Humanities and Social Science Research; Vol. 8, No. 4; 2025 ISSN 2576-3024 E-ISSN 2576-3032 https://doi.org/10.30560/hssr.v8n4p31 31 Published by IDEAS SPREAD Research on the Realization Mechanism of Promoting Provincial Common Prosperity in China through Urban-Rural Integration Development Yue Zhang1, Youquan Liu1 & Linfei Wei1 1 School of Mathematics and Statistics, Pingdingshan University, China Correspondence: Yue Zhang, School of Mathematics and Statistics, Pingdingshan University, Henan, China. Received: July 4, 2025; Accepted: July 17, 2025; Published: July 18, 2025 Fund Project: Henan Provincial Soft Science Research Program Project "Research on the Realization Mechanism and Path Countermeasures of Promoting Henan's Common Prosperity through Urban-Rural Integrated Development"(252400410319). Abstract Under the guidance of the goal of common prosperity in the new era, urban-rural integration development is not only an inherent requirement for solving the problems of unbalanced and insufficient development in China’s provinces, but also an important path for steadily promoting common prosperity in the new development stage. Based on the panel data of 31 provinces (autonomous regions, municipalities) in China from 2014 to 2023, this paper uses the entropy method to measure the level of urban-rural integration development and common prosperity, conducts a spatio-temporal evolution analysis of urban-rural integration development and common prosperity level, and uses the spatial lag model to analyze the impact of urban-rural integration on common prosperity and its spatial effect. The results show that: 1) The urban-rural integration development and common prosperity in China are in a state of steady annual increase, and there are certain differences in the current levels among provinces; 2) The level of common prosperity in China has a significant positive spatial correlation, and there is an obvious positive spatial spillover effect among the levels of common prosperity in provinces. Finally, relevant policy suggestions for promoting provincial common prosperity in China through urban-rural integration development are put forward from aspects such as coordinating resource allocation, giving play to the role of policy intervention, implementing differentiated opening-up policies, promoting urban-rural education equality, optimizing the industrial structure, and supporting scientific and technological innovation. Keywords: urban-rural integration, common prosperity, spatial spillover effects 1. Introduction The report of the 20th National Congress of the Communist Party of China clearly states that "Chinese modernization is the modernization of common prosperity for all people" and that "we must adhere to giving priority to the development of agriculture and rural areas, adhere to urban-rural integration development, and smooth the flow of urban and rural elements [1] ." Promoting the urban-rural integration development strategy and constructing an institutional mechanism adapted to urban-rural integration are the only way for China to narrow the urban-rural development gap and help farmers and rural areas achieve common prosperity. In recent years, the widening of the urban-rural development gap and the gap between the rich and the poor in residents’ incomes are all contrary to common prosperity. Therefore, driving the realization of common prosperity through urban-rural integration development is of great significance for promoting the high-quality development of China’s urban and rural social economy and improving the livelihood well-being of urban and rural residents. On December 16, 1953, the concept of "common prosperity" was first put forward in the "Resolution on the Development of Agricultural Producers’ Cooperatives". After continuous exploration and practice, after the reform and opening up, Deng Xiaoping put forward two theories on common prosperity, advocating that "let some people and some regions get rich first, so as to promote the achievement of the goal of common prosperity [2] ". Thus, the theoretical research on common prosperity has gradually become more rational. After the 19th National Congress of the Communist Party of China first put forward the strategic decision of "establishing and improving the institutional mechanism and policy system for integrated urban-rural development", the research on integrated hssr.ideasspread.org Humanities and Social Science Research Vol. 8, No. 4; 2025 32 Published by IDEAS SPREAD urban-rural development in the academic circles of our country has started to show a blowout development trend. Kong Xiangzhi and Xie Dongdong proposed that integrated urban-rural development is the core path to consolidate the stage achievements of common prosperity and solve the problems of governance of rural relative poverty on the basis of systematically analyzing the evolution law of urban-rural relations [3] . In addition, Li Ning built an analytical framework for integrated urban-rural development to drive common prosperity around the three dimensions of space, resources and system, and carried out an analysis at the theoretical level [4] . Guo Xiaoming and Ding Yanwu deeply analyzed the key points and difficult problems in promoting the process of common prosperity by means of integrated urban-rural development, and then proposed that to achieve the goal of common prosperity in the new stage, it is necessary to focus on promoting from the five dimensions of space, industry, elements, governance and system [5] . 