







































 

 

 

 

 

 

An Empirical Study on the Impact of 

Individual Local Political Elites and 

Decision-Making Collective on Educational 

Fiscal Expenditure in China

Ru Cai, Xinping Zhang 

 
Nanjing Normal University, Nanjing 210024, China 

Abstract. Under the current decentralization system in China, individual 
characteristics of the local political elites and collective characteristics 
of the standing committees of the local party have an impact on local 
education fiscal policy. Yet published research on the similarities and 
differences between the collective influence of the Standing committee 
and the individual influence of the political elite are lacking. To address 
this gap in the literature, our study discussed the impact of local politi-
cal elites represented by the mayor and the secretary and the collective 
of standing committees of the local party on education fiscal expendi-
ture. We construct multiple regression models and analyze the R2 
Change of variables is based on the cross-sectional data from 2015 of 
283 prefecture-level administrative units in China. We find that both 
political elites and the standing committees have significant impacts on 
fiscal expenditure in education, and that the influence of the latter is 
greater than that of the former. The effect of individual characteristics 
and collective characteristics on education fiscal expenditure is not 
completely consistent across prefectures. China's prefectural govern-
ments implement China's unique principle of democratic centralism 
when they make decisions on local spending for education and the col-
lective decision-making under the leadership of the committee plays an 
important role in education fiscal expenditure. Based on this, we put 
forward policy suggestions to further develop the principle of democrat-
ic centralism and to optimize optimizing the local government education 
supply and evaluation mechanism. 

Best Evidence in Chinese Education 2021; 7(2):961-985. 
Doi: 10.15354/bece.21.or023. 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No.2, 2021 962 

How to Cite: Cai, R., & Zhang, X. (2021). An empirical study on the impact of indi-
vidual local political elites and decision-making collective on educational fiscal 
expenditure in China. Best Evidence in Chinese Education, 7(2):961-985. 

Keywords: Official Personal Characteristics; Collective Characteristics of Stand-
ing Committee of Local Party; Democratic Centralism; Education Fiscal Expendi-
ture

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

About the Authors: Ru Cai, Doctorate Candidate, School of Educational Science, Nanjing Normal University, No. 
122, Ninghai Rd., Nanjing 210024, China. Email: 924654819@qq.com. 
Correspondence to: Xinping Zhang, Ph.D., Professor, School of Educational Science, Nanjing Normal University, 
No. 122, Ninghai Rd., Nanjing 210024, China. Email: 403265357@qq.com. 
Funding: This paper is funded by The Key Project of Philosophy and Social Science Research of Ministry of Edu-
cation in 2020 “Research on Evaluation Index System of High Quality Development of Education” (20JZD053). It 
is also A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions 
(PAPD). 
Conflict of Interests: None. 
 

© 2021 Insights Publisher. All rights reserved. 

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Crea-

tive Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-

nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided 

the original work is attributed by the Insights Publisher. 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 963 

Introduction 

ITH decentralization reform in China, Chinese local governments face 

unique incentives and constraints given their institutional design. As a result, 

mainstream Western fiscal decentralization theory provides little insight 

into China’s problems, leading Yingyi Qian (1996) and others to argue that Chinese 

decentralization system design differs from that of the Western. “Chinese-style fiscal 

federalism” is the result of the unity of economic decentralization and political centrali-

zation (Blanchard & Shleifer, 2001). While implementing economic decentralization, 

the party and higher-level government organizations maintain control of the incentives 

and constraints on the party and government organizations at lower levels through or-

ganizational personnel arrangements based on local development performance (often 

expressed as local economic growth performance) (Li & Zhou, 2005). Such institutional 

design has allowed localities to allocate more energy and resources to areas conducive 

to economic growth in the process of “competing for growth” which has mobilized lo-

cal governments to develop the economy through initiatives that promote high-speed 

growth of the local economy, but has also brought problems for local education, health 

care, environmental protection, and investment resources, etc. (Fu & Zhang, 2017; 

Wang & Zhou, 2013; Xu, 2011; Yu, 2017; Zhou, 2006; Qiao, et al., 2005) . On the oth-

er hand, compared with the Western countries, China’s local government officials have 

greater discretionary power in the process of intergovernmental competition and local 

governance, especially in the use of funds and budgetary arrangements. With this great-

er flexibility, China’s local governments exhibit a clear “soft budget” in terms of local 

fiscal expenditures. This means that local officials can take more flexible measures to 

deal with local affairs based on their own experience and preferences (Yang & Zheng, 

2013; Zhang, 2008). 

Given this local flexibility, many scholars have paid attention to the relation-

ship between the personality traits of officials and local governance. Xianbin Wang 

(2009), Li’an Zhou (2005), Tingjin Lin (2009), Xianxiang Xu (2008), Ran Song (2016), 

Yini Jiang (2017) and others use the analysis of government behavior from provincial, 

city and county levels as a starting point to discuss demographic characteristics of local 

officials, such as gender, age, education, and the relationship between work experience 

and the supply of public goods such as education, which provides new perspectives and 

ideas for interpreting China’s local governance model. However, such empirical re-

searches, while paying attention to the influence of individual traits of officials, fail to 

connect this with collective decision-making of local governance in China. As demo-

cratic centralism is the fundamental organizational and leadership system of the local 

government, current researches are clearly insufficient to fully describe China’s local 

governance characteristics. Given the organization of democratic centralism and deci-

sion-making principles, decisions on education finance must be made through a few 

democratic processes that are subject to the majority (Zhu & Hu, 2014). Therefore, ac-

curately describing the decision-making behavior and characteristics of Chinese local 

government officials requires a focus on the relationship between the collective charac-

W 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 964 

teristics of decision-making body and their relationship with the individual characteris-

tics of political elites. 

A proper description of the collective characteristics of local leadership is fun-

damental to such kind of researches. Some early researches have been explored this 

theoretical logic regarding the collective as a rational decision maker, such as the Logic 

of Collective Action (Olson, 2014). From this perspective, the government can be re-

garded as a “personified” individual. In recent years, some foreign studies have begun 

trying to describe the characteristics of decision-making collectives quantitatively. The 

basic idea is similar to the above theoretical logic; that is, by considering the collective 

as an “individual” with certain characteristics, and then using the corresponding indica-

tors (i.e., the composition of the collective average individual characteristics) the collec-

tive can be described (Alesina et al., 2015). Most such researches in China are still at 

the stage of theoretical discussion. Some scholars analyzing public finance behavior 

have reported on officials stating that personal motives partially affected government 

group motivation (Cao et al., 2014). Others start from the concept of “collective leader-

ship” and describe the dimensions and characteristics of collective decision-making 

(Yang et al., 2014). To date, however, there have been few studies on the influence of 

collective leadership in China, and high-quality empirical research is especially lacking 

(Cai & Yao, 2018; Zhang, 2014). 

This paper considers the local government decision-making body in terms of 

individuals of political elite and collective of the party committee. Government officials 

discuss the impact of individual and collective decision-making on education spending 

and its financial interactions. Finally, an analysis of the local government’s supply be-

havior of public goods, such as education, is considered. In the public fiscal expendi-

tures, only the education fiscal expenditure item has the target stipulated explicitly by 

the government, moreover, the education publicity and the education finance expendi-

ture with lag behind effect can reflect the local official’s fiscal expenditure preference 

more. For these reasons, this article focuses on the following questions: What are the 

similarities and differences between the political elite and the party committee’s stand-

ing committee, and how do they interact? What is the impact of the demographic char-

acteristics and job experience characteristics of officials on the education fiscal ex-

penditure? What specific characteristics have a critical impact on the education fiscal 

expenditure? Answering these questions can provide a deeper understanding of the in-

fluence of local officials on education finance, and will allow a better interpretation of 

the behavioral motives of local officials under the “Chinese-style decentralization” sys-

tem. Ultimately, this can help local political elites and party committee to make scientif-

ically-based decisions. 

Methods 

Research design 

The 2015 prefecture-level administrative units are used as the research subject, and data 

are collected on the personal characteristics of the mayor, the municipal party commit-



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 965 

tee secretary and the members of the standing committee of the party committee for use 

in a regression models for analysis. We chose prefecture-level administrative units as 

our research objects because of the availability of data and the need for research meth-

ods. First, provincial data cannot meet sample size requirements and county-level data 

is difficult to obtain; thus, only prefecture-city level data met research needs. Second, 

although China has a “Provincial County” financial management system, with only 

three provincial cities and counties in the administrative relationship, the local govern-

ment level bears an important responsibility for the development of local education. 

Third, the logic of local government behavior between leading individuals and collec-

tives in the supply of education are present at provincial prefecture and county levels, 

the prefecture level can also explain this logic. Therefore, the administrative units at the 

prefecture level are reasonable as the research subjects of this study. 

This paper therefore uses the data of prefecture-level administrative units in 

China to compare and analyze the behaviors of prefecture-level political leaders in fi-

nancial expenditures on education, including the party committee secretary, the mayor 

(including the heads of autonomous league, governors of the autonomous prefectures)
1
 

and the decision-making collectives of the party committee. The basic characteristics of 

the collective committee of the party committee at the prefecture level are described 

using the “personification” method and averaging of individual committee member 

traits, and combined with the demographic and experience characteristics of the party 

committee secretary and the mayor as independent variables to establish six regression 

models. These models explore the relationship between individual and collective char-

acteristics of political leaders at the prefecture level and fiscal expenditures for educa-

tion. The variables of this study are designed as follows. 

Dependent variables 
China’s assessment of the financial responsibility of local government education is 

mainly based on two indicators: the proportion of education fiscal expenditure relative 

to GDP should be greater than 4% and the proportion relative to the fiscal expenditure 

should be greater than 15% (Government Central Committee, 1993; National Education 

Commission, 1993). These two indicators can not only describe the total level and effort 

of local government on education and financial expenditure, but also express the spend-

ing preference of local governments. Thus, we use “educational fiscal expenditure as a 

share of GDP” and “educational fiscal expenditure accounts for the proportion of fiscal 

expenditure” as two dependent variables in each group model. 

