Impact of Transport Infrastructure on Common Prosperity: Based
on the Two-Way Fixed Effects Model
Guoli Ou
1,2
, Zhiqiang Zhu
1,* a
, Xiaoling Xie
1
and Junwei Wang
2
1
The Platform of Transport Technology Thinktank (Research Institute of Highway, Ministry of Transport), Beijing 100089,
China
2
School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
*
Keywords: Transport Infrastructure, Urban-Rural Income Disparity, Common Prosperity, Labor Mobility.
Abstract: Transportation has become the pioneer of Chinese modernization and plays an important role in achieving
common prosperity. From the perspective of urban-rural income disparity, we empirically investigate the
effect of transport infrastructure on common prosperity, the mechanism and nonlinear characteristics based
on panel data of 30 provinces in China from 2001 to 2020. The results show that transport infrastructure can
significantly reduce the urban-rural income disparity and promote common prosperity by the mechanism of
labor mobility. With the continuous improvement of the transportation network, the effect of transport
infrastructure in narrowing urban-rural income disparity and promoting common prosperity shows a marginal
incremental trend. Our findings provide rewarding policy implications for the practice that transportation
continues to empower the common prosperity in the new era.
1 INTRODUCTION
Common prosperity is the essential requirement of
Chinese socialism. Realizing common prosperity in
high-quality development is essentially a process of
correctly handling the relationship between
efficiency and equity and pursuing a balance between
social equity and efficiency. As China enters the stage
of high-quality development, the issue of urban-rural
income disparity has become the most intuitive
manifestation of potential economic and social
inequities. Although the urban-rural income disparity
has begun to converge in recent years, the serious
imbalance in the distribution of income between
urban and rural areas remains a constraint on China's
ability to make substantial progress in promoting
common prosperity.
In the previous literature, the positive effects of
transport infrastructure on economic growth have
emerged a basic consensus. Transport infrastructure
improves the efficiency of capital flows, mainly by
improving accessibility and reducing transport
transaction costs (Baldwin and Martin, 2003), which
in turn facilitates regional exchanges and
a
https://orcid.org/0009-0001-3132-9728
international trade, affecting interregional trade costs
and price differentials and thus increasing regional
income levels (Donaldson, 2018). However, the
positive effect of transport infrastructure on economic
growth is significantly heterogeneous across regions
(Zhang et al., 2024) and modes of transportation (Shi
and Shen, 2023). In response to the existence of
heterogeneity, Banerjee et al. (2020) point out that
while transport infrastructure continues to strengthen
linkages between urban and rural areas (Banerjee et
al., 2020), urban area with more prominent locational
advantages will continue to gather rural out-migration
capital, thereby limiting or even worsening rural
economic development and increasing the disparity
between urban and rural development. Investment in
transport infrastructure such as high-speed rail may
also deteriorate regional economic conditions due to
its high investment price and long payback cycle
(Yoo et al., 2024).
The impact of transport infrastructure on the
urban-rural income disparity has not yet been
unanimously concluded in existing studies. Some
scholars argue that differences in the level of
transport infrastructure may exacerbate urban-rural
Ou, G., Zhu, Z., Xie, X., Wang and J.
Impact of Transport Infrastructure on Common Prosperity: Based on the Two-Way Fixed Effects Model.
DOI: 10.5220/0013573100004671
In Proceedings of the 7th International Conference on Environmental Science and Civil Engineering (ICESCE 2024), pages 37-44
ISBN: 978-989-758-764-1; ISSN: 3051-701X
Copyright © 2025 by Paper published under CC license (CC BY-NC-ND 4.0)
37

