Rural Industrial Revitalization and the Common Prosperity of Rural Inhabitants in China: Exploring Synergies Between Efficient Governance and Effective Markets

Abstract

The common prosperity of rural inhabitants is a fundamental requirement of Chinese-style modernization, with the revitalization of rural industries offering new opportunities to achieve this goal. Utilizing panel data from 31 Chinese provinces (2012–2023), this study examines the impact and mechanisms of the revitalization of rural industries on rural inhabitants’ common prosperity. The results show that the revitalization of rural industries significantly promotes common prosperity among rural inhabitants, with this conclusion holding across various robustness tests. The revitalization of rural industries primarily advances common prosperity through enhancing labor productivity and driving agricultural technological innovation, representing efficiency and impetus transformations. The new rural collective economy positively moderates common prosperity via the efficiency path but moderates it negatively via the impetus path. The “efficient government–effective market” coupling coordination exhibits a positive threshold effect on the revitalization of rural industries’ impact on common prosperity, intensifying this positive effect as coordination deepens. Strategic recommendations include optimizing rural industry structures, enhancing collective economies, and strengthening government–market coupling to accelerate common prosperity.

1. Introduction

1.1. The Motivation

Guanzi Governing the Country says: “The way to govern the country must first enrich the people”. For those aiming to achieve common prosperity for all the people, the focus and difficulty lie in rural areas [1]. Currently, rural areas in China generally face problems such as insufficient internal growth momentum, barriers in the urban–rural factor market, and low levels of agricultural industrial development, which seriously hinder the current process of common prosperity for inhabitants of villages [2]. With the historic shift in the focus of China’s work on “rural issues” to the cause of rural revitalization, the Chinese-style modernization goal of common prosperity for all the people has officially entered a new stage of development. In a report to the 20th National Congress of the Communist Party of China, Xi Jinping, President of the People’s Republic of China, profoundly elaborated on the internal connection between rural revitalization and common prosperity in rural areas and put forward the proposition of “promoting common prosperity of rural inhabitants”. The practical experience of poverty alleviation has proved that industrial revitalization is a catalyst to enhance the endogenous power of rural prosperity and a strong support point for rural inhabitants to become self-reliant and prosperous, and the implementation of rural industrial revitalization is conducive to making the “rural economical cake” bigger and stronger [3]. In essence, the revitalization of rural industries and common prosperity result from coordinated and unified production and distribution and the joint participation of multiple forces, which requires the strategic coordination of various subjects, resources, and capabilities in the field [1,4]. Against this background, the participation relationship between the government and the market has become the core issue of promoting common prosperity, giving play to the effective market price mechanism to regulate the flow of factors and resource allocation between urban and rural areas, and relying on the long-term institutional system embedded in the efficient government to compensate for the failure of the market mechanism in the revitalization of rural industries [5]. It is significant to realize the goal of “taking into account both efficiency and equity” for common prosperity. This study aims to answer the following questions: What is the internal mechanism and implementation path of rural industry revitalization to promote the common prosperity for rural inhabitants? Can the revitalization of rural industries and promoting the common prosperity of rural inhabitants within the framework of coordinated development of an efficient government and an effective market achieve efficiency goals while ensuring social equity? The theoretical analysis and empirical testing of the above problems have great theoretical significance and practical utility for pointing out the development path of rural industry, handling the relationship between efficiency and equity in the revitalization of rural industries, and promoting the common prosperity of all people.

1.2. The Mechanism Relationship Between the Revitalization of Rural Industries and the Common Prosperity of Rural Inhabitants

First, we will describe some research on the cultivation path and influencing effect of rural industry. Zhou L. et al. (2018), while analyzing the cases of rural revitalization in Japan and South Korea, proposed that cultivating rural industries should promote industrial integration, give play to the versatility of agriculture, and create new supplies and business forms [6]. Zhang Y P and Luan J (2022) emphasized the need to bring into play the “dandelion effect” of the digital economy, integrate data elements into agricultural production, strengthen information technology support, and promote the revitalization of rural industries [7]. Shi D Y and Han L D (2024) investigated the key support counties for rural revitalization in Sichuan. They found that to promote the revitalization of rural industries in the support counties, the market needs to stimulate the characteristic industrial impetus, and the local government system needs to guarantee the stability and sustainability of industrial revitalization [5]. Research on the effect of rural industry is mainly carried out from the perspective of the poverty alleviation effect and the income increase effect on rural households. Li D.H and Qiao L Y (2019) believe that industrial poverty alleviation takes economic benefits as the core, and the endogenous development mechanism that promotes local transformation and development and increases the income of poor rural inhabitants by developing characteristic industries in poor areas is a transformation from ‘blood—transfusion’ poverty alleviation to ‘blood—making’ poverty alleviation [8]. In the process of its benign operation, it is necessary to clarify the responsibilities and boundaries of the government and the market in industrial development [9], attach importance to the cultivation of local talents to stimulate endogenous impetus [10], avoid short-sighted behaviors and build a long-term security mechanism [11] to play a positive role in reducing the vulnerability of rural poverty [12]. Academic circles have reached a consensus on the effect of rural industry on increasing rural inhabitants’ income, and the poverty alleviation work in rural industry has significantly increased the property income of rural family units [13,14].

1.3. The Correlation and Motivation of the Revitalization of Rural Industries and Common Prosperity

The core of the connotation of common prosperity lies in the realization of fair distribution and sharing of social wealth. Common prosperity not only requires “making the cake bigger”—that is, liberating and developing productive forces and accumulating material wealth—but also requires “dividing the cake”—that is, fair distribution of wealth, which is the unity of taking into account efficiency and fairness [15]. By promoting production and improving distribution, the revitalization of rural industries not only enhances the quality of economic growth and accelerates the realization of “prosperity” but also expands the scope of prosperity and emphasizes the importance of “commonality” [16]. The revitalization of rural industries is the key basis of the rural revitalization strategy and the only way to achieve the common prosperity of rural inhabitants. The convergence of the two goals is an important guarantee for the prosperity of the country and the happy life of all the people [17]. Given the existing research on the motivation of rural industrial prosperity and the common prosperity of rural inhabitants, scholars found that the new rural collective economic model represented by farmer cooperatives, leading enterprises, and other organizations is conducive to promoting collective economic development and common prosperity in rural areas, and is an important engine that leads rural inhabitants to overcome poverty and move towards common prosperity [18,19]. To break through the path dependence of “blood transfusion” development, it is necessary to accelerate the construction of the interest linkage mechanism between collectivity and rural inhabitants [20] and use the new collective economic development model to drive rural residents to achieve prosperity.

1.4. Novelty and Contribution

In summary, the existing literature provides a valuable logical starting point and theoretical basis for the development of this study. However, most studies on how the revitalization of rural industries can achieve the common prosperity of rural inhabitants remain at the level of theoretical speculation. Discussions and analyses of its internal mechanism and realization path lack empirical support. Studies including efficient government and effective markets in the discussion framework of industrial revitalization and common prosperity are even rarer. In light of this, this paper selects samples from 31 provinces (excluding Hong Kong, Macao, and Taiwan) from 2012 to 2023 to constitute panel data, empirically analyzes the impact of the revitalization of rural industries on rural inhabitants’ common prosperity, and explores the mechanism of the effect of efficient governments and effective markets.

The marginal contribution of this paper is as follows: First, based on the essential requirements of “affluence” and “sharing” of common affluence, the comprehensive evaluation system of rural inhabitants’ common affluence is established by integrating the multiple dimensions of an affluence layer, common layer and sustainable layer to provide a reference evaluation tool for subsequent research. Secondly, from the perspective of efficiency reform and impetus reform, the internal mechanism and action mechanism of the revitalization of rural industries to promote rural inhabitants’ common prosperity are analyzed, and the theory of the revitalization of rural industries is enriched. Thirdly, the research framework of “efficient government and effective market—the revitalization of rural industries—rural inhabitants’ common prosperity” is explored to study the role range of “efficient” government and “effective” market, to provide a useful reference for cultivating and optimizing rural industry decision-making.