Independent variables 
The collective level Party committee as a decision-making body is based on personal 

characteristics of the political elite personnel to generate a quantitative description of 

the collective identity of officials (Alesina et al., 2015). It includes not only demograph-

ic variables such as gender, nationality, age, years of education, and professional back-



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 966 

ground, but also the characteristics of the tenure of office, promotion rate, and working 

in the household registration area or not. 

Control variables 
This study sets the level of local economic development, regional categories, population 

size, education needs, fiscal expenditure decentralization, and fiscal control variables, 

such as autonomy. The level of economic development is expressed in terms of local 

per capita GDP. China is divided into three major regions of East, Central and West, 

which are modeled by virtual variables (using the western region as the reference 

group). Population size is represented by the permanent population at the end of the 

year. The number of students enrolled in the city is used to indicate education needs. 

The financial expenditure decentralization index and the financial autonomy index are 

used as proxies for the local government’s financial operation characteristics. 

Data Processing 

Resumé and socio-economic data in 2015, obtained from the national-level administra-

tive units for the party committee officials, were used for analysis. An information table 

was generated for officials using the party committee leadership directory in the year-

book, from searching resumés for standing committee members from People’s Daily, 

Xinhua, and the government portals directory list, and using the socio-economic data 

and education finance data from the China City Statistical Yearbook (2016) and local 

statistical yearbooks. 

In 2015, 334-prefecture-level administrative units were present in China; anal-

ysis excluded areas where the data were scarce
2
. The term of office of the standing 

committee of each party committee is typically five years. A small number of members 

of the standing committee may change during a non-change year, and the leadership 

role of the new standing committee then takes some time to take effect; thus, members 

of the standing committee of the prefecture-level local party who were changed in 2015 

and have served for less than half a year were excluded. After personal information was 

extracted for members, standing party committee-level characteristics for the group 

were calculated as the average individual characteristic or as a proportion. In this way, 

the personal data from 3,482 prefecture-level party committee members were combined 

into 314 values of the collective characteristics of the standing committee members of 

the prefecture-level party committee. The specific calculation method for each variable 

is shown in Table 1. To match the political elite and the standing committee, samples 

with missing values are deleted
3
. Finally, the Pauta criterion for excluding outliers was 

applied
4
. Using the obtained 283 sets of complete matching samples, we ran the follow-

ing descriptive statistical analysis. 

Results 

Basic Descriptive Statistical Analysis 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 967 

Table 1. Variable Setting and Descriptive Statistical Analysis. 

 Variable Abbr. Metric Method Mean SD Minimum Maximum 

Dependent 

Variable 

Education 

expenditure as 

a percentage of 

GDP (%) 

EX_GDP Education expenditure as 

a percentage of GDP = 

education expenditure / 

GDP * 100 

3.812  1.892  0.857  10.718  

Education 

expenditure as 

a share of fiscal 

expenditure 

(%) 

EX_FE Education expenditure as 

a percentage of local 

fiscal expenditure = 

education expenditure / 

fiscal expenditure * 100 

17.722  3.774  4.836  27.501  

Independent 

Variable – 

Political Elite 

Individual 

Characteristic 

Gender G 1=female; 

0=male 

Secretary 0.060  0.238  0.000  1.000  

 Mayor 0.081  0.274  0.000  1.000  

Nationality N 1=minority; 

0=han 

Secretary 0.081  0.274  0.000  1.000  

 Mayor 0.127  0.334  0.000  1.000  

Age A Age = 

December 

2015 - date 

of birth 

Secretary 53.812  3.233  43.090  61.020  

 Mayor 51.567  3.449  40.040  60.000  

Education 

(years) 

EY Education 

Year = full-

time educa-

tion year + 

in-service 

education 

year (ex-

cluding 

short-term 

training) 

Secretary 19.583  3.037  12.000  31.000  

 Mayor 19.996  3.058  13.000  31.000  

Education 

Major 

EM 1=social 

science; 

0=natural 

science 

Secretary 0.604  0.490  0.000  1.000  

 Mayor 0.580  0.495  0.000  1.000  

Serve in the 

household 

registration 

area 

SHRA 1=yes; 0=no Secretary 0.544  0.499  0.000  1.000  

 Mayor 0.661  0.474  0.000  1.000  

Current posi-

tion tenure 

CPT Current 

tenure of 

office = 

December 

2015 - date 

of the 

current 

position 

Secretary 2.254  1.547  0.060  8.090  

 Mayor 2.081  1.508  0.050  9.100  

Promotion rate PR Promotion 

rate = 1 / 

pre-service 

years of 

service 

Secretary 0.034  0.007  0.024  0.067  

 Mayor 0.037  0.008  0.024  0.084  

Independent 

Variables – 

Collective 

Characteristic 

of the Stand-

ing Commit-

tee the Party 

Female share 

(%) 

FS Female share = number 

of women / total number * 

100 

9.194  6.959  0.000  30.000  

Minority share 

(%) 

MS Minority share = number 

of ethnic minorities / total 

number of people * 100 

7.844  13.662  0.000  57.143  

Average age 

(years) 

A_A Average age = sum of 

age / total number of 

people 

51.996  1.714  48.275  57.146  

Average Edu-

cation (years) 

A_EY Average education year = 

sum of years of education 

/ total number of people 

18.508  1.143  15.000  22.667  

The proportion 

of social sci-

ence (%) 

PSS The proportion of social 

science majors = number 

of social science profes-

54.602  18.876  0.000  92.857  



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 968 

sionals / total number * 

100 

The average 

proportion of 

officials serving 

in household 

registration 

area (%) 

AP_SHRA The average proportion 

of officials serving in 

household registration 

area = number of domi-

ciled tenure / total num-

ber of people 

25.851  16.525  0.000  83.333  

Average cur-

rent position 

tenure  

A_CPT Average current tenure of 

office = total number of 

current tenure / total 

number of people 

2.612  0.764  0.489  4.777  

Average pro-

motion rate 

A_PR Average promotion rate = 

sum of promotion rates / 

total number of people; 

among them, promotion 

rate = 1 / pre- working 

years 

0.040  0.004  0.028  0.067  

Control 

Variable 

Per capita GDP 

of each city 

(10,000 

CNY/person) 

Per_GDP Per capita GDP of each 

city = GDP per year / 

permanent population at 

the end of the year 

4.965  2.931  1.217  20.716  

East area E 1=eastern; 0=others 0.364  0.482  0.000  1.000  

Central area C 1=Central; 0=Others 0.382  0.487  0.000  1.000  

Permanent 

population at 

the end of the 

year (10,000 

people) 

PP The city’s permanent 

population at the end of 

the year 

414.829  256.210  24.390  1465.750  

Urbanization 

rate (%) 

UR Urbanization rate = urban 

household registration 

population at the end of 

the year / total household 

registration at the end of 

the year *100 

53.451  14.333  11.212  100.000  

The proportion 

of students 

enrolled in the 

city (%) 

PSE The proportion of stu-

dents enrolled in the city 

= the number of students 

at all levels of the city at 

the end of the year / the 

number of registered 

households at the end of 

the year * 100 

14.726  4.683  1.472  39.125  

The city’s fiscal 

expenditure 

decentralization 

index (%) 

FED The city’s fiscal expendi-

ture decentralization 

index = the city’s fiscal 

expenditure / the prov-

ince’s fiscal expenditure * 

100 

6.841  4.886  0.889  30.560  

Financial 

autonomy (%) 

FA Financial autonomy = the 

city’s fiscal revenue / the 

city’s fiscal expenditure * 

100 

45.651  22.025  9.242  103.843  

Due to the fact that some data of the Standing Committee of some party committees cannot be collected, the missing official 

information is not included in the calculation. 

 

 

 

 

Among the leaders at the prefecture-level in China, there are fewer female and minority 

members, and male still are the majority of local leaders. The average age of the secre-

tary is 53.81 year-old, which is greater than the average age of the mayor and the stand-

ing committee. The political elites have a higher education level than the standing 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 969 

committee, but the vast majority party members have higher education experience. The 

background of political elite is more balanced; members of the standing committee have 

mostly social science backgrounds. Approximately half of the secretaries and mayors 

are working in the household registration areas, but only 25.85% of the party committee 

members are native. The serving term of secretaries and mayors is 2.254 and 2.081 

years respectively, which are shorter than that of the political elite of the party commit-

tee. All members of three decision-making bodies basically started to take up their cur-

rent positions in the last year of change of leadership, namely around 2012, which 

shows which shows the consistency of the collective party committee. The rate of pro-

motion of the political elite was 0.034 and 0.037 for secretaries and mayors, respective-

ly, indicating that the collective promotion of the party committee is in a slower rate. 

Regression Analysis 

Multiple sets of regression models are analyzed for similarities, differences and interac-

tions between the local political elites and the party committee standing committees on 

the impact of education financial expenditures. Using Stata14.0 software to analyze the 

characteristics of the three leading subjects and the cross-sectional data of education 

fiscal expenditures of 283 prefecture-level administrative units in China in 2015, the 

regression results are shown in Table 2. All models passed the collinearity test, and the 

heteroscedasticity was processed by Weighted Least Squares (WLS) for models 1, 2, 

and 4 according to the White test results, and robust regression results were obtained. 

The six models in Table 2 reveal that prefecture-level officials and the local 

party committee members have a certain degree of influence on educational expendi-

tures, but after controlling for common variables; regression coefficient analysis indi-

cates that the mechanism of influence is not completely consistent. For example, in the 

regression model of the prefecture-level secretary, individual characteristics of the sec-

retary has no significant effect on the proportion of the education fiscal expenditure in 

GDP, but has a significant effect on the proportion of education fiscal expenditure in the 

general public budge expenditures. Specifically, the secretary from the minority nation-

ality has a significant negative impact on the education fiscal expenditure. Model 2 

showed that when the secretary is of minority nationality, then the expenditures in edu-

cation decrease by 1.3296%. In addition, the secretary who works in the household reg-

istration area is more likely to increase financial expenditures on education; that is, the 

secretary of the post has a geographical bias in the education and financial expenditure. 

It is worth noting that the faster the political promotion, the lower the support for educa-

tion finance; the reverse effect is particularly obvious. 