income disparities, as public capital investment tends
to be negatively correlated with income disparities in
the short run, but may be positively correlated in the
long run (Lu et al., 2022). Interregional public
transportation infrastructure may also widen the
urban-rural income disparity (Valenzuela-Levi,
2023). Others hold that the impact of transport
infrastructure on the rural-urban income disparity
may be characterized by significant threshold
nonlinearities, and that while improved transport
infrastructure promotes connectivity between rural
and urban areas and equalization of access to
resources, such improvements may not be sufficient
in the short term to fully reverse the lag in rural areas
(Ma et al., 2023). With regard to the mechanism of
transport infrastructure affecting the urban-rural
income disparity, previous literatures have focused on
the important role of labor mobility factors, such as
the proportion of the rural population, in the impact
of transport infrastructure on the rural-urban income
disparity (Ren and Zhang, 2013), suggesting that its
impact on rural labor mobility shows a dynamically
changing correlation (Sun, 2020).
Existing literature provides substantial references
for revealing the impact of transport infrastructure on
the urban-rural income disparity, but the conclusions
are mostly based on linear assumptions, with certain
deviations from the reality, lacking explanations of
the internal mechanisms, and the theoretical guidance
for promoting urban-rural coordination and common
prosperity needs to be deepened. Therefore, from the
perspective of urban-rural income disparity and based
on the nonlinear correlation hypothesis, we
empirically investigate the impact, mechanism and
nonlinear characteristics of transport infrastructure on
common prosperity by using Chinese provincial
panel data from 2001-2020. The conclusions provide
theoretical guidance and significant policy
implications for the construction of transportation
facilities to further promote common prosperity in the
new era.
2 THEORETICAL ANALYSIS
AND RESEARCH HYPOTHESIS
Compared with urban residents, rural residents have
less access to factors of production and resources in
terms of quantity and quality, as well as less efficient
use of resources, a situation that can be improved by
investing in transport infrastructure. Firstly, transport
infrastructure can directly provide employment
opportunities, and its construction and maintenance
periods generate a large demand for less technically
demanding labor, which enriches the income sources
of rural labor and increases their incomes (Ma et al.,
2023). Secondly, transport infrastructure can
effectively reduce production transaction costs,
smooth urban-rural trade routes, expand the spatial
scope of markets, and increase farmers’ revenue. It
can also improve the structure of industrial
development in rural areas, promote the development
of the non-agricultural economy, solve the problem
of employment for the impoverished (Ren and Zhang,
2013). Thirdly, transport infrastructure can promote
the economy of road diffusion industry, so that the
resources along that are exploited to a greater extent,
radiate and drive the development of the surrounding
areas (Sun, 2020), promote the integration of urban
and rural economy, and thus facilitate the common
prosperity.
According to the dual structure theory, the
existence of a sectoral wage disparity will make rural
laborers tend to move across sectors in order to earn
higher incomes, but high mobility costs will restrict
rural laborers from moving across urban and rural
areas in practice, so that they will continue to engage
in low-income jobs in rural areas, and the urban-rural
income disparity will still exist due to the obstruction
of labor mobility (Banerjee et al., 2020). Transport
infrastructure will enhance urban and rural
connectivity, reduce the cost of rural labor migrating,
and promote labor mobility. As the transportation
network is continuously improved and the cost of
urban-rural travel is increasingly reduced, rural
surplus labor will be transferred to the non-
agricultural sector on a larger scale, and as the degree
of urban-rural connectivity deepens, a large number
of farmers will return to their hometowns to find
employment and start their own businesses, thus
realizing the optimal allocation of a wider range of
labor resources, narrowing the gap between urban and
rural areas, and promoting common prosperity (Liu
and Zheng, 2013).
Transport infrastructure is inseparable from its
construction and use and therefore may have threshold
character. It means that transport infrastructure often
needs to reach a certain scale and size to play its
role (Chen et al., 2021). According to the theory of
matching transport supply and demand, when the
stock of transport infrastructure is lower than the
demand, high transportation costs will affect
production efficiency, impede the cross-regional
circulation of factors and limit economic
development. Non-equilibrium theory shows that
high-investment, long-cycle transport infrastructure
construction needs to be moderately ahead of social
ICESCE 2024 - The International Conference on Environmental Science and Civil Engineering
38