2. Theoretical Analysis and Research Hypothesis

2.1. The Role and Mechanism of the Revitalization of Rural Industries for the Common Prosperity of Rural Inhabitants

The revitalization of rural industries takes the reform of the agricultural supply side as the main line. Changing the traditional agricultural development mode, cultivating new rural industries, new business forms, and new models facilitate the rural revitalization strategy. Agriculture is an important part of rural industry and plays an irreplaceable role in giving play to the unique functions of rural areas [21]. In terms of the cultivation of modern agriculture, the revitalization of rural industries can improve agricultural efficiency and the added value of agricultural products by exploiting and utilizing agricultural resources with local characteristics, cultivating modern agriculture with a brand effect according to the differences in regional resource endowment, and at the same time, using rural infrastructure construction, improving human capital and scientific and technological investment, optimizing agricultural industry organizational systems, etc. The aim is to enhance the market competitiveness of agricultural products, drive rural inhabitants to increase their income and production, and lay a solid material foundation for common prosperity. In terms of modern agricultural value-added, the revitalization of rural industries can extend the agricultural and industrial chain, promote the deep integration of the primary, secondary, and tertiary industries based on the integration of agricultural industry, extend the industrial chain, expand the multiple functions of agriculture, technology penetration, and industrial agglomeration, improve the traditional rural economic structure, and boost the level of rural economic development. In addition, the revitalization of rural industries can also break the barriers that hinder the free flow of production factors such as manpower, capital, and information, smooth the two-way flow channels of urban and rural production factors, stimulate the flow vitality of market production factors, improve the collaborative utilization efficiency of resource factors, and thus promote the process of the common prosperity of rural inhabitants.

The president, Xi Jinping, emphasized that “efficiency change and impetus reform drive quality change, accelerating the formation of sustainable, high—quality development systems and mechanisms”. For rural economic high-quality development, rural industry revitalization, grounded in efficiency change and centered on impetus reform, offers valuable opportunities for rural inhabitants and areas to achieve common prosperity.

The revitalization of rural industries promotes efficiency reform by enhancing rural labor productivity, thus fostering rural inhabitants’ common prosperity. Information technologies, such as cloud computing, 5G, and VR, fuel rural agricultural production. The improved rural digital infrastructure provides crucial support for characteristic industries. In labor production, it boosts resource efficiency and reduces waste. Meanwhile, the industrial revitalization support system standardizes rural land circulation, secures land transactions, curbs land abandonment, revitalizes idle resources, and optimizes factor allocation for large-scale and professional farming. With enhanced infrastructure and optimized resource allocation, the growing rural labor productivity spurs rural endogenous growth. It creates jobs for low-income villagers, increases their labor income, and enables rural inhabitants to share the fruits of economic growth.

From the impetus perspective, rural industry revitalization drives agricultural technological innovation, leading to rural inhabitants’ common prosperity. As the primary productive force, technology witnesses a rising demand in agricultural production due to rural industry revitalization, which accelerates the application of agro-technological innovation. Based on the technology spillover theory, technological innovation in developed areas spills over, narrowing the urban–rural technology gap and powering rural industry-led common prosperity. Moreover, agro-tech innovation reshapes the agricultural production system. Industry integration gives rise to new sectors and models, revitalizing rural industries and energizing the rural economy. From the perspective of industrial structure theory, agriculture-related technological innovation can extend the agricultural industry chain, catalyze the gradual optimization of traditional agricultural structure from low-value-added industries to high-value-added industries, effectively improve the efficiency of resource allocation, guide rational division of labor and cooperation in agricultural production, promote high-quality development of rural economy [22], and then drive rural inhabitants to common prosperity.

2.2. The Regulating Effect of the New Rural Collective Economy

The new rural collective economy is an economic model built in rural areas with rural inhabitants as the main body and through multiple subjects’ cooperation, clear property ownership, precise member boundaries, a sound governance structure, and a fair benefit distribution system. Under the basic national conditions of “big country with small-scale farmers” in China, it is a long-term and arduous task to promote the transformation of small rural inhabitants’ production to agricultural modernization, and the new rural collective economy plays a key role in this transformation process [23]. The new rural collective economy has obvious marketability and community-focused characteristics [24]. Driven by the market attributes of the new rural collective economy, the revitalization of rural industries will concentrate dispersed rural resources to form scale effects, maximize the potential value of various production resources, carry out market competition through the participation mechanism of rural inhabitants and rural inhabitants, reduce the vulnerability of small rural inhabitants’ production to the rapid changes in market demand, and stimulate the endogenous power of rural areas to meet the development needs of rural inhabitants in order to achieve common prosperity. At the same time, the new rural collective economy emphasizes the foundation of its rural collective ownership, clarifies the subject status and property rights of rural inhabitants, and reflects the community’s character [23]. The community nature of the new rural collective economy requires that most of its operating income be used to construct rural infrastructure, public welfare undertakings, and public services; provide members with education, culture, health, sports, and elderly care services; support the service work of villagers’ committees; form social welfare services for villagers; effectively improve the quality of life of collective economic members; and meet the needs of the people to give them a better life. It reflects the shared demand of rural inhabitants for common prosperity [23]. It can be seen that the new rural collective economic model is conducive to promoting the revitalization of rural industries, enhancing the economic vitality of rural areas, promoting the income growth and social status of rural inhabitants, and meeting the development needs and sharing needs of rural inhabitants with the aim of achieving. common prosperity. Based on this, this paper proposes the following hypothesis.

2.3. A Threshold Effect for the Coordinated Development of Efficient Government and Effective Market

To achieve common prosperity for all people, we must strike a balance between efficiency and equity and give play to the “two-wheel drive” role of effective market and efficient government [25]. Under the background that China’s market mechanism is not yet perfect and the development momentum of rural subjects is limited, deepening the mechanism of “effective market + efficient government” has become the main mode and distinctive feature of the revitalization of rural industries and promoting the common prosperity of rural inhabitants. During rural industry revitalization, enhancing regional marketization promotes rational allocation and free circulation of production factors. The free-competition market mechanism, via market prices and supply–demand laws, ensures orderly flow and efficient allocation in rural factor markets. It also stimulates the economic vitality of production factors in primary distribution, generating wealth for the rural industrial economy and laying a solid material foundation for rural common prosperity. However, the lack of supervision of the market mechanism has obvious blind spots and convenience characteristics, which may widen the urban–rural income gap and rural income gap, leading to social wealth distribution disorder, and thus forming the “Matthew effect”, which relates to the realization of common prosperity. The “Lukas Paradox” holds that capital flow is negatively correlated with the rate of return on capital; that is, regional capital flow tends to flow to urban areas rather than rural areas with high marginal returns. Peng X H and Shi Q H (2012) verified this by using Chinese urban and rural data and held that the “Lukas paradox” exists widely in the context of urban and rural capital flow in China [26]. Macroeconomic regulation for the government has an important inhibitory effect on the “Lucas paradox” of cross-regional capital flow in our country [27]. Positioning the government’s “visible hand” overcomes market mechanism flaws. It corrects initial distribution, promotes rural growth, and addresses “market failure” through institutional, macro-control, and supervisory functions. The specific result is that the preferential tax policy dominates the redistribution of social wealth and guides the third distribution, promotes the equalization of basic public services in urban and rural areas, and benefits transfer payments to low-income groups in rural areas to ensure stability while achieving common prosperity [28]. Thus, it effectively addresses the problem of unbalanced and inadequate rural development and guarantees social fairness and justice. However, government governance may also breed local irrational game, which is highlighted by the negative effects of land function alienation, bottom-to-bottom competition of environmental regulation strategies, and excessive debt behavior, which are serious obstacles to the realistic process of common prosperity [25]. Evidently, rural industry revitalization demands an effective market and coordinated government efforts, acting as a “two-wheel drive”. The market should play a decisive role in enhancing rural production efficiency and resource allocation. Meanwhile, the government, via its supervision system, must ensure fair wealth distribution and a healthy, efficiency- and fairness-oriented market environment. Within the framework of deepening the integration of an effective market and an efficient government, the market fuels rural economic growth, laying an economic groundwork for common prosperity in the initial distribution. The government, by optimizing the wealth-distribution system, safeguards rural residents’ share in social wealth, which is essential for rural common prosperity.

Based on the aforementioned theoretical review, this paper proposes the following hypotheses:

H1:

The revitalization of rural industries can significantly promote rural inhabitants’ common prosperity.

