Research on the impact of government digital infrastructure on urban economic resilience: a case study of the Yangtze River Delta urban agglomeration

Introduction: Against the backdrop of the rapid development of the digital economy, information infrastructure has become a key support for enhancing the economic resilience of regions. Exploring the impact of digital infrastructure-related policies on urban economic resilience is of great significance for promoting regional high-quality development.

Methods: Taking the Yangtze River Delta urban agglomeration as the research sample, this paper uses panel data of 27 cities from 2013 to 2022 and adopts the progressive difference-in-differences (DID) model to empirically examine the impact of the “Broadband China” policy on urban economic resilience. Robustness test methods including parallel trend test, placebo test, and PSM-DID are also employed to verify the reliability of the research conclusions.

Results: The results show that the “Broadband China” policy significantly enhances the economic resilience of cities, with a robust positive effect. Mechanism analysis reveals that the policy indirectly boosts economic resilience through two channels: increasing government scientific spending and promoting the development of digital finance, demonstrating a logic of “resource optimization-innovation-driven financial empowerment”. Heterogeneity tests indicate that the policy effect is more pronounced in large cities and those with a favorable business environment. Robustness tests further validate the reliability of the conclusion.

Discussion: This study confirms that the construction of digital infrastructure not only enhances the resilience, recovery, and evolution capabilities of cities but also promotes high-quality economic development through informatization and innovation. The findings provide empirical evidence for improving government science and technology policies and promoting regional digital transformation.

1 Introduction

The rapid development of information technology is profoundly reshaping the global economic structure and operation mode, driving the economic system towards digitalization, networking and intelligence. As a key foundation supporting the development of the digital economy, information infrastructure - especially broadband networks - has become a core element for enhancing regional competitiveness and economic resilience (Aliyev, 2025). In particular, external shocks in the contemporary economic environment often take diverse forms, including global financial fluctuations, public health crises such as the COVID-19 pandemic, supply chain disruptions, natural disasters, and geopolitical conflicts. These shocks can cause sudden interruptions in production and trade, capital flow volatility, and employment instability. In the process of responding to external shocks and achieving high-quality development, the construction of information infrastructure not only relates to the risk-resistance capacity of the economic system, but also affects its recovery speed and structural optimization level (Wang et al., 2025). From the perspective of resilience theory (Holling, 1973; Martin and Sunley, 2015), economic systems can be understood as complex adaptive networks that continuously evolve through interactions among technology, institutions, and innovation. Digital infrastructure serves as a critical “connective tissue” within these systems, enabling real-time information flow, resource reconfiguration, and adaptive governance. Therefore, strengthening digital infrastructure becomes not only a technological agenda but also an institutional and resilience-building strategy for cities.

During the process of promoting informatization and economic digital transformation in China, great emphasis has been placed on the construction of broadband networks. Since the 1990s, the scale of broadband users in China has continued to expand, but issues such as uneven regional development and insufficient technological innovation capabilities still exist (Hansen and Winther, 2011). Therefore, in 2013, the State Council issued the “Broadband China” Strategy and Implementation Plan, clearly elevating broadband network construction to a national strategy and setting the development goals of “popularization, speed-up, and quality improvement”. Subsequently, the Ministry of Industry and Information Technology and the National Development and Reform Commission selected 117 “Broadband China” demonstration cities from 2014 to 2016 in three rounds to promote the modernization of information infrastructure through the example of these cities, and to enhance the national level of digital development. Globally, several countries have pursued similar strategies to strengthen their digital resilience through broadband policies. For instance, the European Union’s “Digital Agenda for Europe,” South Korea’s “Broadband IT Korea” initiative, and the U.S. “National Broadband Plan” all emphasize broadband as a foundation for inclusive growth, innovation, and crisis response capacity (Bo, 2025). Compared with these international experiences, China’s approach exhibits several distinctive features: while the EU and the U.S. focus more on market competition, regulatory reform, and narrowing digital divides, and South Korea highlights demand-driven innovation and early technology adoption, China’s broadband strategy is characterized by strong governmental coordination, large-scale infrastructure investment, and rapid nationwide rollout. This difference in governance mode provides an important basis for examining how state-led infrastructure expansion influences urban economic resilience—a mechanism less discussed in OECD-focused literature. However, while these studies demonstrate broadband’s potential to enhance innovation ecosystems and economic adaptability, empirical evidence from developing economies—especially within the context of large-scale government-led infrastructure policies—remains relatively scarce. This makes China’s “Broadband China” policy an important case for comparative analysis and theoretical enrichment. In the context of increasingly fierce global digital economy competition, the “Broadband China” strategy is not only a systematic measure for the construction of technological infrastructure, but also an important policy tool to support economic transformation and upgrading (Li et al., 2025). By accelerating the popularization of broadband networks, improving the information circulation environment, and promoting the development of the digital industry, this policy helps optimize resource allocation, promote the upgrading of the industrial structure, and enhance the city’s ability to cope with economic fluctuations and external shocks (He et al., 2024). Compared with international broadband initiatives, China demonstrates a more direct linkage between digital infrastructure expansion and macroeconomic resilience enhancement, providing additional empirical insights for global digital resilience research.

