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 Agricultural Science; Vol. 7, No. 1; 2025 
ISSN 2690-5396   E-ISSN 2690-4799 

https://doi.org/10.30560/as.v7n1p118 

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The Impact of County-Level Government Fiscal Expenditure on Rural 
Common Prosperity 

Qilin Sheng1 & Qintian He2 
1 Chongqing Normal University, Chongqing, China 
2 Southwest University, Chongqing, China 

Correspondence: Qilin Sheng, Chongqing Normal University, Chongqing, China. 

 

Received: May 2, 2025   Accepted: June 8, 2025    Online Published: June 11, 2025 

 

Abstract 

Common prosperity, as a core value pursuit of the socialist theoretical system with Chinese characteristics, 
profoundly reflects the essential attributes and distinctive features of Chinese modernization. Among these, 
effectively narrowing the urban-rural income gap is a critical pathway to achieving common prosperity. Scientific 
and rational fiscal expenditure policies, serving as an important tool for adjusting national income distribution and 
promoting social equity and justice, play an indispensable role in advancing common prosperity. Based on county-
level panel data from China between 2000 and 2023, this study constructs a two-way fixed-effects econometric 
model to empirically analyze the impact of government fiscal expenditure on rural common prosperity. The 
findings indicate that government fiscal expenditure significantly enhances rural common prosperity, a conclusion 
supported by robustness tests including alternative econometric methods, lagged treatment, and winsorization. 
Heterogeneity analysis reveals that the fiscal expenditure elasticity in less-developed regions is significantly higher 
than in developed regions, and the fiscal expenditure coefficient in high-transfer regions is markedly greater than 
in low-transfer regions, aligning with the law of diminishing marginal utility and the Lewis dual-sector model. 
Mechanism analysis demonstrates that government fiscal expenditure boosts common prosperity by promoting 
capital deepening (i.e., stimulating fixed-asset investment) and by driving the primary and secondary industries, 
exhibiting partial mediating effects. 

Keywords: government fiscal expenditure, rural common prosperity, income gap, fixed-effects model 

1. Introduction 

Common prosperity is an essential requirement of socialism in China. To achieve common prosperity, 
governments at all levels must strictly implement the policy documents from the Third Plenary Session of the 20th 
CPC Central Committee. Precise optimization should be carried out in areas such as income distribution 
mechanisms to prevent excessive income disparities from deviating from the original intent of socialist 
development. Additionally, against the backdrop of increasing macroeconomic pressures, the employment issues 
faced by young people require special attention. It is imperative to strengthen the employment-first strategy and 
improve the social security network system. Over the past four decades of reform and opening-up, China's 
economic development has significantly improved, with national income levels experiencing leapfrog growth, and 
the sense of happiness and fulfillment among the people has greatly increased. However, imbalances and 
inadequacies in development remain prominent. Research on advancing common prosperity is urgently needed. 

Looking back, China once implemented a series of urban-biased policies to promote rapid economic development, 
resulting in a long-standing gap between urban and rural development, with the income disparity between urban 
and rural residents being particularly prominent. According to data from the National Bureau of Statistics, in 2011, 
the per capita disposable income of urban residents was 21,427 yuan, while that of rural residents was only 7,394 
yuan. By 2020, although both figures had increased significantly to 43,834 yuan and 17,131 yuan respectively, the 
urban-rural income ratio remained at a relatively high level. This indicates that the current actual income gap 
between urban and rural areas is insufficient to support the essential requirements of common prosperity. Research 
on rural common prosperity is therefore necessary, particularly focusing on identifying pathways to enhance the 
level of rural common prosperity, which represents a key direction in this field. From the perspective of socialist 
system development experience, an economic market dominated by public ownership has laid a solid foundation 
for achieving the goal of common prosperity. Government intervention to improve income distribution 
mechanisms is one of the feasible approaches currently under study, with government fiscal expenditure being a 



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noteworthy representative method. Based on this, this paper intends to incorporate government fiscal expenditure 
into the study of rural common prosperity, delving into the impact of government fiscal expenditure on rural 
common prosperity. 

Currently, there remains room for further expansion in domestic and international research on the impact of 
government fiscal expenditure on common prosperity. On one hand, existing studies predominantly focus on the 
direct effects of fiscal expenditure on common prosperity, lacking in-depth analysis of the underlying mechanisms 
through which fiscal expenditure influences common prosperity. On the other hand, within academic research on 
government fiscal expenditure and common prosperity, there is relatively little comprehensive analysis integrating 
both aspects, and the heterogeneous effects of government fiscal expenditure on common prosperity—particularly 
in terms of economic development levels and labor factor mobility—are seldom weighed or considered. This paper 
constructs a fixed-effects model based on county-level statistical data to empirically analyze the impact of 
government fiscal expenditure on rural common prosperity. It further conducts heterogeneity tests across economic 
development levels and labor factor mobility. Building on this foundation, the study introduces mediating variables 
such as fixed asset investment and output values of the primary, secondary, and tertiary industries to establish a 
mediation effect model. This approach delves deeper into the mechanisms through which government fiscal 
expenditure influences rural common prosperity, providing a new perspective for research on balancing economic 
and livelihood considerations in government policymaking. 