Transport
Infrastructure
Common Prosperity
(Urban-Rural Income
Disparity Perspective)
Labor Mobility
(+)
(+)
(+)
Direct
Effect
Indirect
Effect
Primary stage, Developmental stage,
Intermediate stage, Advanced stage
Threshold
Effect
Figure 1: Logical mechanisms by which transport infrastructure affects common prosperity.
demand to give full play to its pioneering role, but too
large a scale may lead to overinvestment, squeezing
the space for other investments and inhibiting the
development of other sectors. Therefore, the level of
transport infrastructure determines the direction and
extent of its effect on the urban-rural income disparity
(Yang and Shi, 2019). Thus, we put forward to the
following hypothesis:
Hypothesis 1: Transport infrastructure can narrow
urban-rural income disparity and thus promote
common prosperity.
Hypothesis 2: Transport infrastructure facilitates
labor mobility, which in turn will affect the urban-
rural income disparity and promote common
prosperity.
Hypothesis 3: The impact of transport
infrastructure on common prosperity from the
perspective of urban-rural income disparity exhibits
significant nonlinear characteristics.
Based on the above theoretical analysis, the
internal mechanism of transport infrastructure
affecting common prosperity is summarized as shown
in Figure 1.
3 METHOD AND RESEARCH
DESIGN
3.1 Empirical Model
Aiming to control for individual and time fixed
effects and accurately estimate the causal
relationship, we employ a Two-Way Fixed Effects
(TWFE) model to examine the effect of transport
infrastructure on common prosperity.
𝑇ℎ𝑒𝑖𝑙

=𝛼

+𝛼

𝑡𝑟𝑎𝑛𝑠

+𝛼

𝑐𝑜𝑛𝑡𝑟𝑜𝑙

+𝜀

+𝛾

+𝜇

(1)
Where 𝑇ℎ𝑒𝑖𝑙

is the dependent variable common
prosperity, i denotes province i, t denotes the year t,
𝑡𝑟𝑎𝑛𝑠 denotes the core explanatory variable
transportation network density, 𝑐𝑜𝑛𝑡𝑟𝑜𝑙 is the control
variable, α denotes the coefficients in front of each
variable, 𝛾

is the time fixed effect, 𝜇

is the
individual fixed effect, and 𝜀

is the error term. 𝛼

is
the regression coefficient of the core explanatory
variable, and since the level of common prosperity is
measured inversely by the rural-urban income
disparity indicator, when the coefficient is less than 0,
it indicates that transport infrastructure has a
significant promotion effect on common prosperity.
In order to verify the mechanism of labor
mobility, we construct a mechanism testing model
based on the causal step-by-step regression
improvement method as follows:
𝑇ℎ𝑒𝑖𝑙

=𝛽

+𝛽

𝑡𝑟𝑎𝑛𝑠

+𝛽

𝑐𝑜𝑛𝑡𝑟𝑜𝑙

+𝜀

+𝛾

+𝜇

(2
)
𝑙𝑎𝑏𝑜𝑟

=𝛾

+𝛾

𝑡𝑟𝑎𝑛𝑠

+
𝛾

𝑐𝑜𝑛𝑡𝑟𝑜𝑙

+𝜀

+𝛾

+𝜇

(3
)
𝐶𝑃

=𝜂

+𝜂

𝑡𝑟𝑎𝑛𝑠

+𝜂

𝑙𝑎𝑏𝑜𝑟

+
𝜂

𝑐𝑜𝑛𝑡𝑟𝑜𝑙

+𝜀

+𝛾

+𝜇

(4
)
Where 𝛽 , 𝛾 , 𝜂 is the variable pre-regression
coefficient, 𝑙𝑎𝑏𝑜𝑟 is the mechanism variable labor
mobility, and the rest of the variables and parameters
have the same meanings as above.
We conduct a panel threshold model to examine
the nonlinear characteristics of transport
infrastructure affecting common prosperity. First, a
single threshold model is constructed as follows:
𝑇ℎ𝑒𝑖𝑙

=𝜔

+𝜔

𝑡𝑟𝑎𝑛𝑠

𝐼

𝑡𝑟𝑎𝑛𝑠

≤𝜆

+𝜔

𝑡𝑟𝑎𝑛𝑠

𝐼

𝑡𝑟𝑎𝑛𝑠

>𝜆

+ 𝜃𝑐𝑜𝑛𝑡𝑟𝑜𝑙

+
𝜀

+𝛾

+𝜇

(5
)
If multiple thresholds exist, the model is
converted as follows:
𝑇ℎ𝑒𝑖𝑙

=𝜔

+𝜔

𝑡𝑟𝑎𝑛𝑠

𝐼

𝑡𝑟𝑎𝑛𝑠

≤
𝜆


+𝜔

𝑡𝑟𝑎𝑛𝑠

𝐼

𝜆

<𝑡𝑟𝑎𝑛𝑠

≤𝜆


+
⋯+𝜔

𝑡𝑟𝑎𝑛𝑠

𝐼

𝑡𝑟𝑎𝑛𝑠

>𝜆


+
𝜃𝑐𝑜𝑛𝑡𝑟𝑜𝑙

+𝜀

+𝛾

+𝜇

(6
)
𝜔 is the pre-regression coefficient of each
variable, 𝜆 is the threshold to be estimated, 𝐼 is the
Impact of Transport Infrastructure on Common Prosperity: Based on the Two-Way Fixed Effects Model
39

