The Impact of Education Input on China's Economic Growth

Lei Ge

and Haoran Xu

Business School of Hohai University, Hohai University, Nanjing, China

Faculty of Social Science, University of Ottawa, Ottawa, Canada

Keywords: Education, Economic, Regional diparities

Abstract: This study examines the correlation between education investment and economic growth in China, with a

focus on regional differences. The study aims to shed light on the positive impacts of education investment

on a country's economic development and emphasizes the importance of understanding these dynamics for

policymakers and stakeholders. The motivation behind this study is to recognize the critical role that education

plays in shaping a country's economic landscape. As China continues to undergo rapid economic

transformation, understanding the delicate relationship between education investment and economic growth

becomes imperative. This paper reveals the different impacts of education spending through a comprehensive

analysis of education spending patterns and economic indicators in different regions. The results of the study

show that education investment has a positive and substantial impact on China's overall economic growth. In

addition, the study identifies regional differences, emphasizing that the extent of this impact varies across

different regions of the country. This differential effect can be attributed to different levels of educational

infrastructure, government policies, and economic activities in each region. Influenced by factors such as

geographic location, resource conditions, and policy advantages, China's industrial structure exhibits

developmental differences in the spatial economic pattern. The significance of this study is that it has the

potential to sensitize policymakers, educational institutions, and investors on the strategic importance of

promoting education for sustained economic development. Recognizing the impact of different regions

requires targeted policies to address the specific educational challenges and opportunities in different regions

of China.

1 INTRODUCTION

Since China's reform and opening, China's

modernization has entered a rapid growth, in the past

decades of China's becoming the world's factory, due

to the demographic dividend brought about by the

economic growth of the population after the number

of people brought by the benefits of a slightly

exhausted economy. The quality of the labor force has

become particularly important. The contradiction

between the development needs of late-developing

countries such as China and the layout of the global

industrial chain is the root cause of the long-standing

problem of the imbalance between human capital and

industrial structure. Therefore, to solve this problem,

we can not only take short-term measures to catch up

with the other side but also focus on the dynamic

process of China's sustainable economic development

and promote the long-term coordination of human

capital accumulation and industrial structure

upgrading (Ni & Ding, 2022). At the beginning of the

21st century, China's working-age population had an

average of 7.18 years of education, and the figure rose

to 10.9 years by 2021, which is enough to show that

the structure of China's human capital has undergone

a great change (Zhang, 2022). It is undeniable that the

human capital dividend will replace the demographic

dividend as the new engine of China's economic

growth. Higher education is regarded as an important

support for economic and social progress, and the

relationship between higher education concentration,

human capital, scientific and technological R&D, and

economic growth has attracted a lot of attention and

become a focus of discussion in all walks of life (Cai

& Tan, 2024).

Education is one of the key determinants of a

country's economic well-being, as it can increase the

human capital of the country's labor force, thereby

promoting economic development and improving

people's living standards (A, 2010). Stable economic

growth and development in the long term can only be

achieved through three main factors: the development

of science and technology, the growth of the various

capital factors, and the development of the education

Ge, L. and Xu, H.

The Impact of Education Input on China’s Economic Growth.

DOI: 10.5220/0012823800004547

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Data Science and Engineering (ICDSE 2024), pages 86-90

ISBN: 978-989-758-690-3

system. Education is the means to raise the national

average level of professional skills and knowledge by

training and attracting the necessary resources.

Defining the dynamic evolution of low educated and

low skilled primary human capital towards high

skilled and highly educated advanced human capital

as the process of advanced human capital structure

(Zhang, 2023). The International Bureau of Education

(IBE) is the only international organization that has a

mandate to promote and protect human rights in the

field of education. With the improvement of national

education level, well educated individuals are more

likely to have innovative abilities, problem-solving

skills, and flexibility to adapt to changes. At the same

time, educated people are more likely to engage in

research and development and innovation activities,

thereby contributing to the technological level of the

economy. Human capital accumulation acts as a

powerful catalyst, providing a constant source of

motivation and support in the process of technological

innovation (Zhang, 2022). In addition, human capital

has other positive effects, including a decrease in

crime rates or an improvement in health conditions,

which are expected by society (Valero). With the

accumulation of human capital, it will also have

further positive effects, such as an increase in the

moral level of the entire society. Education has a

tremendous power to trigger change. By providing

knowledge, developing skills, and shaping values, it

can improve individual health and livelihood

conditions, contribute to social stability, and

effectively promote economic growth in the long term

(Brooks). Education, to a certain extent, improves the

quality of individuals and thus has a sense of social

responsibility, which can work together to maintain

social stability and ensure stable economic

development (Liu, 2023).

Therefore, how to better understand the impact

mechanism of human capital on economic growth is

of great significance to implementing the innovation-

driven development strategy and promoting high-

quality development (Ni & Ding, 2022).

The research on human capital can be traced back

to Schultz, who is the founder of human capital theory

and the main practitioner of human capital investment

today (Zhang, 2023).