2. Literature Review and Research Hypotheses 

2.1 Common Prosperity in Rural Areas 

Common prosperity emphasizes the organic unity of "common" and "prosperity." Currently, research hotspots on 
common prosperity primarily encompass two dimensions: its connotation and realization pathways, with 
diversified research perspectives including income distribution, fairness and efficiency, and rural revitalization. 
Regarding the concept of common prosperity, scholars emphasize that this philosophy takes consolidating poverty 
alleviation achievements and preventing poverty risks as its baseline, adjusting income distribution and mitigating 
wealth polarization as its core tasks, and optimizing public services and enhancing people's well-being as its 
implementation pathways [1]. Common prosperity entails the whole population sharing development outcomes, a 
co-construction and sharing development process, and the organic integration of development efficiency and social 
fairness [2]. It is characterized by long-term, arduous, and complex attributes [3]. Research teams such as Liu 
Peilin, from a political economy perspective, define common prosperity as a multidimensional social development 
goal, with its realization pathway reflecting the high unity of development subjects (the entire population) and 
development outcomes (a better life) [4]. Common prosperity aligns closely with the "Five-Sphere Integrated Plan" 
overall layout, embodying the organic unity of political, economic, social, cultural, and ecological civilization 
construction [5]. This developmental state not only pursues material wealth but also emphasizes spiritual 
abundance, representing a comprehensive manifestation of coordinated and sustainable economic and social 
development [6]. Common prosperity seeks the organic unity of "baseline fairness" and "differential incentives," 
ensuring universal and equitable basic livelihood security while stimulating market vitality through reasonable 
income disparities, ultimately achieving a new development paradigm of shared prosperity and co-construction 
[7]. It is an inclusive prosperity based on high-quality development, a process where universal prosperity, 
comprehensive prosperity, and gradual prosperity coordinate and reinforce each other, embodying developmental, 
sustainable, and equitable characteristics [8].In terms of pathways to achieve common prosperity, Li Shi's [9] 
research highlights that enhancing residents' prosperity levels requires dual drivers—synergistic efforts in 
technological innovation and institutional innovation. Specifically, it is essential to inject contemporary economic 
development drivers and establish a more comprehensive distribution system. Zhang Minghao and Zhao Ziwen 
[10] emphasize that the point-wise diffusion of new quality productive forces can drive the organic renewal of 
traditional agricultural productivity, empowering high-quality agricultural development to propel common 
prosperity, which serves as a critical breakthrough in comprehensively advancing the rural revitalization strategy 
[11]. In primary distribution, attention should be paid to the unity of efficiency and fairness; in redistribution, the 
government's regulatory role should be strengthened; and through tertiary distribution, social forces should be 
guided to participate [9]. Tang Renwu [12] proposes a "trinity" mechanism for driving common prosperity: market 
mechanisms ensure resource allocation efficiency, government regulation safeguards fairness and justice, and 
social forces convey humanistic care. Under this collaborative governance framework, economic development 
dividends are shared by all through a complete distribution system. Huang Zuhui and Zhang Shuping [6] point out 
that one of the key focuses of common prosperity development is raising the income levels of low-income groups. 
Therefore, first, high-quality employment opportunities should be created through industrial upgrading to solidify 
income growth foundations; second, rural idle resources should be activated to expand property income channels; 



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and finally, through dual approaches of capacity building (empowerment) and institutional safeguards 
(entitlement), the development capabilities of low-income groups can be fundamentally enhanced, representing 
one of the critical pathways to achieving common prosperity [13].The core objective of common prosperity lies in 
constructing a fairer social development framework. Research by Zhang Laiming and Li Jianwei [14] indicates 
that optimizing income distribution mechanisms is foundational to achieving this goal. However, modern social 
development theory further reveals that true common prosperity requires multidimensional institutional design: 
while ensuring the rational distribution of material wealth, it is also necessary to build a public service system 
covering the entire population, establish fair competition opportunity mechanisms, improve universal health 
security networks, and promote balanced cultural resource allocation, ultimately achieving the coordinated 
enhancement of individual development capabilities and social progress levels [15]. Equal access to basic public 
services, as a key pillar of common prosperity, plays an irreplaceable role in advancing both material and spiritual 
prosperity by optimizing income distribution patterns, expanding the middle-income group, stabilizing its 
development foundation, narrowing intra-group disparities, and strengthening social fairness recognition [16][17]. 
Simultaneously, digitalization serves as a vital engine for promoting common prosperity, injecting new momentum 
into economic and social development through multiple dimensions: opening broader economic growth spaces, 
driving systemic upgrades in social productivity, improving modern market resource allocation functions, guiding 
industrial transformation toward sustainable development, and enhancing public service and social living standards 
[18]. Consequently, scholars have also explored the impacts of factors such as digital rural construction [19][20], 
the digital economy [21][22], digital financial literacy [23][24], and circulation digitization [25] on farmers' 
common prosperity. It is evident that the academic community has conducted extensive research on the topic of 
farmers' common prosperity, forming a substantial body of work. 

2.2 The Impact of Local Financial Support on Rural Common Prosperity 

Fiscal policy serves as a crucial measure for promoting rural ecological conservation, improving people's 
livelihoods, supporting industrial upgrading, and achieving poverty alleviation and prosperity. It also constitutes 
a fundamental institutional safeguard[26]. Research on the impact of local fiscal expenditures on rural common 
prosperity is rooted in public finance theory, urban-rural integration theory, and the policy framework of the rural 
revitalization strategy. Public finance theory emphasizes the government's role in addressing market failures 
through resource allocation and income distribution functions, particularly in the context of insufficient rural 
public goods provision. Fiscal expenditures become a key instrument for narrowing the urban-rural gap[27]. 
Urban-rural integration theory posits that breaking the urban-rural dual structure requires fiscal investments in 
infrastructure, public services, and industrial linkages to facilitate bidirectional factor flows and balanced resource 
allocation[28]. Urban-rural separation is a historical phenomenon, while urban-rural coordination and integration 
represent the overarching historical trend in future urban-rural relations. Meanwhile, the rural revitalization 
strategy, as a national top-level design, explicitly advocates optimizing rural industrial structures[29]and 
enhancing livelihood security[30][31]through fiscal policies, thereby providing institutional support for common 
prosperity. Song Yanqun and Shang Qi[32]further demonstrated through empirical analysis that livelihood 
expenditures and tax structure optimization positively contribute to rural common prosperity, validating the 
moderating role of fiscal policies.  