2. Theoretical Analysis and Research Hypothesis First of all, integrated urban-rural development can enhance the vitality of rural development. The free flow of various urban-rural elements has enabled the transformation of the agricultural development mode from traditional agriculture to modern agriculture, continuously optimized the agricultural industrial structure, and expanded the large-scale operation of land. At the same time, relying on the unique natural and cultural resources in the countryside, tourism projects are developed to drive the increase of farmers’ income, encourage rural migrant workers to return to their hometowns to start businesses, and form a virtuous circle of rural talent and resource development. The key to promoting the common prosperity of farmers in the new era lies in increasing their income. Relying on the all-round revitalization of the countryside, stimulating the internal vitality of the countryside, increasing farmers’ income in all-round and multi-channel ways, continuously expanding the scale of the middle-income group in rural areas, narrowing the urban-rural income gap, and enabling the vast number of farmers to achieve common prosperity synchronously [6]. Second, the integrated urban-rural development can optimize the allocation of urban-rural public resources. The rational allocation of public resources is an important guarantee for promoting high-quality economic development and achieving common prosperity for all members. At present, there are still many problems in the overall allocation of urban-rural public resources in China. Unequal development opportunities are an important reason for the unequal allocation of urban-rural public resources. Co-construction and sharing is an effective way to achieve common prosperity. By strengthening the connection between cities and rural areas, it can promote the coordinated development of cities and rural areas, drive sustained economic growth, narrow the development gap between urban and rural areas, and substantially promote the progress of common prosperity. Therefore, the following research hypotheses are proposed in this paper. Hypothesis 1: The integrated urban-rural development can directly promote the realization of common prosperity. Common prosperity is not one-sided regional prosperity but an overall concept for the whole society. In the process of promoting common prosperity, there are double spatial spillover effects of policy learning and resource reciprocity. First, when the common prosperity policy brings new development impetus, the models, policies, and innovative practices adopted by advanced regions can stimulate the enthusiasm and willingness to imitate of surrounding and other regions, promoting the formation of a positive spatial spillover effect of policy learning. At the same time, the difference in economic efficiency between developed and underdeveloped regions will further enhance the imitation motivation of backward regions, strengthening the promotion effect of the policy demonstration effect and trickle-down effect on neighboring regions. Second, the spillover effect of urban-rural integration on the level of common prosperity in neighboring regions cannot be ignored. Urban-rural integration can promote the development of cities and rural areas into a territorial community of harmonious coexistence, interest coordination, complementary functions, and interlaced integration, promoting urban-rural connection and spatial integration, and thus eliminating the opposition and division between urban and rural regions. This can promote urban and rural residents to share the fruits of development and accelerate the promotion of common prosperity. At the same time, the integrated urban-rural development also helps to establish a harmonious social relationship, create a stable economic environment, and lay a solid foundation for the common prosperity of neighboring regions. In addition, there is frequent communication among some regions, enhancing the connection of economic activities among regions, promoting the coordinated development among regions, and advancing regional common prosperity. Generally speaking, the spillover effect of the integrated urban-rural development on the common prosperity of neighboring regions is a positive linkage effect, driving the whole region towards the direction of common prosperity[7]. Therefore, the following hypothesis is proposed: Hypothesis 2: Common prosperity has a spatial spillover effect. hssr.ideasspread.org Humanities and Social Science Research Vol. 8, No. 4; 2025 33 Published by IDEAS SPREAD Hypothesis 3: The integrated urban-rural development positively promotes common prosperity in the form of spatial spillover. 