4. Conclusions and Suggestion
Through factor analysis, it shows that the gap of financial capacity between east and west of Shandong grain
producing areas is obvious. Major grain producing areas in East have strong ab ility. There is a more balance in
central areas, but in western major grain producing areas, especially in the southwest, its financial capacity lags
behind other areas in the province. The fiscal capacity is unbalan ced not only b etw een grain produ cing area s and
non-grain producing areas, but also among grain producing areas. Through clustering analysis, the major grain
producing areas’ development factor and financially self-financing factor are key factors to restrict its fiscal ca-

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214
pacity. Non-grain producing areas’ environmental factor doesn’t match with its development level.
For the imbalance of major grain producing areas’ fiscal capacity and the insufficiency of development factor
and self-financing factor, the key is to solve the lack of financial resources. Sugge stion as follows: First, taking
advantage of local conditions, developing their own advantage industry, realizing the optimization and upgrad-
ing of industrial structure and promoting the economic sustainable development in an all-round way. Seco nd,
creating horizontal fiscal transfer payment system [20] and promoting equalization of the fiscal capacity. The
tax reform occurred in 1994. Fiscal capacity is more unbalanced, but the practice proves that the fiscal transfer
payment system of our country is remarkable to balance ability. It is advantageous to the fiscal equalization.
Third, implementing PPP financing model, more cooperating social capital w ith the government and participat-
ing in the production and the supply of public goods.
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