H2:

Based on the perspective of efficiency reform, the revitalization of rural industries promotes the common prosperity of rural inhabitants by improving agricultural labor productivity.

H3:

The revitalization of rural industries can be achieved through encouraging agriculture-related technological innovation, based on the perspective of impetus reform to promote rural inhabitants’ common prosperity.

H4:

The new rural collective economy has a positive regulating effect on the mechanism of rural industrial prosperity, which in turn benefits rural inhabitants’ common prosperity.

H5:

There is a threshold effect between the effective market and the efficient government in promoting the revitalization of rural industries and the common prosperity of rural inhabitants.

3. Research Design and Data Explanation

3.1. Variable Selection and Data Explanation

1.

Dependent variable: common prosperity of rural inhabitants (RGF). Based on the definition of common prosperity proposed by Yang H (2021) [29], this study constructs an index evaluation system for the common prosperity level of rural inhabitants from 14 indicators from three dimensions: prosperity, common degree, and sustainability. The specific indicators are shown in

Table 1. Design an index system for the common prosperity of rural inhabitants and the revitalization of rural industries.

Criterion Layer	Primary Index	Secondary Index
Common prosperity of rural inhabitants	Affluence	Farmer income level
		Farmer consumption level
		Rural medical level
		Rural social security
		Rural education culture
	Communality	Infrastructure support
		Ecological environment
		Urban–rural income gap
		Urban–rural consumption gap
		Farmer urbanization
	Sustainability	Digital finance development level
		Level of financial support for agriculture
		Agricultural science and technology activities
The revitalization of rural industries	Agricultural output increase	Total mechanical power per mu
		Grain yield per mu
		Agricultural production environment detection level
	Agricultural efficiency improvement	Number of agricultural science and technology activities personnel
		Land productivity
	Agricultural industrial chain extension	Crop diversification
		The proportion of agricultural products processing industry

. Based on the index system, the entropy method calculates the development level of rural inhabitants and rural common prosperity in each province from 2012 to 2023. Using the data measurement in this paper, it is found that the development level of common prosperity of rural inhabitants in China is constantly improving. Figure 1 is a chart showing the trend of the common prosperity of rural inhabitants from 2012 to 2023. The green scattered points represent the actual data for each year, with fluctuations. The red straight line is the trend line, indicating an overall upward trend.

2.

Independent variable: the revitalization of rural industries (RIR). Agriculture is the foundation of a country and the foundation of a strong nation. This study suggests that the fundamental task of the revitalization of rural industries is to drive the high-quality development of rural agriculture to consolidate the foundation of a strong agricultural country in the new era. Therefore, this study refers to the analysis and explanation of the connotation of the revitalization of rural industries by Tian T et al. (2022) [30]. The development of rural industrial revitalization was measured based on three aspects: agricultural output increase, agricultural efficiency improvement, and agricultural industrial chain extension, and was calculated using the entropy method. Specific indicators are shown in Table 1; further detailed explanations can be found in Appendix A.

3.

Mediating variables: the revitalization of rural industries promotes rural quality reform with efficiency reform and impetus reform and drives common prosperity of rural inhabitants. In light of this, this paper draws on the research results of Ren B P et al. (2022) [31] and Wang R F (2023) [32] to measure efficiency change and impetus reform. (1) Efficiency change: Agricultural labor productivity (the added value of agricultural industry/the number of employees in regional primary industry) is taken as the substitute variable of rural efficiency reform, reflecting the allocation of agricultural resource factors and the level of agricultural competitiveness. (2) Momentum: After standardization, the number of authorized agricultural patent applications in the region (number of authorized patent applications × added value of the primary industry/gross regional product) is taken as the substitute variable for the impetus reform of rural agricultural science and technology innovation to reflect the activeness and regional innovation ability of regional agricultural science and technology innovation.

4.

Adjustment variable: the development of the new rural collective economy (CE). This study collected the number of rural inhabitants’ cooperatives and leading agricultural enterprises in each province through the database of China agriculture-related enterprises of Carter-Enterprise Research Institute of Zhejiang University. The total number of farm cooperatives and leading enterprises was taken as a natural logarithm to quantify the development level of the new rural collective economy in the region.

5.

Threshold variable: (1) Efficient government. Promoting economic growth, achieving full employment, stabilizing prices, and maintaining the balance of international payments are the four major objectives of government macro-control. This study draws on the efficient government indicators proposed by Li Yao et al. [33]. It combines the four macro-control objectives with the entropy method to measure the regional efficient government construction level. Specifically, the regional economic growth is expressed by the regional real GDP after the base period of 2012. The inflation rate of the current year is calculated by the Consumer Price Index of rural residents (2012 as the base period); The level of full employment is expressed as the regional unemployment rate. The balance of international payments is expressed as the ratio of the number of goods exported from the region to the amount of goods imported and exported after being converted into RMB units according to the average exchange rate of US dollars in the current year. In the process of measurement, the three-year rolling standard deviation of the above four dimensions is also included in the government measurement index system to reflect the relative fluctuation of indicator data. (2) Effective Market: In this study, the marketization process index calculated by Wang Xiaolu et al. (2019) [34] is used to represent the construction level of regional effective markets. The index measures the changes in the marketization process from five sub-dimensions, including the relationship between government and market, the development of a non-state-owned economy, the development of factor markets, the development of product markets, the development of market intermediary organizations, and the legal system environment. It can perfectly reflect the marketization degree of each province and city, so it is reasonable to take it as the proxy variable of the effective market.

To ensure the reliability of the baseline regression results, the following control variables were added to this study: (1) the upgrading of industrial structure (UIS), which was represented by the proportion of the added value of the tertiary industry and the added value of the secondary industry; (2) education investment level (Edu), which is measured by the proportion of regional financial education expenditure to general budget expenditure; (3) the level of economic development (PGDP), expressed as the gross domestic product per capita of the region according to the natural logarithm; (4) communication service level (COM), represented by the number of mobile phones per 100 people; (5) the level of openness to the outside world, represented by the proportion of the total volume of imports and exports of goods in the gross regional product; (6) agricultural industrial structure (AIS), expressed as the proportion of the added value of the primary industry to the gross regional product.

3.2. Data Sources and Descriptive Statistics

To ensure the availability and continuity of the overall data, this study takes the agricultural- and rural-related data of 31 provinces, with the exception of Hong Kong, Macao, and Taiwan, from 2012 to 2023 as the research object. The relevant data are derived from the China Statistical Yearbook, China Rural Statistical Yearbook, China Grain Statistical Yearbook, China Meteorological Yearbook, the Zhejiang Carter-Enterprise Research China Agriculture-related Enterprises Database, the Digital Financial Inclusion Index [35] compiled by the Digital Finance Research Center of Peking University, and the Statistical Bulletin of local national economic and social development. Given the missing data for certain years in some regions, the linear interpolation method was used to make reasonable additions. In subsequent studies, the variables used were uniformly processed by 1% up-down tail shrinkage to reduce the influence of outliers and improve the reliability and stability of the data. There are 372 observed values, and the descriptive statistics of each variable are shown in

Table 2. Descriptive statistics of variables.

Variable	Mean	Standard Deviation	Min	Max
RGF	0.24	0.09	0.08	0.52
RIR	0.21	0.10	0.08	0.51
Momentum	0.16	0.18	0.00	1.00
Efficiency	3.59	1.88	0.95	10.72
Gov	0.51	0.12	0.14	0.71
Market	8.16	2.26	0.84	12.73
UIS	1.33	0.73	0.58	5.17
Edu	16.18	2.79	10.54	21.61
PGDP	10.97	0.44	10.04	12.12
COM	106.37	24.32	62.10	186.70
Open	0.26	0.27	0.01	1.25
AIS	9.51	5.04	0.23	23.40

.

3.3. Model Setting

To verify H1 above, the impact of the revitalization of rural industries on the common prosperity of rural inhabitants, the following baseline regression model is constructed:

$$RG{F}_{it}={\alpha }_0+{\alpha }_{1}RI{R}_{it}+{\Gamma }_1{X}_{it}+{\mu }_i+{\nu }_t+{\epsilon }_{it}$$

(1)

where $RG{F}_{it}$ represents the common prosperity of rural inhabitants in year t of the i region. $RI{R}_{it}$ represents the revitalization level of rural industries in year t of the i region. $X_{it}$ represents the control variable matrix, $\Gamma$ represents the regression coefficient of the control variable matrix, ${\mu }_i$ is the individual fixed effect, ${\nu }_t$ is the time fixed effect, and ${\epsilon }_{it}$ is the random disturbance term and the same below.