From a multidimensional analysis of the mechanism of government fiscal support, it can be divided into three 
aspects: First, the supply of public goods and the enhancement of human capital. Local government fiscal 
expenditures directly promote the accumulation of rural human capital through investments in livelihood areas 
such as education and healthcare. Education expenditures improve the skill levels of rural residents, unlocking 
their ability to participate in high-value-added industries [33][34]; healthcare expenditures reduce household 
precautionary savings, indirectly unleashing consumption potential [35], forming a virtuous cycle of "human 
capital—income growth." Liu Donghua and Wang Jihua [36] pointed out that fiscal investments in urban-rural 
functional zones (such as agricultural industrial parks and eco-tourism zones) can optimize the spatial structure 
between urban and rural areas, promoting functional complementarity and rational population flow.  

Second, infrastructure investment and industrial synergy effects. Specifically, fiscal investments in agricultural 
production infrastructure (such as water conservancy and transportation) significantly reduce agricultural 
production costs and increase rural collective economic income [37]. Chen Xiangguang and Tang Long [38] noted 
that fiscal funds for agriculture support the agglomeration of agricultural production services, driving rural digital 
transformation, lowering transaction costs, and improving the efficiency of factor allocation. Additionally, fiscal 
subsidies have a stronger incentive effect on rural collective economies than tax incentives, particularly in less 
marketized central and western regions, where this effect is more pronounced [39].Third, income redistribution 
and social equity assurance. Fiscal transfers and social security expenditures narrow the urban-rural income gap 



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through redistribution mechanisms. Wu Junpei and Zhang Haoze [40] found that for every 100 million yuan 
increase in livelihood expenditures, the urban-rural income gap narrowed by 0.021 percentage points. Liu 
Xiaoming [39] further revealed that under China's fiscal decentralization system, transfer payments can effectively 
alleviate vertical fiscal imbalances, promoting balanced urban-rural development through a combination of "blood 
transfusion" and "blood-making." The fiscal linkage mechanism between poverty alleviation and rural 
revitalization has also been proven as a crucial safeguard for consolidating poverty alleviation achievements and 
preventing relapse [41].  

2.3 Relevant Hypotheses 

In summary, local government fiscal expenditures promote rural common prosperity through three major pathways: 
public goods supply, industrial linkage, and income redistribution, providing an important reference for studying 
the impact of rural common prosperity. Based on existing literature, most scholars' research results indicate that 
the direction of government fiscal expenditures' impact on common prosperity is positive—that is, government 
fiscal expenditures facilitate rural common prosperity. Additionally, some scholars have conducted targeted 
research using fiscal expenditures at different levels, while others have explored the mechanisms through which 
government fiscal expenditures affect common prosperity, such as fixed asset investments and the effects of 
primary, secondary, and tertiary industries. Based on this, this paper proposes the following hypothesis: 

Hypothesis1: Government fiscal expenditure has a promoting effect on common prosperity in rural areas.  

Hypothesis2: The impact of government fiscal expenditure on rural common prosperity exhibits heterogeneity in 
terms of economic development levels and labor factor mobility.  

Hypothesis3: Government fiscal expenditure promotes common prosperity through the fixed asset investment 
channel.  

Hypothesis4: Government fiscal expenditure promotes common prosperity through the primary, secondary, and 
tertiary industry channels. 

3. Variable Selection and Model Construction 

3.1 Variable Selection 

The county-level economic characteristic data in this paper are primarily sourced from the China County Statistical 
Yearbook. Missing values and outliers in the data were excluded, and variables with significant disparities were 
logarithmically transformed. The specific variable measurements are as follows:  

The core explanatory variable, local fiscal expenditure, is measured by general public budget expenditure and 
logarithmically transformed. The explained variable, rural common prosperity, is measured by the logarithm of 
the per capita disposable income of rural residents at the county level. The control variables encompass nine 
aspects: economic development, agricultural machinery power, proportion of the primary industry, proportion of 
the secondary industry, rural labor force, agricultural labor force, traditional financial index, information 
infrastructure, and the ratio of resident deposits. Specifically Economic development is measured by the logarithm 
of per capita GDP. Agricultural machinery power is measured by the logarithm of total agricultural machinery 
power. The proportion of the primary industry is measured by the added value of the primary industry divided by 
the regional GDP. The proportion of the secondary industry is measured by the added value of the secondary 
industry divided by the regional GDP. The rural labor force is measured by the number of rural employed persons 
divided by the total number of employed persons. The agricultural labor force is measured by the number of 
persons employed in agriculture, forestry, animal husbandry, and fishery divided by the number of rural employed 
persons. The traditional financial index is measured by the year-end balance of loans from financial institutions 
divided by GDP. Information infrastructure is measured by the logarithm of the number of fixed-line telephone 
subscribers. The ratio of resident deposits is measured by the ratio of deposits to GDP. The mediating variables 
are fixed asset investment and the output value of the three industries. Fixed asset investment is logarithmically 
transformed, while the output values of the three industries—the primary industry, secondary industry, and tertiary 
industry—are each logarithmically transformed. 

3.2 Model Building 

This study examines the impact of government fiscal expenditure on rural common prosperity, identifies the 
underlying mechanisms between them, and proposes targeted policy recommendations. Based on an extensive 
review of literature, this section will focus on analyzing the specific effects of government fiscal expenditure on 
rural common prosperity and investigate through which pathways government fiscal spending influences rural 
common prosperity. Additionally, the fixed-effects model provides explicit estimates of individual effects, 



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clarifying differences among various entities, whereas the random-effects model may introduce estimation bias. 
Since the fixed-effects model controls for time-invariant individual heterogeneity, its estimates are generally more 
reliable. Therefore, the empirical analysis will employ a fixed-effects model to examine the relationship between 
government fiscal expenditure and rural common prosperity, conducting baseline regression analysis. In the 
baseline regression section, the specified baseline regression model is as follows: 

Here, the dependent variable is rural common prosperity. Following Zhou Yahong's [42] approach, we select the 
logarithm of per capita disposable income in county-level rural areas based on the perspective of income 
distribution changes. The data is sourced from the China County Statistical Yearbook, with missing values 
removed. The explanatory variable is government fiscal expenditure, measured using general public budget 
expenditure in line with the methodology of Ye Wenhui and Zhang Xiaobin [43] and other scholars. A set of 
control variables is employed, including nine aspects: economic development, agricultural machinery power, 
proportion of primary industry, proportion of secondary industry, rural labor force, agricultural labor force, 
traditional financial index, information infrastructure, and proportion of resident deposits. Additionally, εi 
represents the error term. This paper focuses on the sign of coefficient β. If β>0, it indicates that government fiscal 
expenditure promotes rural common prosperity; conversely, if β<0, it exerts an inhibitory effect. 

