







































 

 

 

 

 

Does the Salary of Elementary and Middle 

School Teachers Affect Students’ 

Participation in Extracurricular Tutoring?
§

Haiping Xue,
1
 Xiang Gao,

1
 Aiai Fan

2
 

 
1. Capital Normal University, Beijing 100048, China 

2. Peking University, Beijing 100871, China 

Abstract. Based on the data of China Family Panel Studies 2016 (CFPS 

2016), this study analyzed the effect of teacher wage index on students’ 

participation in extracurricular tutoring through a two-layer linear 
model. We found that the wage index of elementary and middle schools 

teachers in China is generally low, and this index had a significant 

negative impact on students’ participation in extracurricular tutoring, 
i.e., the lower the teacher’s wage index, the higher the participation rate 

of students’ extracurricular tutoring. Governments at all levels should 
increase financial investment in elementary and middle schools teach-

ers’ salaries. Efforts to improve the salary of elementary and middle 

schools teachers upon the teacher’s wage index as a reference will help 
to reduce the supply and demand of extracurricular tutoring in the basic 

education in China, and will also facilitate the implementation of the 
policy of prohibiting in-service teachers from participating in extracur-

ricular tutoring. 

Best Evid Chin Edu 2020; 6(1):769-787. 

Doi: 10.15354/bece.20.ar065. 

How to Cite: Xue, H., Gao, X., & Fan, A. (2020). Does the salary of elementary and 

middle school teachers affect students’ participation in extracurricular tutoring?  

Best Evidence in Chinese Education, 6(1):769-787. 

Keywords: Extracurricular Tutoring; Teacher Salary; Wage Index

 
 
 
 

§: The original Chinese version has been abridged due to the limited printing layout. In this article, the original 
content that has been deleted is also published. 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No.1, 2020 770 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

About the Author: Xiang Gao, Doctorate Candidate, School of Education, Capital Normal University, Beijing 
100048, China. Email: 2180401008@cnu.edu.cn. 
Correspondence to: Haiping Xue, Director, Professor, Institute of Educational Economics and Management, 

School of Education, Capital Normal University, Beijing 100048, China. Email: xuehaiping_416@163.com; 

or 

Aiai Fan, Associate Editor, School of education, Peking University, Beijing 100871, China. Email: 
fanaa@pku.edu.cn 

Funding: This study was supported by the National Science Foundation of China (NSFC) main project “Family 
Capital, Shadow Education and Social Reproduction” (Project #: 71774112) and Beijing Social Science Fund 

Research Base Key Project: From School Education to Shadow Education: Educational Competition and Social 

Reproduction (Project #: 15JDJYA007). 

Conflict of Interests: None. 
 

© 2020 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. 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 771 

N recent years, extracurricular tutoring has become a hot social issue that concerns 

the government, students and parents. Among them, paid tutoring by in-service 

teachers is a focus problem that the government, society and schools have been pay-

ing close attention to and trying to solve. Some studies have found that teacher salary 

was closely related to students’ participation in extracurricular tutoring (Brehm et al., 

2012; Sujatha & Rani, 2011). Investigation of the relationship between teachers’ salary 

level and students’ participation in extracurricular tutoring will help to understand the 

phenomenon of in-service teacher’s paid tutoring, and it will provide a reference for the 

Chinese government to handle effectively the extracurricular tutoring and paid tutoring 

for in-service teachers. 

Studies found that low salary is a major reason for teachers to participate in ex-

tracurricular tutoring. Researchers found that some in-service school teachers in coun-

tries such as Cambodia, Mauritius and Romania got paid tutoring for students, and the 

official salary of teachers in these countries was very low (Bray et al., 2013; Foondun, 

2002; Popa & Acedo, 2003). Studies by Brehm, Sujatha, and Rani found that in Cam-

bodia and India, many teachers provide extracurricular tutoring to supplement their in-

come (Brehm et al., 2012; Sujatha & Rani, 2011). In Shanghai of China, Zhang and 

Bray discovered through questionnaires and interviews that urban teachers are facing 

increasing economic pressure, and many of them got additional income through shadow 

education. The survey included 548 students in Shanghai, of them 35.8% had received 

tutoring in their teachers’ homes, and 26.1% had received tutoring at schools. During 

the interview, they found that some of the teachers’ colleagues participated in paid tu-

toring outside the classroom, and all the school principals interviewed expressed sym-

pathy for their teachers’ participation in the tutoring even they got the so-called medium 

salary (Zhang & Bray, 2017). 

The in-service teachers will gain income through direct participation in tutoring 

and referral to counseling agencies for getting commission. Bray et al. (2018) found that 

in Siem Reap Province, central Cambodia, almost all extracurricular tutoring is provid-

ed by school teachers rather than commerce, and teachers are usually responsible for the 

same group of students in the school. In addition to direct participation, some school 

teachers play an intermediary role. Zhang and Bray’s survey in Shanghai showed that 

nearly one-third of the students surveyed said that their tutoring information was from 

their teachers, through which some teachers got commission by introducing students to 

counseling agencies (Zhang & Bray, 2017). 

