Study on the Influence of Social Factors on Economic Income Under

the Theory of Regional Coordination

Qiuyue Chen and Yuchen Hu

College of Economics Sichuan Agricultural University Chengdu, China

Keywords: Tibet-Related Areas, Regional Coordination, Social Factors, Economic Income, Resource Allocation.

Abstract: In the context of regional coordination, how to reasonably allocate the resources needed for the

development of social aspects and economic aspects, such as education, communication, and transportation,

has become an important link in achieving the goal of rural revitalization. Based on research data from

Tibet-related areas in four provinces and Lhasa City in Tibet Autonomous Region, this paper empirically

investigates the influence of social factors on economic income in ethnic areas using least squares

regression and propensity matching score model (PSM). The results show that education and

communication levels have a significant positive effect on farm household income in both Tibet and Tibet-

related areas of the four provinces. Through Pearson correlation matrix analysis between Tibetan

autonomous prefectures and representative cities in Tibet, it is found that there is a synergistic correlation

between school-age children's schooling rate, road transportation development, and farm household income

per capita in the two regions, which can promote joint development through a coordinated approach. Based

on this, the article proposes to increase the investment and support for education in ethnic regions, further

improve the construction of telecommunication and communication systems in ethnic regions, and establish

a comprehensive and diversified regional synergy system.

1 INTRODUCTION

In recent years, the government has been paying

more and more attention to the economic and social

development of ethnic regions and has taken a series

of policy actions to provide support and guarantee

for the economic development and livelihood

improvement of ethnic regions in China. With the

in-depth implementation of various policies and

guidelines dedicated to improving social

development, ethnic areas have been improving in

terms of education capability, communication level

and transportation development, and the overall

social development is getting better (Atasoy, 2013).

In the period of transition from precise poverty

alleviation to rural revitalization, the level of farm

household income is still one of the indicators that

needs to be focused on, which reflects the

development of economic level in ethnic areas. At

this stage, the influence of social factors on economy

and the reasonable allocation of resources between

the two have become one of the key concerns in

ethnic areas. Based on this, an in-depth study of the

influence of social factors on farm household

income in ethnic regions is of great significance for

regional development, and the performance of such

influence under the theory of regional coordination

is also a focus of our attention.

2 THEORY AND MECHANISM

ANALYSIS

Firstly, social factors in ethnic areas can promote

farmers' income increase by improving population

quality, innovating production methods, enhancing

production skills and enriching life experiences.

Second, social factors in ethnic areas can promote

farmers' income increase by accelerating information

transfer and cultural exchange and further enriching

the ways of income generation (Fleisher, 2009).

Lack of knowledge and poor communication are

important reasons limiting the development of ethnic

areas. High-efficiency communication and

developed transportation facilities will speed up the

exchange and dissemination of knowledge and

technology, which will help increase the economic

Chen, Q. and Hu, Y.

Study on the Inﬂuence of Social Factors on Economic Income Under the Theory of Regional Coordination.

DOI: 10.5220/0011730800003607

In Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology (ICPDI 2022), pages 93-98

ISBN: 978-989-758-620-0

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

income of households. Finally, social factors in

ethnic areas can promote the increase of household

economic income of farmers through inter-regional

coordination and mutual synergy (Tokila, 2011). At

the theoretical level, social factors in ethnic areas

affect farm household income from the above three

aspects, but the effect of their influence still needs to

be tested empirically. In this paper, we will take the

coordinated development of Tibet and Tibet-related

regions in four provinces as the goal, analyze the

influence of social factors in ethnic regions on

farmers' household economic income through

multiple regression and PSM models, explore the

impact-related points that can be coordinated

between Tibet and Tibet-related regions in four

provinces, and further explore the path of

coordinated and coordinated development of Tibetan

society and economy in Tibet-related regions in four

provinces (Chen, 2008).

3 DATA FOUNDATION AND

MODEL BUILDING

3.1 Data Sources

The data used in this paper come from micro

household data from field research in Tibetan-

related areas in four provinces and Tibet, as well as

macro data from the Sichuan Statistical Yearbook

2020, Qinghai Statistical Yearbook 2020, Gansu

Statistical Yearbook 2020, Yunnan Statistical

Yearbook 2020, and the 2020 National Economic

and Social Development Statistical Bulletin of

representative cities and Tibetan autonomous

prefectures. Among them, the research data

specifically include Hongyuan County, Ganzi

County, Ruoerge County, Markang County, Dafu

County, and Danba County in Tibet-related areas of

Sichuan; Diebe County, Zhuoni County, and Xiahe

County in Tibetan areas of Gansu; Deqin County,

Shangri-La County, and Weixi County in Tibetan

areas of Yunnan; GuiDe County and Duran County

in Tibetan areas of Qinghai and Lhasa City in Tibet

Autonomous Region. A total of 480 questionnaires

were distributed in the survey in Tibet-related areas

of the four provinces, with 454 valid questionnaires

and an actual recovery rate of 94.58%; a total of 780

questionnaires were distributed in the survey in

Lhasa, with 745 valid questionnaires and an actual

recovery rate of 95.5% (Jiang, 2012).