2. Measurement of the Integrated Urban-Rural Development and the Level of Common Prosperity 2.1 Measurement of the Level of Integrated Urban-Rural Development As a key component of economic and social development, the integrated urban-rural development can not only achieve Pareto optimality in resource allocation, but also serve as a powerful "accelerator" leading the rural revitalization. Based on the research of scholars such as Fang Chuanglin[8], this paper constructs an evaluation index system for the level of integrated urban-rural development from three dimensions: urban-rural economic integration, urban-rural factor integration, and urban-rural spatial environment integration, as shown in Table 1. Table1. Index System for Integrated Urban-Rural Development Primary indicator Secondary indicator Indicator nature Urban-rural economic integration Ratio of per capita wage income of urban and rural residents Negative Ratio of per capita consumption expenditure of urban and rural residents Negative Ratio of per capita cultural, educational and entertainment consumption expenditure between urban and rural areas Negative Ratio of Engel coefficients between urban and rural areas Positive Urban-rural factor integration Ratio of the number of urban and rural residents participating in unemployment insurance to the total population Positive Proportion of non-agricultural added value in GDP Positive Ratio of non-agricultural employed population to agricultural employed population Positive Ratio of private car ownership to total population Positive Ratio of total agricultural machinery labor force to agricultural sown area Positive Urban-rural spatial environment integration Per capita park green space area Positive Forest coverage rate Positive Ratio of environmental protection expenditure to general budget expenditure of finance Positive Rate of harmless treatment of domestic waste Positive After dimensionless processing of various indicators of urban-rural integration development, the entropy method is used to calculate the weights of evaluation indicators and the urban-rural integration development indices of each region in the country, and the weighted sum is used to solve the urban-rural integration development level indices of 31 provincial regions in China from 2014 to 2023 (see the appendix table). The measurement of the urban-rural integration development level of some provincial regions is shown in Figure 1. Figure 1. Urban-Rural Integration Development Level of Some Provincial Regions 0 0.1 0.2 0.3 0.4 0.5 0.6 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 Beijing Liaoning Shanghai Henan Chongqing Shanxi hssr.ideasspread.org Humanities and Social Science Research Vol. 8, No. 4; 2025 34 Published by IDEAS SPREAD From 2014 to 2023, the urban-rural integration development level of 31 provincial regions in China showed an upward trend. Among them, the growth was rapid from 2017 to 2020; affected by the COVID-19 pandemic in China, the development speed slowed down from 2020 to 2023. The urban-rural integration development levels of northern regions such as Tianjin and Shanxi in China had the largest increase, and the policy dividends boosted the acceleration of urban-rural integration development in the capital and its surrounding areas. The urban-rural integration development index in the central region was lower than that in the economically developed regions along the southeast coast, but the development prospect was considerable. Driven by the strategy of building a moderately prosperous society in all respects, the disposable income structure of rural residents in the central region was significantly optimized, the proportion of income from wage work in the total income continued to rise, and at the same time, the investment in the field of spiritual and cultural consumption increased significantly. The infrastructure construction in the western region was continuously improved, the non-agricultural employment channels were continuously expanded, the transformation and upgrading of the manufacturing industry helped the coordinated development of industries, and drove the local fiscal and tax revenues to maintain a steady growth trend. In the past decade, the urban-rural gap in income, consumption level, public services, infrastructure, and social welfare in all provincial regions of the country has been gradually narrowing. 