In-service teacher is the classroom leader of school education, so if they direct-

ly or indirectly participate in paid tutoring, they will encourage students and parents to 

participate in tutoring. In-service teacher’s paid tutoring will bring “benefits” to partici-

pating students, and it will be “unfavorable” to those who do not participate in teachers’ 

tutoring. In a survey conducted in Bangladesh in 2017, some students mentioned that 

receiving tutoring from school teachers would receive extra benefits, including answer-

ing skills set by these teachers (Mahmud et al., 2017). Gok’s investigation report in 

Turkey highlighted a teacher’s case, in which the teacher clearly told the students: “You 

didn’t take my private class, so I don’t talk to you anymore” (Gök, 2010). Kodakos and 

I 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 772 

Fragiskos pointed out that the paid tutoring of in-service teacher has the risk of conceal-

ing the content of the classroom to promote their tutoring needs. They emphasized that 

when in-service teachers are also extracurricular tutors, they would use the “Margin 

Management Model”, that is, when teachers tutor their students privately, there is a 

danger of favoring the students who receive tutoring. It is easy for these teachers to de-

liberately conceal content in regular class teaching to promote the need for their private 

classrooms, so margin management is necessary (Kodakos & Kalavasis, 2015). 

In sum, some empirical studies showed that in countries with low teacher sala-

ries, teachers are more likely to participate in paid tutoring, and teachers who get paid 

tutoring will encourage their students to participate in extracurricular tutoring in turn, so 

the in-service teacher salary level will affect students’ participation in extracurricular 

tutoring. Teacher’s wage index is an objective quantitative index to measure the relative 

level of teachers’ wages (Organization for Economic Cooperation and Development, 

2011). A low teacher’s wage index indicates that the level of teachers’ wages is low 

compared to the level of local economic development. Therefore, teachers’ life pressure 

and their income imbalance increase, which may reduce work effort and engage in paid 

tutoring to supplement income. Both of these aspects all may encourage students to par-

ticipate in extracurricular tutoring. Therefore, we hypothesized that the salary level of 

elementary and middle schools teachers has a significant negative impact on students’ 

participation in extracurricular tutoring, i.e., the lower the teachers’ salary, the higher 

the students’ participation in extracurricular tutoring. 

Students’ participation in extracurricular tutoring is affected by two factors: 

supply and demand. At present, there have been studies explored the influence of indi-

vidual and family characteristics of students on extracurricular tutoring from the per-

spective of extracurricular tutoring demand, but no study has explored the impact of 

features such as in-service teacher on student participation in extracurricular tutoring 

from the perspective of extracurricular tutoring supply. This study will comprehensively 

consider the impact of extracurricular tutoring supply and demand on student participa-

tion in extracurricular tutoring. After controlling the individual and family characteris-

tics of students in the econometric model, we will observe the effect of teacher salary 

level on students’ extracurricular tutoring participation. 

Data Source and Variable Description 

The data of the extracurricular tutoring, individual factors, family factors, and school 

factors in this study come from the 2016 data of China Family Panel Studies (CFPS) of 

the China Social Science Survey Center of Peking University. According to the variable 

description of extracurricular tutoring in the data set, extracurricular tutoring mainly 

refers to supplementary educational activities other than formal school education to im-

prove students’ academic performance, including both academic and talent courses. The 

study objects were elementary and middle school students and a total of 3,109 effective 

samples were obtained, including 2,332 from elementary school and 777 from middle 

school. 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 773 

From the perspective of economics, teachers’ wages are the remuneration of 

teachers for their labor in the organization. When analyzing teacher salaries, we usually 

use the teacher income index (Du, 2015). Education at a Glance 2011: OECD Indica-

tors pointed out that when discussing teacher wages, comparing legal wages with GDP 

per capita is easy to analyze, and provides a way to examine teacher wages in the con-

text of national wealth (Organization for Economic Cooperation and Development, 

2011). Du compared the salary level of teachers with the GDP per capita of various 

provinces and the discretionary income of urban residents, and examined the changes in 

the average salary level of teachers in China from 2000 to 2011 (Du, 2014). An sug-

gested that the relative level of teacher wages was a way of judging the comparison be-

tween teacher wages and gross national product, i.e., the proportion of teacher average 

wages to GDP per capita can be called wage index (An, 2014). Xue and Shen used the 

teacher wage index (Shen, 2018; Xue & Tang, 2017) when measuring the salary of el-

ementary and middle schools. Because teachers’ perception of their wages stems from 

the overall wages paid in the previous year, so the wage index of teachers in 2015 is 

selected here. The description of the variables is shown in Table 1. 

Teacher Salary and Student Extracurricular Tutoring 

Participation Rate in Elementary and Middle Schools 

by Province 

Participation Rate of Extracurricular Tutoring of Elementary 

and Middle Students by Province 

Table 2 shows that the participation rate of extracurricular tutoring of elementary 

school students in each province was uneven. The top three provinces with extracurricu-

lar tutoring participation rate for elementary school students were: Jiangsu, Hei-

longjiang and Shanghai. Their rate all exceeded 32%, and the number of participants 

account for more than one third of the sample population in the province. The provinces 

with lower participation rates were: Guangxi, Guizhou, and Jiangxi. Their participation 

rates were 1.1%, 1.8%, and 2.9%, respectively, and the number of participants was less 

than one-third of the number in the province. The participation rate in the eastern China 

was high, the central region was uneven, and the western region was low. The participa-

tion rate of extracurricular tutoring of middle school students in different provinces was 

also mixed. 

