Does the National Key Ecological Function Zones Policy Promote Leapfrog Development in Urban–Rural Integration?

Abstract

Integrated urban–rural development is an inevitable requirement of regional development. Developing green industries based on rural ecological resources are important approaches to promoting urban–rural integration. The National Key Ecological Function Zones (NKEFZ) policy focuses on safeguarding national ecological security. However, whether the resulting ecological improvements can, through the realization of ecological value, provide momentum for urban–rural integration remains unclear in existing research. This study uses a sample of 284 prefecture-level cities in China from 2006 to 2023, treating the establishment of NKEFZ as a quasi-natural experiment. First, the study constructs a “Driving-constraining” bidirectional theoretical framework, and then uses the entropy weight method to measure the level of urban–rural integration, which is selected by 18 sub-indicators from the populational, spatial, and economic dimensions. Finally, a multi-period difference-in-differences (DID) model is constructed to test the impact of NKEFZ on urban–rural integration, and the transmission mechanisms and heterogeneity are explored. The results indicate the following: (1) Following the implementation of the NKEFZ policy, it shows an overall inhibitory trend on urban–rural integration, consequently slowing the progress of urban–rural integration. The inhibitory effects are particularly pronounced in spatial and economic integration dimensions, and these results are robust. (2) Constrained industrial upgrading and increased fiscal pressure on local governments are the main mechanisms behind the slowed urban–rural integration. (3) Due to differences in policy coverage and the heterogeneous characteristics of city locations, the negative effects of the policy are more pronounced in cities with a high proportion of key ecological function counties, as well as in prefecture-level cities in central and western regions. Based on these findings, it is suggested to promote high-quality urban–rural integration in eco-priority areas through pathways such as developing ecological industries, improving the ecological compensation system, and clarifying central–local collaborative governance.

1. Introduction

Cities and rural areas form an interdependent, integrated, and mutually reinforcing community of life. From the counter-urbanization and rebalancing seen in developed countries to the over-urbanization and rural decline faced by developing nations, urban–rural integration is a major strategic issue that is currently confronting the world, especially developing countries. It is not only crucial for inclusive regional economic growth but also key to achieving social equity and improving people’s well-being. For developing countries like China, the deepening imbalance between urban and rural areas could potentially lead to political instability [1]. From the historical stages of development, urban–rural integration is an inevitable requirement once the urban–rural relationship reaches a certain stage of development and serves as an important pathway for optimizing resource allocation and achieving regional coordinated development. Fortunately, under the guidance of China’s new urbanization and rural revitalization strategies, urban and rural areas have experienced a trend from a “unidirectional flow” to a “bilateral interaction”, and from an “urban bias” to “urban–rural integration” [2]. A key point is that, in the evolution of urban–rural relations toward integration in China, the concepts such as “ecological priority” and “green development” define the value orientation of urban–rural development [3]. Especially under increasing ecological demands, rural ecological resources are increasingly playing a unique bridging role. According to ecosystem services theory, rural ecological resources have a high capacity to provide cultural service products, thereby enhancing the value of ecological resources [4]. Based on this, developing rural tourism serves as a key driver in advancing urban–rural integration [5,6]. Pristine ecological environments are a key asset for rural development [7], which could leverage the comparative advantages of rural areas [8] and enhance the attractiveness of rural areas within urban–rural integration, serving as critical leverage points for promoting technological flows, capital circulation, and talent exchanges between urban and rural areas through the supply of ecological products and spillover of environmental services. This, in turn, reshapes the logic of factor allocation and development across urban and rural areas, driving systemic transformation in urban–rural relations. Within the framework of Main Functional Area Planning, the implementation of the National Key Ecological Function Zones (NKEFZ) policy has significantly improved ecological conditions [9], objectively strengthening the resource base for ecological value conversion. In parallel, supporting mechanisms such as ecological transfer payments help improve basic public services in NKEFZ [10], providing a favorable external environment for urban–rural integration. Furthermore, the “Opinions of the Central Committee of the Communist Party of China and the State Council on Establishing and Improving the Urban–rural Integration Development System, Mechanism, and Policy Framework” emphasizes the need to establish incentives for urban talent to enter rural areas, improve fiscal investment guarantees, and promote industrial and commercial capital entry into rural areas—measures highly consistent with the development trajectory of NKEFZ. It is therefore evident that the effective utilization of rural ecological advantages, the development of NKEFZ, and the promotion of urban–rural integration converge toward the same goal. At the same time, it is important to note that NKEFZ are also subject to the rigid constraints of ecological protection, which include short-term limitations on economic activities. Pessoa points out in his research that, while the institutional framework for green transformation is good, green transformation is not feasible in economic development and may lead to the paradox of green transformation [11]. Therefore, under the dual influence of both driving forces and constraining forces, there will be a complex interaction mechanism and effects between the two, and the following question arises: can the implementation of the NKEFZ policy construct an “empowerment channel” for new urban–rural relations through the transmission chain of “ecological value enhancement—industrial transformation—functional leap”, thereby promoting leapfrog development of urban–rural integration on the basis of ecological protection? What is the theoretical logic linking the establishment of NKEFZ to urban–rural integration, and through what mechanisms does this operate? Addressing this question holds significant theoretical and practical value for ecological civilization construction and the development of an urban–rural integration paradigm that reconfigures the human–environment relationship.

2. Literature Review

Although the National Key Ecological Function Zones (NKEFZ) policy may provide opportunities for urban–rural integration, its primary objective is ecological protection and, on that basis, economic development. Consequently, current research on NKEFZ mainly focuses on the environmental and economic effects of the policy. Regarding environmental effects, ecological transfer payments in NKEFZ have been shown to promote ecological improvement [9]. Although the effectiveness of such improvements increases with the number of years of transfer payment allocation [9], if fiscal gaps are too large, local governments tend to allocate ecological transfer payments to improve livelihoods and promote economic development, thereby weakening the environmental effects [12]. Moreover, in the long run, the environmental incentives for ecological transfer payments from local governments weaken [13], and insufficient regulation by local governments may lead to deteriorating outcomes [14]. Beyond environmental aspects, the NKEFZ policy has been found to improve ecological quality while also promoting regional economic growth [15,16,17]. However, in the early stages of policy implementation, certain negative effects were observed, and the policy could not fully offset the adverse impacts of environmental regulation [18]. Existing research also shows that the impact of the NKEFZ policy on regional development is multifaceted.

In existing studies on urban–rural integration, including summarizing and analyzing the historical evolution of urban–rural relations in China [19], some scholars have analyzed the spatiotemporal patterns of urban–rural relations in China [20,21] by constructing an indicator system for measuring urban–rural integration development, and another by constructing a game theory model to predict the Nash equilibrium points of urban–rural integration development in China under different scenarios [22]. Thus, a clearer and more intuitive understanding of urban–rural integration is gained. The main driver of urban–rural integration development is economic growth [23], with the central cities in the region playing a crucial role in driving and radiating influence to surrounding counties and cities [24]. With the development of the information age, the digital economy has also played a role in promoting the coordination of urban–rural relations [25]. Ultimately, in terms of mechanisms promoting urban–rural integration, existing research indicates that two-way flows of urban and rural factors are central to constructing integrated urban–rural development [26].

