Analysis of the Impact of Water Conservancy Investment on

High-quality Economic Development in Western China

Jiwei Zhu

1,2

, Wenxing Fang

1,2,*

, Xining Jing

1,2

and Jianmei Zhang

1,2

State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an, China

Research Center of Eco-hydraulics and Sustainable Development, The New Style Think Tank of Shaanxi Universities,

Xi’an, China

Keywords: Water conservancy investment, Economic development, Influence relationship, Influence path

Abstract: Water conservancy is the lifeblood of the national economy and is of great significance to the high-quality

development of the region. In order to maximize the economic benefits of water conservancy investment

(WCI), this article focuses on panel data from 2005 to 2018 in 12 provinces in western China, and constructs

an economic development evaluation index system from five dimensions: innovative development,

coordinated development, environmental development, opened development and shared development, and

uses dynamic panel model to explore the influence relationship and path of western WCI on economic

development. The results indicate that: there is a significant non-linear effect between WCI and economic

growth, and show an inverted U-shaped relationship. This shows that with the expansion of WCI, economic

growth has risen first and then declined. At present, the impact of WCI in the western region on high-quality

economic development is in the promotion stage of positive and sustained growth. The results of this paper

help to control the scale of water resources input and improve the effectiveness of water resources investment

in the western region to support decision-making.

1 INTRODUCTION

Investment in water conservancy construction, as a

controlling factor that promotes national economic

growth, protects the lives of the people and the

ecological environment, occupies a very important

position in the economically backward western

regions. After the 19th National Congress of the

Communist Party of China, the central government's

investment in water conservancy infrastructure has

reached a new level. The western region has seized

the opportunity to substantially increase the scale of

investment in water conservancy infrastructure. On

the one hand, it is to promote economy development

and improve people’s livelihood, on the other hand, it

is also to solve the prominent contradiction between

economic and social development and water supply

and demand, and to achieve sustainable development

of water resources and economic society (Qiu, 2020).

Therefore, studying the impact of water resources

investment on economic growth is of great

significance for optimizing the structure of water

conservancy construction investment and maximizing

the economic benefits of water resources investment.

Many scholars have launched many discussions

on the relationship between water resources

investment and economic growth. Xu and Li (2012)

measured the contribution of water conservancy

construction investment to economic growth and

found that water conservancy construction investment

has the most direct impact on the primary industry. Ge

and Yan (2015) used the general Solow production

function to estimate that water conservancy

construction investment has a 10% stimulating effect

on GDP growth. Chen Yuanyuan (2019) analyzed the

relationship between economic development and

water conservancy construction investment in the

western region from 2002 to 2016, and found that

economic development has a significant long-term

positive impact on investment in water resources

construction. Wang et al. (2019) established a

dynamic multiplier analysis model and concluded that

the contribution rate of Guangdong's WCI to GDP

from 2000 to 2017 was 0.65%-2.40%. Chen and

Wang (2019) found that the investment in water

conservancy construction has a long-term co-

integration relationship with the total output value of

agriculture, forestry, animal husbandry and fishery. In

Zhu, J., Fang, W., Jing, X. and Zhang, J.

Analysis of the Impact of Water Conservancy Investment on High-quality Economic Development in Western China.

In Proceedings of the 7th International Conference on Water Resource and Environment (WRE 2021), pages 333-340

ISBN: 978-989-758-560-9; ISSN: 1755-1315

333

summary, the existing research mainly focused on

analyzing the direct relationship between WCI and

GDP, and lacks a comprehensive consideration of

economic development, that is, analyzing its

relationship with high-quality economic

development. Therefore, based on panel data, this

article uses a dynamic model to study the impact of

WCI on high-quality economic development in the

western region, and quantifies the contribution of

WCI to economic and social development. This helps

to understand the current situation of investment in

water conservancy construction in the western region

and promote high-quality economic and social

development in the western region.