The Yangtze River Delta urban agglomeration is one of the regions in China with the most vigorous economy, the highest degree of openness, and the strongest innovation capabilities. It undertakes important tasks related to national innovation-driven development and high-quality growth. Studying the implementation effect of the “Broadband China” policy in this region can reveal the mechanism of how digital infrastructure enhances economic resilience, thereby bridging the gap between digitalization policy evaluation and resilience theory. In addition, this research contributes to the comparative literature on how government-led digital infrastructure initiatives can stimulate systemic resilience in the face of global uncertainties such as economic downturns or pandemics. Finally, while this study employs the difference-in-differences (DID) model to estimate the causal effect of the policy, it also acknowledges potential externalities and omitted variable concerns. Regional heterogeneity, macroeconomic shocks, or concurrent national policies could influence the observed effects. Addressing these factors in robustness and future studies will further enrich the understanding of digital infrastructure’s role in resilience building.

In summary, this study explores the impact of the “Broadband China” policy on urban economic resilience in the Yangtze River Delta urban agglomeration by combining resilience theory, innovation system theory, and digital economy perspectives. It aims to provide both empirical evidence and theoretical insight into how digital infrastructure construction contributes to the adaptive and sustainable growth of cities.

2 Theoretical analysis and research hypotheses

2.1 The direct impact effect of digital infrastructure construction on the economic resilience of cities

Economic resilience refers to the ability of a city or region to withstand external shocks, recover quickly, and achieve adaptation and transformation (Simmie and Martin, 2010). In the era of digital economy, information infrastructure, especially broadband networks, has become a crucial support for enhancing economic resilience. It achieves this by facilitating information flow, improving resource allocation efficiency, and optimizing decision-making mechanisms, thereby enhancing the risk-resistance and recovery capabilities of urban systems (Forman et al., 2012).

Firstly, the digital infrastructure has enhanced the interconnection of the urban economic system. The broadband network, as the “nervous system” of modern economy, has facilitated the efficient flow and sharing of resources among different entities (Moriset and Malecki, 2009). Enable cities to rapidly adjust their production and operation through network effects in crisis situations, and enhance the system’s self-regulation and adaptability. Secondly, broadband networks are an important driving force for technological innovation, and technological innovation is the core factor for enhancing economic resilience (Brynjolfsson and McAfee, 2014). It achieves this by accelerating the dissemination of information and knowledge, reducing innovation costs, and promoting the development of emerging industries and the optimization of the industrial structure (Bertschek et al., 2013; Zou, 2024). Furthermore, it enhances the city’s resilience and adaptability in responding to economic fluctuations. Secondly, the construction of broadband infrastructure has improved the city’s ability to withstand external shocks. This is achieved by enhancing the timeliness of information transmission and the speed of decision-making responses, thereby strengthening the emergency response and flexible adjustment capabilities of the government and enterprises (Chen et al., 2025). Especially during emergencies such as the pandemic, broadband networks have ensured the continuity of enterprises' remote work and digital operations, significantly enhancing the recovery and adaptability of the economic system (Yu et al., 2025).