Research on the impact of the NKEFZ policy on urban–rural integration remains limited. Some scholars have examined the policy’s effects on rural development, such as ecological compensation in NKEFZ, which, through mechanisms like expanded natural resource scale, diversified rural employment [27], transfer payment scale, and industrial upgrading [28], improving environmental productivity and increasing crop yields [29] can reduce poverty and narrow urban–rural income gaps [30]. Besides improving the income of rural residents, the policy can also enhance the level of basic public service provision [10,31], among other aspects, thereby partially reflecting the policy’s contribution to urban–rural integration. However, other studies have found that economic disparities between ecological and development zones under the main function zoning framework may further widen [32], suggesting that policy implementation may also exacerbate regional inequality. Some scholars also argue that ecological compensation policies may not necessarily contribute to poverty reduction for farmers [33]. Therefore, the overall effect of NKEFZ on urban–rural integration therefore remains an open question, requiring further investigation.

In summary, previous research has mostly focused on the impact of policies on single dimensions such as ecology, economy, poverty, and income disparity, with little attention paid to how the ‘hard constraint’ of ecological protection policies in NKEFZ affects the broader, more comprehensive process of urban–rural integration. The role of these policies in urban–rural integration is a complex, two-way process. However, existing research has not thoroughly examined this complex mechanism of action and is limited in mechanism and heterogeneity analysis using multi-period DID. This study focuses on the effects of NKEFZ policies on urban–rural integration. First, a theoretical analytical framework of “Driving-Constraining” is constructed to elucidate the mechanisms through which the policy influences urban–rural integration. Second, a comprehensive evaluation index of urban–rural integration is developed from three dimensions—population, spatial, and economic—and a multi-period DID model is employed to examine the policy’s effects, transmission mechanisms, and heterogeneous impacts. Finally, policy optimization directions for promoting urban–rural integration in NKEFZ are proposed. The marginal contributions of this study are threefold. First, it integrates the NKEFZ policy and urban–rural integration into a unified analytical framework, and the proposed “Driving-Constraining” mechanism enriches the theoretical system of urban–rural integration under policy influence. Second, it empirically tests the effects and mechanisms of NKEFZ policies on urban–rural integration, providing new evidence for policy-driven urban–rural integration. Third, it reveals the heterogeneous characteristics of policy effects, offering a reference for differentiated policy design to further promote urban–rural integration. By combining theoretical analysis with empirical research, this study aims to further optimize the development pathways of NKEFZ and provide new insights for advancing urban–rural integration in ecologically prioritized regions.

3. Policy Background

China’s National Key Ecological Function Zones (NKEFZ) policy is a crucial institutional arrangement within the national spatial governance system, aimed at ecological protection and coordinated regional development, and serves as an important measure to advance ecological civilization construction in China. In December 2010, the State Council of China issued the Notice on the Main Functional Area Planning, which, for the first time at the national level, proposed dividing the country’s territory into four major function zones—optimized development zones, key development zones, restricted development zones, and prohibited development zones—based on regional ecological carrying capacity, resource and environmental conditions, and development potential. This division aimed to form a coordinated spatial development pattern in population, economy, and resources-environment, accelerate the transformation of economic development modes, and promote long-term stable and rapid economic growth and social harmony. In September 2016, the State Council’s Approval on Adding Certain Counties (Cities, Districts, and Banners) to the National Key Ecological Function Zones expanded the list of NKEFZ, incorporating additional counties and further enlarging the spatial scope of these zones (Figure 1).

As an important component of restricted development zones, NKEFZ are designated as key areas for ensuring national and regional ecological security. Their main functions include maintaining the stability and integrity of ecosystems, providing critical ecological services such as water conservation, soil preservation, and biodiversity maintenance. These zones are primarily located in Southwest China, South China, Northeast China, and Northwest China. Typically, these regions have weaker economic foundations and relatively underdeveloped infrastructure, but they possess diverse ecosystems and prominent ecological functions. By delineating ecological protection red lines, defining prohibited development areas, and enhancing ecological compensation mechanisms, a spatial control system centered on ecological protection has been established. On one hand, the scientific demarcation of ecological function zone boundaries clarifies ecological protection objectives and constraints, strengthens ecological spatial restrictions, and emphasizes the stability and sustainability of the ecological security pattern. On the other hand, policy support facilitates the transformation of development models within these zones, including ecological compensation, support for green industries, and guidance of population migration, thereby promoting a balance between ecological protection and livelihood improvement to a certain extent. In particular, the establishment of ecological compensation systems provides economic incentives for residents in NKEFZ to participate in ecological protection, alleviating the conflict between ecological conservation and economic returns, and providing institutional support for public service provision and urban–rural development. Since its implementation, NKEFZ have played an important role in safeguarding national ecological security, with ecological benefits such as water conservation, carbon sequestration, and biodiversity protection continuing to increase. At the same time, ecological compensation transfer payments from the central government often fail to meet all the development needs of the regions. NKEFZ continue to face significant fiscal pressure in terms of cultivating ecological industries and local green transformation. Due to significant differences in regional development foundations, levels of urban–rural integration remain highly heterogeneous. Some NKEFZ still face challenges including population outflow, insufficient infrastructure, and limited public service provision, which in turn partially constrain urban–rural integration development.

4. Theoretical Analysis and Research Hypotheses

The implementation of the National Key Ecological Function Zones (NKEFZ) policy exerts both positive and negative effects on urban–rural integration. Therefore, this study analyzes the policy’s impacts based on a the dual-dynamic of driving and constraining forces. The bidirectional mechanism through which NKEFZ influence urban–rural integration is illustrated in Figure 2.

4.1. The Driving Force of the NKEFZ Policy on Urban–Rural Integration

The holistic implementation of NKEFZ on the basis of ecological protection establishes a robust institutional framework that catalyzing urban–rural integration, promoting the flow of various factors from urban to rural areas and strengthening interactive integration between urban and rural regions.

From the industrial cultivation dimension:

First, the cultivation of ecological industry systems provides a endogenous impetus for urban–rural integration. The increase in ecological resources in NKEFZ, resulting from ecological protection, forms a supportive space that enhances the attractiveness of rural areas in urban–rural factor interactions [34], thereby promoting the development of rural ecological industries. Developing ecological industries is an strategic pathway for high-quality, leapfrog development in NKEFZ [35], and the realization of ecological product value constitutes the pivotal mechanism for the monetization of ecosystem services, further promoting urban–rural integration [36]. Second, industrial restructuring optimizes factor allocation. In the context of emerging rural industries, new industrial organizations extend and expand traditional industrial structures vertically and horizontally. By promoting non-agricultural employment and diversifying employment forms for rural residents, labor productivity and income are improved, driving technological progress and management innovation. This enhances the accumulation of various factors for urban–rural integration, creating possibilities for bidirectional empowerment and organic integration of urban and rural actors. Third, the synergistic development paradigm of the ecological value chain fosters integration. The cross-regional connectivity of ecological industries, through market-oriented operation of ecological products, optimizes the spatial reconfiguration of production factors. With the expansion of ecological product consumption markets and the resulting momentum, urban and rural areas establish new economic linkages based on ecological value exchange. Functional synergy and spatial interdependence becomes the core driving force of urban–rural integration, forming a coordinated development pattern based on the division of labor along the ecological value chain and promoting integration across economic, cultural, social, political, and spatial dimensions.