Judging from the regression model of prefecture-level mayors, the personal 

characteristics of the mayor have a significant impact on the proportion of education 

finance relative to GDP and fiscal expenditure. Models 3 and 4 show these results: con-

trolling for other conditions, women mayors increase education fiscal expenditures as a 

proportion of GDP by more than 0.5788% compared to male mayors. Fiscal expendi 

tures on education for minority nationality mayors show a complex relationship; the 

mayor of a minority nationality increases fiscal expenditures on education by 0.9591% 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 970 

Table 2. Regression Model of the effect of the Collective Characteris-
tics of Political Elites and Party Committees on Education Financial 
Expenditure. 

 

Secretary Mayor 
 

Standing Committee 
Collective 

Model 1 Model 2 Model 3 Model 4 
 

Model 5 Model 6 

EX_GDP EX_FE EX_GDP EX_FE 
 

EX_GDP EX_FE 

G 0.0651 -0.3164 0.5788** 1.0087 FS 0.0068 -0.0215 

-0.22 (-0.44) -2.15 -1.32 -0.65 (-0.83) 

N 0.5044 -1.3296*** 0.9591*** -0.9783* MS 0.0214*** -0.0237 

-1.15 (-2.77) -4.01 (-1.73) -3.45 (-1.55) 

A -0.0055 -0.0767 -0.016 -0.0319 A_A -0.0617 -0.0438 

(-0.25) (-1.04) (-0.54) (-0.44) (-1.13) (-0.32) 

EY -0.0095 -0.0125 -0.0652*** -0.0646 A_EY -0.1259* -0.1433 

(-0.49) (-0.22) (-2.68) (-1.13) (-1.81) (-0.83) 

EM 0.062 -0.2158 0.2418 0.054 PSS 0.0093** 0.0139 

-0.45 (-0.61) -1.62 -0.15 -2.23 -1.36 

SHRA -0.2068 0.7371** -0.1605 -0.7019* AP_SHRA 0.0057 0.0097 

(-1.59) -2.21 (-1.02) (-1.80) -1.23 -0.84 

CPT 0.0342 0.0828 0.0314 -0.0075 A_CPT 

  

0.0978 0.2381 

-0.82 -0.73 -0.61 (-0.06) -0.9 -0.89 

PR 

  

-1.0749 -92.8285*** -4.065 -25.8372 A_PR 

  

-32.1286* -98.0084** 

(-0.13) (-2.95) (-0.34) (-0.88) (-1.67) (-2.06) 

Per_GDP -0.2121*** -0.2582** -0.1960*** -0.3256*** Per_GDP -0.2219*** -0.2384** 

(-4.91) (-2.30) (-4.19) (-2.66) (-4.70) (-2.05) 

E -0.6477*** 0.2755 -0.4899** 0.476 E -0.4209* 0.4245 

(-2.89) -0.49 (-2.25) -0.8 (-1.90) -0.78 

C -0.9813*** -2.5500*** -1.0390*** -2.1664*** C -0.9761*** -2.1753*** 

(-4.53) (-5.14) (-5.36) (-4.23) (-4.95) (-4.47) 

PP -0.0005 0.0048*** -0.0002 0.0051*** PP -0.0007* 0.0048*** 

(-1.36) -5.23 (-0.53) -5.31 (-1.74) -4.82 

UR 

  

-0.0154** -0.0254 -0.0182** -0.0358* UR 

  

-0.0219*** -0.0462** 

(-2.23) (-1.37) (-2.30) (-1.80) (-2.68) (-2.29) 

PSE 0.0149 0.2487*** 0.0319* 0.2122*** PSE 0.0208 0.2334*** 

-1.06 -6.35 -1.81 -5.35 -1.18 -5.34 

FED 0.0317 -0.1722*** 0.0374* -0.1776*** FED 0.0550** -0.2757*** 

-1.55 (-3.06) -1.78 (-3.14) -2.31 (-4.69) 

FA 

  

-0.0200*** 0.0037 -0.0264*** 0.0121 FA 

  

-0.0183*** 0.0155 

(-4.88) -0.25 (-4.24) -0.81 (-2.81) -0.97 

Constant 

  

7.4100*** 23.8894*** 8.9141*** 21.6963*** Constant 

  

12.7566*** 25.3126*** 

-4.89 -4.95 -4.51 -4.48 -3.73 -3 

Observa-
tions 

283 283 283 283 
Observa-
tions 

283 283 

R-square 0.6 0.485 0.621 0.413 R-square 0.619 0.418 

Ad R2 0.576 0.454 0.598 0.378 Ad R2 0.596 0.383 

F 24.9212 15.6637 27.1867 11.7111 F 27.0424 11.9181 

t is the value in parentheses; * indicates p < 0.10, ** indicates p < 0.05, and *** indicates p < 0.01. 

 

 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 971 

of GDP, but reduces education finance relative to the proportion of fiscal expenditure 

by 0.9783%. Education expenditure is affected by the number of years of education the 

mayor has – where mayors have more education, less is spent on education. A signifi-

cant negative effect of a domicile serving mayor occurs, that is, the local mayor doesn’t 

have regional favoritism in the education financial expenditure, inversely, it restricts the 

education financial expenditure level.  

Judging from the regression model of the leaders of the prefecture-level stand-

ing committee, the collective characteristics of the standing committee of the party 

committee have a significant impact on the proportion of education finance relative to 

GDP and fiscal expenditure. In Models 5 and 6, it can be seen that gender structure, 

average age, average tenure, and average household registration ratio of the standing 

committee of the prefecture-level party committee do not significantly affect local edu-

cation fiscal expenditures. The proportion of minority nationalities, the average years of 

education, the professional background and the average rate of promotion all signifi-

cantly affect fiscal expenditure for education. Specifically, the party committee and the 

collective members of minority groups is positively correlated with proportion of edu-

cation expenditure relative to GDP, indicating that members of the standing committee 

of minority background are more likely to approve education expenditures. Prefecture-

level party committee members with more years of education on average are less likely 

to increase education spending. In the prefecture-level party committee collective, the 

more members that had a background in social sciences, the more the collective spent 

on education. In party committees that had a faster average promotion rate, the standing 

committee of the collective spent more on education. 

The collective characteristics of political elites and party committees have a 

consistent influence on expenditures in education. First, the national characteristics of 

the secretary, the mayor and the standing committee collectively have a significant and 

complex relationship to education expenditure. Models 2 and 4 showed that party secre-

taries and mayors from minority nationalities tend to reduce the proportion of education 

finances relative to local officials from the Han nationality. However, models 3 and 5 

indicate that officials from minority nationalities will reduce the proportion of fiscal 

expenditures relative to GDP. This shows that the identity of minority officials of local 

officials can increase the overall level of education and financial expenditures, whether 

for individual officials or standing committees. However, their efforts they exert are 

insufficient under the limited financial conditions, and they would like to use other 

basic public fiscal expenditures to take over the education finance. Second, both Models 

3 and 5 showed that the higher the education level of the officials, the less enthusiastic 

they are about financial expenditures on education. This shows that highly educated 

officials have high expectation of achievement and relatively strong promotion motiva-

tion. Third, models 2, 5, and 6 showed that the promotion rate of the secretary and the 

party committee is significantly negatively correlated with financial expenditures on 

education. This shows that with a better development situation, officials do not increase 

education expenditure; the secretary and the standing committee have similar views on 

promotion. Officials promotion assessment and non-financial situation of education 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 972 

occupies an important portion, education has not been given sufficient attention in local 

development. Fourth, regardless of whether the local political elite is an individual or a 

collective, financial expenditures on education are not affected by the age of the official 

or the length of the current term of office. 

The individual characteristics of the political elite and the party committee’s 

standing committee also have inconsistent effects on education expenditures. For exam-

ple, genders have inconsistent impact. Model 3 shows that female mayors can signifi-

cantly affect education expenditures, but models 5 and 6 show no significant gender 

effects in the standing committee. Secondly, the influence of professional background 

characteristics is inconsistent. Models 1, 2, 3, and 4 showed that the professional back-

ground of the secretary and the mayor does not have a significant effect on fiscal ex-

penditures in education, but model 5 shows that the collective professional structure of 

the standing committee does have a significant effect on the fiscal expenditure of educa-

tion. In particular, members of the standing committee with social science professional 

backgrounds have a strong preference for educational expenditures. Furthermore, the 

characteristics of serving in the household registration area or not does not affect this 

relationship. Model 2 and 3 show that a geographical favoritism exists for the secretary 

but the mayor that act in opposition. Models 5 and 6 show the standing committee of 

the collective centralized decision-making process, because the individual is subject to 

the influence of other officials of the standing committee, and such geographical favor-

itism disappears. This shows that the characteristics of the officials working in the 

household registration area have a significant impact on the education fiscal expenditure. 

However, due to inconsistent motivation and demand for the individual’s promotion, 

there is an inconsistent attitude toward the public fiscal expenditures on education. 

In general, influence of the political elite individual and the party committee 

standing committee on the educational fiscal expenditure is affected by nationality, 

years of education and the rate of promotion. Gender and working in the household reg-

istration area at the individual level also affect spending on education, but this effect 

disappears after the collective “personification” is taken into consideration. Professional 

background characteristics are not significant at the individual level of the political elite 

but are significant at the collective level. Age and term characteristics have no signifi-

cant effect. 

The Degree of Influence of Each Variable: ΔR
2
-based 

Calculation 

After comparing and analyzing the relationship between the personal characteristics of 

political elites and the influence of the collective characteristics of the standing commit-

tee on the fiscal expenditure of education, moreover for clarifying what the impact is of 

demographic characteristics and job experience characteristics on the education fiscal 

expenditure, and what specific characteristics have a critical impact on the fiscal ex-

penditure of education, we use ΔR
2
 (R Square Change)to analyze the amount of change 

index; which is majorly used to measure the impact of explanatory variables on the de- 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 973 

Table 3. R2 Change of the Effect of the Secretary’s Individual Charac-
teristics on the Financial Expenditure of Education. 