This thesis analyzes the correlation between

education investment and local economic growth in 21

provincial administrative regions, including Liaoning,

Heilongjiang, Tianjin, Beijing, Shanghai, and Jiangsu.

The relationship between education investment and

GDP changes in each region is analyzed while

controlling for four constant variables: investment

(real utilized foreign capital), the number of tertiary

education students (university plus postgraduate

students), the urbanization rate, and the level of per

capita consumption.

2 LITERATURE REVIEW

The theory of human capital holds that in the process

of economic growth, the importance of human capital

exceeds that of material capital. Human capital

investment is directly proportional to national

income, and compared to material resources, the

growth rate of human capital is faster. The core of

human capital is to improve population quality, and

education investment is the main component of

human capital investment. The human capital theory

originated from economic research. American

economists Schultz and Becker explored the reasons

for the rapid economic growth and productivity

improvement in some developed countries after

World War II, and found that the main reason was the

increase in high-quality talents who received

education in these countries (Cai & Tan, 2024). The

human capital possessed by high-quality talents is

demonstrated through higher education, which in turn

leads to an increase in social output (Cai & Tan,

2024). Since the introduction of the human capital

theory, several empirical studies have emerged in

academia on the role of education in economic

growth, such as Schultz's residual method of

measuring national income growth through education

investment, and Denison's growth accounting method

of linking factor investment with economic growth.

Chen Zhao (2004) studied the differences in

human capital and education development among

regions in China and found that balanced

development of higher education will help to narrow

the income gap between regions (Zhang, 2022).

Higher education is usually accompanied by

economic benefits. A study by economist and global

human development professor George

Psacharopoulos and World Bank advisor Harry

Patrinos found that for every additional year of

education, a person's income increases by

10%(Brooks). Therefore, higher education is

considered an important support for economic and

social progress, and the relationship between the

concentration of higher education and economic

growth has received much attention, becoming a

focus of discussion in various sectors of society.

According to a recent study by the National Bureau

of Economic Research (NBER) in the United States,

learning institutions have found that more education

investment has an impact on national and state

The Impact of Education Input on China’s Economic Growth

economies of over $200 billion. Therefore, it is

evident that education plays a crucial role in the

economic development of a country (Brooks).

Existing literature usually defines the core

connotation of economic growth as the growth of

gross domestic product (GDP). Many existing studies

use per capita GDP or the growth rate of per capita

GDP as a proxy variable to represent economic

growth. This study uses each province's regional

gross domestic product as a proxy variable for

economic growth.

How to leverage the economic growth effect of

human capital based on the regional industrial

structure differences in China has always been a focus

of academic research point. Early literature formed a

consensus view that in the regional industrial

environment, the role of human capital in the central

and western regions is not significant, and the

efficiency of human capital investment in the service

industry is relatively high. This paper further explores

the impact of education investment on economic

growth in different regions based on this.

In summary, this article proposes the following

hypothesis: the increase in education investment has

a positive impact on China's economic growth, and

the impact of education investment on China's

economic growth varies in different regions.

3 THE IMPACT OF EDUCATION

INPUT ON CHINA'S

ECONOMIC GROWTH

3.1 Model Building

In this paper, the following linear regression model is

used for empirical analysis:

𝐺



=𝛼+𝛽𝐸



+𝑦𝐻



+𝜕𝐼



+𝛿𝐶



+𝜀 (1)

Wherein, i represents the city and t represents the

year. The dependent variable Git represents the

economic growth situation, for which the GDP of

each province is selected as an indicator. Eit stands

for the education expenditure for each province.;

Following the research in existing literature, this

paper incorporates other factors that may affect

economic growth as control variables into the model,

including the human capital level Hit. The metrics in

this study include the local higher education

graduates, investment (actual utilization of foreign

capital) Iit, and urbanization rate (urban

population/total population) Cit. In addition, ε

represents the random disturbance term, and α is the

constant of the model.

This paper conducts empirical analysis based on

data from 22 provinces in China, including Jiangsu,

Anhui, Shanghai, Hubei, etc., for the years 2012-

2021. All data were obtained from the statistical

yearbooks of each province and directly administered

municipality each year. For a small amount of

missing data, interpolation or extrapolation methods

were employed for supplementation.

3.2 Data Analysis

Table 1 reveals significant variations in the maximum

and minimum values of each variable, indicating

substantial fluctuations in variables such as regional

gross domestic product (GDP), education

expenditure, human capital level, actual utilization of

foreign capital, and urbanization rate across

provinces. This paper conducts empirical analysis

based on data from 22 provinces in China, including

Jiangsu, Anhui, Shanghai, Hubei, etc., for the years

2012-2021. All data were obtained from the statistical

yearbooks of each province and directly administered

municipality each year. For a small amount of

missing data, interpolation or extrapolation methods

were employed for supplementation.

Table 1. Descriptive statistics of variables.