To further examine the mechanism through which government fiscal expenditure affects rural common prosperity, 
this paper conducts a mediation effect test by introducing two mediating variables: fixed asset investment and 
output value of the three industries 

t 1 itprosperity financei it it itX    
 (4.2) 

2 2 2middle financeit it itX      
 (4.3) 

t 3 4 3 3financeprosperity middlei it i itX      
 (4.4) 

Here, represents the mediating variables of fixed asset investment and output value of the three industries, γ denotes 
the constant term, ε1, ε2, ε3 are random error terms, while the explanatory variables, explained variables, and 
control variables remain the same as in the baseline model. Equation (4.2) represents the overall effect of 
government fiscal expenditure on rural common prosperity, Equation (4.3) indicates the effect of government 
fiscal expenditure on the mediating variables, and in Equation (4.4) represents the direct effect of government 
fiscal expenditure on rural common prosperity after controlling for the influence of the mediating variables. By 
combining Equations (4.3) and (4.4), the mediating effect can be further derived, which reflects the impact of 
government fiscal expenditure on rural common prosperity through the two pathways of fixed asset investment 
and output value of the three industries. 

4. Empirical Analysis 

4.1 Descriptive Statistics  

The data in this paper primarily originates from the "China County Statistical Yearbook." To facilitate empirical 
analysis, outliers and missing values were removed during data processing. The specific content and indicators are 
shown in the descriptive statistics of Table 4.1. 

 

Table 4.1. Descriptive Statistics 

Type of 
variable 

Variable Count Mean  Standard Min Max. 

Explained 
variable 

Common 
prosperity in rural 

areas 
17679 8.232 0.584 6.365 10.195 

Independent. 
variables 

Government fiscal 
expenditure 

17679 11.046 0.890 6.284 14.484 

  t 0 1 itprosperity financei it it itX      
  (4-1) 



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Control 
variables 

Economic 
progress  

17679 9.337 0.843 6.805 12.804 

Agricultural 
machinery power 

17679 3.137 0.929 0.030 5.707 

Agricultural 
machinery power 

17679 0.261 0.138 0.004 0.889 

The proportion of 
secondary 
industry 

17679 0.408 0.162 0.017 0.939 

Rural labor force 17679 9.936 5.701 0.038 36.048 

Agricultural labor 
force 

17679 0.641 0.173 0.079 1.935 

Traditional 
financial index 

17679 0.499 0.318 0.001 4.725 

information 
infrastructure 

17679 10.779 1.046 3.091 13.722 

Resident deposits 
accounted for 

17679 0.621 0.309 0.004 5.649 

Metavariable  

 investment in the 
fixed assets  

17679 12.185 1.344 7.123 15.945 

Output value of 
primary industry 

17679 11.385 0.981 7.048 13.907 

Output value of 
the secondary 

industry 
17679 11.927 1.463 5.011 16.607 

Output value of 
the tertiary 

industry 
17679 11.768 1.136 7.502 16.185 

 

Observing the descriptive statistics table, the mean value of the logarithm of per capita disposable income in rural 
areas, which reflects common prosperity, is 8.232 with a standard deviation of 0.584. This indicates that while 
there are moderate disparities in income levels across China's rural counties, the degree of dispersion remains 
manageable. The range spans 3.83 logarithmic units between the minimum value of 6.365 and the maximum value 
of 10.195, corroborating the reality of uneven development in rural regions. 

The core explanatory variable, government fiscal expenditure, is measured from the perspective of general public 
budget expenditure. Its logarithmic mean is 11.046 with a standard deviation of 0.89, and the distribution ranges 
from 6.284 to 14.484, revealing significant disparities in local government fiscal capacity. Notably, among the 
control variables, the average proportion of primary industry is 26.1%, while secondary industry accounts for 
40.8%, aligning with the characteristic that China's county economies remain dominated by secondary industry, 
with agricultural proportions significantly higher than the national average. The agricultural labor force proportion 
reaches as high as 64.1%, reflecting the urgency of transforming rural employment structures. The traditional 
financial index, represented by the mean ratio of loan balance to GDP at 0.499 and the proportion of resident 
deposits at 0.621, suggests room for improvement in the depth of financial development at the county level. 

4.2 Baseline Regression Results 

By performing OLS regression on Model (4-1), we conducted regression analyses sequentially using fixed effects 
and adding all control variables to examine the impact of government fiscal expenditure on rural common 
prosperity under scenarios with or without fixed effects and categorized control variables. The specific panel data 
regression results are shown in Table 4.2:  

Columns (1)-(4) present the results of government fiscal expenditure's impact on rural common prosperity under 
four different explanatory variable conditions. It can be observed that, with the gradual inclusion of control 



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variables, government fiscal expenditure significantly promotes rural common prosperity. A possible explanation 
is that government fiscal expenditure heavily invests in rural infrastructure such as roads, bridges, and 
communication networks, which improves rural transportation conditions, enhances logistics efficiency, reduces 
transportation costs, and facilitates the export of agricultural products and the inflow of external resources. 
Meanwhile, the widespread adoption of communication networks enables farmers to access market information 
more conveniently, participate in e-commerce, and expand income-generating channels. Additionally, increased 
government fiscal expenditure enhances public services, promotes industrial development, and ensures social 
equity, laying a solid foundation for the comprehensive revitalization and common prosperity of rural areas. 