2.2 Measurement of the Level of Common Prosperity Common prosperity is not simply material civilization prosperity, but common prosperity that unifies material and spiritual life, is prosperity that benefits all people, and is even more prosperity that takes into account both fairness and efficiency. This paper draws on the construction of the common prosperity indicator system by Zou Weiyong, Xu Lingli, etc. [9] , and combines the availability of data to divide common prosperity into two dimensions: sharing degree and prosperity degree, and constructs the common prosperity indicator system as follows: Table 2. Common Prosperity Indicator System First-level indicator Second-level indicator Indicator nature Sharing degree Urbanization rate Positive Registered urban unemployment rate Negative Per capita social security and employment expenditure Positive Per capita urban road area Positive Number of public transport vehicles per 10,000 people Positive Number of hospital beds per 1,000 people Positive Number of health technicians per 1,000 people Positive Number of public toilets per 10,000 people Positive Affluence level Per capita GDP Positive Per capita disposable income Positive Ratio of fiscal education expenditure to total fiscal expenditure Positive Per capita holdings of public library collections Positive Figure 2. The Development Level of Common Prosperity in Some Provincial Regions 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 Beijing Liaoning Shanghai Henan Chongqing Shanxi hssr.ideasspread.org Humanities and Social Science Research Vol. 8, No. 4; 2025 35 Published by IDEAS SPREAD After dimensionless processing of various indicators of common prosperity, the entropy method is used to calculate the weights of evaluation indicators and the urban-rural integration development indices of various regions across the country. By accumulating the weights of indicators, the weights of the two first-level indicator systems of sharing degree and prosperity degree are calculated. Using the corresponding weights of the indicators, the weighted sum is used to solve the common prosperity level index of 31 provincial regions in China from 2014 to 2023. The measurement of the common prosperity development level of some provincial regions is shown in Figure 2. From 2014 to 2023, the gap in the common prosperity indices of provincial regions across the country has gradually narrowed, thanks to the promotion and implementation of government policies and measures. The common prosperity index in the eastern region is greater than that in the central and western regions. The eastern coastal area is the pioneer area of China’s reform and opening up and has strong economic strength. The high-quality economic development in the central and western regions started late. The main development mode is agriculture, with few high-tech industries. There are large gaps in regional infrastructure conditions, public service levels, social security degrees, etc. compared with the eastern region, and the development speed is slow. The level of common prosperity in these regions lags behind that in the eastern region. 3. Research Methods 3.1 Data Sources The research geographical unit of this paper is 31 provinces, municipalities and autonomous regions across the country (excluding Hong Kong, Macao and Taiwan regions due to statistical caliber deviations). The research period is from 2014 to 2023. The research data comes from the China Statistical Yearbook. Some indicator data comes from the statistical bulletins on national economic and social development released by the websites of provincial governments, the statistical data released by provincial statistical bureaus and relevant departments. There are missing values for some individual data, which are filled by extrapolation of adjacent years or interpolation method. 3.2 Variable Selection Main variables. The core explanatory variable of the urban-rural integration development level is selected, and the common prosperity level is selected as the explained variable, and it is measured by constructing a multi- dimensional indicator system and using the entropy method. Control variables. To more accurately analyze the impact of the urban-rural integration development level on common prosperity, referring to the existing research results of scholars, this paper selects five control variables: government intervention, degree of opening to the outside world, human capital, industrial structure, and scientific and technological innovation level. 3.3 Model Construction (1) Spatial autocorrelation analysis. It is a research method to explore the attribute value of a certain element in space and the attribute values of its adjacent spatial elements, including two analysis types: global and local [10]. The Moran index is the most commonly used correlation index to evaluate spatiality, and its value range is [-1,1] , and the Z test is commonly used to judge its significance, which is divided into the global Moran index and the local Moran index. ① Global Spatial Autocorrelation The global Moran’s I index is used to evaluate the spatial autocorrelation of resources in the entire study area. When the index is positive, it indicates a positive correlation among regions, showing an aggregated distribution pattern. The calculation formula for the global Moran’s I index is: I= n ∑ ∑ wij n j=1 n i=1 (xi-x‾) ∑ ∑ wij n j=1 n i=1 (xi-x‾)2 = ∑ ∑ wij n j≠1 n i=1 (xi-x‾)(xj-x‾) S2 ∑ ∑ wij n j=1 n i=1    (1) ② Local Spatial Autocorrelation The local Moran’s I index can identify the distribution pattern and manifestation form of