From the perspective of government ecological transfer payments:

First, ecological transfer payments internalize ecological externalities to foster endogenous urban–rural integration. These payments convert the positive externalities of ecological services into economic value. By tapping the implicit value of rural ecological resources, rural areas transform from “value lowlands” to active providers of ecological services, reversing the one-way flow of urban–rural factors. The cyclical transformation and reproduction of ecological resources require complementary input from urban–rural factors, thereby forming a mutually beneficial and sustainable endogenous cycle. Second, ecological transfer payments promote the improvement of rural public services [31]. The allocation of special ecological transfer funds effectively enhances basic public services in rural areas, improving their livability and development prospects. This offsets the siphoning effect of urban areas on rural factors and creates initial conditions for bidirectional factor flows, establishing an urban–rural development community through public service linkages. Third, ecological transfer payments facilitate the interconnection of infrastructure. Investment in infrastructure in NKEFZ mitigates spatial friction and temporal constraints between urban and rural areas, reducing the transaction costs of factor flows and objectively accelerating the bidirectional movement of labor, capital, and technology. Infrastructure is the most important factor influencing the transformation of urban–rural structure [37]. In the process of realizing the value of rural ecological products, infrastructure construction also serves as a converter connecting the stock of ecological resources with urban consumption demand.

4.2. The Constraining Force of the NKEFZ Policy on Urban–Rural Integration

The tension between stringent ecological constraints and economic development during policy implementation constitutes the systemic impediments affecting urban–rural factor flows, industrial coordination, and fiscal support systems.

From the industrial constraints dimension:

First, a weak industrial foundation precludes optimal factor agglomeration. Due to natural conditions, many NKEFZ are dominated by traditional agriculture and resource-based industries, characterized by homogenized industrial structure, short industrial chains, and low value-added capacity. Under the policy, the supporting industrial infrastructure and existing market maturity cannot sustain the agglomeration of modern production factors. High-level factors find it difficult to flow effectively between urban and rural areas, hindering industrial coordination and limiting development space. Second, government regulatory resistance to industrial transformation arises. Industrialization is generally a driving force for social structural transformation, but NKEFZ policies inhibit industrial expansion, especially industries contributing to air pollution [38]. Under ecological protection pressures, industrial restructuring proceeds slowly, making it difficult to undertake functions such as industrial transfer and population agglomeration. The policy’s negative list for industrial access exacerbates local industrial transformation difficulties [39], constraining economic development. Even local enterprises are unable to expand at scale due to the constraints of ecological protection [40]. Furthermore, green industries, due to long investment return cycles, low marketization, and incomplete supply–demand channels, require a mature industrial development stage to realize scale effects. Third, there is a risk of ecological industry homogenization. While ecological industries are high-value-added, the excessive path dependency on specific ecological resource exploitation, coupled with insufficient interaction among industries of different types and levels, may lead to regional industrial imbalance, intensified competition, weakened industrial resilience, and reduced risk resistance, thereby affecting the stability of the economic system underlying urban–rural integration.

From the perspective of government fiscal pressure:

First, there is a crowding-out effect on productive investment. NKEFZ possess both richness and fragility in ecological resources. Policy priorities allocate resources to ecological compensation and environmental governance, requiring substantial short-term financial inputs to achieve policy goals. This creates explicit constraints on local economic development opportunities, forming a “policy-induced spatial segmentation.” Second, ecological transfer payments may be insufficient. Ecological compensation mechanisms are crucial for resolving the conflict between ecological protection and economic development, but in the early stages of ecological industrialization, local fiscal expenditures remain a key driver of regional development [16]. In many NKEFZ, ecological compensation transfers are biased toward subsistence-oriented fiscal outlays [41], which cannot effectively offset the opportunity costs of development in ecologically protected areas. Third, the endogenous momentum for fiscal revenue growth is insufficient. Prolonged reliance on exogenous fiscal injections partially substitutes for regional economic endogenous growth mechanisms, leading to a dependency in fiscal revenue structures and weakening local governments’ fiscal autonomy. Moreover, rural areas often lack strong resource absorption capacity and effective endogenous development models, further limiting fiscal revenue growth and hindering the formation of sustainable mechanisms necessary for urban–rural integration.

Based on the above theoretical analysis, the following competing research hypotheses are proposed:

Hypothesis 1a.

The driving force of the NKEFZ policy on urban–rural integration outweighs its inhibiting force, resulting in a significant promoting effect.

Hypothesis 1b.

The inhibiting force of the NKEFZ policy on urban–rural integration outweighs its driving force, resulting in a significant slowing effect.

Furthermore, the impact of the NKEFZ policy on local development can be summarized into two dimensions: industrial development and government fiscal pressure. Accordingly, the following hypotheses are proposed:

Hypothesis 2.

The NKEFZ policy influences urban–rural integration by affecting local industrial structure transformation.

Hypothesis 3.

The NKEFZ policy influences urban–rural integration by affecting local government fiscal pressure.

5. Research Design, Variables, and Data

5.1. Model Specification

This study treats the establishment of the National Key Ecological Function Zones (NKEFZ) as a quasi-natural experiment. Given that the NKEFZ were designated in two batches, a multi-period difference-in-differences (DID) model is employed for estimation. Within the framework of the main functional zones planning, the policy implementation targets are at the county level, considering that the primary drivers of urban–rural integration are central cities with large population agglomerations, and the movement of factors such as labor and capital at the county level is often directed toward the core areas of prefecture-level cities, either as a destination or a transit point. Viewing the entire prefecture-level city as a functional area allows for a more accurate assessment of the level of urban–rural integration development. Additionally, the administrative boundaries of prefecture-level cities are relatively stable, and in statistical data, prefecture-level cities provide complete time series data with comparability. Following the approach of Hou et al. [17], the spatial unit is set at the prefecture-level city. Prefecture-level administrative regions containing counties designated as NKEFZ are assigned to the treatment group, while the remaining prefecture-level cities form the control group. The baseline regression model is constructed as follows:

$$ur{i}_{it}={\beta }_0+{\beta }_{1}di{d}_{it}+{\displaystyle \sum _{j=1}^n{\beta }_j}Contro{l}_{ it}+{\mu }_i+{\delta }_t+{\epsilon }_{it}$$

(1)

In the model, i and t represent region and year, respectively. The dependent variable uri_it denotes the level of urban–rural integration. The core explanatory variable did_it is a binary policy indicator for the NKEFZ. It takes a value of 1 if, in year t, region i contains one or more counties designated as NKEFZ, and remains 1 in all subsequent years; otherwise, it takes a value of 0. Control_it represents a set of control variables μ_i and δ_t denote region and time fixed effects, respectively. ε_it is the error term. β₀, β₁ and β_j are the parameters to be estimated.