The provinces with high participation rates of extracurricular tutoring for mid-

dle school students were: Jiangsu, Anhui and Liaoning, with participation rates of 

55.6%, 42.1%, and 35.9%, respectively; the provinces with lower participation rates 

were Guangxi and Guizhou, with 4.2% and 4.4%, respectively. The participation rate of 

middle school students in the eastern region except Guangdong and the northeast region 

was relatively high. The participation rate in the central region except Jiangxi was more 

than 20%, and the participation rate in the western region was uneven. In short, the par- 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 774 

Table 1. Description of Variables in Statistical Analysis. 

Variable Type Variable Name Variable Description 

Extracurricular 
Tutoring 

Whether to Participate in 
Extracurricular Tutoring 

0=No, 1=Yes 

Personal Factors Gender 0=Female, 1=Male 

Household Registration (Hukou) 0=Agricultural, 1=Non-Agricultural 

Math Scores 1=Poor, 2=Medium, 3=Good, 4=Excellent 

Chinese Performance 1=Poor, 2=Medium, 3=Good, 4=Excellent 

Family Factors 
Parent’s Highest Education 

1=Illiterate, 2=Elementary School, 
3=Middle School, 4=High School, 5=Junior 
College, 6=Undergraduate and Above 

 Parental Education Expectations 

1=Middle School And Below, 2= High 
School, 3=Junior College, 4=University 
Undergraduate, 5=Master’s Degree and 
Above 

Annual Household Income Per Capita Continuous Variable, Unit: CNY 

School Factors Demonstration/Key School 0=No, 1=Yes 

Class Size Continuous Variable, Unit: Person 

2015 Teacher 
Wage Index 

Average Salary of Elementary School 
Teachers in the Province in 2015 / 
GDP Per Capita in 2015 

Continuous Variable 

Average Salary of Middle School 
Teachers in the Province in 2015 / 
GDP Per Capita in 2015 

Continuous Variable 

 

 

 

ticipation rate of elementary and middle students in the eastern region is mostly higher 

than that in the western region, and the central region is high, and the rate of elementary 

school students is uneven. 

Relative Salary of Teachers in Elementary and Middle 

Schools by Province 

Teacher wage index refers to the proportion of teachers’ average salary to GDP per cap-

ita. This is a way of judging the comparison of teachers’ wages with gross national 

product, which indicates the relative level of teachers’ wages (An, 2014). Regarding the 

reasonable level of wages, it is believed that the teacher wage index should be reasona-

bly between 1.8:1 and 2:1 in developed countries and 2.5:1 and 3.5:1 in developing 

countries (Qu, 1995). Chinese elementary and middle schools teacher wage index is 

shown in Table 3. The wage index of elementary school teachers in the table is the av-

erage salary of elementary school teachers in 2015/GDP per capita in 2015, and the 

wage index of middle school teachers in 2015 is the average salary of middle school 

teachers in 2015/GDP per capita in 2015. 

Table 3 shows that the average value of the middle school teachers’ wage in-

dex was higher than that of elementary school teachers. The provinces with elementary 

school teachers whose wage index was less than 1 were Jiangsu, Liaoning and Shanghai, 

all of which are provinces in the eastern region where the economies are relatively de- 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 775 

Table 2. Participation Rate of Extracurricular Tutoring in Elemen-
tary and Middle Schools. 

Province 
Participation Rate of Extracurricular Tutoring 

Elementary School Students (%) Middle School Students (%) 

Hebei 16.1 15.9 

Shanxi 18.9 22.2 

Liaoning 22.5 35.9 

Jilin 16.1 33.3 

Heilongjiang 37.0 33.3 

Shanghai 32.7 31.6 

Jiangsu 39.0 55.6 

Zhejiang 27.6 28.6 

Anhui 22.4 42.1 

Jiangxi 2.90 12.5 

Shandong 21.1 16.0 

Henan 20.8 27.4 

Hunan 14.5 27.3 

Guangdong 10.6 8.80 

Guangxi 1.10 4.20 

Chongqing 7.40 25.0 

Sichuan 12.8 17.2 

Guizhou 1.80 4.40 

Yunnan 6.80 11.8 

Shaanxi 18.4 25.0 

Gansu 7.10 15.6 

Nationwide 14.3 20.1 

 

 

 

veloped. The provinces with elementary school teachers whose wage index was higher 

than 2 were Gansu, Guizhou and Yunnan, all of which are western provinces, indicates 

that the teachers’ wage level and economic level are relatively commensurate. The 

wage index of elementary school teachers in the eastern region was lower than the aver-

age level, and the central region was uneven, but the western region, except Chongqing 

and Shaanxi, other provinces were higher than the average. The provinces with middle 

school teachers whose wage index was lower than 1 were Jiangsu and Liaoning, and 

those higher than 2 were Gansu, Yunnan and Guizhou. Therefore, the wage index of 

middle school teachers in the eastern region was lower than the average, the central re-

gion was at the middle level, and the western regions except Chongqing and Shaanxi 

were all above the average. It can be seen that the relative salary of elementary and 

middle schools teachers in the eastern region is not commensurate with the level of 

economic development, but the relative salary of teachers in some western provinces 

matches the level of economic development. Overall, the relative salary of teachers in 

China is relatively low. 

 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 776 

Table 3. The Wage Index of Elementary and Middle School 
Teachers in Each Province in 2015. 