3.2 Explanatory Variables

3.2.1 For Author/S of Only One Affiliation

(Heading 3): To Change the Default,

Adjust the Template as Follows

In this paper, the economic income of farm

households was selected as the explanatory variable,

and the raw data were standardized in order to

eliminate the effects of differences in the average

income levels of different villages and the

measurement unit scale. The formula is:

𝑎 =

𝑎



−𝑎





𝑠

(1)

where, i denotes the states, a denotes the indicator to

be standardized, denotes the mean of this indicator

in Tibetan areas or Tibet-related areas in four

provinces, and s denotes the standard deviation.

3.2.2 Core Explanatory Variables

In this paper, social factors related to farm

households were selected as the core explanatory

variables, firstly, telecommunication network

situation included whether telecommunication was

connected (1=connected, 0=not connected) and

source of electricity (1=powered by national grid,

0=self-generated); education situation was selected

as the core explanatory variable for education level

(1=uneducated, 2=not attended school but could

read and write, 3=graduated from elementary school,

4=graduated from junior high school, 5=general

high school, 6= secondary school, vocational high

school, 7=college undergraduate, 8=university

undergraduate, 9=graduate and above), and

transportation status was selected as the core

explanatory variables (1=yes, 0=no).

3.2.3 Control variables

In this paper, health status (1=very bad, 2=bad,

3=fair, 4=good, 5=very good), ethnicity (1=Tibetan,

2=other), number of laborers, number of household

yaks, employment status, and agricultural insurance

coverage (1=insured, 2=uninsured) were selected as

control variables.

3.3 Model Establishment

In order to avoid the problem of multicollinearity

and eliminate the effects caused by differences in

magnitudes, a multiple linear regression model (1)

was established after standardizing some of the

variables. Further, an OLS+ robust standard error

model (2) was established to deal with the

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heteroskedasticity of the model and make the model

more robust. In addition, this paper also matches

each household with no telecommunication network

or no education with a propensity score for a

household with telecommunication network or

education, so that these two households are not

identical only at the level of whether they have

telecommunication network or education, and other

variables are basically the same.

For the entire group of farmers, this net effect is

called the average treatment effect (ATT) and is

expressed as:

ATT=E(Y

|D=1)-E(Y

|D=1)=E(Y

-Y

|D=1) (2)

where is the household economic income of the

farmer with a better telecommunication network and

is the household economic income of the farmer

with a worse telecommunication network.

4 EMPIRICAL RESULTS AND

ANALYSIS

4.1 Empirical Results and Analysis

In this paper, the effect of social development

factors on household economic income was tested

with farm household economic income as the

dependent variable and household social

characteristics factors as the independent variables,

and the results are shown in Table 1. From model (1)

and model (2), it can be seen that social

characteristics such as telecommunication network

status and education level significantly affect

household economic income.

Comparing the empirical results of the four

Tibetan provinces with those of Tibet, it is easy to

find that, in terms of telecommunication, the

economic income of farm households with

telecommunication networks in villages in the four

Tibetan provinces is significantly higher than those

without telecommunication networks, while the

higher the economic income of farm households

with electricity sources in Tibet tends to be from the

national grid, indicating that when farm households

have telecommunication networks in their villages,

their households can receive faster and more timely

Table 1: Empirical results.

Projects

Tibet-related areas in four

rovinces

Tibet

Variables Model (1) Model (2) Model (1) Model (2)

Standardized household economic income

Telecom Network

Situation

0.337 0.337** 0.396 0.396***

(0.307) (0.152) (0.468) (0.105)

Education level

0.178*** 0.178*** 0.144*** 0.144***

(0.054) (0.060) (0.045) (0.052)

Road condition

0.431 0.431* 0.246 0.246

(0.420) (0.220) (0.321) (0.323)

Health status

0.200*** 0.200*** -0.042 -0.042

(0.058) (0.049) (0.086) (0.087)

Ethnicity

0.104

(0.438)

0.104

(0.175)

-1.393*

(0.742)

-1.393

(1.463)

Labor force and

Employment

0.324***

(0.059)