Dependent 

Variable 

Independent 

Variable 

Dimension 

R R2 AR2 SE 

Change Statistics 

ΔR2 F DF1 DF2 
Significant 

F 

Model 1 Demographic 

Characteristics 
0.23 0.053 0.036 1.857 0.053 3.108 5 277 0.01 

Job Experience 

Characteristics 
0.279 0.078 0.051 1.843 0.025 2.475 3 274 0.062 

Control Variables 0 .760 0.577 0.552 1.267 0.499 39.212 8 266 0 

Model 2 Demographic 

Characteristics 
0.111 0.012 

-

0.006 
3.784 0.012 0.685 5 277 0.635 

Job Experience 

Characteristics 
0 .263 0.069 0.042 3.693 0.057 5.598 3 274 0.001 

Control Variables 0.628 0.395 0.358 3.023 0.325 17.874 8 266 0 

DF: Degree of Freedom; AR2: Adjusted R2; SEE: Standard Error. 

 

 

Table 4. R-Variation of the Effect of the Mayor’s Individual Characteris-
tics on Education Financial Expenditure. 

Dependent 

Variable 

Independent 

Variable 

Dimension 

R R2 AR2 SE 

Change Statistics 

ΔR2 F DF1 DF2 Significant 

F 

Model 3 Demographic 

Characteristics 
0.371 0.137 0.122 1.773 0.137 8.823 5 277 0.000  

Job Experience 

Characteristics 
0.384 0.147 0.122 1.772 0.01 1.069 3 274 0.363  

Control Variables 0 .788 0.621 0.598 1.2 0.473 41.461 8 266 0.000  

Model 4 Demographic 

Characteristics 
0.16 0.025 0.008 3.759 0.025 1.447 5 277 0.208  

Job Experience 

Characteristics 
0 .182 0.033 0.005 3.764 0.008 0.735 3 274 0.532  

Control Variables 0.613 0.376 0.338 3.07 0.342 18.224 8 266 0.000  

DF: Degree of Freedom; AR2: Adjusted R2; SEE: Standard Error. 

 

 

Table 5. R-Variation of the Effect of the Collective Characteristics of 
the Standing Committee on the Education Financial Expenditure. 

Dependent 

Variable 

Independent 

Variable 

Dimension 

R R2 AR2 SE 

Change Statistics 

ΔR2 F DF1 DF2 
Significant 

F 

Model 5 Demographic 

Characteristics 
0.42 0.176 0.161 1.733 0.176 11.849 5 277 0.000  

Job Experience 

Characteristics 
0.444 0.197 0.174 1.72 0.021 2.383 3 274 0.070  

Control Variables 0 .787 0.619 0.596 1.202 0.422 36.867 8 266 0.000  

Model 6 Demographic 

Characteristics 
0 .260 0.067 0.051 3.677 0.067 4.004 5 277 0.002  

Job Experience 

Characteristics 
0.285 0.081 0.054 3.67 0.014 1.36 3 274 0.255  

Control Variables 0.646 0.418 0.383 2.965 0.336 19.207 8 266 0.000  

DF: Degree of Freedom; AR2: Adjusted R2; SEE: Standard Error. 

 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 974 

pendent variable contrast level (Chen & Huan, 2010; Hanaysha et al., 2011). It is a 

measure of the contribution of each dependent variable to the independent variables 

(Johnson et al., 2004). The calculation formula is: 

 

ΔR
2
 =R

2
current − R

2
previous 

 

Where current is a model with an additional explanatory variable but is other-

wise identical to the model previous. ΔR2 thus represents the contribution or additional 

explanatory power of the latest predictor variable on the dependent variable in the mod-

el interpretation. 

Based on the nature and connotation of official characteristic variables, this 

study divides the independent variables into three dimensions and brings them into the 

regression model. Gender, nationality, age, years of education and professional back-

ground variables represent basic information for the officer, referred to as demographic 

characteristics, while serving in the household area, current tenure and promotion rate, 

serving as official’s work experience characteristics. Socioeconomic background is 

used as the control variable. The ΔR
2
 in each dimension was calculated using SPSS 

24.0 and the results were presented below: 

Among the models, model 1 (Table 3) reveals that demographic characteristics 

of the secretary can explain 5.3% of education expenditure relative GDP (ΔR
2
 = 0.0053, 

n = 277, p < 0.05) and the explanatory power of the job characteristics is 7.8% (ΔR
2
 = 

0.025, n = 274, p < 0.1). Thus, secretary individual demographic characteristics and 

work experience characteristics have significant explanatory power on education ex-

penditure, with demographic characteristics explaining a greater proportion of educa-

tion spending than work experience characteristics. The secretary has a relatively strong 

effect on education financial expenditure, explaining 6.9% of the entire model (ΔR
2
 = 

0.057, n = 274, p < 0.01), while population statistical characteristics had no significant 

influence. This suggests that demographic and work experience characteristics of secre-

taries need to be paid peculiar attention because it will significantly explain the finan-

cial supply of local education. 

From Table 4, in individual statistical characteristics of the population, only 

the mayor had any influence on financial education (ΔR
2
 = 0.137, n = 277, p < 0.01). 

This shows that the influence of the individual characteristics of the mayor on the fi-

nancial expenditure in education mainly comes from its demographic characteristics, 

but the impact of work experience characteristics is relatively limited. 

In model 5 of the collective characteristics of the party standing committee on 

the proportion of education fiscal expenditure in GDP, demographic characteristics 

(ΔR
2
 = 0.176, n = 277, p < 0.01) and work experience characteristics (ΔR

2
 = 0.021, n = 

274, p < 0.1) are significant factors (Table 5). For the proportion of education fiscal 

expenditure in public fiscal expenditures, only demographic characteristics have signif-

icant influence (ΔR
2
 = 0.067, n = 277, p < 0.05). This shows that the characteristics of 

the two dimensions of the standing committee are important factors influencing the 

state of education fiscal expenditure, but comparing models 5 and 6 shows that demo- 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 975 

Table 6. The R2 Changes of the Secretary’s Individual Characteristics 
on the Fiscal Expenditure (% of GDP) of Education. 

Dependent 

Variable 

Independent 

Variable 

Dimension 

R R2 AR2 SE 

Adjusted Statistics 

ΔR2 F DF1 DF2 
Significant 

F 

Demographic 

Characteristics 
N 0.202 0.041 0.037 1.856 0.041 11.93 1 281 0.001  

EY 0.222 0.049 0.042 1.851 0.008 2.458 1 280 0.118  

A 0.226 0.051 0.041 1.853 0.002 0.540 1 279 0.463  

EM 0.228 0.052 0.038 1.855 0.001 0.356 1 278 0.551  

G 0.23 0.053 0.036 1.857 0.001 0.292 1 277 0.590  

Job experience 

Characteristics 
SHRA 0.257 0.066 0.046 1.848 0.013 3.843 1 276 0.051  

CPT 0 .266 0.071 0.047 1.847 0.005 1.342 1 275 0.248  

PR 0.279 0.078 0.051 1.843 0.007 2.213 1 274 0.138  

Control Varia-

ble  
0 .760 0.577 0.552 1.267 0.499 39.212 8 266 0.000  

DF: Degree of Freedom; AR2: Adjusted R2; SEE: Standard Error. 

 

 

Table 7. the R2 Changes of the Secretary’s Individual Characteristics 
on the Fiscal Expenditure of Education (The Proportion of Fiscal Ex-
penditure). 

Dependent 

Variable 

Independent 

Variable 

Dimension 

R R2 AR2 SE 

Adjusted Statistics 

ΔR2 F DF1 DF2 
Significant 

F 

Demographic 

Characteristics 
N 0.202 0.041 0.037 1.856 0.041 11.93 1 281 0.001  

EM 0.222 0.049 0.042 1.851 0.008 2.458 1 280 0.118  

EY 0.226 0.051 0.041 1.853 0.002 0.54 1 279 0.463  

G 0.228 0.052 0.038 1.855 0.001 0.356 1 278 0.551  

A 0.23 0.053 0.036 1.857 0.001 0.292 1 277 0.590  

Job Experience 

Characteristics 
PR 0.257 0.066 0.046 1.848 0.013 3.843 1 276 0.051  

SHRA 0 .266 0.071 0.047 1.847 0.005 1.342 1 275 0.248  

CPT 0.279 0.078 0.051 1.843 0.007 2.213 1 274 0.138  

Control Variable 
 

0 .760 0.577 0.552 1.267 0.499 39.212 8 266 0.000  

DF: Degree of Freedom; AR2: Adjusted R2; SE: Standard Error. 

 

 

 

 

graphic characteristics (ΔR
2
 = 0.176,  ΔR

2
 = 0.067) contribute more than do work expe-

rience characteristics (ΔR
2
 = 0.021,  ΔR

2
 = 0.014). This indicates that for the collective 

identity, demographic characteristics have stronger explanatory power, but it is not suf-

ficient to fully explain fiscal education supply factors if without consideration of the 

collective identity. 

Although it is known that it is necessary to focus on the demographic and ten-

ure characteristics of the secretary by calculating R
2
 change in each dimension, the de-

mographic characteristics of the mayor, and the demographic and work experiences 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 976 

Table 8. The R2 Changes in the Effect of the Mayor’s Individual Charac-
teristics on Educational Fiscal Expenditure (% of GDP). 

Dependent 

Variable 

Independent 

Variable 

Dimension 

R R2 AR2 SE 

Adjusted Statistics 

ΔR2 F DF1 DF2 
Significant 

F 

Demographic 

Characteristics 
N 0.322 0.103 0.1 1.795 0.103 32.419 1 281 0.000  

EM 0.346 0.12 0.113 1.781 0.016 5.151 1 280 0.024  

A 0.364 0.133 0.123 1.772 0.013 4.147 1 279 0.043  

EY 0.368 0.136 0.123 1.771 0.003 1.041 1 278 0.309  

G 0.371 0.137 0.122 1.773 0.002 0.518 1 277 0.472  

Job Experience 

Characteristics 
SHRA 0 .381 0.145 0.126 1.768 0.008 2.441 1 276 0.119  

CPT 0 .382 0.146 0.124 1.77 0.001 0.392 1 275 0.532  

PR 0 .384 0.147 0.122 1.772 0.001 0.386 1 274 0.535  

Control Variable   0 .788 0.621 0.598 1.2 0.473 41.461 8 266 0.000  

DF: Degree of Freedom; AR2: Adjusted R2; SE: Standard Error. 