Province Elementary School Teacher Wage Index Middle School Teacher Wage Index 

Hebei 1.35 1.42 

Shanxi 1.62 1.7 

Liaoning 0.88 0.90 

Jilin 1.07 1.11 

Heilongjiang 1.47 1.54 

Shanghai 0.93 1.03 

Jiangsu 0.85 0.91 

Zhejiang 1.14 1.26 

Anhui 1.55 1.64 

Jiangxi 1.45 1.47 

Shandong 1.05 1.15 

Henan 1.17 1.26 

Hunan 1.12 1.21 

Guangdong 1.02 1.08 

Guangxi 1.47 1.58 

Chongqing 1.25 1.41 

Sichuan 1.59 1.76 

Guizhou 2.13 2.21 

Yunnan 2.1 2.27 

Shaanxi 1.14 1.17 

Gansu 2.26 2.32 

Mean Value 1.36 1.45 

 

 

 

 

The Wage Index of Elementary and Middle Schools Teachers 

and the Student Participation Rate of Extracurricular Tutor-

ing  

In 2015, the average value of the elementary school teachers’ wage index was 1.42, and 

the average value of the middle school teachers’ wage index was 1.51. 

Figure 1 shows the relationship between the elementary school teachers’ wage 

index and the students’ extracurricular tutoring participation rate. The provinces with 

lower wage index among elementary school teachers have relatively higher participa-

tion rate; on the contrary, the province with higher wage index among elementary 

school teachers have relatively lower participation rate. For example, the provinces with 

elementary school teachers whose wage index was less than 1 were Jiangsu, Liaoning, 

and Shanghai, all of which are in the eastern China. The participation rates of these 

three provinces in extracurricular tutoring were very high, at 39%, 22.5%, and 32.7%, 

respectively. The provinces with elementary school teachers whose wage index was 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 777 

 

Figure 1. Elementary School Teacher Wage Index and Students’ 
Extracurricular Tutoring Rate. 

 

 

 

higher than 2 were Gansu, Guizhou and Yunnan, all of which are in the western China, 

and the participation rates of extracurricular tutoring in these three provinces were rela-

tively low, at 7.1%, 1.8% and 6.8%, respectively. 

Figure 2 shows that between the wage index of middle school teachers and the 

participation rate of students’ extracurricular tutoring are also reversely related. In the 

provinces with high wage index of middle school teachers, the participation rate of stu-

dents in extracurricular tutoring was relatively low; on the contrary, in the province 

with low wage index of middle school teachers, the participation rate of extracurricular 

tutoring students was also relatively high. For example, the provinces with middle 

school teachers whose wage index was less than 1 were Liaoning and Jiangsu. The par-

ticipation rates of students in these two provinces were very high, at 35.9% and 55.6%, 

respectively. The provinces with middle school teachers whose wage index was higher 

than 2 were Gansu, Yunnan and Guizhou. The rate of students participating in extracur-

ricular tutoring in these three provinces was 15.6%, 11.8% and 4.4%, respectively. 

The Effect of Elementary and Middle Schools Teach-

ers’ Wage Index on Students’ Participation in Extra-

curricular Tutoring 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 778 

 

Figure 2. Middle School Teacher Wage Index and Students’ Ex-
tracurricular Tutoring Rate. 

 

 

 

The hierarchical linear model is proposed to address the limitations of traditional statis-

tical techniques when processing multi-layer structure data and the possible misinter-

pretation of the analysis results. It is suitable for proper and in-depth analysis and inter-

pretation of widely existing multi-layer nested data (Osborne & Neupert, 2013). When 

the hierarchical linear model is analyzed at different levels, it can make full use of the 

information of each layer to decompose the factors influencing students’ participation in 

extracurricular tutoring at all levels, so it is more accurate and more reasonable. 

When analyzing the elementary and middle schools teacher wage index affect-

ing students’ participation in extracurricular tutoring, we introduced the hierarchical 

linear model, because the sample of students in this study is nested in different provinc-

es and regions, and teacher salaries are different in different provinces. For this kind of 

data with nested structure, HLM2 can be used to examine the effect of student-level 

variables and provincial-level teachers’ wage index variables on students’ participation 

in extracurricular tutoring. 

At the beginning of the model construction, the zero model was first estimated 

to explain the percentage and significance of the total variance of the dependent varia-

ble that could be explained by the differences between groups. Then, HLM2 was built. 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 779 

Lay1: Tutor=0+1gender +2parentedu +3parentexpectation +4salary 

+5language+6math +7key school +8classsize + 

(1) 

 

Lay2: 0=00+01teachers’salary +0 

(2) 

 

Among them, the dependent variable Tutor represents whether students partici-

pate in extracurricular tutoring. The independent variables are divided into two levels: 

the first level is individual level variables, including student gender, parental education 

level, parental education expectations, family per capita income, whether it is a key 

school, class size, language performance, and math performance; the second level is 

Provincial level variables, including teachers’ salary index. 

A Hierarchical Linear Model Analysis of the Effect of 

Elementary School Teachers’ Wage Index on Stu-

dents’ Participation in Extracurricular Tutoring 

Construct a zero model in the sample of elementary school students. The zero model 

refers to a model that has no predictor variables at the individual level and the provin-

cial level. This is mainly used to observe whether the dependent variable is statistically 

significant at the provincial level. This study conducted a zero-model analysis of 

whether students participated in extracurricular tutoring in the past 12 months. The re-

sults are shown in Table 4. 