indicator function, 𝜃 is the coefficient of the control
variable, and the rest of the variables and parameters
have the same meaning as above.
3.2 Variable Selection
a) The dependent variable is the level of common
prosperity (𝑇ℎ𝑒𝑖𝑙). This paper chooses Theil index to
measure the urban-rural income disparity, and the
urban-rural income disparity to measure the level of
regional common prosperity. The Theil Index is
calculated as follows:
𝑇ℎ𝑒𝑖𝑙

=𝑃

/𝑃
∑
𝑙𝑜𝑔

𝑦/𝑦




(7)
𝑇ℎ𝑒𝑖𝑙

=
∑
𝑃

𝑇ℎ𝑒𝑖𝑙

+
∑
𝑃

𝑙𝑜𝑔𝑃

/




𝑉


(8)
Where Theil is the Theil index, 𝑃

denotes the
number of population in region i, P denotes the total
population of the regional, 𝑦

denotes the per capita
income of region i, 𝑦 is the average of 𝑦

, and
equation (8) is the decomposition formula further
grouped according to the region, and the first term of
the formula denotes the difference in per capita
income among the regions within each group divided
into groups, and the second term denotes the
difference between the groups, and 𝑉

denotes the
proportion of income of group 𝑔 to the total income,
and 𝑃

denotes the proportion of population of group
𝑔 to the total population of the region, and larger
values of the Theil Index imply a wider urban-rural
income disparity and a lower level of common
prosperity in the region.
b) The core explanatory variable is transport
infrastructure (trans). In this paper, we use the
transportation network density (the ratio of the
mileage of transport infrastructure in operation to the
administrative area), which is an indicator of the stock
of two modes of transportation: road and rail, to
measure the level of transport infrastructure
development.
c) The mechanism variable is labor
mobility(labor). Considering that urban-rural
connectivity brought about by transport infrastructure
is largely manifested in the expansion of non-farm
employment income by the rural labor force going out
to work, we select the proportion of the labor force
going out to work to the total labor force to measure
the labor mobility.
d) Control variables. In order to avoid the bias of
estimation results caused by omitted variables, this
paper introduces a series of control variables that may
affect the common prosperity based on the existing
literature, specifically included: financial
development(fina), industrial structure(indus), the
level of openness to the world(open), government
intervention(gov), economic growth(gdp), and
education level(edu). The description of the specific
variables is shown in Table 1.
Table 1: Description of variables.
Type Definition Notation Conjecture
dependent variable Common prosperity Theil Urban and rural Theil Index
Core explanatory
variable
transportation network
density
trans
Sum of public-railway
mileage/administrative area
Mechanism variable labor mobility labor Outworker labor force/overall labor force
Control variables
financial development fina
Year-end loan balances of financial
institutions/GDP
industrial structure indus
Secondary and tertiary industry output/total
output
the level of openness to the
world
open Total exports and imports/GDP
government intervention gov Government budget expenditure/GDP
economic growth gdp GDP per capita
education level edu Average years of schooling
ICESCE 2024 - The International Conference on Environmental Science and Civil Engineering
40

