The research team, led by Miao Qian, Xiuyu Huang, and Jiaomeng Li of Qingdao Agricultural University, constructed a multidimensional evaluation system to measure both cooperative development and collective economic development across each province. For cooperatives, the index captured five dimensions: standardized operation, operational performance, service scope, driving effect, and industrial upgrading, built from 18 underlying indicators such as average operating income per cooperative, farmer membership rates, and the share of cooperatives holding registered trademarks. The collective economy was measured across four dimensions covering scale and efficiency, profit distribution and accumulation, organizational management, and public service provision. Rather than relying on subjective weighting, the researchers used the entropy method, which assigns weights based on the information content of the data itself, reducing the bias that plagues expert-driven scoring systems.

The temporal picture that emerged is strikingly asymmetric. Between 2015 and 2023, the composite development score for farmers’ cooperatives actually declined slightly, falling from 3.499 to 3.324, a drop of roughly 5 percent. The rural collective economy, by contrast, grew steadily and substantially, its composite score more than doubling from 1.608 to 3.471. Within the cooperative sector, only industrial upgrading improved consistently, with its score rising from 0.695 to 0.992, driven by explosive growth in processing-oriented cooperatives, whose numbers expanded from 26,364 to 121,378, an average annual growth rate of about 21 percent. Service-oriented cooperatives grew from 108,700 to 162,560 over the same period. The data suggest a sector shifting from quantity to quality, even as its overall composite performance slipped.

To establish causality rather than mere correlation, the team employed a two-way fixed-effects panel regression that controls for both unchanging provincial characteristics and nation-wide temporal shocks. The baseline result showed that a one-unit increase in the level of cooperative development raises the level of collective economic development by an average of 0.351 units, a coefficient that remained highly significant at the 1 percent level across multiple model specifications. The researchers then confronted the classic endogeneity problem: prosperous villages might simply build better cooperatives, reversing the direction of causation. Using the one-period lag of cooperative development as an instrumental variable in a two-stage least squares estimation, they found the effect not only survived but grew slightly, to 0.436, with a first-stage F-statistic of 23.74 comfortably exceeding the Stock–Yogo threshold for instrument strength.

Robustness checks reinforced the conclusion. Replacing the entropy weighting with grey correlation analysis, an entirely different algorithm for constructing the composite index, produced a coefficient of 1.015 that remained significant at the 1 percent level, demonstrating that the result does not hinge on how the index was assembled. Adding further control variables for industrialization and trade openness left the core coefficient at 0.278, still significant. Interestingly, the degree of openness carried a significantly negative coefficient, suggesting that export-oriented economies can siphon resources away from local collective development, a nuance that underscores how global integration and village-level prosperity do not always pull in the same direction.

Perhaps the most consequential finding concerns how cooperatives actually deliver their benefit. When the researchers decomposed cooperative development into its five dimensions and tested each against the collective economy, only two channels proved significant: operational performance and industrial upgrading. Standardized operation, service scope, and the direct driving effect on farmers showed no significant impact. In other words, it is not the mere existence, formal compliance, or membership reach of cooperatives that powers collective growth, but their actual economic performance and their capacity to move up the value chain through branding, quality certification, and processing. This helps explain the well-documented phenomenon of hollow shell cooperatives in China, entities registered on paper that generate no substantive economic activity and, according to these results, no measurable collective benefit.

Geography matters enormously. When the sample was split into eastern, central, and western regions, the promotional effect was significant only in the east, with a coefficient of 0.318 at the 5 percent level, while the central and western coefficients of −0.078 and 0.085 failed every significance test. The authors attribute this to the east’s high degree of agricultural marketization, mature industrial chains, and standardized cooperative operations, which allow performance gains to transmit efficiently to village collectives. In the central and western provinces, cooperatives started later, remain smaller in scale, and lack the market infrastructure to convert organizational form into economic output. The lesson is uncomfortable for one-size-fits-all policymaking: the same institutional design produces radically different results depending on the surrounding economic ecosystem.

Two further nonlinear patterns sharpen the picture. First, the growth rate of the agricultural industry, measured as value added across farming, forestry, animal husbandry, and fisheries, acts as a positive moderator: as the moderator rises from its mean minus one standard deviation to its mean plus one standard deviation, the marginal effect of cooperatives on the collective economy climbs monotonically from 0.321 to 0.494. Vibrant agricultural sectors expand market demand, improve processing and logistics infrastructure, and lower the transaction costs of resource integration. Second, land transfer exhibits a single-threshold effect at a value of 0.3903. Below that threshold, the cooperative coefficient is 0.459; above it, the coefficient jumps to 0.626. Only once land consolidation reaches a critical scale can cooperatives fully exploit mechanization, centralized procurement, and branded marketing, unlocking economies of scale that fragmented smallholder plots cannot achieve.

The most surprising result may be spatial. Using a spatial Durbin model with an economic distance weight matrix, the researchers found that cooperative development in one province significantly boosts the collective economy of neighboring, economically linked provinces. The decomposition of effects is remarkable: the direct local effect is 0.383, but the indirect spillover effect is 1.198, more than three times larger, yielding a total effect of 1.581, all significant at the 1 percent level. Cross-regional diffusion of governance models, extension of market linkage networks, and the mobility of capital, talent, and agricultural services appear to dominate the story. Cooperative development, in this reading, is less a local intervention than a contagious one, with benefits propagating across provincial borders faster than they accumulate at home.