In conclusion, the popularization and upgrading of broadband networks have jointly enhanced urban economic resilience by improving information flow, promoting technological innovation, and strengthening emergency response. Based on this, the following hypothesis is proposed:

Hypothesis 1

Hypothesis 1. The construction of “Broadband China” demonstration cities is conducive to enhancing the economic resilience of each city in the Yangtze River Delta urban agglomeration.

2.2 The mechanism of digital infrastructure construction in enhancing the economic resilience of cities

The construction of “Broadband China” demonstration cities not only directly enhances the resilience of urban economic systems by improving information infrastructure, but also indirectly exerts its influence through two paths: government scientific spending and the development of digital finance. Specifically, the policy increases governmental investment in technological infrastructure, which provides both the material and institutional foundation for innovation activities, while simultaneously promoting the expansion and accessibility of digital financial services, thereby creating an integrated system of technological and financial support for urban economies. This demonstrates the systematic enhancement effect of digital infrastructure policies on economic resilience within the framework of “technology investment–innovation-driven development–financial empowerment”.

Firstly, government scientific expenditures serve as a critical intermediary in the link between the “Broadband China” policy and urban economic resilience. By allocating financial resources to broadband construction and related technological innovation, the government not only improves information transmission efficiency and public service provision but also creates favorable conditions for regional innovation activities. According to the theory of the national innovation system (Lundvall, 1992; Nelson, 1993). Regional innovation capabilities depend on the collaborative interaction among enterprises, universities, research institutions, and government. The increased broadband coverage under the policy enhances knowledge flows, promotes technological cooperation, and facilitates the development of sectors such as smart cities, intelligent manufacturing, and e-government. These improvements contribute directly to both the production efficiency and structural resilience of cities (Maqousi et al., 2025). Secondly, the development of digital finance provides financial support and risk buffering mechanisms for the economic resilience of cities. According to the theory of institutional change (North, 1990) and the theory of financial inclusion (Ozili, 2020). The widespread adoption of information and communication technologies has laid the foundation for digital financial innovation. Digital finance has improved the financing conditions for small and medium-sized enterprises and innovative entities by expanding the coverage of financial services, reducing transaction costs, and enhancing the ability to identify risks. This has also strengthened market vitality. At the same time, broadband networks have enhanced the data processing and risk management capabilities of the financial system, and improved the stability of the financial market and the efficiency of capital allocation. (D Andrea and Limodio, 2024; Yang et al., 2022). Moreover, digital finance interacts closely with other forms of technological and institutional innovation. By enabling real-time information sharing and data-driven governance, broadband-based financial platforms support the development of smart cities, e-governance, and digital industrial ecosystems. These interactions create a multi-layered resilience structure where technology, finance, and governance mutually reinforce each other, enhancing cities’ adaptive capacity to shocks. In particular, digital finance not only supports innovation-led enterprises but also fosters inclusive growth by extending financial access to smaller firms and peripheral cities that previously faced financial exclusion (Demirgüç-Kunt et al., 2022). However, its impact may vary by city size: in larger cities, digital finance amplifies innovation efficiency and capital flows, while in smaller cities, it primarily contributes to risk sharing and market participation, thereby narrowing regional disparities in resilience.

In conclusion, the “Broadband China” policy has established a dual mechanism of technological innovation and financial empowerment by increasing scientific expenditures and promoting the development of digital finance. This has systematically enhanced the economic resilience of cities at the levels of resource allocation, innovation-driven development, and capital flow. Based on this, this paper proposes the following hypotheses:

Hypothesis 2

Hypothesis 2. The construction of “Broadband China” demonstration cities can enhance the economic resilience of the cities by increasing scientific expenditures and empowering the development of digital finance.