autocorrelation at specific spatial locations. Its calculation formula is: Ii= (xi-x‾) S2 ∑ wij j≠i (xj-x‾)   (2) hssr.ideasspread.org Humanities and Social Science Research Vol. 8, No. 4; 2025 36 Published by IDEAS SPREAD In equations (1) and (2), I represents the Moran’s I index, xi, xj represents the attribute value of spatial unit i、j , w represents the spatial weight, x represents the average value of the observed values. wij represents the element of the spatial weight matrix, with the spatial adjacent value being 1 and the non-adjacent value being 0. (2) Spatial econometric model.Since regions are not independent economic entities and there is a certain spatial correlation. Based on this, this paper introduces the spatial Durbin model (SDM) to discuss the impact of high- quality development of social security on common prosperity. First, use the LM test to judge whether it is appropriate to use the spatial Durbin model; second, judge the robustness of the spatial Durbin model through the LR and Wald tests; finally, conduct the Hausman test to verify whether to choose fixed effects or random effects. 4. Empirical Result Analysis 4.1 Spatial Correlation Test By reading a large number of literatures, it is found that when calculating the global Moran’s I index, the commonly selected spatial weight matrices include the adjacency distance matrix, economic distance matrix, economic geography matrix, and geographical inverse distance square matrix. After comparing the measurement effects of different matrices through experiments, it is found that the spatial economic geography nested matrix has the best effect. Therefore, this paper uses this matrix to calculate the global Moran’s I index. The test results of the global Moran’s I index of the level of common prosperity in each year in China are shown in Table 3. Table 3. Global Moran’s I index of the level of common prosperity Year Moran’s Index Sd(I) Z value 2014 0.709 *** 0.102 7.306 2015 0.701 *** 0.101 7.267 2016 0.682 *** 0.100 7. 123 2017 0.691*** 0.099 7.283 2018 0.715 *** 0.099 7. 466 2019 0.634 *** 0.101 6.640 2020 0.741 *** 0.098 7.913 2021 0.587 *** 0.103 6.005 2022 0.560 *** 0.104 5.700 2023 0.722 *** 0.098 7.735 As can be seen from Table 3, the global Moran’s Index p values of common prosperity from 2012 to 2021 are all less than 0.05 and pass the test at the 95% confidence interval, indicating that the level of common prosperity in China shows significant spatial dependence characteristics, that is, spatial lag terms or error terms must be included in the econometric model to avoid estimation errors; the global Moran’s Index of common prosperity is all positive, indicating that there are positive spatial correlation characteristics in the level of provincial common prosperity in China, that is, in regions with a high level of common prosperity, the level of common prosperity in adjacent regions also remains at a relatively high level; from 2014 to 2023, the absolute value of the global Moran’s Index of common prosperity gradually decreases, indicating that the gap in the level of common prosperity among provinces is gradually narrowing. To study the spatial autocorrelation and agglomeration status of the level of common prosperity in each province, based on the local Moran’s Index, this paper uses Stata18 to draw Moran’s Index maps for 2014, 2017, 2020, and 2023, as shown in Figures3,4, 5, and 6. hssr.ideasspread.org Humanities and Social Science Research Vol. 8, No. 4; 2025 37 Published by IDEAS SPREAD Figure 3. Moran’s Index Map of Common Prosperity in 2014 Figure 4. Moran’s Index Map of Common Prosperity in 2017 Figure 5. Moran’s Index Map of Common Prosperity in 2020 Figure 6. Moran’s Index Map of Common Prosperity in 2023 As can be seen from the figure, most provinces are in the first and third quadrants, and as the years increase, the number of provinces in the first and third quadrants gradually increases, that is, the number of provinces showing positive spatial autocorrelation gradually increases. High-High (H-H) agglomeration type: Provinces belonging to this agglomeration type are located in the first quadrant, mainly including Beijing, Jiangsu, Zhejiang, Shandong, Tianjin, etc. These provinces are relatively economically developed and have been in the high-high agglomeration type for many years. From 2014 to 2023, the number of provinces in the first quadrant gradually increases, indicating that the development level of common prosperity is gradually increasing. Low-High (L-H) agglomeration type: Provinces belonging to this agglomeration type are located in the second quadrant, mainly including Fujian, Liaoning and other regions. From a national perspective, the comprehensive development level of these provinces is in the middle range, and regions with prominent development advantages can effectively drive the surrounding areas. Low-Low (L-L) agglomeration type: Provinces belonging to this agglomeration type are located in the third quadrant, mainly including western regions such as Tibet, Guizhou, Gansu, Qinghai, and