Open public data could strengthen rural innovation and urban-rural coordination

Open public data is becoming a new policy lever for closing the urban-rural gap, as governments seek better ways to direct resources, reduce information barriers and link rural communities with urban markets and services. A new China-focused study finds that opening government-held data can strengthen urban-rural integration by improving the flow of labour, capital, technology and information. 

The study, titled Public Data Openness and Urban-Rural Integration: Causal Inference Based on Double Machine Learning, was published in Land, shows that public data openness can significantly promote urban-rural integration, with stronger effects in eastern cities and non-resource-based cities.

The study is based on panel data from 259 prefecture-level Chinese cities from 2012 to 2024.

Public data becomes a new engine for urban-rural integration

China’s urban-rural divide is one of the major structural challenges facing its modernization agenda. Uneven resource allocation, information barriers, weak factor mobility and gaps in digital infrastructure continue to limit the flow of labor, capital, technology and services between cities and rural areas. The study claims that open public data can help address these barriers by turning government-held information into a usable production factor in the digital economy.

Public data openness, as the study defines, is the process by which government agencies integrate, standardize and release public data for wider social and market use while protecting state secrets, business secrets and personal privacy. Public data is not only a transparency tool, it's a form of digital infrastructure that can help markets, firms, governments and rural actors make better decisions.

The study uses the roll-out of data trading platforms as a turning point to assess how public data openness affects development. These platforms provide governments a way to share, combine and use data more effectively, turning scattered administrative records into practical resources that can support economic growth and social planning.

The level of urban-rural integration was measured via a comprehensive index covering five dimensions: economic integration, population integration, social integration, spatial integration and ecological integration. The indicators include urban-rural income and consumption gaps, employment structure, population concentration, social security access, medical services, education conditions, land urbanization, internet coverage, telecommunications activity, transport conditions, green space and environmental protection.

Public data openness has a significantly positive impact on urban-rural integration. After controlling for city-level factors and fixed effects, the effect remains positive. The result also holds after a wide set of robustness checks, including excluding municipalities, using an instrumental variable, changing the machine learning algorithm, adjusting the sample split, shifting the model structure and controlling for other digital policies such as Broadband China and Smart City programs.

Data openness helps break the traditional dual structure between urban and rural areas by improving the market-oriented allocation of data elements. Data platforms reduce information asymmetry, cut search costs, improve public governance efficiency and make it easier for urban and rural actors to coordinate.

Public data has several features that are especially useful for urban-rural integration:

• It is authoritative because it comes from public institutions.
• It is scarce because many data resources were previously concentrated in government systems and not fully accessible.
• It has high value density because it can support targeted applications in transportation, healthcare, ecology, investment, agriculture and public services.

By opening and circulating these data resources, governments can reduce the isolation of rural areas from urban markets. Rural enterprises can gain better access to policy, infrastructure and market information. Urban investors can better assess rural opportunities while workers can make more informed decisions about mobility. Public agencies can match resources more accurately with development needs.

The study positions public data openness as part of a broader shift in which data becomes active economic fuel rather than passive administrative information. For urban-rural integration, that shift is especially important because rural areas often face higher information costs and weaker digital access than cities.

Factor mobility and innovation drive the effect

The study identifies two main channels through which public data openness promotes urban-rural integration: factor mobility and technological innovation.

Factor mobility

Urban-rural integration depends on the free and orderly movement of labor, capital, land-related resources, technology and information. The study argues that public data openness lowers transaction costs and reduces uncertainty, making it easier for factors to move between urban and rural areas.

Labor mobility is key to this process. Rural workers may return to their hometowns for entrepreneurship or employment when better data on markets, policies, infrastructure and enterprise opportunities becomes available. Urban capital may flow into rural industries when investors can access more credible information about land, logistics, services and local policy support. Data openness can also help rural firms lower production and information costs, improving their ability to attract talent, financing and partnerships.

The mechanism test supports this channel. Public data openness significantly increases the scale of labor mobility between urban and rural areas. The authors interpret this as evidence that data openness promotes urban-rural integration by improving factor allocation and making cross-regional movement less costly and more efficient.