 

Table 4.2. Benchmark regression results 

Variable (1) (2) (3) (4) 

Government fiscal 
expenditure 

0.507*** 
(0.001) 

0.182*** 
(0.004) 

0.074*** 
(0.005) 

0.030*** 
(0.002) 

economic progress   
0.483*** 

(0.005) 
 

0.211*** 

(0.006) 

Agricultural 
machinery power 

 
0.079*** 

(0.004) 
 

0.048*** 

(0.004) 

Proportion of 
primary industry 

 
0.637*** 

(0.028) 
 

0.462*** 

(0.028) 

The proportion of 
secondary industry 

 
-0.189*** 

(0.482) 
 

-0.082*** 

(0.482) 

Rural labor force  
-0.001***

(0.001) 
 

0.001*** 

(0.001) 
Agricultural labor 

force 
 

-0.252***

(0.017) 
 

-0.077*** 

(0.017) 
Traditional financial 

index 
 

0.008*

(0.005) 
 

0.005* 

(0.005) 
information 

infrastructure 
 

-0.037***

(0.003) 
 

0.005*** 

(0.003) 
Resident deposits 

accounted for 
 

0.145***

(0.008) 
 

-0.018*** 

(0.008) 

fixed effect  NO NO YES YES 

_cons 
2.643*** 
(0.018) 

1.861*** 
(0.051) 

1.997*** 
(0.882) 

1.698*** 
(0.919) 

Sample capacity 17679 17679 17679 17679 

R2 0.534 0.811 0.460 0.685 

Note: The values in parentheses in the table are standard errors, and *, **, and *** indicate significance at the 
10%, 5%, and 1% levels, respectively. 

 

Specifically, column (1) shows the impact of government fiscal expenditure on rural common prosperity without 
adopting dual fixed effects or adding control variables, with a significantly positive direction of effect. Column 
(2) presents the influence of government fiscal expenditure on rural common prosperity without dual fixed effects 
but with control variables added, demonstrating that the direction of impact remains unchanged and still meets the 
criteria for statistical significance. Column (3) reflects the effect of government fiscal expenditure on rural 
common prosperity when dual fixed effects are applied without adding control variables, indicating that 
government fiscal expenditure continues to promote the enhancement of rural common prosperity. Column (4) 
displays the regression results after simultaneously applying fixed effects and incorporating all control variables, 



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revealing that for every 1-unit increase in government fiscal expenditure, rural common prosperity rises by 3.0%, 
maintaining statistical significance. In summary, the direction of government fiscal expenditure's impact on rural 
common prosperity remains consistent after adding control variables, and the baseline regression conclusions align 
with the theoretical analysis presented earlier, thereby validating Hypothesis 1 of this study. 

4.3 Robustness Test 

4.3.1 Change the Measurement Method 

To verify the robustness and reliability of empirical results under different estimation models and to exclude the 
influence of limited dependent variables, the Tobit method was selected for re-estimation while reporting the 
benchmark regression results. The specific test results are shown in Table 4.3. 

 

Table 4.3. Robustness Test for Alternative Measurement Methods 

 OLS Tobit 
Variable (1) (2) (3) (4) 

Government fiscal 
expenditure 

0.074*** 
(0.005) 

0.030*** 
(0.002) 

0.102*** 
(0.005) 

0.035*** 
(0.005) 

Controlled variable NO YES NO YES 
Fixed effect  YES YES YES YES 

_cons 
1.997*** 
(0.882) 

1.698*** 
(0.919) 

1.126*** 
(0.005) 

1.126*** 
(0.005) 

Sample capacity 17679 17679 17679 17679 
Note: Same as table 4.2. 

 

Columns (1) and (2) present the baseline model estimates of the impact of government fiscal expenditure on rural 
common prosperity, indicating that government fiscal expenditure has a significantly positive effect on rural 
common prosperity. Columns (3) and (4) show the results estimated using the Tobit method, where the coefficient 
for government fiscal expenditure on rural common prosperity is significantly positive, demonstrating that 
government fiscal expenditure exerts a positive influence on rural common prosperity. These findings align with 
the results estimated by the baseline OLS model.  

In summary, the robustness test results obtained after replacing the econometric methods are consistent with the 
previous conclusions, indicating that the earlier empirical findings are reliable and robust.  

4.3.2 Lag Period Treatment  

To mitigate reverse causality, capture the time-lagged effects of fiscal expenditure on rural income, and eliminate 
contemporaneous endogeneity interference, this study employs one-period and two-period lag approaches for 
robustness testing. The robustness regression results are presented in Table 4.4 below. 

 

Table 4.4. Robustness Test for Lag Period Processing 

Variable Lag phase I Lag phase II 

Government fiscal 
expenditure 

0.053*** 
(0.006) 

0.013*** 
(0.006) 

0.011*** 
(0.006) 

0.023*** 
(0.006) 

Controlled variable NO YES NO YES 
fixed effect YES YES YES YES 

_cons 
1.997*** 
(0.882) 

1.698*** 
(0.919) 

2.076*** 
(1.086) 

2.255*** 
(1.130) 

Sample capacity 15725 15725 13822 13822 
R2 0.392 0.621 0.307 0.517 

Note: Same as Table 4.2. 

 

Table 4.4 presents the results of the robustness test for lag period processing. It can be observed that after adding 
control variables, the marginal effect coefficients for the first and second lag periods are 0.013 and 0.023, 
respectively. Government fiscal expenditure continues to exert a significantly positive impact on rural common 



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prosperity, remaining statistically significant. The regression results after lag period processing are consistent with 
the baseline regression findings discussed earlier, indicating the robustness of the empirical test results. 

4.3.3 Altering Sample Size  

The data underwent winsorization to eliminate extreme values. Following the approach of Zhang Ping and Zhou 
Qianru (2022), this study conducted a 1% winsorization on both ends of the logarithmic values of per capita income 
for rural common prosperity to test the robustness of the estimation results. The robustness test results are shown 
in the table below. Columns (1) to (4) display the regression results after sequentially applying two-way fixed 
effects and adding control variables to the winsorized sample. The estimated coefficients for government fiscal 
expenditure across these four columns are 0.503, 0.181, 0.077, and 0.037, respectively, all passing the 1% 
statistical significance level. Thus, the regression results after winsorization still demonstrate that government 
fiscal expenditure has a significantly positive effect on rural common prosperity. 