 

 

Table 9. The R2 Changes of the Effect of the Mayor’s Individual Charac-
teristics on the Fiscal Expenditure of Education (The Proportion of 
Fiscal Expenditure). 

Dependent 

Variable 

Independent 

Variable 

Dimension 

R R2 AR2 SE 

Adjusted Statistics 

ΔR2 F DF1 DF2 
Significant 

F 

Demographic 

Characteristics 
N 0 .143 0.021 0.017 3.741 0.021 5.89 1 281 0.016  

G 0 .152 0.023 0.016 3.743 0.003 0.781 1 280 0.378  

EM 0 .156 0.024 0.014 3.747 0.001 0.317 1 279 0.574  

A 0 .160 0.025 0.011 3.752 0.001 0.31 1 278 0.578  

EY 0 .160 0.025 0.008 3.759 0 0 1 277 0.983  

Job Experience 

Characteristics 
SHRA 0 .174 0.03 0.99 3.756 0.005 1.34 1 276 0.248  

CPT 0 .179 0.032 0.007 3.76 0.002 0.518 1 275 0.472  

PR 0 .182 0.033 0.005 3.764 0.001 0.355 1 274 0.552  

Control Variable   0 .613 0.376 0.338 3.07 0.342 18.224 8 266 0.000  

DF: Degree of Freedom; AR2: Adjusted R2; SE: Standard Error. 

 

 

 

 

characteristics of the standing committee. However, we still do not know which charac-

teristic independent variables would produce the greatest impact on the fiscal expendi-

ture of education. Next, we use the stepwise method to calculate the ΔR
2
 of all charac-

teristic independent variables. 

Among the demographic characteristics, the contribution rate of nationality 

characteristics is the largest (ΔR
2
 = 0.041, n = 281, p < 0.01; Table 6). When combined 

with the regression coefficients in Table 2, it can be concluded that the secretary origi-

nated from minorities nationality will inhibit education expenditure to a large extent, 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 977 

Table 10. The R2 Changes of the Effect of the Collective Characteristics 
of the Standing Committee on the Education Fiscal Expenditure (GDP 
Ratio). 

Dependent 
Variable 

Independent 
Variable 
Dimension 

R R2 AR2 SE 
Adjusted Statistics 

ΔR2 F DF1 DF2 
Significant 
F 

Demographic 
Characteristics 

N 0 .143 0.021 0.017 3.741 0.021 5.89 1 281 0.016  

G 0 .152 0.023 0.016 3.743 0.003 0.781 1 280 0.378  

EM 0 .156 0.024 0.014 3.747 0.001 0.317 1 279 0.574  

A 0 .160 0.025 0.011 3.752 0.001 0.31 1 278 0.578  

EY 0 .160 0.025 0.008 3.759 0 0 1 277 0.983  

Job Experience 
Characteristics 

SHRA 0 .174 0.03 0.99 3.756 0.005 1.34 1 276 0.248  

CPT 0 .179 0.032 0.007 3.76 0.002 0.518 1 275 0.472  

PR 0 .182 0.033 0.005 3.764 0.001 0.355 1 274 0.552  

Control Variable   0 .613 0.376 0.338 3.07 0.342 18.224 8 266 0.000  

DF: Degree of Freedom; AR2: Adjusted R2; SE: Standard Error. 

 

 

Table 11. The R2 Changes of the Effect of the Collective Characteristics 
of the Standing Committee on the Fiscal Expenditure of Education 
(The Proportion of Fiscal Expenditure). 

Dependent 

Variable 

Independent 

Variable 

Dimension 

R R2 AR2 SE 

Adjusted Statistics 

ΔR2 F DF1 DF2 
Significant 

F 

Demographic 

Characteristics 

MS 0 .198 0.039 0.036 3.705 0.039 11.455 1 281 0.001  

PSS 0 .250 0.063 0.056 3.666 0.023 7.015 1 280 0.990  

A 0 .257 0.066 0.056 3.667 0.003 0.975 1 279 0.324  

EY 0 .259 0.067 0.054 3.671 0.001 0.38 1 278 0.538  

FS 0 .260 0.067 0.051 3.677 0 0.064 1 277 0.800  

Job Experience 

Characteristics 

PR 0 .269 0.072 0.052 3.674 0.005 1.48 1 276 0.225  

A_CPT 0 .280 0.079 0.055 3.668 0.006 1.849 1 275 0.175  

A_SHRA 0 .285 0.081 0.054 3.67 0.003 0.75 1 274 0.387  

Control Variable   0 .646 0.418 0.383 2.965 0.336 19.207 8 266 0.000  

DF: Degree of Freedom; AR2: Adjusted R2; SE: Standard Error. 

 

 

 

 

and that this feature should be focused more than any other demographic characteristics 

of the secretary. 

In the secretary’s tenure characteristics, the promotion rate contributed the 

largest component (ΔR
2
 = 0.052, n = 276, p < 0.01), making it the most important focus 

(Table 7). From this, it can be inferred that the secretary is overly concerned with per-

sonal political promotion, and this concern is unfavorable toward improving the fiscal 

expenditure on education. 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 978 

Tables 8 and 9 revealed that nationality in the demographic characteristics con-

tributed the most for the mayor (ΔR
2
 = 0.103, ΔR

2
 change = 0.021), along with the pro-

fessional background and age (ΔR
2
 = 0.016, ΔR

2
 = 0.013). This indicates that the dif-

ference in the individual characteristics of the mayor on education finance expenditure 

mainly comes from nationality, professional backgrounds, and age; but not the work 

experience characteristics. 

Among the collective demographic characteristics of the standing committee, 

the contribution rate of nationality is the largest (ΔR
2
 = 0.127, ΔR

2
 = 0.039; Table 10 

and 11, respectively), followed by professional background (ΔR
2
 = 0.023, ΔR

2
 = 0.023), 

and then the average years of education (ΔR
2
 = 0.011) and average age (ΔR

2
 = 0.013); 

in the work experience characteristics, the current tenure had the highest contribution 

(ΔR
2
 = 0.012, n = 276, p < 0.05). Thus, in the standing committee of the party commit-

tee, demographic characteristics are an important influencing factor on the state of edu-

cation fiscal expenditure, and its importance is greater than the characteristics of work 

experiences.  

By comparing ΔR
2
, it can be seen that the state of education fiscal expenditure 

is affected by the demographic characteristics of political elites and the collective char-

acteristics of the standing committee. Each subject has its own key characteristics; it is 

necessary to pay attention to the nationality characteristics and promotion rate of the 

secretary; the nationality, professional background, and age characteristics of the mayor; 

the nationality, professional background, average years of education, average age, and 

average years of service of the Standing Committee. It can also be found that nationality 

characteristics in the political elite and the party committee standing committee are al-

ways the more important factors affecting the state of education and financial expendi-

ture; for the collective, in addition to the nationality, the professional background, the 

average years of education, and the average age are also very important; in the impact 

of the tenure characteristics on the financial expenditure of education, the secretary is 

more likely to be affected by the rate of promotion, whereas the Standing Committee is 

more likely to be limited by the average length of current tenure. 

Discussion 

Regression results (Table 2) on the effects of the political elite’s individual characteris-

tics and the standing committee’s collective characteristics on expenditures on educa-

tion have similarities and differences. The ΔR
2
 in each dimension responds to which 

type of characteristic has a greater impact; the ΔR
2
 of each independent variable further 

presents the influence of each characteristic reflecting the importance and explanatory 

power of each feature. Based on the empirical analysis above, we draw four main con-

clusions as follows. 

First, local officials from minority nationalities can increase education fiscal 

expenditure in terms of the proportion of GDP, while at the same time restraining this 

expenditure relative to public fiscal expenditures. In fact, local officials from minority 

nationalities are mostly distributed in administrative areas with settlements of minority 

nationalities. Although the underdeveloped economic, the mandatory requirement of 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 979 

education, the regional education financial expenditure lever is higher than the overall 

economic development level, and occupies an important position. However, due to the 

urgent need for public financial expenditures in the construction of basic public facili-

ties and medical security in these areas, education has not maintained a priority in terms 

of limited public finances. This is exactly a direct reflection of the urgent needs in Chi-

na’s minority nationality areas, such as economic development and the contradictory 

public finance expenditures (Yao, 2008). It is precisely because of the realistic meaning 

of nationality, the characteristics of nationality have a high explanatory power, which, 

in turn, has a significant impact on both political elites and party committee members. 

Second, the years of education of local officials are negatively correlated with 

fiscal expenditures on education, i.e. officials with higher education levels do not pay 

attention to funding education. This result agrees with Tingjin Lin (2009), Ran Song 

(2016), and Dingxing Wang (2017) who also found that for mayor or prefecture-level 

city secretary, the higher the education level was, the less local education expenditure 

was. Thus, elites with higher education do not improve the local leaders’ passion for 

investing in public education. Instead, it implies that the diminishing marginal benefit 

of the official’s own education experiences produces a negative impact on the personal 

cognition. Local officials, no matter on the individual or collective level, have strong 

desire for the political promotion, therefore, the rate of promotion has a greater influ-

ence on the secretary’s decision-making of education fiscal expenditures, but this same 

effect is not significant for the mayor. The secretary has a stronger desire of promotion 

than the mayor, the reason is that the prefecture-level secretary is already the highest-

ranking official at the prefecture level, so the next promotion target is a breakthrough 

from the prefecture level to the provincial level, and subsequently the competition is 

obviously more intense than that of the peers at the same level, which eventually re-

quires more prominent political performance. Besides, given the restrictions on the age 

of promotion, they will easily neglect the public expenditure of education that generally 

has a lag of efficiency, and pay more attention to the “dominant” performance project in 

economic development. For the mayor, the next step is to promote further to the higher 

prefecture-level as a party committee secretary, the internal promotion base of the same 

level unit and the pressure are small, so, it is easier for them to take into account the 

education in the public fiscal expenditures, and to guarantee a certain fiscal expenditure 

in education. 