Yunnan. Restricted by their remote geographical locations, the economic and social development levels of these provinces are relatively low. Since they are all in border regions, the economic radiation capacity of the surrounding areas is insufficient, and it is difficult to form a surrounding driving effect, resulting in a continuous expansion of the development gap with the southeast coastal areas. High-Low (H-L) agglomeration type: Provinces belonging to this agglomeration type are located in the fourth quadrant, mainly including Xinjiang, Heilongjiang and other regions. Generally speaking, there are significant spatial differences in the development levels of different regions. The disparities in the level of common prosperity between the western regions and the more developed regions in terms hssr.ideasspread.org Humanities and Social Science Research Vol. 8, No. 4; 2025 38 Published by IDEAS SPREAD of economic development are relatively large, indicating an imbalance in the development level of common prosperity in China. 4.2 Model Identification and Verification To select the most appropriate spatial econometric model for empirical research, it is first necessary to use the LM test to conduct Lagrange multiplier tests on the spatial error model and the spatial lag model. Table 4. Results of the LM Test Inspection Statistic P-value SEM Moran’s I 1.802 0.028 LM 3. 958 0.047 RLM 14.268 0.000 SLM LM 20.665 0.000 RLM 30.975 0.000 As can be seen from Table 4, the LM tests of SEM and SLM are both significant at the 95% confidence interval. Therefore, this paper can choose the spatial Durbin model for further research. Subsequently, the Hausman test is used to identify the effect type of the model. The result of the Hausman test is -3.76, which is negative. Therefore, this paper should choose the spatial Durbin model with fixed effects. As can be seen from Table 5, the P values in the LR test results are all less than 0.05 and pass the test at the 99% significance level. Therefore, the best spatial econometric model should be the two-way fixed effects spatial Durbin model. From Table 6, the Wald tests and LR tests of SEM and SAR have all passed the 90% significance test. Therefore, it is considered that the spatial Durbin model cannot be simplified into the spatial lag model or the spatial error model. Table 5. Results of LR Test Inspection Items Statistic Value P Value Inspection Items Statistic Value P Value "Individual" fixation and "two-way" fixation 44.58 0.000 "Time"fixation and "two-way" fixation 352.11 0.000 Table 6. Results of Wald Test Inspection Items Statistic Value P Value Inspection Items Statistic Value P Value Wald Test for SEM 13.36 0.037 Wald Test for SAR 14.8 0.022 LR Test for SEM 14.39 0.025 LR Test for SAR 13. 15 0.041 4.3 Results Analysis of the Two-Way Fixed Effects Spatial Durbin Model This paper selects the spatial Durbin model (SDM) with two-way fixed effects for empirical analysis, and the fitting results of the model are as follows: Table 7. Econometric Results of the Two-Way Fixed Effects Spatial Durbin Model Variable Coef Main Coef Wx Z value P value Z value P value Level of urban-rural integrated development 0.935 3.66 0.000 0.698 2. 16 0.031 Government intervention 0.046 0.49 0.047 0.053 0.57 0.006 Degree of opening to the outside world -0.201 -1.34 0.018 -0.041 -0.47 0.006 Human capital 0.131 0.81 0.049 0.581 1.79 0.044 Industrial structure 0.068 0.72 0.012 0.465 1.44 0.014 Level of scientific and technological innovation 0.342 1.55 0.041 0.634 1.96 0.050 Spatial rho Coef: 0.396 P value: 0.015 From the measurement results of the double fixed-effects spatial Durbin model, it can be seen that the value of spatial rho is 0.396,P value is 0.015, which passes the significance test. It is considered that there is spatial hssr.ideasspread.org Humanities and Social Science Research Vol. 8, No. 4; 2025 39 Published by IDEAS SPREAD autocorrelation in the level of common prosperity among provinces in China. The positive coefficient of the direct effect indicates that the level of urban-rural integration development in neighboring provinces has a significant positive impact on the level of local common prosperity; the passing of the significance test of the indirect effect shows that the level of urban-rural integration development in this region can not only promote the development of local common prosperity, but also drive the development of common prosperity in surrounding areas through the spatial spillover effect. Among them, the improvement of the level of urban-rural integration development, the role of government intervention, the growth of human capital, the optimization of the industrial structure, and the improvement of the level of scientific and technological innovation all have a positive impact on the realization of common prosperity; while expanding opening up to the outside world has an inhibitory effect on the realization of common prosperity. Whether in the short-term impact or long-term effect, the improvement of the level of urban- rural integration development will increase the level of common prosperity. 