5.2. Variable Selection

5.2.1. Dependent Variable: Level of Urban–Rural Integration Development

The essence of urban–rural integration lies in the free flow and efficient allocation of urban–rural factors, breaking the dualistic urban–rural structure. Based on systems theory, this study divides urban–rural integration into three interrelated dimensions: population integration, spatial integration, and economic integration, forming a theoretical framework and constructing a comprehensive evaluation index system for urban–rural integration, thereby providing theoretical support for the scientificity and rationality of the indicators.

First, population is the core factor and driving force of urban–rural integration. The restructuring of urban–rural relations is prominently reflected in changes in population mobility patterns. Population agglomeration and flow affect the spatial distribution of labor and the direction of resource allocation. The urbanization rate reflects the extent of population concentration in cities and serves as a fundamental indicator for measuring urban–rural population structure transformation and labor allocation optimization. A higher urbanization rate increases per capita resource availability in rural areas, enhancing benefits for both urban and rural populations. Urban–rural employment levels indicate the integration of labor markets and reflect the smoothness and balance of labor factor flows. Wage levels reveal disparities in labor remuneration and productivity, serving as important measures of economic integration and social equity. Coverage of social security for urban and rural residents reflects the equalization of social protection systems, providing the institutional foundation for population social integration. Population density indicates spatial distribution and carrying capacity, offering a basis for optimizing regional development layout. The population integration dimension embodies a people-centered new urbanization concept, emphasizing equality in economic opportunities and social welfare for urban and rural residents.

Second, the spatial dimension constitutes the material foundation and implementation carrier of urban–rural integration. Spatial integration is not limited to geographic proximity but also includes connectivity in information, transportation, logistics networks, as well as sharing of environmental, public service, and living spaces. The degree of product flow measures the level of material circulation and market integration, reflecting the spatial efficiency of factor exchanges. Information communication and digitalization levels indicate the development of communication and information infrastructure, serving as key drivers for efficient allocation of spatial and economic factors. Road accessibility and postal network development represent the completeness of transportation and logistics systems, providing essential support for urban–rural connectivity and regional integration. The supply level of urban and rural environments reflects the balanced development of ecological and living spaces and the coordination of public space provision. The spatial integration dimension emphasizes the transition from “spatial segregation” to “spatial interconnection”, requiring optimization and interconnectivity of spatial structures for urban–rural integration.

Finally, the economic dimension represents the ultimate manifestation and core goal of urban–rural integration. The fundamental purpose of integration is to achieve coordinated economic development and optimized resource allocation between urban and rural areas. Economic integration reflects the interaction among production factors, industrial structure, income levels, and public finance between urban and rural areas, serving as a concentrated measure of urban–rural integration effectiveness. Per capita GDP reflects regional economic development and overall performance of urban–rural production activities. Differences in budget expenditure and the ratio of urban-to-rural budget revenue and expenditure measure the balance of the government’s public financial resource allocation, reflecting the degree of institutional integration. Urban–rural income disparities indicate the fairness of economic outcomes, serving as a core metric of economic integration. Development levels of the tertiary sector reflect industrial structure optimization and service industry linkage effects. Per capita household savings balances indicate wealth accumulation and consumption capacity, supporting stable economic development between urban and rural areas.

The three dimensions of population, spatial, and economic integration interact and reinforce each other, forming a systematic structure for urban–rural integration. Logically, they progress hierarchically and comprehensively reflect the dynamic process of urban–rural integration. This approach not only aligns with the intrinsic logic of urban–rural integration but also ensures the scientificity, completeness, and operability of the evaluation system. Based on existing studies [42,43,44] and considering data availability and representativeness, the comprehensive indicator system for urban–rural integration is presented in

Table 1. Comprehensive evaluation index system for urban–rural integration development.

Composite Indicator	First-Level Indicator	Second-Level Indicator	Explanation	Unit	Direction
Comprehensive Evaluation Indicators for Urban- Rural Integration	Population Integration	Urbanization Rate	Urban Population/Resident Population	%	+
		Urban–rural Employment Level	Employed Population in Municipal Districts/Total Employed Population	%	−
		Wage Level	Average Wage of Employed Workers	CNY	+
		Coverage Rate of Social Security for Urban and Rural Residents	Number of Basic Pension Insurance Participants/Resident Population	%	+
			Unemployment Insurance Coverage/Resident Population	%	+
		Population Density	Resident Population/Land Area of Administrative Region	People per Square Kilometer	+
	Spatial Integration	Degree of Product Mobility	Total Road Freight Volume/Total Domestic Road Mileage	Ten Thousand Tons per Kilometer	+
		Degree of Information Communication	Telecommunication Revenue/Resident Population	CNY per Capita	+
		Degree of Digitalization	Number of Internet Users/Resident Population	Households per Ten Thousand People	+
		Road Accessibility	Total Domestic Road Mileage/Land Area of Administrative Region	Kilometers per Square Kilometer	+
		Degree of Postal Development	Total Postal Service Revenue/Resident Population	CNY per Capita	+
		Urban Environmental Supply Level	Green Coverage Rate	%	+
	Economic Integration	Per Capita GDP	GDP/Resident Population	CNY per Capita	+
		Urban–rural Budget Expenditure Gap	General Budget Expenditure of Municipal Districts/General Budget Expenditure of Administrative Regions	%	−
		Urban–rural Budget Revenue–Expenditure Ratio	General Budget Revenue of Municipal Districts/General Budget Revenue of Administrative Regions	%	−
		Urban–rural Income Gap	Urban Residents’ Disposable Income/Rural Residents’ Disposable Income	-	−
		Urban–rural Tertiary Industry Development	Tertiary Industry Output of Municipal Districts/Tertiary Industry Output of Administrative Regions	%	−
		Per Capita Year-End Savings Balance of Urban and Rural Residents	Year-End Savings Balance of Urban and Rural Residents/Total Population	CNY per Capita	+

. The entropy weight method is used to determine the weights of the indicators and to calculate the level of urban–rural integration.

5.2.2. Independent Variable

A binary dummy variable indicating the implementation of the National Key Ecological Function Zones (NKEFZ) policy. Prefecture-level cities that established Key Ecological Function Zones in both the first and second batches are classified as part of the first batch treatment group [17]. Since the first batch was established in December 2010, following the approach of Ding and Zhuang et al. [16], the policy shock for the first batch is set as 2011 and the second batch as 2016.

5.2.3. Control Variables

This study includes the following variables as controls: (1) Level of Economic Development: The degree of urban–rural integration is influenced by the scale of urban development. Larger cities typically exhibit stronger bidirectional flows of resources and factors between urban and rural areas, thereby fostering higher levels of integration. (2) Economic Vitality: Measured by the outstanding balance of institutional loans, economic vitality reflects financing capacity. A higher loan balance suggests greater access to credit, which supports rural economic development, enhances public services, and accelerates the urban–rural integration process. (3) Scale of Educational Expenditure: Increased investment in education improves rural educational infrastructure, narrows the urban–rural education gap, enhances human capital, strengthens employment capabilities, and contributes to social integration. (4) Scale of Science and Technology Expenditure: Investment in science and technology—particularly in rural technological infrastructure and smart services—facilitates the development of emerging industries, addresses bottlenecks in traditional agriculture, and improves rural productivity. (5) Per Capita Fiscal Expenditure: Higher levels of public fiscal spending enhance rural infrastructure and public services, improve the quality of life for rural residents, increase investment in agriculture and rural development, and support diversified development pathways.