0.324***

(0.066)

0.055*

(0.029)

0.055

(0.034)

Total number of yaks

0.007*** 0.007*** 0.015*** 0.015***

(0.003) (0.002) (0.003) (0.004)

Agricultural Insurance

-0.304*** -0.304** -0.246** -0.246**

(0.117) (0.129) (0.120) (0.117)

Study on the Inﬂuence of Social Factors on Economic Income Under the Theory of Regional Coordination

In particular, the national power supply is more

efficient than the farmers' own power generation, so

it is conducive to the production and living of the

farmers' households, thus promoting the increase of

their economic income. Therefore, Tibet and the

Tibet-related regions in the four provinces can

promote the overall economic development of the

region by improving the level of telecommunication

(especially the national electricity supply and the

popularity of intelligent communication). As for

education, both regions show a significant positive

effect of education level on household economic

income, indicating that both regions can further

promote coordinated regional economic

development by improving education services,

enriching farmers and herdsmen's knowledge, and

innovating production methods and efficiency while

improving population quality. In terms of road

construction, the road construction in the four Tibet-

related provinces positively affects the economic

income of farm households at a statistical level of

10%. On the one hand, the development of

transportation will speed up the exchange and

synergy among regions and drive the overall

economic development of western ethnic regions,

thus promoting the improvement of household

economic income; on the other hand, the

construction of roads will affect the labor force

transfer to a certain extent, and the development of

transportation will drive the outflow of labor, and its

joint offset with the promotion effect brought by

regional linkage shows positive influence, which

will promote the house-hold economic income of

farmers in a comprehensive way (Liu, 2021). This

effect is not significant in Tibetan region, so Tibet

can learn from the highlights of road construction in

Tibet-related areas of four provinces to further

improve road transportation service capacity, thus

further increasing the economic income of local

farm households.

4.2 Robustness Test

In order to ensure the scientificity of the research

results, this paper adopts the method of replacing

variables for robustness testing. Jing You et al.

(2020) had used the indicator of years of education

to measure the educational attainment of the

research subjects in their study, so this paper will

replace the educational attainment with years of

education, i.e., the original categorical variables will

be replaced by the specific length of years of

education. After the OLS+ robustness standard error

model regression, it was found that the significance

levels and coefficient signs of the core explanatory

variables remained basically unchanged, and social

factors such as telecommunication network status and

education level remained significant, indicating that

the results were more robust, as shown in Table 2.

Table 2: Robustness test results.

Tibet-related areas

in four provinces

Tibet

Family economic income

Telecommunica

tions Network

Status

0.324** 0.399***

(0.133) (0.105)

Years of

education

0.040** 0.050***

(0.020) (0.018)

Road condition

0.469** 0.265

(0.224) (0.319)

Health status

0.209*** 0.042

(0.048) (0.088)

Ethnicity

0.139 -1.379

(0.157) (1.468)

Labor force and

employment

0.326*** 0.052

(

0.066

)

(

0.034

)

Total number of

yaks

0.007*** 0.015***

(0.002) (0.004)

Agricultural

Insurance

-0.284** -0.247**

(0.130) (0.117)

4.3 Propensity Score Matching Model

(PSM) Analysis of The Effect of

Social Factors on Economic Income

The results of the propensity score matching model

(PSM) analysis on social factors for income increase

in Tibet and Tibet-related areas in four provinces

using stata15.0 software can be obtained as shown in

Table 3. In terms of telecommunication network, the

average treatment effect ATT measured by the one-

to-one matching method, caliper matching method,

and kernel matching method in the four Tibetan

provinces and Tibet are all significantly positive at

the 1% level, which indicates that the development

of communication business can significantly

increase the economic income of farm households.

In terms of education level, the average treatment

effect ATT measured by the nuclear matching

method in the four Tibetan provinces is significantly

positive at the 10% level, and the results measured

by the three methods in Tibet are significantly

positive at the 5% level or more, which indicates

that the development of education in the two regions

can increase the economic income of farm

households to a certain extent (Sun, 2016). Taking

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Table 3: PSM Propensity Score Matching Table.