Technological innovation

Public data can support innovation by giving firms, public institutions and rural actors access to high-quality information on industries, patents, policies, markets and public services. Open data can help innovators identify demand gaps, reduce redundant research and development, and match technology with real development needs.

This is particularly relevant for rural areas, where digital resources and innovation capacity often lag behind cities. Public data openness can reduce the information gap, support agricultural technology adoption, encourage rural enterprise innovation and promote knowledge spillovers from cities to rural regions.

The study measures regional innovation through patent authorizations and finds that public data openness significantly strengthens scientific and technological innovation vitality. This supports the authors’ argument that open public data does not merely improve information access; it can also create new innovation scenarios and help data-driven technologies spread across urban and rural systems.

Together, the two channel effects show that public data openness works through both market coordination and technological upgrading. It helps resources move more smoothly while also improving the capacity of cities and rural areas to generate and apply new ideas.

The findings also underline why data openness should not be viewed as a narrow government transparency policy. It can influence economic structure, industrial links, labor decisions, investment behavior and rural modernization. In the authors’ framework, public data openness can weaken the boundary between urban and rural systems by improving the flow of data, labor, capital, technology and services.

Benefits are stronger in eastern and non-resource-based cities

The effect of public data openness is not uniform across China. Heterogeneity analysis shows that public data openness has a stronger impact on urban-rural integration in eastern cities and non-resource-based cities. In eastern cities, the promoting effect is significant, while it is weaker or not significant in central and western cities. The authors suggest that eastern cities have stronger economic foundations, more advanced digital infrastructure, higher levels of marketization and more mature data platforms. These conditions make it easier for public data openness to translate into practical gains for urban-rural integration.

The finding suggests major policy challenge. Public data openness may widen regional gaps if less-developed regions lack the infrastructure, institutional capacity and market conditions needed to turn open data into development outcomes. The study thus argues that central and western regions need stronger digital infrastructure, better data resource layouts and more support for data element market construction.

The difference between resource-based and non-resource-based cities is also important. Public data openness has a stronger effect in non-resource-based cities than in resource-based cities. Resource-based cities often rely heavily on coal, minerals, oil, forests or other natural resources, which can lock them into fixed development paths. That path dependence may slow the use of data-driven development tools and weaken the impact of public data openness.

Non-resource-based cities, on the other hand, may have more flexibility to use data elements to support rural enterprises, industrial restructuring and urban-rural coordination. Without the same dependence on legacy resource industries, they may be better positioned to integrate data openness into broader development strategies.

Policy recommendations

The study’s policy recommendations call for the cultivation of a standardized and unified data element market, including common data standards, transparent trading rules and stronger governance systems. It also urges faster data rights confirmation, assetization, circulation and trading so that data can be integrated into agricultural industrial chains and rural development systems.

For central and western regions, the authors recommend stronger data infrastructure construction and better coordination with national digital strategies. Improving data infrastructure in less-developed regions could help narrow gaps in digital access and support more balanced urban-rural integration.

The study also recommends using public data platforms to improve the flow of labor, land, capital and other factors between cities and rural areas. Municipal governments should build urban-rural resource allocation systems with data as the core hub, guiding resources toward weaker rural areas and improving the efficiency of factor circulation.

For resource-based cities, the authors call for combining public data openness with the digital transformation of traditional industries. Applications in energy management, safety production and supply chain optimization could help these cities develop data-resource industrial clusters and reduce dependence on old growth paths.

The study authors also acknowledge several limits:

• The study period may be too short to show how public data openness works once smart city policies are fully established.
• The use of prefecture-level data may also miss sharper digital divides at the county or village level, where gaps in connectivity, skills and access are often more visible.
• Patent records, meanwhile, may overlook informal rural innovation that does not enter official intellectual property systems.
• Future research, the authors suggest, should use more detailed spatial data, geospatial analysis and cross-country comparisons to better explain how public data openness reshapes the links between cities and rural areas.