5.2.4. Mechanism Variables

(1) Industrial Structure Upgrading: Given the significant policy interventions on the secondary industry within the NKEFZ, which complicate capturing the autonomous benefits of industrial restructuring, the ratio of tertiary industry output to GDP is used as a proxy for industrial structure upgrading. (2) Government Fiscal Pressure: Measured using the ratio of the difference between general budget expenditures and general budget revenues to GDP.

5.2.5. Covariates

To improve the precision of sample selection during the propensity score matching (PSM) process, in addition to all control variables, two covariates—annual average vegetation coverage and the share of primary industry in GDP—are incorporated into the regression model. These covariates, along with the control variables, are used to estimate the propensity scores, ensuring a more accurate matching process and mitigating potential selection bias.

5.3. Data Sources and Descriptive Statistics

The study sample comprises 284 prefecture-level cities in China from 2006 to 2023. Data were obtained from the annual editions of the China Urban Statistical Yearbook and the China Urban Construction Statistical Yearbook, as well as statistical yearbooks of respective provinces, municipalities, and autonomous regions, and the annual Statistical Communiqué on National Economic and Social Development. Missing data were supplemented using linear interpolation or estimated by calculating average growth rates. The list of National Key Ecological Function Zones was sourced from the Ministry of Ecology and Environment. NDVI data (Vegetation Coverage) were obtained from the China Regional 250 m Normalized Difference Vegetation Index dataset provided by the Qinghai–Tibet Plateau Scientific Data Center.

Descriptions of variables and their summary statistics are presented in

Table 2. Variable Definitions and Descriptive Statistics.

Variable Categories	Variable Name	Measurement Method	Variable Symbols	Mean	Standard Deviation	Minimum Value	Maximum Value
Dependent Variable	Urban–Rural Integration Development	Entropy Weight Method for Indicator System Calculation	uri	0.254	0.050	0.153	0.603
Independent Variable	Policy Variable	Whether It Includes Key Ecological Function Zones	did	0.253	0.435	0	1
Control Variable	Level of Economic Development	Logarithm of GDP	led	16.417	1.028	13.160	19.973
	Economic Vitality	Year-End Total Loans Balance of Financial Institutions/GDP	ev	1.001	0.642	0.027	12.817
	Scale of Education Expenditure	Education Expenditure/Fiscal Expenditure	see	0.180	0.042	0.015	0.408
	Scale of Science and Technology Expenditure	Technology Expenditure/Fiscal Expenditure	sste	0.015	0.016	0	0.178
	Per Capita Fiscal Expenditure	General Budget Expenditure/Resident Population	pcfe	0.822	0.605	0.058	11.665
Mechanism Variable	Industrial Structure Upgrading	Tertiary Sector Output/Primary Sector Output	isu	0.943	0.017	0.844	0.992
	Government Fiscal Pressure	(General Budget Expenditure − General Budget Revenue)/GDP	gfp	0.116	0.097	−0.002	0.521
Covariates	Vegetation Coverage	Statistical Division by Prefecture-Level Cities, Averaging Monthly Data	vc	0.502	0.140	0.067	0.765
	Share of Primary Industry	Primary Sector Output/GDP	spi	0.129	0.083	0.002	0.499

.

6. Empirical Results and Analysis

6.1. Analysis of Baseline Regression Results

Table 3. Baseline Regression Results.

Variable	(1)	(2)	(3)	(4)
	uri	pop	spa	eco
did	−0.005 *** (0.001)	−0.001 (0.002)	−0.006 *** (0.002)	−0.008 *** (0.002)
lngdp	0.012 *** (0.002)	0.008 ** (0.004)	0.013 *** (0.003)	0.016 *** (0.003)
act	0.003 * (0.002)	0.003 (0.002)	0.005 ** (0.002)	0.000 (0.002)
edu	0.067 *** (0.018)	0.099 *** (0.029)	0.052 ** (0.024)	0.050 ** (0.023)
sci	0.254 *** (0.047)	0.266 *** (0.081)	0.268 *** (0.066)	0.219 *** (0.048)
pfis	0.012 ** (0.005)	0.013 * (0.008)	0.005 ** (0.002)	0.019 *** (0.007)
Constant Term	0.029 (0.034)	0.016 (0.061)	−0.111 ** (0.044)	0.253 *** (0.050)
Fixed Effects by Region	YES	YES	YES	YES
Fixed Effects by Year	YES	YES	YES	YES
Observation	5112	5112	5112	5112
R2	0.960	0.965	0.826	0.923

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

presents the baseline regression results. Column (1) reports the estimated impact of the National Key Ecological Function Zones (NKEFZ) policy on the overall level of urban–rural integration development. After controlling for regional and time fixed effects as well as other control variables, the coefficient on the core explanatory variable (did) is −0.005, which is statistically significant at the 1% level and negative. This indicates that the driving force of the NKEFZ policy implementation has not fully offset its inhibitory effects, resulting in a net deceleration of urban–rural integration development during the sample period. Thus, the competitive research hypothesis 1b is supported. This is because the ‘constraints’ of ecological protection are immediate and rigid, directly affecting the flow of urban–rural integration factors. In contrast, the ‘promotion’ effects of integration are more indirect and soft, relying on factors such as the timely provision of compensation funds, the establishment of supporting mechanisms, and market-oriented operations. These conditions are often not fully met in the current context, which is why the inhibitory effects are more pronounced in the short and medium term.

Regarding control variables, improvements in economic development level (led), education expenditure scale (see), science and technology expenditure scale (sste), and per capita fiscal expenditure (pcfe), all of them significantly enhance the level of urban–rural integration, consistent with previous studies. Columns (2), (3), and (4) report regressions on subdimensions of urban–rural integration: population integration (pop), spatial integration (spa), and economic integration (eco), respectively. Results show that the NKEFZ policy significantly inhibits spatial and economic integration, while its effect on population integration is not statistically significant. This may be due to the existence of China’s household registration system (hukou system). Other Policies like the household registration (hukou) system create significant institutional barriers that often require a long period to overcome, meaning the effect of a specific regional policy like NKEFZ on population integration may not materialize within the limited time frame of our current observation. In terms of coefficient magnitude, the estimated effect on economic integration (−0.008) is greater than that on spatial integration (−0.006), indicating the strongest inhibitory impact of the policy on urban–rural economic integration. This may be because, compared to its impact on spatial integration, the implementation of the policy has the most direct, rigid, and strict effect on the economy in the short term.