2 GENERAL SITUATION OF WCI

AND ECONOMY IN THE

WESTERN REGION

2.1 Data Sources

The data in this article are mainly derived from the

2005-2018 China Water Conservancy Yearbook,

China Water Conservancy Statistical Yearbook,

China Statistical Yearbook, National Economic and

Social Development Statistical Bulletin, and

statistical yearbooks of 12 provinces in the western

region and their portal websites public information.

Figure 1: Completed amount and growth rate of WCI

in the western region.

2.2 WCI in the Western Region

2.2.1 Analysis of WCI Scale

Water conservancy construction, as a key support

area of national infrastructure construction, is one of

the key investment directions of government financial

funds (Wang, 2017). In terms of investment

arrangements, the state pays attention to the central

and western regions, especially the western regions.

The details of the completion of the western WCI are

shown in Figure 1.

2.2.2 Analysis of Sources of WCI

With the continuous expansion of WCI, the sources

of WCI have gradually shown diversified

characteristics. By categorizing the amount of WCI

completed in 2005-2018 according to the source of

funds, it is found that government investment has

always occupied the main position, of which the

central government has the largest proportion.

Enterprise and private investment, and domestic

loans, as new forces,

also account for about one-

seventh of each year. The use of foreign capital,

others, and bonds account for a relatively small

proportion, with an annual share of less than 10%.

Figure 2 shows the proportion of different sources of

funds in each year.

Figure 2: Distribution of WCI sources in the western region.

Figure 3: Distribution map of WCI by purpose in the

western region.

2.2.3 Analysis of WCI Use

Based on the data of WCI completed in the western

region from 2005 to 2018, it is divided into flood

control engineering, water supply engineering,

irrigation engineering, soil and water conservation

and ecological engineering, water logging

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334

engineering, hydropower engineering and

preliminary work according to purpose. The specific

situation is shown in Figure 3.

2.3 Economic Development in the

Western Region

With the implementation of the western development

strategy, new historical achievements have been made

in the economic and social development of the

western region, which has played an important

supporting role in national development (Wang &

Wang, 2019). The western region has entered a period

of rapid development, and some provinces have been

in the forefront of the country in economic indicators

for many years. However, compared with the eastern

region, the overall level of economic development in

the western region is relatively backward, with its

GDP accounting for only one-fifth of the country, and

investment in fixed assets is relatively small.



Figure 4: The economic development of the western region

from 2005 to 2018

Although the disposable income of urban

residents has been growing, there is still a large gap

between the national average and the disposable

income, as shown in Figure 4. Therefore, in the future,

the western region should still be the main target of

national policy support and investment tilt.

3 MODELS AND METHODS

3.1 Variable Selection

3.1.1 The Explained Variable

The explained variable is the level of economic

development. This article quantifies the economic

level of the western provinces from five dimensions:

innovative development, coordinated development,

green development, open development, and shared

development, and establishes an indicator system

(Pan & Luo, 2020), the results are shown in Table 1.

It can be seen from the table that the indicator system

consists of 5 first-level indicators, 12 second-level

indicators, and 20 third-level indicators.

In order to eliminate the differences in dimension,

order of magnitude, and orientation among the

various indicators, this paper adopts the entropy

method to standardize the selected indicator data. The

forward index is processed by formula (1), and the

reverse index is processed by formula (2).

min

max min

(1)

max

max min

(2)

Among them, x



represents the value in the i-th

row and j-th column in the original data, x



represents the maximum value in the j-th column in

the original data, and x



represents the minimum

value in the j-th column in the original data. See (3),

(4), (5) for specific calculation formulas, and it is

stipulated that when q



0, limq



ln q



0.





(3)

iijij







(4)



i=1

1-s





（）

(5)

Among them, q



represents the proportion of



in the comprehensive sum of the data; s



represents the index information entropy; w



represents the index weight, the number of columns

n=14, and the number of indicators m=20. Based on

the entropy weighting method, the weights of each of

the indicators are calculated to obtain the

comprehensive economic development level of each

province.

Analysis of the Impact of Water Conservancy Investment on High-quality Economic Development in Western China

335

Table 1: Indicator system of economic development level.