The zero model showed that with student participation in extracurricular tutor-

ing as the dependent variable, its p value was < 0.01, which means that the predictor 

variables of the second layer have a significant impact on the variation of the dependent 

variable. In Table 4, the variance between groups was 0.009, the variance within the 

group was 0.117, and the intra-group correlation coefficient (ICC) = 0.071 was further 

calculated. ICC is to test whether the dependent variable is different between different 

groups. According to Cohen’s definition, 0.071 is a moderate intra-group correlation 

(Less than 0.059 indicates low-level intra-group correlation, 0.059-0.138 is moderate 

intra-group correlation, and greater than 0.138 is high-level intra-group correlation). 

The data in this study were moderately related within the group, so the differences with-

in the group cannot be ignored. This means that the degree of variability caused by the 

difference from the provincial level in students participating in extracurricular tutoring 

was 0.009, which was about 7.1% of the variance. On the one hand, the predictor varia-

bles of the second layer have a significant impact on the variation of the dependent var-

iable; on the other hand, according to the estimation results of ICC (cross-level correla-

tion coefficient), the dependent variable has obvious differences between groups, and 

the characteristics of the differences between groups must be considered. Therefore, it 

is suitable to use a HLM2 for analysis. 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 780 

Table 4. Elementary School Sample Zero Model Parameter Esti-
mation. 

Parameter 
Variance 
Estimation 

Standard 
Error 

Intra-Group Correla-
tion Coefficient 

Chi-Square 
Value 

P-
Value 

Intercept Term 
(Variation Between 
Groups U0 ) 

0.009 0.004 0.071 52.043 0.000 

Level 1 
(Variation Residual 
Within the Group R) 

0.117 0.003       

 

 

 

Model 1 and Model 2 (Table 5) were the influencing factors of extracurricular 

tutoring participation of elementary school students. Model 1 was the basic model, 

which estimated the influence of control variables on extracurricular tutoring participa-

tion in the elementary school samples. The data showed that in elementary school, the 

higher the annual per capita income of the family, the more non-agricultural students 

were less likely to participate in extracurricular tutoring. The larger the class size, the 

higher the likelihood of students participating in extracurricular tutoring. The higher the 

parent’s education level, the higher the likelihood of students participating in extracur-

ricular tutoring. 

Model 2 adds the variable of 2015 average salary of elementary school teach-

ers/2015 GDP per capita (2015 elementary school teachers’ wage index) to the control 

variable. After the addition, the logarithm likelihood drops from 1,378.003 to 1,376.780, 

and the values of AIC and BIC also decrease. . This showed that the addition of this 

variable had statistical significance, which made the model fit better. The data shows 

that the agricultural household in Model 2 is negatively significant, that is, the more 

agricultural household students, the lower the possibility of participating in extracurric-

ular tutoring. Parents’ education level, family per capita income and class size were 

positively significant, i.e., the higher the parent’s education level, the higher the fami-

ly’s per capita income and the larger the class size, the greater the possibility of students 

participating in extracurricular tutoring. The coefficient of elementary school teachers’ 

wage index was -0.096 (p < 0.05). The results of the data showed that the greater the 

ratio of the average salary of elementary school teachers to the annual per capita GDP, 

the less likely students was to participate in extracurricular tutoring. For each additional 

unit of elementary school teacher wage index, the possibility of students participating in 

extracurricular tutoring decreases by 0.096 units, i.e., the higher the elementary school 

teacher wage index, the lower the possibility of students participating in extracurricular 

tutoring. 

Mixed Model Analysis of Middle School Teacher Salary to 

Students Participating in Extracurricular Tutoring 

 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 781 

Table 5. Multi-Layer Linear Model Analysis Results of the Impact 
of Elementary School Teacher Wage Index on Students’ Partici-
pation in Extracurricular Tutoring. 

Variable Model 1 Model 2 

Individual Level Variable 

Gender: Female (Male=1) 0.022 (0.015) 0.023 (0.015) 

Agricultural Household Registration  
(Non-Agricultural Household Registration=1) 

-0.096 *** (0.025) -0.094*** (0.025 ) 

Chinese Performance 0.008 (0.010) 0.008 (0.010) 

Math Scores -0.016 (0.010) -0.016 (0.010 ) 

Annual Household Income Per Capita 1.726*** (5.862) 1.650 *** (5.856) 

Parent’s Highest Education 0.015* (0.008) 0 .014* (0.008) 

Parents’ Educational Expectations for Their Children 0.008 (0.007) 0 .009 (0.007) 

Non-Key School (Key School=1) -0.014 (0.019) - 0.015 (0.019 ) 

Class Size 0.001** (0.000) 0 .001** ( 0.000) 

Provincial Level Variable 

Average Salary of Elementary School Teachers  
in 2015 / GDP Per Capita in 2015 

  - 0.096** ( 0.036 ) 

Intercept Term 0.094 (0.067) 0.229*** (0.084) 

Sample Size 2,332 2,332 

Random Effect 

Sd (Intercept) 0.004 (0.002) 0.003 (0.001) 

Sd (Residual Error) 0.110 (0.003) 0.110 (0.004) 

Goodness of Fit 

-2 Restricted Log Likelihood 1,378.003 1,376.780 

Akaike’s Information Criterion (AIC) 1,382.003 1,380.780 

Schwarz’s Bayesian Criterion (BIC) 1,393.119 1,391.972 

Note: 1. ***, **, * represent significant at the 1%, 5% and 10% levels, respectively. 

2. Standard errors are in parentheses. 

 

 

 

 

Table 6. Middle School Sample Zero Model Parameter Estima-
tion. 