Variable Name Max Min Mean

Standard

Deviation

Median

GDP(in hundred million CNY) 124369.67 828.2 27937.444 23910.462 21499.28

Education Expenditure

(

in ten thousand CNY

)

37966900 1071776 9363447.233 5867674.779 8085153

Foreign Direct Investment

(in ten thousand USD)

18400200 321 1180908.298 2255023.056 719749.5

Higher Education Enrollment

(in people)

1178402 33500 412398.838 221547.547 393658

Urbanization rate/% 93.768 23.93 60.383 13.471 59.771

ICDSE 2024 - International Conference on Data Science and Engineering

Table 2. Analysis of regression result.

Standardized Coefficients

(1) (2) (3)

Education

Expenditure

0.937 0.891

Foreign Direct

Investment

0.637 -0.001

Higher

Education

Enrollment

-0.063 -0.014

Urbanization

rate

0.251 0.166

0.877 0.537 0.899

The paper adopts the method of controlling

variables. Specifically, in columns (1) and (2),

education expenditure and control variables are

individually added to the regression model, while

column (3) includes all variables simultaneously in

the regression model. In multivariate analysis, the

value of the normalization coefficient represents the

standardized change of the dependent variable when

the unit standard deviation of the independent

variable changes. This aids in a more comprehensive

understanding of the impact of each independent

variable on the dependent variable and allows for a

better comparison of their relative influences.

Therefore, Table 2 selects the standardized

coefficients of each independent variable for analysis.

The results indicate that, in the three models, the

fit is higher for models (1) and (2) which include the

independent variable of education expenditure, while

the fit is lower for the model that includes only

control variables. Moreover, the standardized

coefficients for education expenditure are

consistently around 0.9%. These findings strongly

support the hypothesis proposed in the paper,

indicating that an increase in education expenditure in

various provinces leads to positive GDP growth.

Specifically, a 1% increase in education expenditure

is associated with approximately a 0.9% increase in

GDP.

Next, the collected data will be segmented into

three regions: East, Central, and West. Linear

regression analysis will be conducted again to explore

the varying impact of education expenditure on

economic growth in different regions.

Table 3. The impact of education expenditure in different regions

Normalization

Coefficients

(1) (2) (1) (2)

Eastern 0.974 1.029 0.948 0.976

Central 0.920 0.825 0.843 0.850

West 0.895 0.547 0.798 0.955

The eastern region comprises eight provinces,

including Beijing, Tianjin, Liaoning, Shanghai,

Jiangsu, Zhejiang, Fujian, and Guangdong. The

central region includes six provinces: Jilin,

Heilongjiang, Anhui, Jiangxi, Hubei, and Hunan. The

western region encompasses eight provinces: Inner

Mongolia, Guangxi, Sichuan, Guizhou, Gansu,

Qinghai, Ningxia, and Xinjiang. In column (1),

education expenditure is individually added to the

regression model, while column (2) includes all

variables simultaneously for analysis.

From the results in Table 3, it is observed that the

model has a high fit, and the single independent

variable, education expenditure, positively influences

economic growth. Additionally, it is noted that the

influence of education expenditure on GDP growth

decreases gradually from the eastern to the western

regions. After incorporating control variables,

changes in the standardized coefficients of education

expenditure are observed. A comparative analysis of

the data reveals that the eastern region, with stronger

economic strength and better infrastructure, shows

higher values for all variables compared to both the

central and western regions. Consequently, education

expenditure in the eastern region is significantly

correlated with economic growth, with a 1% increase

capable of driving approximately a 1.029% increase

in GDP. Despite lower data values in the central

region, education expenditure still exhibits a

considerable impact on economic growth, with a 1%

increase associated with approximately 0.825% GDP

growth. In the western region, where economic

development is slower compared to the eastern and

central regions, and with the lowest data values, the

The Impact of Education Input on China’s Economic Growth

impact of education expenditure on economic growth

shows the greatest variation.

4 CONCLUSION

From an overall analysis of the results, it can be

observed that the growth in education expenditure

effectively drives economic growth in China. In

addition, there are significant differences in the

impact of education expenditure on different regions

of China. For the eastern region, an increase in

education expenditure significantly stimulates

economic growth. Higher education expenditure in

the central region plays an important role in

promoting economic growth. However, compared to

other regions, the impact of education expenditure on

economic growth is less pronounced in the western

region.

Therefore, this article proposes the following

suggestions for China's economic growth: firstly,

increasing education investment in various regions is

crucial to drive economic growth. Secondly, from the

data, it can be seen that the infrastructure construction

in some provinces is not yet developed enough, and

the urbanization rate is relatively low. With the

increase of urbanization rate, cities usually pay more

attention to investment in infrastructure and

educational resources. Therefore, it is necessary to

vigorously promote infrastructure construction in

various regions, increase urbanization rates, and

create more favorable conditions for promoting

economic growth through education investment.

Finally, considering the significant regional

economic disparities and imbalanced development,

the effectiveness and focus of education investment

should vary among different regions. It is necessary

to strategically allocate resources in each region in

order to maximize the effectiveness of education

investment under limited economic conditions.

AUTHORS CONTRIBUTION

All the authors contributed equally and their names were

listed in alphabetical order.

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