Based on the baseline regression results, in order to prove H2 and H3, the mechanism of efficiency change and impetus reform as the intermediate variables of rural industrial revitalization affecting the common prosperity of rural inhabitants is investigated. Based on the mediating effect model proposed by Jiang C (2022) [36], the regression model of the core explanatory variable on the intermediary variable is constructed as follows:

$$M_{it}={\beta }_0+{\beta }_{1}RI{R}_{it}+{\Gamma }_2{X}_{it}+{\mu }_i+{\nu }_t+{\epsilon }_{it}$$

(2)

where $M_{it}$ represents the intermediate variable.

After verifying the intermediate effects of efficiency and impetus reform, this study builds a moderated mediation model to test H4. It explores how the new rural collective economy moderates rural industry revitalization’s impact on rural common prosperity and its moderating role in the transmission path.

$$RG{F}_{it}={\lambda }_0+{\lambda }_{1}RI{R}_{it}+{\lambda }_{2}C{E}_{it}+{\lambda }_3(RI{R}_{it}\times C{E}_{it})+{\Gamma }_3{X}_{it}+{\mu }_i+{\nu }_t+{\epsilon }_{it}$$

(3)

$$M_{it}=b_0+b_{1}RI{R}_{it}+b_{2}C{E}_{it}+b_3(C{E}_{it}\times RI{R}_{it})+{\Gamma }_4{X}_{it}+{\mu }_i+{\nu }_t+{\epsilon }_{it}$$

(4)

$$RG{F}_{it}=c_0+c_{1}RI{R}_{it}+c_{2}C{E}_{it}+c_3(RI{R}_{it}\times C{E}_{it})+c_4{M}_{it}+c_5(M_{it}\times C{E}_{it})+{\Gamma }_5{X}_{it}+{\mu }_i+{\nu }_t+{\epsilon }_{it}$$

(5)

where $C{E}_{it}$ represents the development of the new rural collective economy.

Finally, this paper constructs a panel threshold model to empirically verify its internal mechanism to prove H5 and further reveal the nonlinear effect of the synergistic effect of an effective market and an efficient government on the relationship between the revitalization of rural industries and the common prosperity of rural inhabitants. A threshold value is assumed here, and a single or multi-threshold model is selected based on the threshold test results.

$$RG{F}_{it}={\theta }_0+{\theta }_{1}RI{R}_{it}\times (D_{it}\le {\eta }_1)+{\theta }_{2}RI{R}_{it}\times (D_{it}>{\eta }_1)+{\Gamma }_6{X}_{it}+{\mu }_i+{\nu }_t+{\epsilon }_{it}$$

(6)

where $D_{it}$ represents the coupling coordination degree of the threshold variable of effective market and efficient government.

4. Analysis of Empirical Results

4.1. Baseline Regression

The Hausman test showed that the double fixed-effect model for subsequent regression analysis was more appropriate.

Table 3. Baseline regression result.

Variables	RGF
	(1)	(2)	(3)	(4)
RIR	0.6714 ***	0.4054 ***	0.5097 ***	0.3482 ***
	(20.159)	(9.318)	(14.711)	(7.427)
UIS			−0.0107 *	0.0038
			(−1.825)	(0.516)
Edu			0.0055 ***	−0.0002
			(5.186)	(−0.191)
PGDP			0.0910 ***	−0.0138
			(6.745)	(−1.138)
COM			0.0010 ***	0.0002
			(3.904)	(1.112)
Open			−0.1089 ***	−0.0564 **
			(−6.642)	(−2.152)
AIS			0.0019 **	−0.0031 ***
			(2.186)	(−3.644)
Constant term	0.1011 ***	0.1563 ***	−1.0346 ***	0.3441 **
	(14.443)	(17.283)	(−7.966)	(2.550)
Time fixed-effect	NO	YES	NO	YES
Individual fixation effect	NO	YES	NO	YES
Observed value	372	372	372	372
R2	0.530	0.972	0.705	0.974

Note: ***, **, and * are significant at the level of 1%, 5% and 10%, respectively. The t value is in parentheses, using robust standard error. And the same applied below.

shows the regression results of the revitalization of rural industries on the development of common prosperity of rural inhabitants. Columns (1) and (3) are the regression results of the least squares method (OLS), and columns (2) and (4) are the regression results of the bidirectional fixed-effects model (FE). It can be seen that regardless of whether control variables are added, the regression results of the two models show that the revitalization of rural industries has a positive promoting effect on the common prosperity of rural inhabitants, indicating that promoting the revitalization of rural industries can significantly improve the development of common prosperity among rural inhabitants. According to the regression results in column (4), every 1-unit increase in the RIR will drive the RGF to increase by 0.3482 units; thus, hypothesis 1 is verified. The reason is that with the continuous improvement of the revitalization of rural industries, the agricultural industrial organization system has been continuously optimized, effectively driving the extension of the agricultural industrial chain and promoting the deep integration of the primary, secondary, and tertiary industries, which is conducive to rural inhabitants’ production and income increase. Meanwhile, the equalization of basic social public services and the continuous improvement of digital infrastructure have gradually broken down the barriers to the two-way circulation of urban and rural elements. Thus, the realization of common prosperity of rural inhabitants takes place, consistent with Tang R.W’s views [1].

4.2. Robustness Test

1.

Replace the measurement method of variables. This paper changes the index construction method to eliminate inaccurate benchmark regression results that may be caused by bias in calculating the revitalization of rural industries and rural inhabitants’ common prosperity index. It uses principal component analysis to recalculate the development levels of the revitalization of rural industries and rural inhabitants’ and rural common prosperity index for regression. Specific results are shown in columns (1) and (2) in

Table 4. Robustness test.

	Replace the Explained Variable	Replace the Core Explanatory Variable	One-Phase Lag	Control Exogenous Factors	Add a Residual Term
Variables	(1)	(2)	(3)	(4)	(5)
RIR	0.9677 ***			0.2898 ***	0.3840 *
	(4.24)			(6.18)	(1.66)
RIR1		0.0185 **
		(2.01)
L.RIR			0.3474 ***
			(6.17)
Institutional environment				YES
Economic factor				YES
Residual term					YES
Constant term	−1.1384 *	0.1333	0.3772 ***	0.1012	−0.2969 *
	(−1.81)	(0.97)	(2.63)	(0.78)	(−1.82)
Control variable	YES	YES	YES	YES	YES
Time fixed-effect	YES	YES	YES	YES	YES
Individual fixation effect	YES	YES	YES	YES	YES
Observed value	372	372	341	341	248
R2	0.984	0.970	0.976	0.981	0.983

Note: ***, **, and * are significant at the level of 1%, 5% and 10%, respectively. The t value is in parentheses, using robust standard error.

. The results show that the baseline regression result is still significantly positive after changing the measurement method, which further supports the establishment of hypothesis 1.

2.

Endogenous processing: Although the bidirectional fixed-effect model can alleviate the endogenous problem to a certain extent, the following endogenous issues may still exist.

(1)

Measurement error: The lag effect of the revitalization of rural industries may not be considered in the benchmark regression, resulting in measurement error. The revitalization of rural industries lag covers one period, acting as the core explanatory variable for regression. The specific results are shown in column 3 of Table 4.

(2)

Missing variables; that is, failing to include economic factors or regional institutional environmental factors that may affect the revitalization of rural industries and the common prosperity of rural inhabitants into the regression equation, resulting in endogenous problems. It is necessary to control the regional institutional environment and economic factors that may affect the revitalization of rural industries and incorporate them into the regression model for re-regression (The regional institutional environment factors are reflected by the frequency of use of the words “rural revitalization, common prosperity, the revitalization of rural industries, farmers’ income increase, farmers’ prosperity, and industry prosperity” in the annual government work reports of each province and city from 2012 to 2023. The breadth economic factor is reflected in the Digital Financial Inclusion Index released by the Digital Finance Research Center of Peking University). The specific results are shown in column 4 of Table 4.