Parameter 
Variance 
Estimation 

Standard 
Error 

Intra-Group Correla-
tion Coefficient 

Chi-Square 
Value 

P-
Value 

Intercept Term 
(Variation Between 
Groups U0 ) 

0 .008 0 .005 0 .049 73.537 0.000 

Level 1 
(Variation Residual 
Within the Group R) 

0 .154 0 .008       

 

 

 

 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 782 

Table 7 : Multi-Layer Linear Model Analysis Results of the Influ-
ence of Middle School Teacher Wage Index on Students’ Partici-
pation in Extracurricular Tutoring. 

Variable Model 3 Model 4 

Individual Level Variables 

Gender: Female (Male=1) 0.022 (0.031) 0.024 (0.031) 

Agricultural Household Registration 
(Non-Agricultural Household Registration=1) 

-0.126*** (0.046) -0.108** (0.046) 

Chinese Performance -0.016 (0.020) -0.012 (0.020) 

Math Scores -0.015 (0.018) -0.021 ( 0.015) 

Annual Household Income Per Capita 4.429 (5.192) 3.633 (5.184) 

Parent’s Highest Education 0.052*** (0.015) 0 .052*** (0.015) 

Parents’ Educational Expectations for Their Children 0.011 (0.015) 0 .008 (0.015) 

Non-Key School (Key School=1) -0.035 (0.036) - 0.040 ( 0.035) 

Class Size 0.002 (0.001) 0 .002 (0.001) 

Provincial Level Variables 

Average of Secondary Education Teachers in 2015 
Wages/2015 GDP Per Capita 

  - 0.089* (0.048) 

Intercept Term 0.105 (0.150) 0.233 (0.167) 

Sample Size 777 777 

Random Effect 

Sd (Intercept) 0.004 (0.003) 0.004 (0.003) 

Sd (Residual Error) 0.144 (0.008) 0.143 (0.008) 

Goodness of Fit 

-2 Restricted Log Likelihood 682.061 677.424 

Akaike’s Information Criterion (AIC) 686.061 681.424 

Schwarz’s Bayesian Criterion (BIC) 695.027 690.378 

Note:  1. ***, **, * represent significant at the 1%, 5% and 10% levels, respectively. 

2. Standard errors are in parentheses. 

 

 

 

By constructing a zero model in the middle school samples, the results were shown in 

Table 6. In this zero model, whether the student participated in extracurricular tutoring 

was the dependent variable, the inter-group variance was 0.008, the intra-group vari-

ance was 0.154, and the significance level was p < 0.001. 

Further calculation of the intra-group correlation coefficient (ICC) = 0.049, its 

P value was < 0.01, i.e., the second-level predictor variables have a significant impact 

on the variation of the dependent variable, and the impact of the provincial-level varia-

bles on the dependent variable needs to be considered. Therefore, it was suitable to use 

hierarchical linear model for analysis. 

Models 3 and 4 were the influencing factors of extracurricular tutoring partici-

pation of middle school students. Model 3 was the basic model, which estimated the 

influence of control variables on extracurricular tutoring participation in the middle 

school samples. It can be seen from Table 7 that in the basic model, middle school par-



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 783 

ents’ educational background and household have a significant impact on students par-

ticipating in extracurricular tutoring. 

Model 4 added the variable of 2015 middle school teachers’ wage index to 

model 3, the logarithm likelihood dropped from 682.061 to 677.424, and the values of 

AIC and BIC also decreased, indicating that the addition of this variable had statistical-

ly significance, and the model fitting was better. The data showed that the highest edu-

cational level of parents was significant at 0.01 and household was significant at 0.05, 

i.e., non-agricultural household students were more likely to participate in extracurricu-

lar tutoring than agricultural household students. The coefficient of the variable of wage 

index for middle school teachers was -0.089 (p < 0.1). The data showed that the greater 

the ratio of the average salary of middle school teachers to the annual per capita GDP, 

the less likely students was to participate in extracurricular tutoring. For every addition-

al unit of middle school teacher wage index, the possibility of students participating in 

extracurricular tutoring decreased by 0.090 units, i.e., the higher the secondary school 

teacher wage index, the lower the possibility of students participating in extracurricular 

tutoring. 

Discussion and Conclusion 

Through the above analysis, it is found that the relative salary of elementary and middle 

schools in China is relatively low. In 2015, the Wage Index of elementary school teach-

ers in all provinces of China was between 0.87-2.26, and the Wage Index of middle 

school teachers was between 0.9-2.32. None of them has reached the level of 2.5-3.5 for 

the wage index of teachers in developing countries. This study showed that the wage 

index of elementary and middle schools teachers in China had a significant negative 

effect on students’ participation in extracurricular tutoring. The province with the lower 

elementary school teacher wage index has the higher participation rate of extracurricu-

lar tutoring. Elementary school teachers with the lowest wage index in Jiangsu (0.85) 

had the highest extracurricular tutoring participation rate (39%), accounting for more 

than one-third of the province’s elementary school samples. The same was true for 

middle school teachers. In Liaoning (0.9) and Jiangsu (0.91), where the middle school 

teachers’ wage index was lower than 1, and their students’ participation in extracurricu-

lar tutoring was high, at 35.9% and 55.6%, respectively. This showed that the relative 

level of teachers’ salary had a significant impact on students’ participation in extracur-

ricular tutoring. Our findings corroborate the findings of Foondun et al. in Cambodia 

and other countries (Foondun, 2002), the lower the teacher’s salary, the more students’ 

tutoring; this also was agreement with Zhang and Bray’s survey in Shanghai, China 

from the perspective of teacher salary (Zhang &Bray, 2017). 