3.3 Data Sources
In this paper, we select the panel data of 30 provinces
(municipalities directly under the central government
and autonomous regions) in China, excluding Tibet,
Hong Kong, Macao and Taiwan, from 2001 to 2020
to examine the impact of transport infrastructure on
common prosperity from the perspective of the urban-
rural income disparity, and the data are mainly from
the National Bureau of Statistics (NBS), China
Statistical Yearbook, China Science and Technology
Statistical Yearbook, China Industrial Statistical
Yearbook, China Transportation Statistical
Yearbook, China Internet Development Statistical
Bulletin, GuotaiAn database, CEI statistics, as well as
provincial and municipal statistical yearbooks.
Figure 2 and Figure 3 show the overall level of
transport infrastructure development and urban-rural
income disparity in China from 2001 to 2020, and it
can be seen that the trend and direction of transport
infrastructure and urban-rural income disparity are
negatively correlated in general, and this paper
further estimates and verifies the effect of transport
infrastructure affecting the common prosperity and
the mechanism of which from the perspective of
urban-rural income disparity through the following
empirical model.
Figure 2: Transport infrastructure development.
Figure 3: Urban-rural income disparity.
4 EMPIRICAL RESULT AND
ANALYSIS
4.1 Benchmark Regression Results
In this paper, we use Stata17.0 to analyze and
estimate the model for each variable and related data.
According to the results of Hausman's test, a TWFE
model is chosen to verify the core hypothesis 1. Table
2 reports the estimation results of the effect of
transport infrastructure on common prosperity after
adding control variables, time fixed effects, and
province fixed effects. The results show that the
estimated coefficient of the core explanatory variable,
transport network density trans, is significantly
negative at 1% statistical level, indicating that the
improvement of transport infrastructure conditions
contributes to the reduction of the urban-rural income
disparity and thus promote the realization of common
prosperity. The regression coefficients and
significance of the remaining control variables are
basically consistent with expectations, proving the
rationality of the model setup in this paper, and
hypothesis 1 is supported by empirical evidence.
Table 2: Benchmark regression results.
Explanatory Variable Theil
trans
-0.3233
***
(0.0718)
fina
-0.1319
**
(0.0617)
indus
-0.3188
(
0.5588
)
open
-0.0688
**
(
0.0312
)
gov
0.0707
(
0.0587
)
gdp
-0.1684
**
(0.0783)
edu
-0.8284
**
(0.4003)
cons
-9.8685
***
(0.8510)
Province/Year
f
ixed e
ff
ects YES
N
600
R
2
0.5291
Note:
***
,
**
,
*
indicate significant at the 1 percent, 5
percent and 10 percent significance levels,
respectively, and () is the standard error, as below.
4.2 Mechanical Test
The estimation results of the labor mobility
mechanism test are shown in Table 3. As shown in
Impact of Transport Infrastructure on Common Prosperity: Based on the Two-Way Fixed Effects Model
41

column (1) of Table 3, the regression coefficient of
the total effect of transport infrastructure on common
prosperity is -0.3233. In column (2), the coefficient of
the effect of transport infrastructure on labor mobility
is 0.0665. In column (3), the coefficient of the effect
of labor mobility on common prosperity is -0.2904,
and all of them are signed at the 1% significance level
in line with the expected hypothesis. It indicates that
labor mobility is an important mechanism path in the
process of transport infrastructure to narrow the
urban-rural income disparity and promote common
prosperity, and hypothesis 2 of this paper is verified.
Table 3: Mechanism path test results.
Variable
(1) (2) (3)
Thei
l
labo
r
Thei
l
trans
-
0.3233
***
(0.0818)
0.0665
***
(0.0125)
-0.2904
***
(0.0753)
cons
-
9.8685
***
(0.8510)
-
0.7429
***
(0.1308)
8.8462
***
(0.6217)
control
variable
YES YES YES
Province/Yea
r fixed
effects
YES YES YES
N
600 600 600
R
2
0.5291 0.7592 0.5565
4.3 Threshold Effect Test
The non-linear characteristics of transport
infrastructure affecting common prosperity are
regressed using Stata 17.0 software. The results of
threshold value estimation are shown in Table 4.
Comparison of the F-statistics reveals that the triple
threshold estimates pass the 1% significant level test,
indicating the existence of three thresholds for
transportation on common prosperity. The regression
results in Table 5. Results show that the three
threshold estimates are 0.1421, 0.7458 and 1.2875,
respectively, and based on the actual values of the
threshold estimates, the development of transport
infrastructure can be divided into four phases, which
are the primary stage(0<trans≤0.1421), the
developmental stage(0.1421<trans≤0.7458), the
intermediate stage(0.7458<trans≤1.2875), and the
advanced stage(trans>1.2875).
Table 4: Threshold effect test results.
model F-value P-value
single
threshold
23.7734 0.0000
double
threshold
12.6531 0.0000
triple
threshold
5.7457 0.0010
As can be seen from Table 5, when the density of
the transport network is less than the 1st threshold
0.1421, the impact coefficient is 0.0399, which is
significantly positive at 5% statistical level,
indicating that in the primary stage of the
development of transport infrastructure, the
inadequate transport infrastructure will exacerbate
the urban-rural income disparity, which is detrimental
to the promotion of the common prosperity. When the
density of the transport network is between the 1st
threshold 0.1421 and the 2nd threshold 0.7458,
between the 2nd threshold 0.7458 and the 3rd
threshold 1.2875, and higher than the 3rd threshold
1.2875, the regression coefficients are -0.0754, -
0.2978, and -0.4428, respectively, which are
significantly negative at 1% statistical level,
indicating that as the transport infrastructure crosses
over to the stage of development and further develops
to the intermediate and advanced stages, it can
significantly narrow urban-rural income disparity and
promote common prosperity. It is obvious that as the
level of transport infrastructure stock increases, the
contribution of transport infrastructure to common
prosperity has a marginal increasing trend in the
second, third and fourth stages. Therefore,
Hypothesis 3 of this paper is validated.
Table 5: Threshold effect parameter estimation results.
Explanatory variable: Theil
Threshold variables:
trans
Coefficient Estimate
0<trans≤0.1421
0.0399
**
(0.0184)
0.1421<trans≤0.7458
-0.0754
***
(-0.0201)
0.7458<trans≤1.2875
-0.2978
***
(-0.0611)
trans>1.2875
-0.4428
***
(-0.0948)
Possible explanations for the non-linear growth
characteristics of China's transport infrastructure in
narrowing the urban-rural income disparity and
promoting common prosperity are: when the
transport infrastructure is in the primary stage, the
density of the transport network is inadequate, and the
ICESCE 2024 - The International Conference on Environmental Science and Civil Engineering
42