(3)

Reverse causality: In the process of realizing common prosperity in rural areas, it will stimulate the endogenous power of rural industries, accelerate the integration of rural industries, complement the advantages of various industrial organizations, and enable rural industries to develop appropriately according to local conditions, thus enabling the revitalization of rural industries. Rural entrepreneurial activities can produce a significant depression effect on the vertical extension and horizontal expansion of industries [37,38]. In this paper, to exclude the influence of the entrepreneurial activity of farmers, referring to the method of Tan Xiaofen et al. (2024) [39], we substituted the residual term obtained by the regression of the entrepreneurial activity of rural inhabitants to the revitalization of rural industries as the control variable into the benchmark regression. (The entrepreneurial activity of rural households is represented by the ratio of the number of rural individuals employed to the number of people comprising the rural population). The specific results are shown in column 5 of Table 4.

The results show that the regression coefficient for the revitalization of rural industries remains significantly positive, indicating that this study’s results are robust.

Finally, based on the practices of Bartik (2009) [40], Duan W Q and Jing G Z (2021) [41], two instrumental variables for the revitalization of rural industries were constructed. First, the intersection term of the annual average precipitation of each province and city and the regional agricultural output value of the year were used as instrumental variables for the revitalization and development of rural industries in each province and city. Regional average annual precipitation, as a natural climate condition, has an important impact on agricultural production, while agricultural output value reflects the economic achievements of rural industry. The product of the two is directly related to the development of rural industry and is closely related to the revitalization and development of rural industry, meeting the correlation requirements. Precipitation, as a variable determined by natural factors, has no direct impact on developing common prosperity in rural areas. Therefore, the product of natural climate conditions and economic output as an instrumental variable has certain externalities. The second step is to add the Bartik instrumental variable of the revitalization of rural industries, which is equal to the cross-multiplication term of the first-order difference between the level of the revitalization of rural industries with a lag of one stage and the time dimension at the national level. As the development level of rural industry after first-order difference comes from 31 provinces and cities, its change trend is unaffected by a single province or city. Therefore, the development and development of rural industry at the national level is relatively exogenous to the common prosperity of rural inhabitants, and the revitalization of rural industries that lag by one stage has a certain correlation with the revitalization and development of rural industry in the current period. Therefore, this variable satisfies the requirements of correlation and externality. Based on the above instrumental variables, the two-stage least squares method (2SLS) was used for estimation, and the results are shown in

Table 5. Results of two-stage regression of instrumental variables.

Variables	IV1		IV2		IV1 + IV2
	(1)	(2)	(3)	(4)	(5)	(6)
	RGF	RIR	RGF	RIR	RGF	RIR
RIR	0.7948 ***		0.3039 ***		0.3684 ***
	(3.09)		(4.55)		(5.18)
IV1		0.0028 ***				0.0022 **
		(3.17)				(2.33)
IV2				2.7880 ***		2.6707 ***
				(8.02)		(7.84)
LM statistics	9.449 ***		11.000 ***		16.542 ***
Wald F statistic	22.931		102.862		63.200
	[16.38]		[16.38]		[19.93]
Hansen J statistic	Equation exactly identified				2.058
					(p = 0.1514)
Control variable	YES	YES	YES	YES	YES	YES
Time fixed-effect	YES	YES	YES	YES	YES	YES
Individual fixation effect	YES	YES	YES	YES	YES	YES
Observed value	372	372	341	341	341	341

Note: The threshold value for the weak instrumental variable test at the 10% significance level is shown in square brackets. And ***, **, and * are significant at the level of 1%, 5% and 10%, respectively. The t value is in parentheses, using robust standard error.

. In the first stage, whether it is a single instrumental variable or a combination of instrumental variables, its coefficient is significantly positive, and the results of the unidentifiable test, weak instrumental variable test, and overidentification test indicate that the selection of instrumental variables is reasonable. It can be seen from the regression results of the second stage that after considering the endogenous problem, the coefficients of the revitalization of rural industries (RIRs) are significantly positive at the level of 1%, which proves that the baseline regression results in this paper are robust.

4.3. Heterogeneity Analysis

• Based on regional grain production and marketing characteristics, the samples were divided into two major agricultural functional areas: main grain-producing areas and non-grain-producing areas (including main sales areas and balanced production and marketing areas), and the impact of the revitalization of rural industries in different agricultural functional areas on the common prosperity of rural inhabitants was analyzed. The regression results are shown in columns (1) and (2) of

  Table 6. Heterogeneity analysis.

  Variables	Regional Function Division		Time Interval Division		Economic Development Division
  	Major Grain-Producing Areas	Non-Major Grain-Producing Areas	2012–2016	2017–2023	Low Economic Level	High Economic Level
  	(1)	(2)	(3)	(4)	(5)	(6)
  RIR	0.428 ***	0.392 ***	0.0373	0.349 ***	0.171 ***	0.34 9***
  	(7.70)	(7.12)	(0.35)	(7.22)	(3.13)	(5.08)
  Constant term	0.810 ***	−0.190	−0.251	0.723 ***	−0.162	0.749 ***
  	(4.50)	(−1.40)	(−1.14)	(4.52)	(−1.28)	(3.08)
  Empirical p-value	0.036		−0.312 **		−0.178 *
  	(p = 0.399)		(p= 0.015)		(p= 0.084)
  Control variable	YES	YES	YES	YES	YES	YES
  Time fixed-effect	YES	YES	YES	YES	YES	YES
  Individual fixation effect	YES	YES	YES	YES	YES	YES
  Observed value	216	156	155	217	228	144
  R2	0.973	0.990	0.989	0.989	0.982	0.981

  Note: The empirical p-value is obtained by sampling Fisher’s combined test 1000 times. And ***, **, and * are significant at the level of 1%, 5% and 10%, respectively. The t value is in parentheses, using robust standard error.

  . Whether it is a major grain-producing area or a non-major grain-producing area, the revitalization of rural industries will promote the common prosperity of rural inhabitants. This paper uses the Fisher combination method to test the differences between the regression coefficients. The results show that the differences between the groups do not pass the significance test, indicating that the division of agricultural functions does not affect the revitalization of rural industries and its effect on promoting common prosperity. At the same time, it also reflects that the revitalization of rural industries strategy has the universality to promote the common prosperity of all regions in the country, helps to solve the problem of unbalanced and inadequate rural development, and is an important foundation for realizing the common prosperity of rural inhabitants.
• Characteristics based on time stage. The specific goals, processes, and corresponding policies and measures to be achieved for the development of common prosperity are different in each time stage, and these factors may have other impacts on the revitalization of rural industries on the common prosperity of rural inhabitants. The report to the 19th CPC National Congress pointed out that “the period from the 19th to the 20th CPC National Congress is the historical confluence of the two centenary goals, the decisive stage in building a moderately prosperous society in all respects, and the crucial period for socialism with Chinese characteristics to enter a new era”. This paper takes the 19th National Congress of the Communist Party of China as the demarcation point to analyze the time-stage heterogeneity. The results of columns (3) and (4) in Table 6 show that rural industrial revitalization had a significant positive impact on rural common prosperity during 2017–2023, and its regression coefficient passes the inter-group coefficient difference test. This shows that since the 19th National Congress, the role of the revitalization of rural industries in promoting the common prosperity of rural inhabitants has gradually emerged, indicating that since the 19th National Congress, due to the coordination and cooperation between the central top-level design and local governments, China’s rural undertakings have realized the historic shift from poverty alleviation to rural revitalization, and the policy dividend has been gradually released. Therefore, based on building a well-off society in an all-round way, the revitalization of rural industries can significantly promote the common prosperity of rural inhabitants.
• Based on the characteristics of economic development level, in this study, the median GDP per capita of each province was selected as the classification standard, and the research samples were divided into two groups: low level of economic development and high level of economic development. Then, the differing impacts of rural industrial revitalization on promoting the common prosperity of rural inhabitants under different standards of economic development level were discussed. The results are shown in columns (5) and (6) of Table 6. The results show that the regression coefficients of the two methods pass the Fischer combination test, and the common prosperity effect of the revitalization of rural industries is stronger in areas with a higher economic development level. A possible explanation for this is that areas with a higher economic development level often have perfect infrastructure conditions, which are conducive to rapidly breaking down the barriers of urban and rural factors and driving the connection between human capital and scientific and technological input and the revitalization of rural industries. Therefore, such areas have a first-mover advantage in promoting the revitalization of rural industries, and the common prosperity effect is more obvious.