Object level

Primary

targets

Secondary

indicators

Three-level indicators Unit Direction

Economic

development

Innovation

and

Development

Innovation

Input

Research and experimental

development expenditures (Liu,

2020; Qiao, 2021)

billion yuan +

Full-time equivalent of research and

erimental develo

ment

ersonnel

Ten thousand

Innovation

Outputs

Number of domestic patent

lications acce

ted

(

Li & Ju, 2021

)

item +

Technical turnover (Cao, 2021) billion yuan +

Coordinated

Development

Industrial

development

coordination

Industry rationalization index (Peng

& Zhu, 2020)

% -

Industrial Structure Advanced Index

(

Qiao, 2021; Pen

& Zhu, 2020

)

% +

Urban-rural

economic

harmonious

Consumption ratio of urban and rural

residents (Cao, 2021; Peng & Zhu,

2020)

- -

Income ratio of urban and rural

residents (Liu, 2020) (Peng & Zhu,

2020)

- -

Green

Development

Green Life

Forest coverage (Ma & Chen, 2020;

Wan et al., 2020

)

% +

Harmless treatment rate of domestic

arba

(

Liu, 2020; Cao, 2021

)

% +

Energy

consumption

Total city natural gas supply (Liu,

2020)

billion cubic

meters

Environmental

management

Urban green area (Liu, 2020; Peng &

Zhu, 2020; Wan et al., 2020)

million hectares +

Open

Development

Foreign trade

The proportion of total import and

export in GDP (Liu, 2020; Duan et

al., 2020)

% +

Utilize foreign

capital

The proportion of foreign direct

investment in GDP (Ran & Zheng,

2021)

% +

Tourism

openness

International tourism receipts (Cao,

2021)

One hundred

million dollars

Shared

Development

Economic

shared

development

per capita GDP (Liu, 2020; Duan et

al., 2020; Ma & Chen, 2020; Wan et

al., 2020)

yuan/people +

Urbanization rate (Peng & Zhu,

2020)

% +

Social shared

development

Staff in health institutions (Cao,

2021

)

million people +

Education funding (Liu, 2020) million yuan +

Volume of passenger traffic (Liu,

2020)

million people +

3.1.2 Core Explanatory Variables

The core explanatory variables are the WCI and the

square item of WCI in 12 provinces, municipalities,

and autonomous regions in the western region.

3.1.3 Control Variables

In order to better describe the explained variables, this

article selects human capital, government

intervention, urbanization rate, and degree of opening

to the outside world as the control variables of this

model. The main variables involved in this article

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include: economic development (Eco), WCI (Water),

WCI square item (Waterq); intermediary variables

include: industrial structure (Ind), technological

progress (Rd) and resource allocation (Diskl); control

Variables include: human capital (Hum), urbanization

level (Urb), government intervention (Gov), and

degree of openness (Imp). To ensure the stability of

the data, the logarithmic value of the WCI and the

degree of openness are taken, and the square term of

the WCI is obtained by taking the logarithmic value

of the WCI and then square (Sun & Zhou, 2019).

3.2 Model Construction

Based on the endogenous economic growth model,

combined with the economic development indicator

system, this paper studies the impact of WCI on

economic development and establishes a basic model,

as shown in formula (6).

it 0 1 2

Eco = + + + +

it it i it

ββW β Xuε

(6)

Among them, Eco



represents the level of

economic development of place i in period t, W



the amount of WCI completed in place i in period t,



is other factors that affect economic development

in the same period and the same place, u



is the

individual disturbance term, and ε



is random

disturbance items.



is the intercept term of the model, β



is the

variable coefficient of WCI, the positive and negative

coefficients represent the direction of the influence of

WCI on economic development, and the magnitude

indicates the degree of influence. To improve the

accuracy and scientific character of the model, this

article optimizes the above basic model as follows:

3.2.1 Dynamic Panel Model

In order to assess whether there is a difference in the

impact of WCI on economic development under

different investment scales, this paper introduces the

square term of WCI. Economic development is a

process of dynamic changes in the economic

structure. The impact of the previous level on the

current development cannot be ignored. In order to

better explore the impact of water investment on

economic development, a dynamic Panel model is

constructed by introducing third-order lagged

variables of the explanatory variables. The optimized

model is shown in (7).