investment will be biased towards the urban areas,
which promotes the economic development and
income enhancement of the urban areas much more
than the rural areas, resulting in the widening of the
income disparity between urban and rural areas,
which is not conducive to the common prosperity.
With the continuous improvement of the transport
infrastructure, the transportation network gradually
covers rural areas and tends to be more
comprehensive, due to the slow development of rural
areas at the initial stage, the development potential is
huge, so the latecomer advantage is strong, and this
promotion effect gradually exceeds that of urban
areas, showing a non-linear growth trend with an
increasing marginal effect.
4.4 Robustness Test
In order to ensure the robustness of the research
results, this paper replaces the core explanatory
variable urban-rural Theil index with urban-rural
residents' income ratio for the robustness test, and
with the rest of the variables unchanged, regresses the
baseline regression model, the mechanism model and
the threshold effect respectively. The results of the
three tests show that neither significance nor the
direction of the coefficients have changed
significantly, so the findings of this paper are very
robust and all hypotheses are strongly validated. Due
to space constraints, the robustness test estimates are
not reported in the paper and can be obtained by
contacting the authors.
5 CONCLUSIONS AND POLICY
IMPLICATIONS
This paper studies the impact of transport
infrastructure on common prosperity from the
perspective of urban-rural income disparity using
China's provincial panel data from 2001 to 2020.
Regression results show that transport infrastructure
significantly reduces the urban-rural income disparity
and promotes the process of common prosperity in
China. Further mechanistic analysis finds that
transport infrastructure can facilitate urban-rural
labor mobility and enhance urban-rural connectivity,
thereby narrowing the urban-rural income disparity
and promoting common prosperity. The impact of
transport infrastructure on common prosperity shows
significant non-linear characteristics. At the primary
stage, when the level of transport infrastructure
development is low, it exacerbates the urban-rural
income disparity, and when it transitions to the
developmental stage, the intermediate stage and the
advanced stage, transport infrastructure markedly
reduces the urban-rural disparity and promotes
common prosperity, with the effect showing a
tendency to increase at the margin.
The findings of this study provide valuable policy
implications for empowering transportation for
common prosperity in the new era. First of all, the
government should pay attention to the construction
of transport infrastructure, focus on urban-rural
transport connection, enhance the accessibility of
transport infrastructure, maximize the effect of
transport infrastructure in narrowing urban-rural
income disparity, and continue to promote common
prosperity. Secondly, the government should
optimize the process of mobility of rural labor,
strengthen the construction and supervision of the
labor market, enhance urban-rural economic ties,
raise the income of rural labor, and ensure that the
transport infrastructure boosts labor mobility to
maximize its effect. Thirdly, other factors affecting
the urban-rural income disparity need to be
emphasized by the government. Strengthening
interregional open exchanges, unleashing the vitality
of rural economic development, improving the
competitiveness of rural employment, supporting
rural industries with special characteristics, and
synergizing with transport infrastructure will
continue to empower the common prosperity to move
to a new level.
6 DISCUSSION
In this study, we constructed a TWFE model to reveal
the impact of transport infrastructure on common
prosperity from the perspective of the urban-rural
income disparity, and also clarified the mechanism
and non-linear effects of transport infrastructure on
common prosperity, which provides policy
implications for the practice, but the study still has
several limitations. First, the connotation of common
prosperity is abundant, and this paper only focuses on
urban-rural income disparity, which can be studied in
the future by constructing a quantitative index system
taking other social factors into consideration. Second,
the mechanism that transport infrastructure affects
common prosperity is complicated, although we have
revealed it from the perspective of labor mobility
based on provincial data, it is still an important
research direction to further explore its mechanism
with a more detailed urban dimension data in the
future.
Impact of Transport Infrastructure on Common Prosperity: Based on the Two-Way Fixed Effects Model
43