4.4. Mechanism Analysis

4.4.1. Mediating Effect

The above benchmark regression verifies that the revitalization of rural industries affects the common prosperity of rural inhabitants, but what is the operating mechanism behind it? To answer this, it is necessary to further explore the path of the revitalization of rural industries to promote the common prosperity of rural inhabitants, and this paper will clarify the internal mechanism. According to the above theoretical analysis, the revitalization of rural industries can promote the common prosperity of rural inhabitants from the perspective of efficiency reform and impetus reform by improving labor productivity and promoting agriculture-related technological innovation. Based on this, this paper verifies the above research hypothesis concerning the constructed intermediary effect model (2), and the regression results are shown in columns (1) and (3) of

Table 7. Mediated regression results.

Variables	Efficiency		Momentum		RGF
	(1)	(2)	(3)	(4)	(5)	(6)	(7)
RIR	7.8468 ***	5.4829 ***	0.9497 ***	0.6966 ***	0.2520 ***	0.2177 ***	0.1650 ***
	(3.90)	(2.75)	(4.04)	(2.81)	(5.71)	(5.38)	(3.78)
Efficiency						0.0051 ***
						(3.63)
Momentum							0.1058 ***
							(5.67)
CE		−1.1903 ***		0.0275	−0.0234***	−0.0153 **	−0.0283 ***
		(−4.61)		(1.02)	(−4.06)	(−2.46)	(−5.26)
RIR×CE		3.5776 ***		0.5382 ***	0.1705 ***	0.1397 ***	0.1582 ***
		(4.39)		(4.26)	(7.23)	(6.26)	(6.28)
Efficiency×CE						0.0018 **
						(2.32)
Momentum×CE							−0.0489 ***
							(−3.37)
Control variable	YES	YES	YES	YES	YES	YES	YES
Time fixed-effect	YES	YES	YES	YES	YES	YES	YES
Individual fixation effect	YES	YES	YES	YES	YES	YES	YES
Constant term	3.6492	2.6347	2.9360 ***	1.5667 **	0.0997	0.0848	−0.0624
	(0.59)	(0.46)	(4.18)	(2.51)	(0.83)	(0.73)	(−0.57)
Observed value	372	372	372	372	372	372	372
R2	0.911	0.924	0.867	0.884	0.980	0.981	0.982

Note: ***, **, and * are significant at the level of 1%, 5% and 10%, respectively. The t value is in parentheses, using robust standard error.

. The results show that the regression coefficient of the revitalization of rural industries on labor productivity and agriculture-related technological innovation is significantly positive at the 1% level, indicating that the revitalization of rural industries is based on efficiency reform, takes impetus reform as the main line, improves labor productivity in rural areas, promotes agriculture-related technological innovation, and promotes common prosperity of rural inhabitants. In the cause of the revitalization of rural industries, we must firmly grasp the main tone of “efficiency change, impetus reform to promote quality change” and steadily promote common prosperity. Accordingly, H2 and H3 are assumed to be true.

4.4.2. Moderated Mediation Effect

After verifying the mediating effect of efficiency and impetus reform, this paper further discusses the regulating impact of new rural collective economic development. It conducts regression analysis on Equations (3), (4), and (5), respectively.

Three interactive terms (collective economic development level and the revitalization of rural industries, collective economic development level and efficiency change, collective economic development level and impetus reform) are included in the regression model. In Table 7, the regression results (2), (4), and (5) to (7) are based on efficiency reform, impetus reform, and common prosperity of rural inhabitants as dependent variables and the new rural collective economy as moderating variables, respectively.

First, this paper tests whether the revitalization of rural industries and the common prosperity of rural inhabitants are affected by the development of the new rural collective economy. The results are shown in column (5), where the regression coefficient is 0.1705 and is significant at the 1% level, indicating that the development of the new rural collective economy can significantly enhance the rural common prosperity effect of the revitalization of rural industries. It plays a positive regulating role between the two constructs, and therefore, H4 is verified. In the second step, this paper regards the intermediary variable as the dependent variable. It examines whether the regulating variable has a regulating effect on the efficiency change and the impetus reform. The results are shown in columns (2) and (4). It can be seen that the new rural collective economy can significantly strengthen the promoting effect of rural industry revitalization on efficiency reform and impetus reform in rural areas. Furthermore, two interaction terms, efficiency reform and new collective economy, and dynamic reform and new collective economy, are added to the regression model to investigate whether the new rural collective economy will affect the intermediary variables and thus have an effect on the common prosperity of rural inhabitants.

The specific results are shown in columns (6) and (7). The results show that the interaction terms between the efficiency reform and the new collective economy are significantly positive, indicating that the development of the new rural collective economy has a positive moderating effect on the efficiency reform to promote the common prosperity of rural areas, indicating that the development of the new collective economy can effectively improve the labor productivity of rural areas, provide a material guarantee to increase rural inhabitants’ income, and help with the realization of the common prosperity of rural areas. The interaction term between the impetus reform and the new collective economy is significantly negative, indicating that the new rural collective economy has a negative regulating effect on the relationship between the rural industrial revitalization and the common prosperity of rural inhabitants. A possible reason for this is that it is difficult to carry out large-scale management in the development of a rural collective economy in the present stage due to the insufficient allocation efficiency of production factors such as talent and capital. As a result, the endogenous growth impetus of rural areas is inadequate, which limits the technological development space and competitiveness of the new collective economy, and thus is not conducive to the technological innovation and development of rural areas, which is consistent with the research conclusion of Wen F G (2024) [42]. Therefore, it is necessary to speed up the removal of barriers to the circulation of urban and rural factors, release new collective economic momentum, and promote the healthy development of the new rural collective economy.

5. Further Analysis: Can the Revitalization of Rural Industries Under the Framework of Efficient Government and Effective Market Strike a Balance Between Efficiency and Equity?

President Xi Jinping emphasized at the opening ceremony of the seminar at the 20th National Congress of the Communist Party of China: “We must not only create higher efficiency than capitalism, but also more effectively safeguard social equity, and better realize the balance, promotion, and unification of efficiency and equity”. Historical experience shows that the relationship between efficiency and equity has always been a major issue for Chinese modernization. The construction of an income distribution system that considers both efficiency and fairness need to be based on the market promoting efficiency and ensuring fairness through government regulation and guidance of redistribution and the third distribution to achieve mutual promotion and common development among regions. Then, at the present stage, it must be determined whether China’s rural industry revitalization can guarantee the balance of efficiency and fairness in the framework of effective market and efficient government to promote the common prosperity of rural inhabitants; that is, whether the revitalization of rural industries can reach the rich level of increasing rural inhabitants’ disposable income, achieve the common goal of narrowing the income gap between urban and rural populations, and maintain sustainability. Further, compared with the framework of a single role, is it more conducive to deepening the multidimensional development of the revitalization of rural industries at this stage to promote the coupling and coordination of effective markets and efficient government? To answer these questions, this paper uses the panel threshold regression model to verify the possible nonlinear relationship between the single role of the government, the effective market, and the effect of their collaborative development framework on the common prosperity of rural inhabitants in the revitalization of rural industries. Specifically, this paper divides the common prosperity of rural inhabitants into three levels, namely the rich level, the common level, and the sustainable level. It includes them in the above regression model in Equation (6), considering the empowering effect of the revitalization of rural industries on the three levels in the framework of “efficient government–effective market” (The per capita disposable income of rural residents after standardized processing is used as a measure of the affluent class. The ratio of per capita disposable income of urban residents and per capita disposable income of rural residents was selected to measure the common layer. Since the sustainability level is a comprehensive concept, this paper takes the sustainability index system in the common prosperity for rural inhabitants as the benchmark and uses the entropy method to quantify the analysis).

5.1. Threshold Effect Test

Before the threshold regression model is estimated, the concrete form of the threshold model is determined. This paper adopts the specific form of the panel threshold model based on 300 self-sampling, and the results are shown in

Table 8. Threshold effect test results.