The policy implications are pointed. The authors argue that China should shift from subsidizing cooperative numbers to phasing out shell entities, strengthening annual reporting and dynamic exit mechanisms, and supporting chains that extend into processing, warehousing, logistics, and rural tourism. Eastern provinces should consolidate replicable models of deep cooperative-collective integration, while central and western regions need targeted fiscal support, talent deployment, and industrial chain repair before their cooperatives can deliver. Because spillovers are so large, removing barriers to cross-regional factor flows and building interprovincial cooperative federations could multiply returns. And because the land transfer threshold is real, orderly land consolidation emerges as a prerequisite rather than an afterthought. For a country betting heavily that organized smallholders can fund common prosperity, this study offers both a validation and a warning: the cooperative engine works, but only when it is fueled by genuine performance, adequate scale, and a living industrial environment.

Subject of Research: The impact of farmers' cooperatives on the development of China's rural collective economy

Article Title: The enabling effect of farmers’ cooperatives on the rural collective economy: evidence from China

Article References: Qian, M., Huang, X., & Li, J. (2026). The enabling effect of farmers’ cooperatives on the rural collective economy: evidence from China. Frontiers in Sustainable Food Systems, 10, Article 1971166. https://doi.org/10.3389/fsufs.2026.1971166

Image Credits: AI Generated

DOI: 10.3389/fsufs.2026.1971166

Keywords: farmers' cooperatives, rural collective economy, China, panel data, spatial spillover effects, land transfer, industrial upgrading, agricultural economics, rural revitalization, threshold effect, entropy method, two-way fixed-effects model

One of the most striking findings of this comprehensive analysis is the pronounced spatial inequality in STFE distribution across China. The eastern regions, with their dense concentration of financial resources, dramatically outpace the central and western regions in terms of STFE development. This uneven distribution creates a distinct gradient characterized by “high in the east and low in the west.” Correspondingly, the pattern of TFCP exhibits a block-like spatial distribution predominantly centered around mid- and low-level cities, punctuated by isolated high-TFCP urban points. This spatial heterogeneity reflects underlying economic and infrastructural discrepancies, with technological innovation serving as a crucial driver underpinning improvements in TFCP.

Delving deeper into the spatial dynamics, the study’s regression models reveal a complex dual effect of STFE on carbon emission reduction. Locally, the existence and growth of STFE are strongly associated with enhanced emission reduction within the city itself, underscoring its role in fostering green technologies and sustainable practices. Yet this beneficial local effect is counterbalanced by a troubling negative externality in neighboring cities. The indirect effects highlight a “beggar-thy-neighbor” spatial spillover, where STFE growth in one city inadvertently hampers carbon reduction efforts in adjacent regions. This paradox illustrates the spatial competition for financial and technological resources that can lead to environmental degradation beyond a city’s borders.

This pattern persists robustly across both static and dynamic spatial Durbin models and remains statistically significant after rigorous robustness checks and endogeneity corrections. Such findings emphasize the intricate and sometimes counterintuitive spatial interdependencies that complicate the relationship between financial scientific ecosystems and environmental outcomes. They reveal that uncoordinated local development of STFE may, paradoxically, undermine regional sustainability objectives by displacing polluting activities or drawing away critical innovation inputs from neighboring regions.

Further dissection of the data uncovers notable regional and resource-based heterogeneities driving these spatial spillovers. The negative spillover effect of STFE development on carbon reduction manifests predominantly in the eastern region, reflecting the region’s advanced state and aggressive financial ecosystem growth. In contrast, the central and western regions exhibit minimal spatial spillover impacts, likely due to their relatively nascent stages of STFE development. Moreover, non-resource-based cities display a more pronounced positive spatial spillover effect, leveraging the STFE to bolster emission reduction beyond their boundaries, while resource-rich cities face challenges transitioning their economies and thus exert less beneficial spillovers.

The financial development level also emerges as a critical moderator. Areas with high financial maturity significantly amplify the positive carbon reduction effects of STFE both locally and on adjoining regions, whereas regions with weaker financial infrastructures lag behind. This underscores the importance of an integrated approach that enhances both the financial environmental ecosystem and underlying financial institutional development to maximize emission reduction benefits across the economic geography.

Mechanistically, the study sheds light on the pathways through which STFE affects neighboring regions’ carbon emissions. Counterintuitively, several mechanisms—including green technology innovation, human capital siphoning, informatization digital divides, and competitive exclusion in financial resource allocation—act to increase emissions in adjacent areas. This paradoxical effect exacerbates the “beggar-thy-neighbor” phenomenon as cities with advanced STFE siphon talent, technology, and financial resources away from neighbors, intensifying their carbon output. The interplay of informatization levels and human capital availability further intensifies these negative spillovers, revealing an unsettling complexity in regional coordination challenges.