ACKNOWLEDGEMENT
This paper is financially supported by Opening
Funding Supported by the Platform of Transport
Technology Thinktank (Research Institute of
Highway, Ministry of Transport), Beijing, PRC,
"How does Transportation Promote Common
Prosperity".
REFERENCES
Baldwin, R. E., Martin, P. 2003. Agglomeration and
Regional Growth. Handbook of Regional and Urban
Economics, 4(3960): 2671-2711.
Donaldson, D. 2018. Railroads of the Raj: Estimating the
impact of transportation infrastructure. American
Economic Review, 108(4-5): 899-934.
Zhang, L. L., Tong, Q., Liu, J., et al. 2024. Research on the
characteristics and spatial effects of transportation
infrastructure on Common Prosperity—Based on Inter-
provincial panel data and Spatial Durbin Model.
Inquiry into Economic Issues, (2): 82-96.
Shi, M. Y., Shen, K. R. 2023. Transport infrastructure
development and regional resource allocation —Based
on the urban roads index. Modern Economic Research,
(4): 26-40.
Banerjee, A., Duflo, E., Qian, N. 2020. On the road: Access
to transportation infrastructure and economic growth in
China. Journal of Development Economics, 145:
102442.
Yoo, S., Kumagai, J., Managi, S. 2024. Urban-rural gap
induced by high-speed rail: 35 years of evidence from
Japan. Research in Transportation Business &
Management, 55: 101131.
Lu, H., Zhao, P., Hu, H., et al. 2022. Transport
infrastructure and urban-rural income disparity: A
municipal-level analysis in China. Journal of Transport
Geography, 99: 103292.
Valenzuela-Levi, N. 2023. Income inequality and rule-
systems within public transport: a study of Medellin
(Colombia) and Santiago (Chile). Journal of Transport
Geography, 112: 103700.
Ma, Y. T., Jiang, Y., Bao, H. J. 2023. Transportation
infrastructure, digital economy and trade growth: A
research on the regions along the New Western Land-
Sea Route. Reform, (6): 142-155.
Ren, X. H., Zhang, Z. Y. 2013. Transportation
infrastructure, factor mobility and urban-rural income
disparity. Management Review, 25(2): 51-59.
Sun, Y. P. 2020. Transportation infrastructure construction,
labor mobility and urban-rural income gap. Nanjing
Audit University, 17(3): 103-111.
Liu, S. L., Zheng, S. L. 2013. Research on the cross-
regional economic growth spillover effects of
infrastructures——The empirical results come from
China's provincial panel data. Industrial Economics
Research, 65(4): 59-69.
Chen, Y., Wang, X. W., Zhang, G. X. 2021. Threshold
effect of transportation infrastructure on rural poverty
reduction. Journal of China University of
Geosciences(Social Sciences Edition), 21(5): 110-123.
Yang, Q., Shi, D. Q. 2019. Transportation infrastructure,
factors mobility and urban-rural income disparity.
South China Journal of Economics, (9): 35-50.
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