Adams’s Equity Theory believes that the enthusiasm of employees depends on 

the degree of fairness in distribution (i.e., sense of fairness); and this sense of employ-

ees depends on a process of social comparison, that is, a person not only cares about his 

absolute income, but also cares about his relative income (Chen & Gao, 2008). When 

teachers in elementary and middle schools in China compare their income horizontally 

with other professionals in the society, if they feel that their income is lower, they will 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 784 

feel unfair, so they will seek to increase their income or reduce their work to obtain a 

sense of fairness. On the one hand, some in-service teachers will participate in paid tu-

toring in an attempt to increase their income. On the other hand, some in-service teach-

ers who do not participate in paid tutoring will reduce the work effort in their daily 

school teaching. Meanwhile, some in-service teachers not only participate in paid tutor-

ing but also reduce the teaching effort, and they will intentionally teach less important 

content in the classroom, deliberately guide or encourage students to participate in ex-

tracurricular tutoring activities they organized or involved in. This had pushed up the 

scale of students’ participation in extracurricular tutoring, impacted the order of school 

education and disrupted the normal school education ecology, and also harmed the equi-

ty of education and increased the burden of student learning. 

In 2015, the Ministry of Education of China issued the Regulations on Prohib-

iting Elementary and Middle Schools and In-service Teachers from Participating Paid 

Tutoring (Ministry of Education of China, 2015), which prohibits in-service teachers 

from participating in paid tutoring. Since the document was issued, some provinces and 

cities had also issued relevant policy documents. On the basis of “6 prohibitions”, He-

nan Province put forward “prohibition on elementary and middle schools in-service 

teachers from deliberately failing to complete education and teaching tasks in the class-

room” and “prohibition on elementary and middle schools teachers from teaching after 

school for being paid” (Henan Provincial Department of Education, 2015); Beijing also 

issued policy document stating “whether the in-service teacher organizes or participates 

in paid tutoring will be regarded as an important basis for annual assessment, job title 

evaluation, promotion, rewards, and punishments” (Liang, 2017). On the basis of prohi-

bition, the relevant documents also proposed to “educate and guide the teachers to prac-

tice the core values of education, stand up for morality, and consciously refuse paid 

tutoring; select and promote outstanding teacher models, and fully demonstrate the spir-

it of dedication and kindness of teachers” (Ministry of Education of China, 2015). The 

guidance of correct values is conducive to weakening teachers’ sense of injustice and 

reducing motivation to go out for tutoring. 

Given that Chinese elementary and middle schools teachers’ wage index has a 

significant negative impact on students’ participation in extracurricular tutoring, and the 

current Chinese elementary and middle schools teachers’ wage index is generally low, 

governments at all levels should increase financial invest to teachers’ salaries. With the 

teacher’s wage index as the reference standard, strive to increase the relative salary of 

elementary and middle school teachers. For provinces with stronger financial strength 

and lower teacher wage indexes, governments at and below the provincial level should 

increase the financial input, and focus on raising the teacher wage index and improving 

the relative level of teacher wages. For provinces with weaker financial strength and 

lower teacher wage index, central and provincial governments should increase fiscal 

transfer payments to help local governments at all levels of the province increase the 

input and strive to improve the teacher wage index. The efforts of governments at all 

levels to increase the salary of elementary and middle schools teachers will help reduce 

the supply and demand of extracurricular tutoring in the basic education in China, and 



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 785 

also provide a basis for prohibiting in-service teacher from participation in extracurricu-

lar tutoring. 

 

 

 

 

 

 

 

 

References

An, X. (2014). A Study on the changes and 

differences of teacher salary levels in el-

ementary and middle schools in China. 

Education Research, 35(12):44-53. [Chi-

nese] 

http://www.cqvip.com/QK/96925X/20141

2/663321538.html 

Bray, M., & Kwok, P. (2013). Demand for 

private supplementary tutoring: Concep-

tual considerations, and socio-economic 

patterns in Hong Kong. Economics of Ed-

ucation Review, 22(6):611-620. DOI: 

https://doi.org/10.1016/S0272-

7757(03)00032-3 

Bray, M., Kobakhidze, M.N., Zhang, W., Liu 

J. (2018). The hidden curriculum in a hid-

den marketplace: relationships and values 

in Cambodia’s shadow education system. 

Journal of Curriculum Study, 50(4):435-

455. DOI: 

https://doi.org/10.1080/00220272.2018.14

61932 

Brehm, W., Silova, I., & Tuot, M. (2012). The 

public-private education system in Cam-

bodia: The impact and implications of 

complementary tutoring. Buda pest: Edu-

cation Support Programme, Open Society 

Foundations, 34.  

Chen, X, & Gao, H. (2008). Education man-

agement. Beijing Normal University Press, 

pp46-pp47. [Chinese] 

Du, X. (2014). Empirical analysis and policy 

suggestions on teachers’ wages in China. 

Education Theory Practice, 34:20-24. 

[Chinese] 

Du, X. (2015). Comparative analysis and 

suggestions of elementary and middle 

schools teachers’ salary levels in China. 