Given these multi-layered findings, policy implications are both urgent and multifaceted. Tailored regional policies recognizing the stark interregional disparities in STFE capacity are imperative. For the underdeveloped central and western regions, direct financial incentives such as subsidies, tax rebates, and the establishment of specialized technology finance entities can catalyze local STFE, bridging the gap with the eastern powerhouses. Supporting medium- and low-level TFCP cities in these regions to transition toward higher productivity through targeted investment in low-carbon technologies is essential to rebalancing the spatial distribution of emission reduction capabilities.

Simultaneously, regional cooperation frameworks must be strengthened to overcome the inefficiencies and externalities spawned by fragmented STFE development. Collaborative governance that explicitly accounts for responsibility-sharing and compensates regions adversely affected by neighboring financial ecosystems is crucial. For instance, cross-region carbon emission reduction compensation mechanisms can provide economic incentives that mitigate competitive negative spillovers. Moreover, harmonized environmental supervision and policy alignments will be vital to prevent the geographic shifting of carbon-intensive activities under the guise of STFE-driven development.

Within the eastern region, where STFE is strongest, efforts should concentrate on innovating cooperation modalities with neighboring areas to mitigate negative spillovers while sustaining aggressive local carbon reduction. Investment in green technology industries must be scaled up, alongside fostering synergies that spread environmental benefits rather than exacerbate regional inequalities. For resource-dependent cities, strategic industrial transformations anchored by STFE-led green technology development are necessary to minimize carbon footprints and stimulate low-carbon competitiveness.

Financial infrastructure development remains a cornerstone for broader emission reduction. In financially lagging areas, increased investment in financial services capacity and infrastructure will enable more effective STFE deployment. Contrastingly, in financially advanced regions, leveraging synergies with neighbors through joint ventures and collaborative innovation can magnify carbon reduction outcomes, transforming localized gains into regional progress.

Governments also bear a crucial role in dismantling the structural constraints that perpetuate spatial environmental externalities. Establishing cross-regional collaborative governance frameworks and transferable green technology compensation systems can diffuse technological monopolies and foster equitable innovation distribution. Cultivating human capital through graduated educational investment and enabling flexible talent mobility policies will bridge discrepancies in environmental governance capabilities, enhancing regulatory reach across regions.

Bridging digital divides remains central to curbing negative spillovers. The equalization of digital infrastructure promotes transparency and limits spatial arbitrage opportunities exploited through emerging technologies such as blockchain for carbon footprint tracking. Developing digital regulatory competence alongside shared carbon credit and emission right trading mechanisms opens promising avenues for reconfiguring resource allocation at a supra-local scale, integrating financial and environmental goals more tightly.

Finally, nuanced policy instruments addressing the observed moderating effects of informatization and human capital must be prioritized. Enhancing digital regulatory frameworks and bolstering human capital reserves attuned to low-carbon technologies will mitigate amplified negative externalities. Complementing these efforts with horizontal ecological compensation payment systems can equitably distribute the costs and benefits of carbon reduction, fostering a cooperative spatial planning landscape where emission targets and innovation trajectories are jointly owned.

This pioneering research elucidates that science and technology financial ecosystems hold transformative potential to shape sustainable urban futures in China. Yet, unlocking this potential requires sophisticated regional coordination and policy innovation that transcends traditional boundaries of fiscal competition and environmental governance. Mitigating the “beggar-thy-neighbor” effect involves orchestrating a delicate balance of incentives, regulatory frameworks, and cross-sector collaboration. As the world grapples with climate urgency, China’s experience offers critical lessons in harnessing financial science and technology pathways to achieve spatially equitable carbon emission reductions.

The study’s integration of dynamic spatial econometric modeling with robust empirical evidence marks a significant advance in understanding the geography of green finance and its environmental repercussions. Policymakers globally can glean insights on aligning financial innovation ecosystems with sustainable development goals, highlighting the need for holistic systems thinking in the design of green finance strategies. As STFE continues to evolve, ongoing monitoring and adaptive governance will be paramount to amplify positive impacts and suppress adverse spatial externalities.

In conclusion, while science and technology financial ecosystems are pivotal in driving local carbon emission reductions, their spatial spillovers introduce complexities demanding strategic regional cooperation and infrastructural investment. The path forward lies in embracing a collaborative, multi-dimensional governance paradigm that harmonizes financial dynamism with environmental integrity. Through such integrative approaches, the promise of STFE as a catalyst for sustainable urban decarbonization can be realized in a manner that is inclusive, equitable, and resilient across diverse socio-economic landscapes.

Subject of Research: Science and Technology Financial Ecosystem (STFE) and its spatial spillover effects on carbon emission reduction efficiency across Chinese cities.

Article Title: Mechanisms and spatial spillover effects of science and technology financial ecosystem on carbon emission reduction from multiple perspectives: evidence from China.

Article References:
Zhang, J., Sun, Z. Mechanisms and spatial spillover effects of science and technology financial ecosystem on carbon emission reduction from multiple perspectives: evidence from China.
Humanit Soc Sci Commun 12, 1025 (2025). https://doi.org/10.1057/s41599-025-05423-5

Image Credits: AI Generated