Threshold Variable	Dependent Variable	Model	F-Value	p-Value	BS Degree	1% Critical Value	5% Critical Value	10% Critical Value
Efficient government	RGF	Single Threshold	102.81 ***	0.000	300	26.39	17.06	14.01
		Double Threshold	37.18 ***	0.000	300	19.70	15.85	11.73
	Affluent tier	Single Threshold	43.42 **	0.017	300	47.78	31.39	24.93
	Common tier	Single Threshold	35.60 **	0.023	300	45.48	29.45	24.15
	Sustained tier	Single Threshold	125.28 ***	0.000	300	32.87	18.44	15.29
		Double Threshold	45.21 **	0.030	300	117.46	17.91	12.42
Effective market	RGF	Single Threshold	185.83 ***	0.000	300	43.55	29.20	24.36
		Double Threshold	48.65 ***	0.000	300	36.49	25.53	21.01
	Affluent tier	Single Threshold	123.91 ***	0.000	300	66.89	43.79	37.68
	Common tier	No Threshold	10.83	0.640	300	39.36	28.94	25.72
	Sustained tier	Single Threshold	143.45 ***	0.000	300	43.27	31.32	25.70
		Double Threshold	66.89 ***	0.000	300	34.90	25.55	20.94
The coupling coordination degree of “efficient government–effective market”	RGF	Single Threshold	152.88 ***	0.000	300	44.94	25.62	21.18
		Double Threshold	57.76 ***	0.000	300	33.58	20.58	16.84
	Affluent tier	Single Threshold	81.44 ***	0.000	300	51.18	41.37	31.64
		Double Threshold	25.48 **	0.043	300	34.62	25.59	19.73
	Common tier	Single Threshold	54.50 ***	0.003	300	46.92	33.85	25.53
	Sustained tier	Single Threshold	160.14 ***	0.000	300	32.20	25.99	20.18
		Double Threshold	53.69 ***	0.000	300	32.45	23.77	17.06

Note: ***, **, and * are significant at the level of 1%, 5% and 10%, respectively. The t value is in parentheses, using robust standard error.

. It can be seen that while that the p-value of the common layer when the effective market is the threshold variable is 0.640, which fails the significance test, the other threshold test results all show the existence of the threshold effect, so it is necessary to use threshold regression to clarify the nonlinear relationship among them.

5.2. Threshold Regression Analysis

5.2.1. Efficient Government

The panel threshold regression model is used to deeply explore the nonlinear effect of the revitalization of rural industries on the common prosperity of rural inhabitants, and the results are shown in

Table 9. Threshold model regression results.

Threshold Variable	Dimensionality	Variable	Coefficient Estimates	F-Value
Efficient government	RGF	RIR (Gov ≤ 0.5037)	0.1028 ** (2.13)	66.55 ***
		RIR (0.5037 < Gov ≤ 0.6608)	0.1861 *** (3.96)
		RIR (0.6608 < Gov)	0.3444 *** (7.28)
	Affluent tier	RIR (Gov ≤ 0.6458)	0.0282 (0.24)	25.72 ***
		RIR (0.6458 < Gov)	0.2680 ** (2.19)
	Common tier	RIR (Gov ≤ 0.3848)	−0.1980 (−0.97)	172.17 ***
		RIR (0.3848 < Gov)	−0.6328 *** (−3.33)
	Sustained tier	RIR (Gov≤ 0.6242)	0.3551 *** (3.52)	23.32 ***
		RIR (0.6242 < Gov ≤ 0.6866)	0.5697 *** (5.32)
		RIR (0.6866 < Gov)	0.8621 *** (8.46)
Effective market	RGF	RIR (Market ≤ 8.6300)	−0.0166 (−0.36)	80.44 ***
		RIR (8.6300 < Market ≤ 11.1040)	0.0936 ** (2.11)
		RIR (11.1040 < Market)	0.2692 *** (6.31)
	Affluent tier	RIR (Market ≤ 11.1040)	−0.2255 ** (−1.99)	27.93 ***
		RIR (11.1040 < Market)	0.1218 (1.12)
	Common tier	-	-	-
	Sustained tier	RIR (Market≤ 8.6300)	0.0096 (0.09)	24.09 ***
		RIR (8.6300 < Market ≤ 11.1040)	0.2951 *** (3.00)
		RIR (11.1040 < Market)	0.6382 *** (6.73)
Coupling coordination	RGF	RIR (D ≤ 0.8421)	0.0669 (1.48)	76.79 ***
		RIR (0.8421 < D ≤ 0.9502)	0.1623 *** (3.62)
		RIR (0.9502 < D)	0.3382 *** (7.66)
	Affluent tier	RIR (D ≤ 0.8605)	−0.1438 (−1.26)	28.27 ***
		RIR (0.8605 < D ≤ 0.9208)	0.0109 (0.09)
		RIR (0.9208 < D)	0.2673 ** (2.36)
	Common tier	RIR (D ≤ 0.7423)	−0.2564 (−1.33)	165.54 ***
		RIR (0.7423 < D)	−0.7304 *** (−3.92)
	Sustained tier	RIR (D ≤ 0.8257)	0.2081 ** (2.13)	23.26 ***
		RIR (0.8257 < D ≤ 0.9502)	0.4268 *** (4.37)
		RIR (0.9502 < D)	0.8106 *** (8.45)
Control variable	YES
Observed value	372

Note: The coefficients correspond to t values in parentheses in the column of coefficient estimates. And ***, **, and * are significant at the level of 1%, 5% and 10%, respectively. The t value is in parentheses, using robust standard error.

. According to the results, when the progressive deepening development of the government level crosses the corresponding threshold, the revitalization of rural industries significantly affects the common prosperity of rural inhabitants, affecting the rich, common, and sustainable layers. Specifically, with the deep penetration of the government level, the common prosperity effect of the revitalization of rural industries gradually increases from 0.1028 to 0.3444 and passed the significance level of 1%. From different levels, the gradually enhanced level of efficient government leads the revitalization of rural industries to effectively promote an increase in rural residents’ income and narrow the urban–rural income gap, sustaining its positive effect. Thus, in the context of the weakening of the primary distribution equity led by the market mechanism due to the short-sightedness and profit seeking of the market, an efficient government can effectively overcome the inherent defects of the market economy through macro-control and improve the stability and sustainability of economic growth in rural areas in the process of the revitalization of rural industries. When it comes to wealth distribution, institutional arrangements, policy incentives, and other means lead rural redistribution and guide the third distribution, ensure social fairness and justice in the process of common prosperity in rural areas, and provide necessary support for the social distribution of common prosperity in rural areas.

5.2.2. Effective Market

As can be seen from the regression results in Table 9, as far as the overall regression is concerned, when the effective market is less than the threshold value of 8.6300, the regression coefficient of the revitalization of rural industries does not pass the significance level. When the effective market is between the first threshold value of 8.6300 and the second threshold value of 11.1040, and after crossing the second threshold value, the regression coefficient of the revitalization of rural industries does not pass the significance level. Its regression coefficient rises to 0.2692 and passes the 1% significance test, which indicates that in the framework of continuous cultivation of an effective market, the promoting effect of the revitalization of rural industries on the common prosperity of rural inhabitants is gradually enhanced, which indicates that the effective market effectively guarantees the orderly flow and efficient allocation of production factors in the rural market and improves the labor efficiency in rural areas. It has laid a good foundation for the common prosperity of rural inhabitants. However, from the perspective of different levels, when the effective market is less than the threshold value of 11.1040, it has a significant inhibitory effect on the rich layer of common prosperity. At the same time, the regression coefficient of the revitalization of rural industries becomes insignificant after crossing the threshold value. The effective market has no significant effect on the common level of the revitalization of rural industries. Its impact on the revitalization of rural industries promoting rural inhabitants’ common prosperity is mainly achieved by strengthening the promoting effect on a continuous level. A possible explanation is that the decisive role of the market has not achieved its full potential at this stage, and the market of production factors presents an obvious dual structure. Different degrees of local protection and regional segmentation exist in many links, such as production, circulation, and pricing, resulting in limited efficient and reasonable allocation of production factors [25]. The decisive role of the market alone will lead to the problem of “market failure”. The single role of the market players cannot achieve the Pareto-optimal allocation of social resources, but may cause the urban–rural income gap to be too large and form the “Matthew effect”. Therefore, to achieve common prosperity among rural inhabitants, it is necessary to clarify the responsibilities and boundaries of the government and the market in the revitalization of rural industries.