 

Table 4.5. Robustness Test of Winsorization 

Variable (1) (2) (3) (4) 

Government fiscal 

expenditure 

0.503*** 

(0.001) 

0.181*** 

(0.004) 

0.077*** 

(0.005) 

0.037*** 

(0.005) 

Controlled variable NO YES NO YES 

 Fixed effect  YES YES YES YES 

_cons 
2.688*** 

(0.018) 

1.900*** 

(0.008) 

1.997*** 

(0.882) 

1.698*** 

(0.919) 

 Sample capacity 17503 17503 17503 17503 

R2 0.520 0.803 0.449 0.680 

Note: Same as Table 4.2. 

 

It can be seen that the robustness test regression results above are close to the benchmark regression results in this 
paper, with no significant changes in the direction and significance of the core explanatory variables and control 
variables, indicating that the estimation results of government fiscal expenditure on rural common prosperity are 
robust. 

4.4 Heterogeneity Test 

4.4.1 Test of Heterogeneity of Economic Development 

Endowments, industrial structure, and policy transmission efficiency, the impact of government fiscal expenditure 
on rural common prosperity may exhibit heterogeneity across regions with varying levels of economic 
development. In less developed regions, the per capita GDP and initial capital stock are relatively low. According 
to the phased characteristics of capital deepening in the Solow growth model, the marginal productivity of fiscal 
expenditure is higher. For instance, fiscal spending on infrastructure such as roads and power grids can produce a 
"timely assistance" effect. In contrast, developed regions have nearly saturated infrastructure, and additional fiscal 
investments may flow into inefficient sectors, leading to adverse outcomes like redundant construction and 
consequently diminishing marginal returns. Therefore, under the influence of diminishing marginal utility, 
differences in resource endowments, industrial structure, and policy transmission efficiency, the impact of 
government fiscal expenditure on rural common prosperity may exhibit heterogeneity across regions with varying 
levels of economic development.  

Based on this, to better examine this characteristic of how government fiscal expenditure affects rural common 
prosperity in the context of China's economic development levels, this paper divides the sample data according to 
the average per capita GDP. The table below presents the heterogeneous effects of government fiscal expenditure 
on rural common prosperity. 

 

 

 



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Table 4.6. Heterogeneity Test of Economic Development Level 

Variable Developed area  Less developed areas 

Government fiscal 

expenditure 

0.066*** 

(0.006) 

0.056*** 

(0.006) 

0.067*** 

(0.009) 

0.080*** 

(0.008) 

Controlled variable NO YES NO YES 

 Fixed effect  YES YES YES YES 

_cons 
2.219*** 

(0.007) 

1.826*** 

(4.098) 

1.957*** 

(0.882) 

1.198*** 

(0.919) 

Sample capacity 8713 8713 8966 8966 

R2 0.250 0.308 0.247 0.330 

Note: Same as Table 4.2. 

 

From the regression results of developed regions, columns (1) and (2) present the estimated impact of government 
fiscal expenditure on rural common prosperity under fixed effects with control variables added sequentially. It can 
be observed that government fiscal expenditure significantly promotes rural common prosperity. Columns (3) and 
(4) show the results for underdeveloped regions under the same fixed effects framework with sequentially added 
control variables, indicating that government fiscal expenditure still exerts a significant positive effect on rural 
common prosperity. However, judging by the marginal regression coefficients, after fully incorporating control 
variables, the fiscal expenditure elasticity in underdeveloped regions (0.080) is significantly higher than that in 
developed regions (0.056), which aligns with the law of diminishing marginal utility. This finding provides 
empirical support for the "Targeted Poverty Alleviation" policy, demonstrating that allocating fiscal funds to 
backward regions yields higher marginal returns. 

4.4.2 Heterogeneity Test of Labor Factor Transfer 

The transfer of labor factors is an important indicator for measuring the degree of labor mobility. Its composition 
is calculated as (1 - the number of workers engaged in agriculture, forestry, animal husbandry, and fishery) / the 
total rural population. A higher proportion of agricultural labor, reflected in more workers engaged in these primary 
industries, indicates a lower level of labor factor transfer, and vice versa. Rural labor with a high transfer level 
tends to engage more in secondary and tertiary industries, leading to diversified economic structures. Conversely, 
low transfer levels result in labor remaining concentrated in agricultural production, leading to a more singular 
economic structure. Analyzing the impact of government fiscal expenditure on rural common prosperity from the 
perspective of labor factor transfer levels may also reveal heterogeneity.  

To this end, this study divides the sample based on the mean value of labor factor transfer levels. Samples above 
the mean are defined as high transfer level samples, while those below the mean are classified as low transfer level 
samples. The heterogeneous impact results are presented in the table below. 

 

Table 4.7. Heterogeneity Test of Labor Factor Transfer 

Variable High transfer levels Low transfer levels 

Government fiscal 

expenditure 

0.077*** 

(0.006) 

0.033*** 

(0.006) 

0.056*** 

(0.008) 

0.031*** 

(0.008) 

Controlled variable NO YES NO YES 

Fixed effect  YES YES YES YES 

_cons 
2.219*** 

(0.007) 

1.826*** 

(4.098) 

1.957*** 

(0.882) 

1.198*** 

(0.919) 

Sample capacity 9111 9111 8568 8568 

R2 0.398 0.617 0.487 0.700 



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Note: Same as Table 4.2. 