Third, the political elite has a geographically-biased effect at the individual 

level, i.e. in terms of the special demographic characteristics of gender and serving in 

the household registration area or not, individual political elites tend to bring in their 

own emotional factors to educational financial decision-making, confirming the results 

of Persson and Zhuravskaya (2016) and Yiming Wang (2015). Relatively speaking, the 

standing committee of the party can avoid personal sensibility in collective decision-

making, and is more likely to provide advice more rationally. 

Finally, the differences in the professional background of the local political 

elites at the individual level do not significantly lead to decision-making differences. 

However, at the collective level, due to the collective efforts, each member can express 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 980 

their own point of view on the basis of their personal cognition that depicts a significant 

impact of professional background, which exactly confirms the view that the local offi-

cials at the prefecture-level are “complementary” in administrative skills (Chen, 2017). 

Meanwhile, members of the Standing Committee who have the social science back-

ground are more inclined to spend on education than those with natural science back-

ground when make a decision collectively. This may be due to the impact of profes-

sional curriculum and professional ability, which makes them be more professional in 

interpreting local social phenomena and policies at length, and be greater in the prefer-

ence of education development. 

In summary, the prefecture-level government is affected by the different char-

acteristics of the secretary, mayor and standing committee of local party when deciding 

financial expenditure on education, but the chief executive effect of the secretary and 

the mayor changes during the operation of the democratic centralism. Comparative 

analysis of models and ΔR
2
 reveal that, individually, the political elites have only a few 

characteristics that have significant impact and explanatory power, but the Standing 

Committee has more collective characteristics that produce more significant influence 

and stronger explanatory power. This shows that the influence of the collective charac-

teristics of the Standing Committee on education expenditure is more significant. The 

potential reason for this may be attributed to the stronger promotion desire of the politi-

cal elite in comparison to the collective, and such promotion impulse has been “buff-

ered” to some extent in the collective decision-making process. This also proves, at 

least in part, that prefecture-level governments adhere to and implement the principle of 

democratic centralism in the local education fiscal expenditures such as providing edu-

cation as the public goods, and the collective decision-making under the leadership of 

the party committee plays a leading role in deciding the supply of education. 

Conclusions and Recommendations 

Based on the 2015 data of 283 prefecture-level administrative units in China, we found 

that local governments embody collective leadership in education finance decision-

making. Local political elites and party committee leaders have a significant impact on 

education expenditures, with the influence of the latter greater than that of the former. 

The way in which individual characteristics and collective characteristics affect educa-

tion fiscal expenditure is not completely consistent; however, nationality is always an 

important and significant influencing factor. 

Our findings not only have important theoretical significance, but also have 

crucial reference value to further improve the choice of local leadership behavior, to 

optimize of local education financial decision-making, to understand the influence of 

local party and government leaders on education finance and the behavioral motives of 

local officials under the “Chinese-style decentralization” system, and to improve the 

supply of local education, Based on this, we make the following brief policy recom-

mendations. 

First, rationally allocate of the structure of both local party and government of-

ficials and the standing committee, in order to reduce bias of education financial deci-



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 981 

sion-making. Our data showed that the demographic characteristics of both political 

elites and standing committees have significant impacts on the fiscal expenditure of 

education. The influence of the individual characteristics of political elites will be re-

stricted by other members of the collective, and their influence will change in collective 

decision-making. For example, the differences in the professional background of the 

local political elites at the individual level do not significantly lead to decision-making 

differences, but at the collective level it can produce significant impact; however, the 

localization of the political elite disappeared at the collective level of the party commit-

tee. Considering that officials with different characteristics have their own advantages, 

we believe that the Standing Committee with complementary “skills” and “characteris-

tics” should be able to comprehensively grasp the needs of local education development 

and rationally arrange local education and financial expenditures. Therefore, the leader-

ship team should be structured with special attention by combining the demographics 

and work experiences, and so strengthening the guarantee of financial expenditure for 

education from the composition of officials.  

Second, adhere to democratic centralism, give full play to the advantages of 

collective decision-making, and encourage stakeholders to participate in education and 

financial expenditure decision-making consultation. Our empirical results showed that 

the influence of local political elite characteristics on education expenditures is concen-

trated in a few individual characteristics, while the characteristics of standing collec-

tives are relatively uniform; that is, local governments insist on democratic concentra-

tion in educational financial decision-making – the embodiment of the system. Moreo-

ver, the political elite’s desire for political performance is significantly higher than that 

of the standing committee, indicating that officials may not fully guarantee their pub-

licity in decision-making. Therefore, in the decision-making process, the democratic 

system should be fully implemented, and the decision-making process strictly observed. 

The core leader, as the “squad leader” and the collective “squad”, must unite and work 

together to make a scientific and rational decision on education fiscal expenditure (Hu 

& Yang, 2018). 

Third, increase education fiscal support for the poverty-stricken areas, support-

ing financial assessment and supervising administrative measures to ensure education 

“precise poverty alleviation”. In the individual model of the political elite and the col-

lective model of the standing committee, nationality characteristic has the greatest ex-

planatory power. As mentioned above, there exists dilemma of education fiscal ex-

penditure in the underdeveloped minority nationality areas In recent years, a series of 

education poverty alleviation policies such as the “Poverty Alleviation and Implementa-

tion Program for Deprivation of Poverty in Deep Poverty Areas (2018-2020)” are 

strengthening education support for minority nationalities, and guarantee special funds 

for education and local government funds to be timely available will enable the goal of 

education financial support to be truly achieved (The Ministry of Education’s State 

Council Office, 2018). Therefore, The Third-party Evaluation Agencies should be cre-

ated to guarantee an open and transparent process to improve the financial situation of 

education in poverty-stricken areas. 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 982 

Fourth, innovate better evaluation mechanisms for appointment and removal of 

local government officials, convert public satisfaction with the education supply situa-

tion into performance appraisal and appointment criteria, and encourage local govern-

ments to increase education expenditure. Our empirical study revealed that government 

spending behavior on education finance varies by geographical, nationality and other 

social logic, promotion and other bureaucratic logic and by personnel incentives and 

other marketing logic. As the attitudes of official education expenditure are easily af-

fected by personnel evaluation systems, so we recommend reforming the organization 

and personnel system as a starting point, it is possible to start with the reform of the 

organization and personnel system, start with “incentive engagement”, and innovate in 

inspiring and restricting government behavior, and improve the enthusiasm of local 

governments in education and financial investment. For example, the provision of edu-

cation as a “soft” public goods is included in the performance evaluation - not only the 

performance during the current term, but also the prior performance to avoid the short-

term surface project, and give far greater weight of public satisfaction etc., so as to form 

a multi-faceted assessment system, to build up local government and diversified action 

logic, and to promote local governments to make reasonable behavioral choices in pub-

lic education supply. 

 

 

 

 

Notes 

1. For convenience, this article refers to the mayor, the governor, the governor, and the 
executive head of the General Administration of Administration as the mayor. 

2. Among the 334 prefecture-level administrative units, there are 291 prefecture-level 
cities, 10 regions, 30 autonomous prefectures, and 3 alliances. There are 20 prefec-
ture-level administrative units with serious socio-economic data missing: Alashan 
League, Shannan Distric , Sansha City, Shigatse City, Ganzi Prefecture, Nagqu Dis-
trict, Liangshan Prefecture, Ali District, Qiannan Prefecture, Linzhi City, Wenshan 
state, Golog prefecture, Chuxiong, Yushu prefecture, Diqing, Haixi, Lhasa, 
Kezilesukeerkezi states, Chamdo, Turpan City. 

3. Delete 24 samples of missing features of the secretary or executive head, namely Shen-
yang City, Benxi City, Dandong City, Jinzhou City, Panjin City, Jilin City, Siping City, 
Liaoyuan City, Tonghua City, Songyuan City, Daxinganling Region, Zhangzhou City, 
Putian City, Sanming City, Nanping City, Xinyu City, Jieyang City, Yuxi City, Baoshan 
City, Zhaotong City, Nujiang Prefecture, Hainan Tibetan Autonomous Prefecture, 
Shizuishan City, Yili Kazakh Autonomous Prefecture. 

4. Excluding the seven outlier samples of education fiscal expenditure as a percentage of 
GDP: Huangnan, Linxia, Gannan, Dingxi, Guyuan, Kashgar, and Hotan. 

 

 

 



Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 983 

Acknowledgement: The author is grateful to Dr. Jingping Sun, Associate Professor of the University 
of Alabama, and Professor Huang Bin of Nanjing University of Finance and Economics for their 
guidance and assistance during the writing process. This article was reported at the annual meeting of 
the China Education Finance Professional Committee in 2018 and won the third prize for outstanding 
papers. The author would like to thank the anonymous reviewers of the Education Finance Annual 
Conference for their review. 
 

 

 

 

 

 

 

References

Alesina, A. F., Troiano, U., & Cassidy, T. 

(2015). Old and young politicians (No. 

w20977). National Bureau of Economic Re-
search. DOI: 

https://doi.org/10.3386/w20977  

Blanchard, O., & Shleifer, A. (2001). Federalism 

with and without political centralization: 

China versus Russia. IMF Staff Papers, 

48(1):171-179. 

https://doi.org/10.3386/w7616  

Cai, R. & Yao, J.J. (2018). An empirical study 

on the influence of the collective characteris-

tics of the standing committee of the party 

committees at the level on the educational 

expenditure of education. Research in Edu-
cational Development, 38(17):15-20+42. 

[Chinese] DOI: 

https://www.cnki.com.cn/Article/CJFDTotal

-SHGJ201817007.htm  

Cao, C., Ma, L., & Shen, X. (2014). Financial 

pressure, promotion pressure, official tenure 

and excessive investment by local state-

owned enterprises. China Economic Quar-
terly, 13(4):1415-1436. 

Chen H.R., & Huang H.L. (2010). User ac-

ceptance of mobile knowledge management 

learning system: Design and analysis. Edu-
cational Technology & Society, 13(3):70-77. 