5.2.3. Coupling and Coordination Between Efficient Government and Effective Markets

According to the above theoretical analysis, the coordinated development of an efficient government and an effective market can ensure the revitalization of rural industries and promote the common prosperity of rural inhabitants. In order to verify whether the coordinated development of efficient government and effective market is consistent with the above theoretical analysis, this paper establishes the coupling coordination degree model of “efficient government–effective market” by referring to the coupling concept of physics. The model is as follows:

$$C=\sqrt{(U_1\times U_2)/{({\displaystyle \frac{U_1+U_2}{2}})}^2}$$

(7)

$$\left\{\begin{array}{l}D=\sqrt{C\times T}\\ T=\alpha U_1+\beta U_2\end{array}\right.$$

(8)

where C is the coupling degree between efficient government and effective market; U₁ and U₂ respectively represent the level of efficient government and the level of effective market development; T is the comprehensive coordination index of the two; $\alpha$ and $\beta$ are undetermined coefficients; and the constraint condition is $\alpha +\beta =1$, indicating the corresponding weight of an efficient government and an effective market. This paper gives equal weight to both, according to the common practice of the existing literature: $\alpha =\beta =0.5$. On this basis, the coupling coordination degree D represents the coordinated development degree of the interface between efficient government and the effective market. In this paper, is coupling coordination degree was incorporated into the threshold regression model as a threshold variable for regression analysis, and the regression results are shown in Table 9.

According to the regression results, when the coupling coordination degree of “efficient government–effective market” is less than the first threshold value of 0.8421 from the overall perspective, the empowering effect of the revitalization of rural industries on the common prosperity of rural inhabitants has not yet appeared. With the deepening of the coordinated development degree between the government and the market, the empowering effect of the revitalization of rural industries began to appear and gradually increased. When the coupling coordination degree exceeded the second threshold value of 0.9502, the regression coefficient of the revitalization of rural industries on the common prosperity of rural inhabitants was significantly positive, and with the deepening of the coordinated development of the government and the market, its “two-wheel effect” has been fully brought into play: the effective market has played a decisive role in liberating rural social productivity and improving the efficiency of market operation, providing a continuous driving force for the material basis of common prosperity. By improving the social security system and transfer payment, an efficient government has effectively narrowed the gap between urban and rural inhabitants and created a fair and just social environment for the realization of the common prosperity of rural inhabitants. These findings are consistent with the research and analysis of Li N and Wang J C (2022) [25]. In this context, the rural common prosperity effect of the revitalization of rural industries has been further released, verifying the establishment of hypothesis H5; that is, giving full play to the synergistic effect of “efficient government–effective market”, which can enhance the impact of the revitalization of rural industries on rural inhabitants’ rural common prosperity. From different perspectives, compared with the framework of effective market and the single role of government, the coupling and coordinated development of the two can not only ensure the stable growth of rural residents’ income at the rich level and drive the improvement of rural production efficiency, but can also narrow the urban–rural income gap at the common level and overcome the problem of unbalanced economic development caused by market mechanism failure. It can ensure the realization of social equity, strengthen the enabling role of the revitalization of rural industries at a sustained level, and provide necessary support for the common prosperity of rural inhabitants. Therefore, this paper holds that under the coordinated development framework of “efficient government–effective market”, the revitalization of rural industries can consider both efficiency and fairness and steadily promote the realization of common prosperity of rural inhabitants.

6. Conclusions and Suggestions

Based on the panel data of 31 provinces in China from 2012 to 2023, this study empirically tested the impact of the revitalization of rural industries on the common prosperity of rural inhabitants and determined its mechanism. It systematically analyzed the regulatory role of the new rural collective economy and the threshold effect of the efficient government and effective market. Our research draws the following conclusions: First, the revitalization of rural industries significantly promotes the common prosperity of rural inhabitants, and this conclusion remained robust after strict robustness tests and endogeneity treatment. Second, the revitalization of rural industries mainly promotes the common prosperity of rural inhabitants through improving labor productivity and promoting agriculture-related technological innovation, respectively, from the two paths of efficiency reform and impetus reform. Developing the new rural collective economy has a positive regulating effect on the common prosperity under efficiency reform. In contrast, it negatively regulates the common prosperity under the path of impetus reform. Third, from the perspective of regional functional heterogeneity, there is no significant difference in the positive impact of the revitalization of rural industries on the common prosperity of rural inhabitants in major grain-producing areas and non-major grain-producing regions. From the perspective of time stage heterogeneity and economic development-level heterogeneity, the promoting effect of the revitalization of rural industries on common prosperity was more significant in the wake of the 19th National Congress of the Communist Party of China. The promoting effect on the common prosperity of rural inhabitants in the provinces and cities with high economic development level is stronger. Fourthly, the impact of the revitalization of rural industries on the common prosperity of rural inhabitants presents a threshold effect based on the coupling coordination of “efficient government–effective market”. With the deepening of the coupling coordination degree, the positive impact of the revitalization of rural industries on the common prosperity of rural inhabitants is further strengthened, and the relationship between efficiency and equity can be effectively handled.

Based on the dual-path analysis framework of “efficiency transformation—impetus transformation”, this study systematically reveals the micro-mechanism of rural industry prosperity to promote farmers’ common prosperity and provides three supplementary aspects to the existing research. First, it expands the research dimension of the effect of rural industry prosperity, and for the first time, it empirically verifies the dual path effect of improving labor productivity (efficiency reform) and driving agricultural technological innovation (impetus reform), deepening the theoretical cognition of the current academic circle on the synergistic mechanism of “efficiency–equity” for common prosperity [6,7]. Second, it enriches the research perspective of the new rural collective economy and empirically finds its positive regulatory effect on the efficiency reform path and negative regulatory impact on the impetus reform path by using the data from the provincial perspective, providing new evidence for understanding the complex functions of China’s collective economic organizations [24,25]. Thirdly, it innovatively introduces the coupling coordination degree of “efficient government–effective market” in new structural economics as the threshold variable of this paper, reveals its nonlinear strengthening effect on industrial prosperity, and provides an institutional analysis framework for solving the imbalance of urban and rural factor allocation.

Based on the findings above, the following policy recommendations are proposed:

Firstly, construct a modern agricultural industrial system to stimulate the endogenous driving force of rural areas. Local governments should capitalize on regional resource endowments, develop distinctive agricultural industrial clusters through differentiated strategies, and empower the entire agricultural production chain with digital technology to transition from traditional agriculture to smart agriculture. Efforts should focus on overcoming technological bottlenecks in agricultural product processing, extending the agricultural industrial chain, and establishing an integrated operational system encompassing “production + processing + sales” to enhance the added value of agriculture. Research indicates that improvements in labor productivity and technological innovation are the core pathways to promoting common prosperity. Establishing a precise alignment mechanism of “technology demand—research and development—application” is essential to expedite the transformation of scientific and technological achievements into actual productive forces.

Secondly, deepen the reform of China’s new rural collective economy and refine the interest connection mechanism. Promote the reform of collective property rights, clarify the market entity status of collective economic organizations, and explore diversified distribution models such as “minimum income + dividend by shares”. In response to the negative regulatory effect of the collective economy on technological innovation pathways identified in the research, it is recommended that local governments take the lead in establishing a collaborative innovation platform integrating “collective economic organizations + university research institutions + leading enterprises”, thereby enhancing their technological absorption capacity through mechanisms like technology equity and talent sharing. Simultaneously, increase financial support by setting up a dedicated fund to develop the collective economy to overcome financing constraints and talent bottlenecks.

Thirdly, innovate the collaborative governance model between the government and the market and optimize institutional supply. Establish a dynamic coupling mechanism characterized by an “efficient government–effective market”: in regions with underdeveloped markets, reinforce the government’s leading role in infrastructure construction and factor market cultivation; in areas with well-established market mechanisms, implement the “negative list + credit supervision” model to fully unleash market vitality. Studies demonstrate that when the coupling coordination degree between the government and the market surpasses a specific threshold, the effect of industrial prosperity significantly improves. Therefore, it is necessary to establish a coupling coordination degree evaluation system, promote institutional innovation in phases, and form a new paradigm of rural revitalization marked by “government guidance–market dominance–social coordination”.