6.2. Robustness Checks

6.2.1. Parallel Trend Test

Based on the Event Study Approach (ESA) in the previous studies [30], we select a time window of five years before and seven years after the policy implementation to specifically test whether there are significant differences between the treatment and control groups prior to the policy intervention. The model is specified as follows:

$$y_{it}=\alpha +{\displaystyle \sum _{j=-5}^6{\beta }_j\cdot di{d}_{i,t+j}}+{\displaystyle \sum _{j=1}^n{\beta }_j}Control+{\mu }_i+{\delta }_t+{\epsilon }_{it}$$

(2)

In the equation, did_i,t+j indicates whether city i is in the j-th year relative to the policy implementation year. It equals 1 if j ≥ 0 (denoting j years after implementation) or if j < 0 (denoting the j-th year prior to implementation), and 0 otherwise.

To avoid perfect multicollinearity, the fifth year before policy implementation was excluded. The test results, shown in Figure 3, indicate no significant differences between the treatment and control groups prior to the policy implementation, satisfying the parallel trend assumption required for the difference-in-differences (DID) model. This suggests that the baseline regression results reflect the impact of the National Key Ecological Function Zones Policy rather than pre-existing differences between the treatment and control groups. In the year of policy implementation and the following year, the coefficients did not pass the significance test, indicating a certain lag effect of the policy [45]. From the second year after implementation onward, the estimated coefficients are statistically significant at the 1% level and consistent in direction with the baseline regression results, confirming the robustness of the baseline findings.

6.2.2. Placebo Test

To ensure that the regression results are not driven by other unobserved disturbances, a nonparametric permutation test [17] was conducted. Fictitious treatment groups and pseudo policy implementation years were randomly assigned, and 500 iterations of the experiment were performed. The kernel density distributions of the p-values and estimated coefficients of the policy variable were plotted to conduct the placebo test, as shown in Figure 4.

The estimated coefficients of the fictitious policy variables mostly cluster around zero, which is far from the baseline regression coefficient of −0.005. Moreover, the majority of p-values exceed 0.1, indicating that the placebo test is passed. These results confirm that the observed effects on urban–rural integration are attributable to the actual policy intervention rather than other unobserved factors.

6.2.3. PSM-DID

To mitigate bias caused by sample selection, propensity score matching (PSM) was applied before estimation. After excluding unmatched samples, the estimation was performed again. In addition to the control variables used in the baseline regression, vegetation coverage (NDVI) and the share of primary industry output (ind) were added as covariates in the logit regression. A caliper-based 1:2 nearest neighbor matching method was employed, and using the control group prior to policy implementation for matching to avoid biases in the matching results that may arise from sample selection induced by policy implementation. The analysis re-estimates the model using the matched sample obtained through propensity score matching (PSM). As shown in Columns (1) and (2) of

Table 4. Robustness Check Results.

Type	PSM-DID		Omitted Samples		Alternative Dependent Variable
Variables	(1)	(2)	(3)	(4)	(5)	(6)
	uri	uri	uri	uri	D	D
did	−0.003 * (0.002)	−0.004 *** (0.001)	−0.004 *** (0.001)	−0.004 *** (0.001)	−0.008 *** (0.002)	−0.007 *** (0.002)
Constant Term	0.246 *** (0.000)	0.039 (0.038)	0.248 *** (0.000)	0.097 *** (0.031)	0.252 *** (0.001)	−0.038 (0.049)
Control Variable	NO	YES	NO	YES	NO	YES
Fixed Effects by Region	YES	YES	YES	YES	YES	YES
Fixed Effects by Year	YES	YES	YES	YES	YES	YES
Observation	3294	3294	4482	4482	5112	5112
R2	0.947	0.954	0.951	0.958	0.872	0.885

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

, the PSM-DID results are consistent with the baseline regression, confirming the robustness of the estimates.

6.2.4. Sample Exclusion

The level of urban–rural integration may systematically vary due to the distinctive characteristics of certain cities. Municipalities directly under central government control, provincial capitals, and sub-provincial cities have unique administrative and economic statuses that may bias the estimates. Therefore, these cities were excluded from the sample, leaving 249 observations for re-estimation. The results, presented in Columns (3) and (4) of Table 4, remain robust.

6.2.5. Alternative Dependent Variable

The baseline regression measured the urban–rural integration level by calculating weights for all indicators in the composite index system using the entropy method. Here, the urban–rural integration levels for population, spatial, and economic dimensions are recalculated using the coupling coordination degree method, which is then used to replace the dependent variable in the baseline regression. The coupling coordination degree is calculated as follows:

$$C={\displaystyle \frac{3\sqrt[3]{U_1{U}_2{U}_3}}{U_1+U_2+U_3}},T=\alpha U_1+\beta U_2+\gamma U_3,D=\sqrt{C\cdot T}$$

(3)

In the equation, C denotes the coupling degree, where U₁, U₂, and U₃ represent the population, spatial, and economic systems, respectively. The coefficients α, β, and γ indicate the relative importance of these three systems. Following conventional practice that assumes equal weighting among systems, we set α = β = γ = 1/3. D represents the coupling coordination degree, which serves as our alternative dependent variable. As shown in Columns (5) and (6) of Table 4, the estimation results remain consistent with the baseline regression, confirming their robustness.

6.2.6. Addressing Heterogeneity in Multi-Period Difference-in-Differences (DID)

In multi-period DID models, the staggered timing of policy implementation may lead to heterogeneous treatment effects, potentially causing bias in estimates from two-way fixed effects models [46]. Therefore, this study first employs the Goodman–Bacon decomposition method to identify sources of bias, followed by re-estimation using the Callaway and Sant’Anna approach [47]. The results of the Goodman–Bacon decomposition are presented in

Table 5. Results of the Goodman–Bacon Decomposition.

Type	2 × 2 Treatment Approach		Proportional Weight	Average Treatment Effect
	Treatment Group	Control Group
A	Treatment Group of the First Policy Implementation Cohort	Treatment Group of the Second Policy Implementation Cohort	0.056	−0.004
B	Treatment group of the second policy implementation cohort	Treatment Group of the First Policy Implementation Cohort	0.089	0.003
C	All Cohorts of the Policy Implementation Treatment Groups	Control Group that has never been Exposed to Policy Implementation	0.855	−0.007

.

As shown in Table 5, the proportion of bias-prone comparisons (Type B) accounts for only 8.9% of all categories, which is much lower than the combined proportion of Types A and C (91.1%). Moreover, the average treatment effect for Type B comparisons is smaller relative to other types, indicating that the impact of potential bias on the two-way fixed effects estimates is minimal. Thus, the two-way fixed effects regression remains appropriate.

To further ensure robustness, the Callaway and Sant’Anna estimation method was applied. The estimated average treatment effect of the policy is −0.003, which is slightly smaller than the baseline estimate but remains negative and statistically significant at the 5% level. These results confirm the robustness of the baseline findings.

7. Further Analysis

7.1. Mechanism Analysis

Based on the baseline regression results, which clearly indicate a negative inhibitory effect of the key ecological functional zone policy on urban–rural integration development, a two-step approach [48] is employed to test the underlying mechanisms theoretically. The focus is on examining the effect of the policy variable (DID) on the mechanism variables. The model is specified as follows:

$$M_{it}=\alpha +{\beta }_1\cdot di{d}_{it}+{\displaystyle \sum _{j=1}^n{\beta }_j}Control+{\mu }_i+{\delta }_t+{\epsilon }_{it}$$

(4)

In the equation, M_it denotes the mechanism variables, including industrial structure transformation (isu) and government fiscal pressure (gfp), while the other variables remain consistent with those in the baseline regression.