3 Research design and descriptive statistics

Given that the Yangtze River Delta region is one of the most economically dynamic areas in China, this study selects the panel data of 27 cities in the Yangtze River Delta urban agglomeration from 2013 to 2022. The dataset covers economy, finance, education, population, foreign investment, and policy implementation, providing strong regional representativeness. The designation of demonstration cities was not random; it depended on factors such as existing digital infrastructure, economic development level, and local government capacity, which correlate with economic resilience. To address potential endogeneity, we include extensive control variables and fixed effects, conduct parallel trend and dynamic DID tests, and apply a PSM–DID approach to balance pre-policy characteristics between treated and control cities. The data mainly come from the “China Urban Statistical Yearbook”, “China Education Statistical Yearbook”, “China Fiscal Yearbook”, “Foreign Investment Statistical Yearbook”, and the statistical bulletins of each city. Missing values are supplemented by local yearbooks and the “National Economic and Social Development Statistical Bulletin”, and the remaining missing parts are handled using interpolation methods. Macro data of cities (such as GDP, fixed asset investment, population, etc.) are used to calculate physical capital (pcs) and city size (cs), where physical capital is based on 2013 as the base period and estimated using the method of Zhang (2008) combined with the growth rate of fixed asset investment; human capital (hc) is measured by the proportion of college students in the total population; the “Broadband China” (BC) policy variable is defined based on the documents of the Ministry of Industry and Information Technology and the implementation time of the demonstration cities. After integrating multiple sources of data, a systematic panel data set for the Yangtze River Delta urban agglomeration from 2013 to 2022 is formed, providing a solid foundation for empirical analysis.

3.1 Specification of variables

3.1.1 Interpreted variable

In this study, urban economic resilience (ER) was taken as the dependent variable and was calculated by comprehensively evaluating the performance of 27 prefecture-level cities in the Yangtze River Delta urban agglomeration in terms of resistance, resilience and adaptability from 2013 to 2022. The study drew on the analytical framework and relevant literature of Martin and Sunley (2015). Specifically, resistance captures the city’s ability to withstand external shocks, measured by indicators such as economic diversity, employment stability, and infrastructure reliability; recovery emphasizes the speed and capacity of a city’s restoration after a disruption, using indicators including economic growth rate, government emergency response capability, and infrastructure repair speed; evolution focuses on the city’s adaptability and innovation capability, represented by indicators such as technological innovation, industrial upgrading, and institutional innovation (as shown in Table 1). When calculating the economic resilience (ER) of a city, this paper adopts a combined weighting approach using the entropy weight method and Analytic Hierarchy Process (AHP). The entropy weight method objectively determines the weights of indicators based on the variation and information contained in the data, reducing subjective bias, while AHP incorporates expert judgment to reflect the relative importance of different indicators according to theoretical and practical considerations (Yang et al., 2025). This combination ensures a balance between data-driven objectivity and expert-driven interpretability, making the index more robust and meaningful compared to principal component or factor analysis, which may obscure the contribution of individual indicators and reduce interpretability.

Table 1

Table 1. Economic resilience index system of cities in the Yangtze River Delta.

Finally, the resilience score of each city is calculated using the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) model, which ranks cities based on their proximity to an ideal resilience profile. This approach allows for a clear, interpretable, and comparative evaluation of urban economic resilience across multiple dimensions.

3.1.2 Core explanatory variables

The “Broadband China” policy (BC) is the core explanatory variable of this study, used to measure the impact of digital infrastructure construction on the economic resilience of cities. This policy enhances the adaptability and recovery capabilities of cities by promoting information communication technology and network infrastructure construction, particularly in terms of innovation and industrial structure optimization. Based on the Difference-in-Differences (DID) model, this study sets up a dummy variable for demonstration cities: if city i is designated as a demonstration city in year t, then BC = 1, otherwise it is 0, to identify the differences between demonstration cities and non-demonstration cities before and after the implementation of the policy. Between 2014 and 2016, a total of 16 cities in the Yangtze River Delta region were included in the demonstration scope (2014: Shanghai, Nanjing, Suzhou, Zhenjiang, Jinhua, Wuhu, Anqing; 2015: Yangzhou, Jiaxing, Hefei, Tongling; 2016: Wuxi, Nantong, Taizhou, Hangzhou, Ma’an), serving as the experimental group, while the remaining cities were the control group. This design helps to systematically evaluate the overall and differentiated impacts of the “Broadband China” policy on the economic resilience of cities in the Yangtze River Delta region.