5. Conclusions and Policy Recommendations 5.1 Conclusions This paper closely focuses on the level of urban-rural integration development and the level of common prosperity in China’s provincial regions, and comprehensively uses a variety of model methods to deeply analyze the realization mechanism of urban-rural integration development promoting common prosperity in China’s provincial regions, and obtains the following conclusions: (1) From a national perspective, except for the decline in the comprehensive scores of some provincial regions affected by the epidemic from 2020 to 2023, the level of urban- rural integration development in China is generally on a steady upward trend, and there are certain differences in the level of urban-rural integration development in different regions. (2) Generally speaking, the level of common prosperity in China has significant positive spatial autocorrelation, and the level of common prosperity in each province shows a positive spatial aggregation state. (3) The improvement of the level of urban-rural integration development, the role of government intervention, the growth of human capital, the optimization of the industrial structure, and the improvement of the level of scientific and technological innovation all have a positive impact on the realization of common prosperity; while expanding opening up to the outside world has an inhibitory effect on the realization of common prosperity. 5.2 Policy Recommendations (1) Collaborate on resource allocation, give play to the role of policy intervention, and improve rural guarantees. As the core area and important driving force for the high-quality improvement of non-urban regions, rural areas are the foundation for the stable development of society. Under the guidance of the concept of regional coordinated development, a cross-regional industrial cooperation platform should be established to achieve the gradient transfer of development achievements through the mechanism of complementary advantages, so as to form a virtuous cycle pattern of two-way flow of factors. (2) Differentiated opening-up policies to strengthen two-way factor flows. In the process of opening up to the outside world, the government should formulate supporting policies for rural industry protection and training programs for the labor force to mitigate the impact of international competition on rural areas. At the same time, efforts should be made to promote the two-way flow mechanism of urban and rural factors, deepen the market- oriented reform process of urban and rural factors, give full play to the feedback effect of urban resources on rural areas, and improve the policy support system for rural migrant workers to start businesses back in their hometowns. (3) Optimize the industrial structure to achieve coordinated urban and rural economic growth. Each region should be based on its actual conditions, focus on cultivating characteristic agriculture and rural tourism projects, and promote the coordinated development of multiple industries. Strengthen industrial support and employment security, guide enterprises to give priority to providing local employment opportunities, and effectively broaden the channels for farmers to increase their incomes. At the same time, build a national unified large market governance system, improve the cross-regional supervision coordination framework, use blockchain technology to establish a factor circulation traceability system, and realize the paradigm shift of resource optimal allocation from Pareto improvement to Kaldor improvement. (4) Support scientific and technological innovation to contribute to common prosperity. Industrial technological innovation can not only rapidly improve the development speed of rural economy and society, promote the gradual improvement of residents’ consumption levels and living qualities, but also drive rural employment through industrial technological innovation and promote the continuous improvement of the rural industrial system. Therefore, the government should, through different means such as policy support, special funds support, and improvement of service levels and capabilities, continuously improve the level of industrial technology innovation and entrepreneurship, continuously increase the innovation activity level of enterprises and the participation degree hssr.ideasspread.org Humanities and Social Science Research Vol. 8, No. 4; 2025 40 Published by IDEAS SPREAD of mass entrepreneurship through incentive measures, enhance the overall level of industrial technology innovation in society, stimulate development vitality, update the economic driving engine, and promote common prosperity. Acknowledgments This paper was supported by Henan Provincial Soft Science Research Program Project "Research on the Realization Mechanism and Path Countermeasures of Promoting Henan's Common Prosperity through Urban-Rural Integrated Development"(No:252400410319). References [1] Xi, J. (2022). 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