Variables Area

Before and after

matchin

unmatched matched ATT T

Telecommu

nications

Network

Tibet-related

areas in four

provinces

One to One Matching 0.527 0.056 0.0432 3.75

***

Caliper Matching 0.527 0.110 0.0226 2.96

***

Nuclear Matching 0.527 0.097 0.0643 3.66

***

Tibet

One to One Matching 0.039 0.267 0.0107 3.48

***

Caliper Matching 0.039 0.014 0.0107 3.25

***

Nuclear Matching 0.039 0.008 0.0107 3.54

***

Education

level

Tibet-related

areas in four

provinces

One to One Matching 0.050 0.020 0.1172 -0.27

Caliper Matching 0.050 0.002 0.1259 1.04

Nuclear Matching 0.050 0.006 0.1172 1.64

Tibet

One to One Matching 0.032 0.008 0.2125 2.29

Caliper Matching 0.032 0.002 0.2192 2.59

***

Nuclear Matching 0.032 0.001 0.2125 2.51

Roads

Tibet-related

areas in four

provinces

One to One Matching 0.119 0.075 0.1333 -0.61

Caliper Matching

0.119

0.036 0.2343 -0.85

Nuclear Matching

0.119

0.058 0.2165 -1.09

Tibet

One to One Matching 0.057 0.020 -0.0383 -0.22

Caliper Matching 0.057 0.003 -0.0383 -1.06

Nuclear Matching 0.057 0.018 -0.0383 -0.71

the caliper matching method to test the development

of telecommunication networks in Tibetan-related

areas in four provinces as an example, the calculated

mean treatment effect ATT= 0.0226 and is

significantly positive at the 1% level of significance,

indicating that the economic income of farm

households receiving education in Tibetan-related

areas in four provinces is 4.3% (i.e., 0.0226/ 0.527)

higher than that of farm households not receiving

education.

4.4 Correlation Analysis under

Regional Synergy Theory

In order to study the regional synergistic correlation

between Tibet-related areas in four provinces and

Tibet, this paper adopts the Pearson correlation

coefficient to measure the correlation between

representative indicators of social and economic

development in the two regions, which is calculated

as follow:

∑



∑

)



∑

)

(3)

The correlation analysis shows that there is a

strong positive correlation between the per capita

disposable income of farming households in the four

Tibetan-related provinces and the Tibet Autonomous

Region and the schooling rate of school-age

children, and there is a strong positive correlation

between the road density in the four Tibetan-related

provinces and the per capita disposable income of

farming households in the Tibet Autonomous

Region, so there is a certain connection between the

economic and educational development of the two

regions, especially in the stage of precise poverty

alleviation. The concept of "helping the poor to help

the wise" makes education in the two regions

popular and synergistic, and in the future, we can

combine more ethnic cultural characteristics to

promote the synergistic development of education

and culture in the two regions. At the same time, the

analysis of the matrix results also reveals that

although there is a positive correlation between the

road density in the Tibet-related areas of the four

provinces and the per capita disposable income of

farm households in the Tibet Autonomous Region,

the value of the correlation coefficient is not high

enough, and the positive role that the synergy effect

should play is not fully reflected, and the

transportation development in the Tibet-related areas

will, to a certain extent, drive the economic

development of the surrounding areas and even the

Tibetan region, thus increasing the per capita income

Study on the Inﬂuence of Social Factors on Economic Income Under the Theory of Regional Coordination

of farm households in Tibet (Su, 2016). In the

future, the two regions can strengthen the synergistic

linkage in transportation construction, and drive the

synergistic economic progress of the two regions

through the transportation development of Tibet-

related areas.

5 CONCLUSION

Focusing on the development of ethnic regions, this

study explores the influence of social factors on the

economic income of farm households from an

empirical perspective, based on micro research and

macro yearbook data. The results of the study show

that. (1) telecommunication network situation and

education level have a significant positive impact on

the economic income of farm households, and the

results of PSM propensity score matching are higher

in Tibet than in Tibet-related areas in four provinces.

(2) The effect of road transportation situation on

household economic income is not significant, and

the results obtained in Tibetan-related areas in the

four provinces are not significant. (3) There is a

strong positive correlation between school-age

children's enrollment rates in both regions, and there

is a strong positive correlation between road density

in Tibet-related regions and per capita disposable

income of farm households in the Tibet Autonomous

Region, and the two regions can strengthen

synergistic links in education and transportation in

the future. Based on the above analysis, this paper

proposes the following recommendations: First, the

state should continue to increase the investment and

support for education in rural areas, especially ethnic

areas. Second, local governments should further

improve the construction of telecommunication and

communication systems in ethnic areas to enhance

the ability of farmers and herdsmen to increase their

income. Third, grassroots management organizations

should establish a comprehensive and diversified

regional synergy system and strengthen the

coordination and cooperation of Tibetan-related

areas in the four provinces.

ACKNOWLEDGMENT

This paper is supported by the Sichuan University

Student Innovation Training Program project

"Research on the path of credit support for yak

industry from the perspective of supply and demand

- Hongyuan County as an example" (Project No.:

202010626099).

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