Chen, S., Zhou, S., & Lu, S. (2017). Official 

professional collocation and urban economic 

development: “skill complementarities” or 

“cognitive conflict”. Economic Perspectives, 

2017(11): 88-103. [Chinese] 

https://www.cnki.com.cn/Article/CJFDTotal

-JJXD201711008.htm  

Fu, Y., & Zhang, Y. (2007). Chinese-style de-

centralization and fiscal expenditure struc-

ture bias: the cost of competition for growth. 

Management World, 2007(3):4-12+22. 

[Chinese] DOI: 

https://doi.org/10.19744/j.cnki.11-

1235/f.2007.03.002  

Government Central Committee. (1993). State 

education funding system for monitoring the 

implementation of (Trial). 

Hanaysha, J.R.M., Abdullah H.H. & Warokka, 

A. (2011). Service quality and students’ sat-

isfaction at higher learning institutions: The 

competing dimensions of Malaysian univer-

sities’ competitiveness. The Journal of 
Southeast Asian Research, 1-10. DOI: 

http://dx.doi.org/10.5171/2011.855931  

Hu, A., & Yang, Z. (2018). Innovative Chinese 

collective leadership system. Information for 
Decisions Magazine, 1101(6):16. [Chinese] 

https://www.cnki.com.cn/Article/CJFDTotal

-JJDK201709005.htm  

Jiang, Y., & Yi, W. (2017). Regional differences, 

characteristics of local officials and behav-

iors of educational expenditure. Journal of 
Guangdong University of Finance & Eco-
nomics, 32(06):58-66. 

Johnson, J. W., & Lebreton, J. M. (2004). Histo-

ry and use of relative importance indices in 

organizational research. Organizational Re-

https://doi.org/10.3386/w20977
https://doi.org/10.3386/w7616
https://www.cnki.com.cn/Article/CJFDTotal-SHGJ201817007.htm
https://www.cnki.com.cn/Article/CJFDTotal-SHGJ201817007.htm
https://www.cnki.com.cn/Article/CJFDTotal-JJXD201711008.htm
https://www.cnki.com.cn/Article/CJFDTotal-JJXD201711008.htm
https://doi.org/10.19744/j.cnki.11-1235/f.2007.03.002
https://doi.org/10.19744/j.cnki.11-1235/f.2007.03.002
http://dx.doi.org/10.5171/2011.855931
https://www.cnki.com.cn/Article/CJFDTotal-JJDK201709005.htm
https://www.cnki.com.cn/Article/CJFDTotal-JJDK201709005.htm


Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 984 

search Methods, 7(3):238-257. DOI: 

https://doi.org/10.1177/1094428104266510  

Li, H., & Zhou, L. (2005). Political turnover and 

economic performance: the incentive role of 

personnel control in China. Journal of Pub-
lic Economics, 89(9-10):1743-1762. DOI: 

https://doi.org/10.1016/j.jpubeco.2004.06.00

9  

Lin, T. (2009). The influence of mayors of pre-

fecture level cities on expenditure of educa-

tion within the budget. Journal of Public 
Administration, 1(1):175-190+205-206. 

[Chinese] 

https://doi.org/10.3969/j.issn.1674-

2486.2009.01.010  

Lin, T. J. (2009). The influence of prefecture-

level city mayors on budgetary education 

expenditures. Public Administration Review, 

2(1):175-190. 

National Education Commission of the National 

Bureau of Statistics. (1993). National Educa-

tion Funds Implementation Monitoring Sys-

tem (Trial). 

Olson, M.L. (2014). Translated by Chen, Y., 

Guo, Y., & Li, C. The logic of collective ac-

tion. Shanghai: Gezhi Publishing House: 

Shanghai People’s Publication. 

Persson, P., & Zhuravskaya, E. (2016). The 

limits of career concerns in federalism: Evi-

dence from China. Journal of the European 
Economic Association, 14(2):338–374. 

http://citeseerx.ist.psu.edu/viewdoc/downloa

d?doi=10.1.1.683.9371&rep=rep1&type=pdf  

Qian, Y., & Weingast, B.R. (1996). China’s 

transition to markets: Market-preserving 

federalism, Chinese style. Journal of Policy 
Reform, 1(2):149-185. DOI: 

https://doi.org/10.1080/13841289608523361  

Qiao, B., Fan, J., & Feng, X. (2005). China’s 

fiscal decentralization and compulsory pri-

mary education. Social Sciences in China, 

2005(6): 37-46+206. [Chinese] 

http://lib.cufe.edu.cn/upload_files/other/4_2

0140526033222_72_%E4%B8%AD%E5%9

B%BD%E7%9A%84%E8%B4%A2%E6%9

4%BF%E5%88%86%E6%9D%83%E4%B8

%8E%E5%B0%8F%E5%AD%A6%E4%B9

%89%E5%8A%A1%E6%95%99%E8%82

%B2_%E4%B9%94%E5%AE%9D%E4%B

A%91.pdf  

Song, R., & Chen, G. (2016). Official character-

istics, experience and local government edu-

cation expenditure preference: Evidence 

from Chinese prefectural cities. Business 
Management Journal, 38(12):149-169. 

[Chinese] 

https://www.cnki.com.cn/Article/CJFDTotal

-JJGU201612014.htm  

The Ministry of Education’s State Council Of-

fice of Poverty Alleviation issued the “Im-

plementation Plan for Poverty Alleviation in 

Deep Poverty Areas (2018-2020)”. 2018-7-

15, 

http://www.cpad.gov.Cn/art/2018/2/27/art_4

6_79213.html  

Tian, D., & Yu, Q. (2017). The influence of 

background characteristics of top manage-

ment on corporate green innovation. Re-
search on Financial and Economic Issues, 

2017(6):108-113. [Chinese] 

https://www.cnki.com.cn/Article/CJFDTotal

-CJWT201706016.htm  

Wang, D. (2017). Characteristics of local offi-

cials and public expenditure. Journal of 
Nanjing University of Finance and Econom-
ics, 2017(4):36-46. [Chinese] 

https://www.cnki.com.cn/Article/CJFDTotal

-NJJJ201704005.htm  

Wang, X., & Xu, X. (2008). Source, destination, 

tenure and economic growth of local offi-

cials: evidence from the provincial party sec-

retary of China. Management World, 

2008(3):16-26. [Chinese] 

https://doi.org/10.19744/j.cnki.11-

1235/f.2008.03.003  

Wang, X., & Xu, X. (2009). Political incentives, 

fiscal decentralization and economic behav-

ior of local officials in the transition period. 

Nankai Economic Studies, 2009(2):58-79. 

[Chinese] 

https://www.cnki.com.cn/Article/CJFDTotal

-NKJJ200902007.htm  

Wang, X., & Zhou, J. (2013). Heterogeneity of 

local officials and performance of public 

service supply. South China Journal of Eco-
nomics, 2013(11):47-59. [Chinese] 

https://doi.org/10.19592/j.cnki.scje.2013.11.

005  

Wang, Y., Liu, Z., & Yang, Y. (2015). Regional 

hemiplegia and education supply of local of-

ficials. Business Management Journal, 

https://doi.org/10.1177/1094428104266510
https://doi.org/10.1016/j.jpubeco.2004.06.009
https://doi.org/10.1016/j.jpubeco.2004.06.009
https://doi.org/10.3969/j.issn.1674-2486.2009.01.010
https://doi.org/10.3969/j.issn.1674-2486.2009.01.010
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.683.9371&rep=rep1&type=pdf
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.683.9371&rep=rep1&type=pdf
https://doi.org/10.1080/13841289608523361
http://lib.cufe.edu.cn/upload_files/other/4_20140526033222_72_%E4%B8%AD%E5%9B%BD%E7%9A%84%E8%B4%A2%E6%94%BF%E5%88%86%E6%9D%83%E4%B8%8E%E5%B0%8F%E5%AD%A6%E4%B9%89%E5%8A%A1%E6%95%99%E8%82%B2_%E4%B9%94%E5%AE%9D%E4%BA%91.pdf
http://lib.cufe.edu.cn/upload_files/other/4_20140526033222_72_%E4%B8%AD%E5%9B%BD%E7%9A%84%E8%B4%A2%E6%94%BF%E5%88%86%E6%9D%83%E4%B8%8E%E5%B0%8F%E5%AD%A6%E4%B9%89%E5%8A%A1%E6%95%99%E8%82%B2_%E4%B9%94%E5%AE%9D%E4%BA%91.pdf
http://lib.cufe.edu.cn/upload_files/other/4_20140526033222_72_%E4%B8%AD%E5%9B%BD%E7%9A%84%E8%B4%A2%E6%94%BF%E5%88%86%E6%9D%83%E4%B8%8E%E5%B0%8F%E5%AD%A6%E4%B9%89%E5%8A%A1%E6%95%99%E8%82%B2_%E4%B9%94%E5%AE%9D%E4%BA%91.pdf
http://lib.cufe.edu.cn/upload_files/other/4_20140526033222_72_%E4%B8%AD%E5%9B%BD%E7%9A%84%E8%B4%A2%E6%94%BF%E5%88%86%E6%9D%83%E4%B8%8E%E5%B0%8F%E5%AD%A6%E4%B9%89%E5%8A%A1%E6%95%99%E8%82%B2_%E4%B9%94%E5%AE%9D%E4%BA%91.pdf
http://lib.cufe.edu.cn/upload_files/other/4_20140526033222_72_%E4%B8%AD%E5%9B%BD%E7%9A%84%E8%B4%A2%E6%94%BF%E5%88%86%E6%9D%83%E4%B8%8E%E5%B0%8F%E5%AD%A6%E4%B9%89%E5%8A%A1%E6%95%99%E8%82%B2_%E4%B9%94%E5%AE%9D%E4%BA%91.pdf
http://lib.cufe.edu.cn/upload_files/other/4_20140526033222_72_%E4%B8%AD%E5%9B%BD%E7%9A%84%E8%B4%A2%E6%94%BF%E5%88%86%E6%9D%83%E4%B8%8E%E5%B0%8F%E5%AD%A6%E4%B9%89%E5%8A%A1%E6%95%99%E8%82%B2_%E4%B9%94%E5%AE%9D%E4%BA%91.pdf
http://lib.cufe.edu.cn/upload_files/other/4_20140526033222_72_%E4%B8%AD%E5%9B%BD%E7%9A%84%E8%B4%A2%E6%94%BF%E5%88%86%E6%9D%83%E4%B8%8E%E5%B0%8F%E5%AD%A6%E4%B9%89%E5%8A%A1%E6%95%99%E8%82%B2_%E4%B9%94%E5%AE%9D%E4%BA%91.pdf
http://lib.cufe.edu.cn/upload_files/other/4_20140526033222_72_%E4%B8%AD%E5%9B%BD%E7%9A%84%E8%B4%A2%E6%94%BF%E5%88%86%E6%9D%83%E4%B8%8E%E5%B0%8F%E5%AD%A6%E4%B9%89%E5%8A%A1%E6%95%99%E8%82%B2_%E4%B9%94%E5%AE%9D%E4%BA%91.pdf
https://www.cnki.com.cn/Article/CJFDTotal-JJGU201612014.htm
https://www.cnki.com.cn/Article/CJFDTotal-JJGU201612014.htm
http://www.cpad.gov.cn/art/2018/2/27/art_46_79213.html
http://www.cpad.gov.cn/art/2018/2/27/art_46_79213.html
https://www.cnki.com.cn/Article/CJFDTotal-CJWT201706016.htm
https://www.cnki.com.cn/Article/CJFDTotal-CJWT201706016.htm
https://www.cnki.com.cn/Article/CJFDTotal-NJJJ201704005.htm
https://www.cnki.com.cn/Article/CJFDTotal-NJJJ201704005.htm
https://doi.org/10.19744/j.cnki.11-1235/f.2008.03.003
https://doi.org/10.19744/j.cnki.11-1235/f.2008.03.003
https://www.cnki.com.cn/Article/CJFDTotal-NKJJ200902007.htm
https://www.cnki.com.cn/Article/CJFDTotal-NKJJ200902007.htm
https://doi.org/10.19592/j.cnki.scje.2013.11.005
https://doi.org/10.19592/j.cnki.scje.2013.11.005