Eco

𝛽



𝛽



𝐸co



𝛽



𝐸𝑐𝑜



𝛽



𝐸𝑐𝑜





𝛽



𝑊



𝛽



𝑊





𝛽



𝑋



𝑢



𝜀



(7)

In the formula, Eco



, Eco



, Eco



respectively represent the first, second, and third-

order lagging terms of the economic development

level, and W_q



is the square term of WCI, and the

meaning of other variables is the same as equation (6).

3.2.2 Model Robustness Test

The robustness of the model has an important impact

on the accuracy of the measurement results, and index

replacement is a common method to test the

robustness of the model. The development level of the

tertiary industry is one of the important indicators that

reflect the level of productivity development of a

country or region (Zhao, 2013). This article uses the

added value of the tertiary industry as a test index for

the replacement economic development level.

4 RESULTS AND ANALYSIS

4.1 Analysis of Benchmark Results

Considering that the relationship between the

explained variable and the core explanatory variable

may be mutual: WCI will promote economic

development, and economic development will in turn

affect the scale of WCI, so the model may be

endogenous. The results of LR test and Wald test both

concluded that there is heteroscedasticity between the

model disturbance items. In order to improve the

accuracy of the regression results, the system GMM

method is used to regress the model after the second-

order difference of the variables.

The test results of AR (1) and AR (2) in Table 2

show that the model has first-order autocorrelation,

but no second-order autocorrelation and no

autocorrelation of the disturbance terms. Meanwhile,

the p-values of the Sargan test are both greater than

0.1, indicating that the instrumental variables are

effectively chosen. Therefore, it is feasible to use the

systematic GMM method to estimate the model.

It can be seen from the results that the regression

coefficients of the economic development of the three

lagging periods are all very significant, indicating that

the economic development of the western region will

be affected by the previous development level.

Further observation of the regression coefficient of

WCI, we found that regardless of the introduction of

control variables, the regression coefficient of WCI

on economic development are all positive,

Analysis of the Impact of Water Conservancy Investment on High-quality Economic Development in Western China

337

respectively 0.3276*, 0.2949**, 0.2028*, 0.2535*

and 0.3297***, and the P values are all within their

respective ranges, so they have also passed the

significance test. The significance test shows that in

the transitional stage of economic growth in the west

of our country, strengthening WCI to promote

economic development is a viable path choice. For the

square term of WCI in Table 2, the coefficients are all

significantly negative, which shows that with the

increase of WCI, the economy shows a trend of first

increase and then decrease, that is, there is an inverted

U-shaped relationship between WCI and economic

development. It shows that the role of WCI in

promoting economic growth is conditionally limited,

and a reasonable investment scale is the key to giving

full play to the economic benefits of WCI. Once it

exceeds the best advantage, it will hinder economic

growth.

Table 2: Analysis of the impact of WCI on economic development.

(1) (2) (3) (4) (5) Robustness test

Eco(-1)

0.6685***

-0.6551*** -0.5778*** -0.5808***

0.6119***

-0.4524***

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Eco(-2)

-0.2502** -0.2468** -0.2872*** -0.2710** -0.2794** -0.2285***

(0.013) (0.004) (0.001) (0.001) (0.009) (0.000)

Eco(-3)

0.2686***

-0.2745** -0.2524* -0.2279* -0.1943* -0.1448

(0.001) (0.001) (0.016) (0.015) (0.033) (0.053)

Water

0.3276* 0.2949** 0.2028* 0.2535* 0.3297*** 0.3615***

(0.012) (0.008) (0.018) (0.013) (0.001) (0.000)

Waterq

-0.0117* -0.0106* -0.0073* -0.0090*

0.0119***

-0.0129***

(0.015) (0.011) (0.024) (0.015) (0.001) (0.000)