Chinese Journal of Education, 

2015(4):27-31, 74. [Chinese] 

Foondun, A.R. (2002). The issue of private 

tuition: An analysis of the practice in 

Mauritius and selected South-East Asian 

countries. International Review of Educa-

tion, 48(6):485-515. DOI: 

https://doi.org/10.1023/A:1021374811658 

Gök, F. (2010). Marketing hope: Private insti-

tutions preparing students for the univer-

sity entrance examination in Turkey, in: K. 

Amos (Ed). Int Edu Gov (London, Emer-

ald), pp123-pp134. DOI: 

https://doi.org/10.1108/S1479-

3679(2010)0000012009 

Henan Provincial Department of Education. 

(2015). Henan Province strictly prohibits 

elementary and middle schools and serv-

ing elementary and middle schools teach-

ers from paying tutoring. Teachers [2015] 

No. 739. 2015-9-9. [Chinese] 

http://www.haedu.gov.cn/2015/09/09/144

1775234525.html 

Kodakos, A. & Kalavasis, F. (eds.). (2015). 

Shadow Education System: Border Man-

agement Models of the School with the 

Structures of the Education Market. 

Rhodes: University of the Aegean, 2015, 

pp78.  



Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 786 

Liang, T. (2017). Beijing clearly prohibits in-

service elementary and middle schools 

teachers from “paid tutoring”. Xinhua 

Daily Telecommunications. 2017-3-3(3). 

[Chinese] 

http://www.moe.gov.cn/s78/A10/moe_60

1/201703/t20170314_299519.html 

Mahmud, R.A.F.S.A.N., & Bray, T.M. (2017). 

School factors underlying demand for 

private supplementary tutoring in English: 

Urban and rural variations in Bangladesh. 

Asia Pacific Journal of Education, 

37(3):299-309. DOI: 

https://doi.org/10.1080/02188791.2017.13

21525 

Ministry of Education of China. (2015). 

Regulations on paid tutoring of elemen-

tary and middle schools and in-service el-

ementary and middle schools are strictly 

prohibited. Teachers [2015] No. 5. 2015-

6-29. [Chinese] 

http://www.moe.gov.cn/srcsite/A10/s7002

/201507/t20150706_192618.html 

Organization for Economic Cooperation and 

Development. (2011). Overview of 

OECD Index Education 2011. Central In-

stitute of Educational Sciences, translated. 

Beijing: Education Science Press, 

2011:436. [Chinese] 

Osborne, J.W., & Neupert, S.D. (2013). A 

brief introduction to hierarchical linear 

modeling. Sense Publishers, 112. DOI: 

https://doi.org/10.1007/978-94-6209-404-

8_9 

Popa, S., & Acedo, C. (2003). Redefining 

professionalism: Romanian teachers and 

the private tutoring system. Paper pre-

sented at the annual conference of the 

Comparative and International Education 

Society, New Orleans, USA, 12-16 March. 

DOI: 

https://doi.org/10.1016/j.ijedudev.2005.07

.019 

Qu, H. (1995). Several questions about the 

salary income of elementary and middle 

schools teachers in China. Higher Normal 

Education Research, 1995(3):49. [Chi-

nese] 

http://www.cqvip.com/QK/82925A/19953

/4001269047.html 

Shen, Y. (2018). Analysis on the differences 

in regional allocation of wages, benefits 

and subsidies for secondary vocational 

teachers-based on data from 2007 to 2016. 

Education Academy Monthly, 2018(11): 

33-46. [Chinese] DOI: 

https://doi.org/10.16477/j.cnki.issn1674-

2311.2018.11.004 

Sujatha, K., & Rani, P.G. (2011). Manage-

ment of secondary education in India. 

New Delhi: Shipra and National Universi-

ty of Educational Planning and Admin-

istration (NUEPA), 2011:65.  

Xue, H, & Tang, Y. (2017). Ideal and reality: 

A study on teacher salary level and struc-

ture of elementary and middle schools in 

China. Peking University Education Re-

view, 15(2):17-38, 186-187. [Chinese] 

DOI: 

https://doi.org/10.19355/j.cnki.1671-

9468.201702002 

Zhang, W., &Bray, T.M. (2017). Micro-

neoliberalism in China: Public-Private In-

teractions at the Confluence of Main-

stream and Shadow Education. Journal of 

Education Policy, 32(1):63-81. [Chinese] 

DOI: 

https://doi.org/10.1080/02680939.2016.12

19769

Received: 11 May 2020 

Revised: 27 June 2020 

Accepted: 10 July2020 

 

 

 

 

 

https://schlr.cnki.net/Detail/DOI/STJDLAST/STJDBD878065BBB6214D4B9392B5B4F483AD
https://schlr.cnki.net/Detail/DOI/STJDLAST/STJDBD878065BBB6214D4B9392B5B4F483AD


Xue et al. Interrelationship between Teacher Salary Students’ Extracurricular Tutoring. 

Vol.6, No. 1, 2020 787 

The Chinese version of this article has been published in Education Science, 2019; 35(5):36-45. The 

English version has been authorized for being publication in BECE by the author(s) and the Chinese 

journal. 

薛海平,高翔,范皑皑. (2019). 中小学教师工资水平对学生参与课外补习的影响研究. 教育科学, 
35(5):36-45. 

 


	Article-HaipingXue-BECE_title_18Sep2020
	Article-HaipingXue-BECE_Maintext18Sep2020

