Digital finance fuels high-quality growth, if infrastructure is in place

A new spatial econometric study reveals that digital inclusive finance (DIF) significantly boosts high-quality economic development in China, but only when supported by strong regional infrastructure and financial literacy. The research employs a decade of city-level panel data to uncover direct, indirect, and threshold-based effects of DIF across 281 Chinese cities.

Published in the journal Economies, the study “Exploring the Impact of Digital Inclusive Finance and Industrial Structure Upgrading on High-Quality Economic Development: Evidence from a Spatial Durbin Model” uses a Spatial Durbin Model (SDM) framework to examine the spatial spillovers and regional disparities in the relationship between digital finance and economic quality.

Can digital finance directly enhance urban development?

The study finds a strong and statistically significant positive impact of DIF on high-quality economic development (HQED) across Chinese prefecture-level cities. Utilizing spatial autocorrelation metrics and regression models, the authors demonstrate that regions with higher DIF penetration experience improved innovation, coordination, environmental sustainability, openness, and social inclusiveness. These are the five pillars of HQED as outlined in China’s national development agenda.

Digital finance, defined by services like mobile payments, credit scoring through big data, and digital lending, has become a catalyst for economic transformation, particularly in urban areas with a robust digital ecosystem. By expanding financial access, improving service delivery efficiency, and lowering transaction costs, DIF allows households and micro-enterprises to participate more effectively in economic activity. The results confirm that even a marginal increase in DIF leads to measurable gains in local economic quality.

Importantly, the positive effects are not confined to cities where DIF is implemented. Spatial spillover effects are clearly identified, meaning that DIF also boosts HQED in neighboring regions through mechanisms like capital mobility, cross-regional innovation diffusion, and supply chain coordination. In fact, the indirect or spillover effect of DIF was found to be larger than the direct effect in many cases, underscoring the role of regional connectivity in amplifying digital finance’s economic benefits.

Do all regions benefit equally from digital finance?

Despite DIF’s aggregate positive impact, the study exposes stark regional disparities in its effectiveness. While cities in eastern China benefit significantly from DIF both locally and through regional spillovers, cities in the central and western parts of the country experience neutral or even negative effects.

In the eastern region, home to advanced industrial hubs and digital infrastructure, DIF improves both the quality and coordination of economic development. These cities already possess the technological foundation and institutional frameworks to harness digital tools effectively, which enhances the marginal value of financial innovation. Here, DIF serves as a multiplier of existing strengths.

In contrast, the central and western regions exhibit underdeveloped financial ecosystems, limited broadband and digital access, and weaker industrial diversity. In these areas, DIF sometimes contributes to inefficient capital allocation, over-financialization, and even resource outflow to more developed neighboring cities, a phenomenon the authors describe as a “siphon effect.” The digital divide, rather than narrowing, may thus widen in absence of adequate local support systems.

A two-regime SDM model applied in the study further confirms that non-central cities, those not designated as provincial capitals or municipalities, demonstrate stronger spatial spillover benefits than central cities. This suggests that marginal returns from DIF expansion are higher where financial services were previously scarce, provided there is minimal infrastructure to support the uptake.

What conditions must be met for digital finance to work?

A crucial insight from the study is the identification of a double-threshold effect in the impact of DIF on economic quality. This means that DIF only generates significant economic benefits when a city’s DIF index exceeds a specific critical value. Below these thresholds, the impact is either negligible or negative.

Two key preconditions are identified: the presence of adequate digital infrastructure and a minimum level of user financial literacy. Without reliable internet access, mobile payment platforms, and secure data systems, digital finance cannot be effectively deployed. Similarly, if citizens lack the skills to navigate digital platforms or understand financial products, the adoption of DIF may lead to mismanagement, fraud exposure, or financial exclusion.

The study reveals that when DIF remains below the lower threshold value, its influence on HQED is strongly negative. As cities move into the intermediate range, the effect remains negative, albeit less severe. Only when DIF surpasses the upper threshold does its impact turn positive, although this effect, too, requires supportive local conditions to manifest fully.

Another important channel through which DIF promotes HQED is industrial structure upgrading. DIF facilitates the flow of resources to emerging sectors such as green technology, artificial intelligence, and digital services, while also helping traditional industries transition to more sustainable and efficient models. This economic restructuring strengthens both productivity and environmental performance. The authors find that roughly 30% of the total impact of DIF on economic quality is mediated through this upgrading mechanism.

Policy implications: Infrastructure, inclusion and risk management

Based on the findings, the authors recommend a regionally differentiated policy approach. In the underperforming central and western regions, targeted investments in digital infrastructure, fintech platforms, and education programs are urgently needed. Government support should focus on enabling foundational access and minimizing digital exclusion for vulnerable populations.

In already-developed eastern regions, policies should incentivize continuous innovation in digital financial services, including AI-based credit scoring, blockchain applications, and cybersecurity measures. These tools can help maintain economic leadership while minimizing risks.

Regulatory bodies must also recognize the non-linear, conditional nature of DIF’s effectiveness. Over-expansion without corresponding infrastructure or literacy support can worsen inequality and increase systemic risks. Policymakers are thus urged to balance innovation with inclusive safeguards to ensure DIF promotes equitable and sustainable development across all regions.

The authors call for further research using micro-level data to explore how DIF affects different stakeholder groups, such as small businesses or low-income households. They also advocate for cross-country comparisons to test whether the observed effects hold across different regulatory and institutional environments.