Cai & Zhang. Impact of Individual Political Elites and Educational Fiscal Expenditure in China. 

Vol.7, No. 2, 2021 985 

37(8):12-22. [Chinese] 

https://doi.org/10.19616/j.cnki.bmj.2015.08.

004  

Xu, C. (2011). The fundamental institutions of 

China’s reforms and development. Journal 
of Economic Literature, 49(4):1076-1151. 

[Chinese] DOI: 

https://doi.org/10.1257/jel.49.4.1076  

Yang, B., Wang, N., & Zhang, Z. (2014). Analy-

sis of the theoretical basis of collective lead-

ership. Chinese Journal of Management, 
11(10):1428-1435. [Chinese] DOI: 

https://doi.org/10.3969/j.issn.1672-

884x.2014.10.003  

Yang, Q., & Zheng, N. (2013). Local leadership 

promotion competition is a ruler, tournament 

or qualifying competition. The Journal of 
World Economy, 36(12): 130-156. [Chinese] 

https://www.cnki.com.cn/Article/CJFDTotal

-SJJJ201312008.htm  

Yao, J. (2008). Governance of China’s decen-

tralization and balanced development of ed-

ucation. Nanjing Journal of Social Sciences, 

2008(8): 119-125. [Chinese] DOI: 

https://doi.org/10.3969/j.issn.1001-

8263.2008.08.020  

Yu, Z. (2017). Local government and public 

education – From the perspective of fiscal 

decentralization. GuangZhou: Social Science 

Literature Publication Press. 

Zhang, J. (2008). Decentralization and growth: 

The story of China. China Economic Quar-
terly, 7(1):21-52. [Chinese] 

https://www.airitilibrary.com/Publication/al

DetailedMesh?docid=a0000151-200710-7-

1-21-52-a  

Zhang, Y. (2014). Leadership team heterogenei-

ty, conflict and management strategy in the 

background of collective leadership. Leader-
ship Science, 2014(8):52-53. [Chinese] DOI: 

https://doi.org/10.19572/j.cnki.ldkx.2014.08.

016  

Zhou, F. (2006). Ten years of tax distribution 

system: System and its influence. Social Sci-
ences in China, 2006(6):100-115+205. [Chi-

nese] 

http://www.shehui.pku.edu.cn/upload/editor/

file/20171116/20171116092221_5559.pdf  

Zhou, L., Li, H., & Wei, C. (2005). Relative 

performance appraisal: An empirical study 

on the promotion mechanism of local offi-

cials in China. Journal of Economics, 

1(1):83-96. [Chinese] 

https://www.researchgate.net/profile/Li_An_

Zhou/publication/281365130_Relative_Perf

ormance_Evaluation_An_Empirical_Analysi

s_of_Turnover_of_Chinese_Local_Officials/

links/5743a10b08ae298602f0f21c/Relative-

Performance-Evaluation-An-Empirical-

Analysis-of-Turnover-of-Chinese-Local-

Officials.pdf  

Zhu, X., & Hu, X. (2014). Institutionalization of 

democratic centralism: A comprehensive 

study of leadership system, institutional sys-

tem and working mechanism. Marxism & 
Reality, 2014(3):13-19. [Chinese] DOI: 

https://doi.org/10.15894/j.cnki.cn11-

3040/a.2014.03.031 

Received: 24 February 2021 
Revised: 12 March 2021 

Accepted: 17 March 2021 
 

 

 

https://doi.org/10.19616/j.cnki.bmj.2015.08.004
https://doi.org/10.19616/j.cnki.bmj.2015.08.004
https://doi.org/10.1257/jel.49.4.1076
https://doi.org/10.3969/j.issn.1672-884x.2014.10.003
https://doi.org/10.3969/j.issn.1672-884x.2014.10.003
https://www.cnki.com.cn/Article/CJFDTotal-SJJJ201312008.htm
https://www.cnki.com.cn/Article/CJFDTotal-SJJJ201312008.htm
https://doi.org/10.3969/j.issn.1001-8263.2008.08.020
https://doi.org/10.3969/j.issn.1001-8263.2008.08.020
https://www.airitilibrary.com/Publication/alDetailedMesh?docid=a0000151-200710-7-1-21-52-a
https://www.airitilibrary.com/Publication/alDetailedMesh?docid=a0000151-200710-7-1-21-52-a
https://www.airitilibrary.com/Publication/alDetailedMesh?docid=a0000151-200710-7-1-21-52-a
https://doi.org/10.19572/j.cnki.ldkx.2014.08.016
https://doi.org/10.19572/j.cnki.ldkx.2014.08.016
http://www.shehui.pku.edu.cn/upload/editor/file/20171116/20171116092221_5559.pdf
http://www.shehui.pku.edu.cn/upload/editor/file/20171116/20171116092221_5559.pdf
https://www.researchgate.net/profile/Li_An_Zhou/publication/281365130_Relative_Performance_Evaluation_An_Empirical_Analysis_of_Turnover_of_Chinese_Local_Officials/links/5743a10b08ae298602f0f21c/Relative-Performance-Evaluation-An-Empirical-Analysis-of-Turnover-of-Chinese-Local-Officials.pdf
https://www.researchgate.net/profile/Li_An_Zhou/publication/281365130_Relative_Performance_Evaluation_An_Empirical_Analysis_of_Turnover_of_Chinese_Local_Officials/links/5743a10b08ae298602f0f21c/Relative-Performance-Evaluation-An-Empirical-Analysis-of-Turnover-of-Chinese-Local-Officials.pdf
https://www.researchgate.net/profile/Li_An_Zhou/publication/281365130_Relative_Performance_Evaluation_An_Empirical_Analysis_of_Turnover_of_Chinese_Local_Officials/links/5743a10b08ae298602f0f21c/Relative-Performance-Evaluation-An-Empirical-Analysis-of-Turnover-of-Chinese-Local-Officials.pdf
https://www.researchgate.net/profile/Li_An_Zhou/publication/281365130_Relative_Performance_Evaluation_An_Empirical_Analysis_of_Turnover_of_Chinese_Local_Officials/links/5743a10b08ae298602f0f21c/Relative-Performance-Evaluation-An-Empirical-Analysis-of-Turnover-of-Chinese-Local-Officials.pdf
https://www.researchgate.net/profile/Li_An_Zhou/publication/281365130_Relative_Performance_Evaluation_An_Empirical_Analysis_of_Turnover_of_Chinese_Local_Officials/links/5743a10b08ae298602f0f21c/Relative-Performance-Evaluation-An-Empirical-Analysis-of-Turnover-of-Chinese-Local-Officials.pdf
https://www.researchgate.net/profile/Li_An_Zhou/publication/281365130_Relative_Performance_Evaluation_An_Empirical_Analysis_of_Turnover_of_Chinese_Local_Officials/links/5743a10b08ae298602f0f21c/Relative-Performance-Evaluation-An-Empirical-Analysis-of-Turnover-of-Chinese-Local-Officials.pdf
https://www.researchgate.net/profile/Li_An_Zhou/publication/281365130_Relative_Performance_Evaluation_An_Empirical_Analysis_of_Turnover_of_Chinese_Local_Officials/links/5743a10b08ae298602f0f21c/Relative-Performance-Evaluation-An-Empirical-Analysis-of-Turnover-of-Chinese-Local-Officials.pdf
https://www.researchgate.net/profile/Li_An_Zhou/publication/281365130_Relative_Performance_Evaluation_An_Empirical_Analysis_of_Turnover_of_Chinese_Local_Officials/links/5743a10b08ae298602f0f21c/Relative-Performance-Evaluation-An-Empirical-Analysis-of-Turnover-of-Chinese-Local-Officials.pdf
https://doi.org/10.15894/j.cnki.cn11-3040/a.2014.03.031
https://doi.org/10.15894/j.cnki.cn11-3040/a.2014.03.031

	OriginalArticle-RuCai-BECE_title_March2021
	OriginalArticleArticle-RuCai-BECE_MaintextMarch2021