 

From the perspective of estimated coefficients for high and low labor transfer levels, the fiscal expenditure 
coefficient of 0.077 in high-transfer regions is significantly greater than the 0.056 in low-transfer regions, 
indicating that each unit of fiscal investment generates 2.1% higher income growth effects in the former compared 
to the latter. This highlights the amplifying effect of labor transfer on policy efficacy. The results align with the 
Lewis dual-sector model, suggesting fiscal expenditure in high-transfer regions functions as an "industrialization 
catalyst," accelerating labor movement from low-productivity agricultural sectors to high-productivity modern 
sectors, thereby achieving overall income enhancement. The heterogeneity tests on economic development levels 
and labor factor mobility validate Hypothesis 2 of this study. 

4.5 Mechanism Test 

4.5.1 Mechanism Test Based on Fixed Asset Investment Approach 

Fiscal expenditures directly form fixed assets through public investments. The increased investment in fixed assets 
such as infrastructure, roads, water conservancy, and power grids enhances the rural capital-labor ratio, breaks the 
"low-level equilibrium trap" of agricultural productivity, generates capital deepening effects, and thereby promotes 
the rise in farmers' income levels, facilitating rural common prosperity. Additionally, infrastructure construction 
projects themselves absorb local labor, increasing farmers' wage income in the short term. World Bank research 
shows that every 1 yuan invested in rural infrastructure can create 0.8–1.2 non-agricultural employment 
opportunities. Under the combined effect of this multiplier and job creation, government fiscal expenditures 
promote rural common prosperity through the channel of fixed asset investments.  

To better analyze the role of fixed asset investments in the mechanism between government fiscal expenditures 
and rural common prosperity, this study incorporates fixed asset investments into the analysis of the impact of 
government fiscal expenditures on rural common prosperity. The regression results of the impact mechanism are 
shown in Table 4.8. 

 

Table 4.8. Results of the Fixed Asset Investment Mechanism Test 

Variable (1) (2) (3) 
Government fiscal 

expenditure 

0.030*** 
(0.002) 

0.387*** 
(0.018) 

0.024*** 
(0.005) 

 investment in the 
fixed assets  

  
0.015*** 
(0.002) 

Controlled variable YES YES YES 
 Fixed effect  YES YES YES 

_cons 
1.698*** 
(0.919) 

0.978*** 
(0.882) 

1.927*** 
(4.098) 

Sample capacity 17679 17679 17679 
R2 0.685 0.757 0.693 

Note: Same as Table 4.2. 

 

Table 4.8's three-step test shows: The estimated coefficient of government fiscal expenditure on fixed asset 
investment is 0.387, which is statistically significant at the 1% level, indicating that government fiscal expenditure 
significantly promotes fixed asset investment. The estimated coefficient of fixed asset investment on rural common 
prosperity is 0.015, showing that fixed asset investment has a positive impact on rural income. The mediation 
effect accounts for 19.4%, confirming the transmission path of "fiscal input → capital deepening → income 
growth," thereby validating Hypothesis 3 of this paper. 

4.5.2 Mechanism Test Based on the Output Value Pathway of Three Industries  

Government fiscal expenditure can promote rural common prosperity by boosting the output value of three 
industries: agriculture, rural industry (secondary sector), and rural services (tertiary sector). The core logic lies in 
the precise allocation of fiscal resources to activate rural endogenous dynamics, forming a virtuous cycle of 
"industrial upgrading → employment expansion → income growth → social equity."  



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To better analyze the mechanism of the three industries' output value in the relationship between government fiscal 
expenditure and rural common prosperity, this study incorporates the output value of the three industries into the 
analysis of the impact of government fiscal expenditure on rural common prosperity. The regression results of the 
mechanism are presented in Table 4.9. 

Table 4.9. Results of the Mechanism Test for Output Value of the Three Industries 

Variable 
Primary 
industry  

 common 
prosperity  

Secondary 
industry 

 Common 
prosperity  

Tertiary 
industry 

 Common 
prosperity  

Government fiscal 
expenditure 

0.043*** 
(0.007) 

0.021*** 
(0.005) 

0.103*** 
(0.009) 

0.026*** 
(0.005) 

0.044*** 
(0.007) 

0.027*** 
(0.006) 

Output value of 
the three industries 

 
0.156*** 
(0.006) 

 
0.009*** 
(0.005) 

 
0.002 

(0.006) 
Controlled 

variable 
YES YES YES YES YES YES 

Fixed effect  YES YES YES YES YES YES 

_cons 
1.997*** 
(0.882) 

0.978*** 
(0.882) 

1.927*** 
(4.098) 

0.997*** 
(0.882) 

1.927*** 
(4.098) 

0.957*** 
(4.098) 

Sample capacity 17679 17679 17679 17679 17679 17679 
R2 0.247 0.725 0.614 0.680 0.506 0.678 

Note: Same as Table 4.2. 

 

Observing Table 4.9, columns (1), (3), and (5) report the estimated results of government fiscal expenditure on the 
output value of the primary, secondary, and tertiary industries, respectively, with estimated coefficients of 0.043, 
0.103, and 0.044, indicating that government fiscal expenditure promotes the output value of the primary, 
secondary, and tertiary industries. Columns (2), (4), and (6) present the overall effect of government fiscal 
expenditure on rural common prosperity after sequentially controlling for the mediating variables of the output 
value of the primary, secondary, and tertiary industries. The results show that after controlling for the mediating 
variables of the output value of the primary and secondary industries, government fiscal expenditure still has a 
significant positive impact on rural common prosperity, suggesting that the mediating variables of the output value 
of the primary and secondary industries partially mediate the effect of green finance on new quality productivity. 
The mediating effect of the tertiary industry output value is not significant. Thus, it can be concluded that in the 
pathway of the primary industry output value mediating effect, the mediating effect of government fiscal 
expenditure on rural common prosperity is 0.007. In the pathway of the secondary industry output value mediating 
effect, the mediating effect of government fiscal expenditure on rural common prosperity is approximately 0.001. 
That is, government fiscal expenditure can generate a mediating effect on rural common prosperity through the 
pathways of the primary and secondary industry output values, validating Hypothesis 4 of this paper. 