Urb

1.1795* 1.2354* 1.1501* -3.6883 1.5548*

(0.021) (0.017) (0.036) (0.847) (0.042)

Imp

0.0159*** 0.0159*** 0.0363 0.0060*

(0.000) (0.000) (0.700) (0.022)

Gov

0.0315 1.0521 0.2879*

(0.729) (0.052) (0.017)

Hum

0.0165*** -45.5774*

(0.001) (0.027)

_cons

0.0136*** 0.01318838*** 0.0116*** 0.0119*** 0.0121*** -0.0079*

(0.000) (0.000) (0.000) (0.000) (0.000) (0.011)

AR(1)

-3.0243 -2.9216 -2.9193 -2.8952 -2.9031 -2.5414

(0.0025) (0.0035) (0.0035) (0.0038) (0.0037) (0.0110)

AR(2)

-0.0652 0.3596 0.5131 0.5373 0.7738 1.2505

(0.9480) (0.7191) (0.6079) (0.5911) (0.4390) (0.2111)

Sargan test 84.47629 102.6454 107.5081 115.7045 132.7714 136.2922

(0.6722) (0.7886) (0.9489) (0.9483) (0.8405) (0.7817)

Note: * p<0.05, ** p<0.01, *** p<0.001; The P value of the corresponding statistic is in parenthes

WRE 2021 - The International Conference on Water Resource and Environment

338

However, judging from the WCI coefficient, the

western region is still far from the best point at this

stage, and it is still at a stage where it is necessary to

continue to increase investment. The rapid

development of the western region still requires

government investment and policy support. As far as

the control variables are concerned, the regression

coefficients of human capital, degree of development,

and urbanization are all significantly positive,

indicating that higher levels of human capital, degree

of openness, and urbanization rate are all conducive

to economic development. Although the coefficient of

government intervention on economic development is

positive, However, the reliability is not high due to its

low significance.

4.2 Robustness Analysis

Re-regression the value added of the tertiary industry

as the explained variable, and the results are shown in

Table 2. The significance and direction of the

regression coefficients did not change substantially,

but only the magnitude of the coefficients changed.

The estimated results still support the conclusion that

WCI can effectively improve economic development

and the relationship between the two is inverted U-

shaped, indicating the regression of the model The

result is robust.

5 SUMMARY AND CONCLUSION

Using descriptive data statistics, analyzing from the

three aspects of GDP, investment in fixed assets, and

people’s living standards, it is concluded that the

social and economic development of the western

region is in a state of continuous growth, but there is

a certain gap compared with the eastern region. Some

indicators have not reached the national average.

Analyzing the current situation and evolution trend of

WCI in the western region from three perspectives of

investment scale, investment source and investment

purpose, it can be found that the total amount of water

investment in the western region has been increasing

in the past 14 years. Mainly for irrigation projects, soil

and water conservation, ecology, and preliminary

work have gradually become the focus of investment.

The results show that there is a significant non-linear

effect between WCI and economic growth, showing

an inverted U-shaped relationship, that is, as the scale

of WCI expands, economic growth shows a trend of

rising first and then falling. It shows that the

expansion of WCI scale before reaching the optimal

scale has a positive impact on economic growth, and

exceeding the optimal investment scale will hinder

economic development.

The scale of WCI should match the local

economic development, population size, and natural

conditions. We should not blindly pursue scale

expansion. It is necessary to reasonably control the

scale of investment according to specific needs. At

this stage, the western region is still at a stage where

it is necessary to continue to increase investment in

water conservancy, and we must continue to pay

attention to investment in weak links in water

conservancy infrastructure construction. Pay attention

to the gradual transformation of WCI from traditional

power generation and irrigation to water conservation

and ecological and water conservancy informatization

construction, and continue to accelerate the pace of

water conservancy modernization.

ACKNOWLEDGMENTS

This research was funded by Project of National

Natural Science Foundation of China (71774132),

Shaanxi Water Conservancy Science and Technology

Project (2020SLKJ-22), Shaanxi Provincial

Department of Education Key Scientific Research

Project (20JT053).

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