7.1.1. Industrial Structure Upgrading

Industrial structure upgrading is the fundamental path for the development of a green economy and leapfrog development in National Key Ecological Function Zones. It is the driving force that promotes urban–rural integration through industrial development. Li Chenglong et al. [49] find that industrial structure upgrading significantly facilitates urban–rural integration. According to the estimation results in Columns (1) and (2) of

Table 6. Results of the Mechanism Test.

Type	(1)	(2)	(3)	(4)
	isu	isu	gfp	gfp
did	−0.002 ** (0.001)	−0.001 * (0.001)	0.020 *** (0.004)	0.016 *** (0.003)
Constant Term	0.944 *** (0.000)	1.123 *** (0.034)	0.111 *** (0.001)	1.716 *** (0.132)
Control Variable	NO	YES	NO	YES
Fixed Effects by Region	YES	YES	YES	YES
Fixed Effects by Year	YES	YES	YES	YES
Observation	5112	5112	5112	5112
R2	0.864	0.875	0.881	0.936

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

, during the study period, the policy significantly inhibited industrial structure restructuring, thereby slowing down the process of urban–rural integration in these areas.

The NKEFZ policies require substantial technological innovation and financial investment to drive the green transformation of industries. The increased burden and costs of environmental protection investments have suppressed industrial competitiveness and innovation, causing the original industrial advantages to gradually fade. While ecological industrialization emphasizes converting ecological resources into economic value, this transformation requires long-term investment and market cultivation. Emerging industries face high environmental protection standards and entry barriers, and under strict regulatory measures, the replacement of old and new industries during the policy implementation period has suppressed market vitality. The high market entry barriers have led to an imbalance in industrial structure, hindering the interlinkage between industries. While emerging industries create job opportunities, they also require a highly skilled workforce, whereas traditional agricultural labor often lacks the relevant skills. The mismatch between the supply and demand for skills has led to instability in employment for a large portion of the rural population during the transformation process, further intensifying the flow of people from rural to urban areas, which affects the balance of the urban–rural labor market. Faced with livelihood pressures, rural residents have increasingly focused on basic agriculture, further inhibiting industrial restructuring and transformation. The delay in industrial restructuring has made it difficult for effective collaboration between urban and rural areas in industrial division and cooperation, thereby hindering the coordinated development of urban–rural integration in economic, social, and cultural aspects.

7.1.2. Government Fiscal Pressure

The structure of government revenue and expenditure is a key factor in enabling fiscal support for urban–rural integration in NKEFZ. Liu Xinzhi and Zhou Hanmei [50] point out that increased fiscal pressure reduces the capacity to provide essential financial support for integration and has a significantly negative impact on local urban–rural integration efforts. Based on the estimation results in Columns (3) and (4) of Table 6, the policy significantly increased the fiscal burden on local governments. This is consistent with the findings of existing research [14].

Although the central government’s ecological transfer payments to NKEFZ and the regions’ own development of the green economy have somewhat alleviated local fiscal pressures, they have not fully offset them. The core of the Key Ecological Function Zone policies lies in environmental protection, maintaining ecological security, and preventing over-exploitation of resources. After the policy implementation, land use is strictly regulated, limiting industrial and commercial projects, restricting the number and scale of enterprises, and reducing tax revenues and non-tax income such as land transfer fees and land use rights. A significant portion of funds is allocated to ecological protection, environmental management, and ecological restoration. The strict limitations on natural resource development, the cultivation of emerging industries, and additional investments in social security and job training further exacerbate fiscal pressures. To ensure effective ecological protection, NKEFZ also need to establish a comprehensive ecological monitoring and management system. This includes purchasing monitoring equipment, building a network platform for monitoring, and training monitoring and management personnel. The construction and operation of this system require continuous and stable financial investment. As fiscal expenditures increase, local governments often face the dual dilemma of ‘policy pressure’ and ‘fiscal burden,’ limiting the economic and social support they can provide in the urban–rural integration process. Due to insufficient fiscal investment, emerging industries struggle to develop infrastructure, promote their initiatives, and fully leverage urban tourism markets and clientele, which affects the industrial foundation for urban–rural integration development. Therefore, the implementation of the Key Ecological Function Zone policies has increased local government fiscal pressure, which in turn slows down the urban–rural integration process.

7.2. Further Analysis: Heterogeneous Effects

The number of key ecological function counties within a prefecture-level city and the city’s regional location may lead to heterogeneous impacts on urban–rural integration. Grouped regressions are employed to estimate effects for different types of samples.

7.2.1. Proportion of Key Ecological Function Counties

First, the number of key ecological function counties within treated prefecture-level cities is counted. Then, the total number of county-level administrative divisions for all sample cities is calculated based on the 2023 national administrative division standards. Finally, the proportion of key ecological function counties in each prefecture-level city is computed. Cities are divided into three groups according to quantiles: “low proportion”, “medium proportion”, and “high proportion.” Regression results are reported in Columns (1), (2), and (3) of

Table 7. Results of the Heterogeneity Test.

Type	Proportion of the Number of Key Ecological Function Counties			Geographical Location
Variables	(1)	(2)	(3)	(4)	(5)
	Low Proportion	Medium Proportion	High Proportion	Eastern Region	Central and Western Regions
did	−0.001 (0.002)	−0.009 *** (0.002)	−0.009 *** (0.002)	−0.003 (0.003)	−0.003 *** (0.001)
Constant Term	−0.005 (0.037)	0.052 (0.038)	0.059 (0.042)	−0.044 (0.075)	0.024 (0.035)
Control Variable	YES	YES	YES	YES	YES
Fixed Effects by Region	YES	YES	YES	YES	YES
Fixed Effects by Year	YES	YES	YES	YES	YES
Observation	3672	3636	3636	1764	3348
R2	0.961	0.965	0.965	0.970	0.950

Note: *** indicates significance at the 1% level. The values in parentheses are standard errors.

.

When the proportion of key ecological function counties is low, policy implementation is concentrated in a few counties of a prefecture-level city, while other counties develop under relatively relaxed conditions, allowing regional economies to remain active. Ecological protection generates ecological benefits that provide expanded ecological space for the flow of urban factors, and ecological–economic benefits are rapidly realized through market penetration in other areas. Under such conditions, the negative effects of the policy on urban–rural integration are alleviated, and the policy’s inhibiting effect is not significant. As the proportion increases, the policy coverage becomes broader, and ecological protection requirements become stricter, restricting the economic development potential of more counties. The intensified conflict between ecological protection and economic development then hinders the progress of urban–rural integration.

7.2.2. Regional Location

There are systematic differences across the eastern, central, and western regions in terms of economic development stages, fiscal self-sufficiency, and marketization levels, necessitating heterogeneous effect testing. The results are reported in Columns (4) and (5) of Table 7.