5. Conclusions and Policy Recommendations 

5.1 Conclusion  

This study utilizes county-level economic characteristic data from the China County Statistical Yearbook to 
construct a fixed-effects econometric model, empirically analyzing the impact of government fiscal expenditure 
on rural common prosperity.  

The baseline regression results show that government fiscal expenditure significantly promotes rural common 
prosperity when fixed effects and all control variables are sequentially added. For robustness checks, the Tobit 
method is employed to re-estimate using alternative econometric approaches, along with one-period lag, two-
period lag treatments, and winsorization to examine result stability across different estimation models, enhance 
credibility, address limited dependent variables, and mitigate reverse causality. All three robustness check methods 
consistently demonstrate a positive directional effect of government fiscal expenditure on rural common prosperity.  

Heterogeneity analysis reveals that from the perspective of economic development disparity, fiscal expenditure 
elasticity in less-developed regions is significantly higher than in developed regions, aligning with the law of 
diminishing marginal utility. This finding provides empirical support for the "Targeted Poverty Alleviation" policy, 
indicating that fiscal allocations to backward areas yield higher marginal returns. From the labor mobility 
heterogeneity perspective, fiscal expenditure coefficients in high-mobility regions are markedly greater than in 
low-mobility regions, showing that each unit of fiscal input generates 2.1% higher income growth in the former, 
highlighting labor mobility's amplifying effect on policy efficacy. This result aligns with the Lewis dual-sector 



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model, suggesting fiscal expenditure acts as an "industrialization catalyst" in high-mobility areas, accelerating 
labor shifts from low-productivity agricultural sectors to high-productivity modern sectors, thereby boosting 
overall income.  

Mechanism tests indicate that government fiscal expenditure enhances common prosperity through capital 
deepening (stimulating fixed-asset investment) and by driving primary and secondary industries, demonstrating 
partial mediating effects. 

5.2 Policy Advice 

First, it is essential to anchor efforts in regional disparities and optimize the structure of government fiscal 
expenditures. Each region must closely align with its own developmental realities, tailoring adjustments to its 
fiscal expenditure structure while fully accounting for regional heterogeneity. For instance, economically advanced 
eastern regions should prioritize addressing income disparities across industries. While steadily driving economic 
growth, these regions should deepen reforms in education, healthcare, housing, and other areas to ensure ordinary 
citizens tangibly benefit from the dividends of development. Central and western regions, on the other hand, should 
focus on industrial restructuring, directing fiscal resources toward areas of critical need. By stimulating economic 
growth, increasing fixed asset investment, and leveraging their inherent factor endowments, these regions can 
enhance regional economic expansion while promptly addressing income growth for low- and middle-income 
populations.  

Second, it is crucial to refine the policy framework and execute coordinated policy measures. To begin, local 
governments at all levels must rigorously implement the directives of central policies while formulating 
supplementary strategies tailored to local conditions. This involves clarifying fiscal relations between central and 
local governments and defining relevant fiscal expenditure policies. Through continuous reform, localities should 
be granted greater autonomy to ensure fiscal resources align with responsibilities, thereby securing sufficient 
funding for economic development and livelihood improvements. Furthermore, policies must be synergized—
fiscal, industrial, employment, and social security measures should operate in harmony to maximize the impact of 
government spending and avoid inefficiencies.  

Third, efforts must be made to solidify the foundation of people's livelihoods, with a particular focus on supporting 
vulnerable groups. In advancing common prosperity, safeguarding basic living standards is paramount, especially 
in reinforcing fundamental, inclusive, and safety-net social protections. Striking a balance between development 
and welfare is critical, with special attention given to ensuring the basic needs of low-income groups, the elderly, 
persons with disabilities, and other disadvantaged populations. Regions should progressively strengthen social 
security and assistance systems based on their fiscal capacities, guaranteeing that all citizens, especially those in 
hardship, have their livelihoods secured. Concurrently, emphasis should be placed on enhancing population quality 
through education and skills training, enabling more individuals to meet the demands of economic development 
and fostering long-term societal stability. 

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    /UKR <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>
    /ENU (Use these settings to create Adobe PDF documents best suited for high-quality prepress printing.  Created PDF documents can be opened with Acrobat and Adobe Reader 5.0 and later.)
  >>
  /Namespace [
    (Adobe)
    (Common)
    (1.0)
  ]
  /OtherNamespaces [
    <<
      /AsReaderSpreads false
      /CropImagesToFrames true
      /ErrorControl /WarnAndContinue
      /FlattenerIgnoreSpreadOverrides false
      /IncludeGuidesGrids false
      /IncludeNonPrinting false
      /IncludeSlug false
      /Namespace [
        (Adobe)
        (InDesign)
        (4.0)
      ]
      /OmitPlacedBitmaps false
      /OmitPlacedEPS false
      /OmitPlacedPDF false
      /SimulateOverprint /Legacy
    >>
    <<
      /AddBleedMarks false
      /AddColorBars false
      /AddCropMarks false
      /AddPageInfo false
      /AddRegMarks false
      /ConvertColors /ConvertToCMYK
      /DestinationProfileName ()
      /DestinationProfileSelector /DocumentCMYK
      /Downsample16BitImages true
      /FlattenerPreset <<
        /PresetSelector /MediumResolution
      >>
      /FormElements false
      /GenerateStructure false
      /IncludeBookmarks false
      /IncludeHyperlinks false
      /IncludeInteractive false
      /IncludeLayers false
      /IncludeProfiles false
      /MultimediaHandling /UseObjectSettings
      /Namespace [
        (Adobe)
        (CreativeSuite)
        (2.0)
      ]
      /PDFXOutputIntentProfileSelector /DocumentCMYK
      /PreserveEditing true
      /UntaggedCMYKHandling /LeaveUntagged
      /UntaggedRGBHandling /UseDocumentProfile
      /UseDocumentBleed false
    >>
  ]
>> setdistillerparams
<<
  /HWResolution [2400 2400]
  /PageSize [612.000 792.000]
>> setpagedevice