Compared with the eastern region, the NKEFZ policy significantly slows urban–rural integration in the central and western regions, as verified by statistical significance tests. The eastern region benefits from a highly developed, diversified industrial system, well-established urban agglomeration networks, strong inter-city synergies, and comprehensive urban–rural integration planning. With a market-oriented ecological product value realization mechanism, the region possesses stronger endogenous industrial development capabilities, allowing policy pressures to be effectively converted into new driving forces for urban–rural integration. In contrast, the central and western regions have weaker urban–rural planning foundations. Many counties lack systematic development plans, and township construction is dispersed, resulting in irrational urban–rural spatial structures and insufficient functional coordination. This creates conflicts between ecological protection policies and local development needs. Moreover, the central and western regions are more dependent on resource-based development, and alternative industry cultivation is constrained by weak technological accumulation and limited financial resources, leading to slow development of emerging industries. In addition, these regions rely heavily on central fiscal transfer payments. Ecological compensation is limited in scope and form, lacking diversified incentives and market-oriented operational channels. Consequently, the policy’s incentive effects are constrained, further restricting the realization of policy impacts and the momentum for factor flows necessary for urban–rural integration.

8. Conclusions, Recommendations, and Discussion

8.1. Research Conclusions

The establishment of National Key Ecological Function Zones (NKEFZ) is primarily aimed at safeguarding national ecological security, but it also generates policy spillover effects for the regions where it is implemented. This study focuses on urban–rural integration within NKEFZ, theoretically constructs a dual dynamic “Driving-Constraining” framework, and analyzes both the driving and inhibiting forces of the policy on local urban–rural integration. Based on a sample of 284 prefecture-level cities from 2006 to 2023, a multi-period difference-in-differences approach is employed to examine the impact of the NKEFZ policy on urban–rural integration, along with mechanism testing and heterogeneous effect analysis.

The study finds the following: First, during the study period, the implementation of the NKEFZ policy significantly slowed the process of urban–rural integration, particularly exerting pronounced negative effects on spatial and economic integration. This conclusion remains robust after a series of robustness tests. Second, mechanism analysis indicates that the NKEFZ policy primarily affects urban–rural integration negatively by inhibiting industrial structure transformation and increasing fiscal pressure on local governments. Third, the policy effects are more pronounced in prefecture-level cities with a high proportion of key ecological function counties, as well as in cities located in the central and western regions.

8.2. Policy Recommendations

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

First, actively leverage ecological resources as a driving pivot for promoting urban–rural integration. The regional ecological advantages brought by policy implementation should be further utilized to enhance functional complementarity between cities and rural areas. Priority should be given to cultivating an ecological-oriented industrial synergy system, deepening the integration of ecological protection with characteristic industries, developing the ecological economy, extending ecological industry chains, and promoting industrial diversification. Efforts should also accelerate reasonable industrial restructuring, forming a new pattern in which ecological capital drives the efficient allocation of urban–rural factors and fosters positive urban–rural integration.

Second, improve the diversified ecological compensation system. Horizontal ecological compensation mechanisms should be further refined to address the limitations in intensity and efficiency of vertical transfer payments, establishing a composite compensation system that integrates vertical transfers, horizontal compensation, and market-based transactions. The establishment of dedicated ecological value realization funds should be explored, and innovative policy-based financial instruments should be used to broaden financing channels. Social capital and the private sector should be encouraged to participate in ecological protection projects, for example, developing market-based tools such as EOD (Ecology-Oriented Development) and ROD (Resource-Oriented Development), or adopting models like PPP (Public–Private Partnership), BOT (Build-Operate-Transfer), or ABO (Authorize-Build-Operate), which focus on government–enterprise cooperation. Additionally, collaboration between public welfare organizations, individuals, businesses, and government departments to establish ecological industry development funds and participate in ecological protection projects should be encouraged. This approach would create a diversified compensation model led by the government, regulated by the market, and involving social participation, innovating pathways for shared ecological protection costs and value realization, alleviating fiscal pressure, and enhancing the self-reinforcing mechanism for advancing urban–rural integration.

Third, clarify the functional division between central and local governments and establish a categorized collaborative governance framework. A differentiated policy objective system should be constructed between central and local levels. The central government should lead ecological protection regulation and provide overarching institutional support, strengthening baseline ecological security management and consolidating ecological protection outcomes. Local governments, based on the proportion of key ecological function counties and regional economic development conditions, should focus on innovating urban–rural integration pathways, prioritizing the industrialization of ecological resources, construction of new rural infrastructure, and integration of urban–rural factor markets. This would establish a “central focus on protection, local focus on development” two-tiered functional system. Additionally, the central government could establish an ecological protection performance reward fund to incentivize regions with significant urban–rural integration achievements, thereby enhancing the coordination of central–local government functional objectives.

8.3. Discussion

The study indicates that the ecological protection policies of National Key Ecological Function Zones (NKEFZ) are multidimensional: they serve both as environmental governance tools and also play a regulatory role in the development of the economy and society. The policy effects may exhibit heterogeneous outcomes across different regions, institutional contexts, and stages of development. This multidimensionality arises not only from the multiple layers of policy objectives but also from the interactions among resource allocation, institutional constraints, and social behaviors during policy implementation. As an environmental governance tool, ecological protection policies effectively maintain ecosystem integrity and enhance regional ecological security over the long term. From the perspective of economic and social systems, environmental control measures often increase the opportunity cost of resource allocation and diffuse through various mechanisms, generating complex, multidimensional feedback that exerts indirect pressures on economic and social development. The design and implementation of NKEFZ policies must fully recognize their multidimensionality and complexity, rather than assessing policy performance solely based on environmental objectives. China’s ecological civilization construction emphasizes the development concept that ‘lucid waters and lush mountains are invaluable assets’. However, in the short term, the restrictive nature of ecological protection policies remains significant, and the role of ecological resources in promoting regional development is still limited, resulting in a very limited transformation of ‘lucid waters and lush mountains’ into ‘invaluable assets’. This is an important issue that the government must recognize when implementing ecological protection policies. Therefore, policymakers need to balance ecological security with economic growth, industrial upgrading, and social development, and create more tools for transforming ecological resources into economic benefits, achieving coordinated optimization between environmental benefits and socio-economic effects. From a systemic and dynamic balance perspective, it is essential to prevent “green gains” from producing unintended negative impacts at the socio-economic level, and laying an institutional and practical foundation for regional sustainable development. Of course, the full realization of ecological resource advantages will take a longer time to become more noticeable. When evaluating the effects of the policy over a broader time span, the impact on urban–rural integration may lead to different conclusions. This is also an issue that requires further attention in future research.

This study enriches the theoretical framework linking ecological protection policies and urban–rural integration and provides references for institutional innovation in promoting green development and regional coordination in China and globally. It also lays a foundation for the systematic integration of economic development, social progress, and ecological protection in the future. Since this study validates the effects of the policy at the macro-regional level, future research could further focus on a specific ecological function zone, using more detailed and comprehensive data to explore the policy’s effects at the micro level. This would deepen the understanding of ecological protection policies and their operational mechanisms, representing a key direction for future research.