3.1.3 Control variables

To reduce the bias caused by omitted variables, this paper adds key urban characteristic variables to the baseline regression model in order to improve the accuracy of identifying the impact of the “Broadband China” policy. Based on existing studies, the control variables include: the physical capital stock, which is the logarithm of capital stock (Zhao and Dong, 2025), Urban size is defined as the logarithm of the average annual population (Glaeser and Maré, 2001), Human capital refers to the proportion of college students in the population (Abel and Deitz, 2012), Government intervention, namely, the proportion of fiscal expenditure to GDP (Mensah and Adukpo, 2025) and direct foreign investment, that is, the proportion of foreign capital in GDP (Kwilinski, 2025). These variables can effectively control the economic, population and institutional differences among cities, thereby enabling a more accurate identification of the impact of digital infrastructure construction on economic resilience and enhancing the robustness of the results. In addition, each control variable is closely related to the development and effectiveness of digital infrastructure: cities with higher physical capital stock tend to have stronger capacity to support broadband deployment; larger urban size often corresponds to greater digital service demand and network externalities; higher levels of human capital facilitate the absorption and application of digital technologies; government intervention shapes the intensity of public investment in digital infrastructure; and foreign investment contributes to technology spillovers and digital industry development. Incorporating these variables thus helps isolate the specific contribution of the “Broadband China” policy from broader structural factors influencing digital infrastructure outcomes.

3.2 Model specification

This article regards the construction of “Broadband China” demonstration cities in the Yangtze River Delta region as a kind of quasi-natural experiment. A progressive double-difference model is constructed to explore the impact of government science and technology policies on the economic resilience of various cities in the Yangtze River Delta region. The specific setting of the baseline regression model is as follows (Model 1):

$E{R}_{it}={\beta }_0+{\beta }_1{BC}_{it}+\phi X_{it}+{\mu }_i+{\nu }_t+{\epsilon }_{it}(1)$

Here, $E{R}_{it}$ is the dependent variable, representing the urban economic resilience index of city $i$ in year $t$ in the Yangtze River Delta region. The core explanatory variable ${BC}_{it}$ represents the dummy variable for the “Broadband China” demonstration city construction policy in city $i$ in year $t.X$ represents other characteristic variables that may affect the urban economic resilience. ${\mu }_i$ and ${\nu }_t$ respectively represent the fixed effects for the city and the year. ${\epsilon }_{it}$ is the random error term.

3.3 Descriptive statistics

After integrating multiple sources of data, a systematic panel dataset of the Yangtze River Delta urban agglomeration from 2013 to 2022 was formed, providing a solid foundation for empirical analysis. The descriptive statistics results show that the urban economic resilience (ER) varies significantly among cities (standard deviation 0.061), the policy variable (BC) is bimodally distributed (standard deviation 0.501), and the other control variables also have significant differences, reflecting the imbalance in regional economic development and resource endowment, laying the foundation for subsequent heterogeneity analysis (see Table 2).

Table 2

Table 2. Descriptive statistics of variables.

Furthermore, this paper compares the average trend of urban economic growth quality in the control group and the experimental group from 2013 to 2022. As shown in Figure 1, both groups of cities showed an upward trend as a whole, indicating that China’s economy is transitioning from “quantity-driven” to “quality-driven”. Before the implementation of the “Broadband China” policy (before 2014), the economic growth quality trends of the two groups of cities were basically the same; however, after the policy was implemented (after 2014), the economic resilience index in the Yangtze River Delta region showed a significant decline in 2015, mainly due to factors such as China entering the “new normal”, strengthened capacity reduction policies, slowdown in fixed asset investment, and weakened external demand. Nevertheless, compared to the control group, the economic resilience of the demonstration cities (experimental group) decreased to a lesser extent, indicating that the “Broadband China” policy has to some extent alleviated the adverse effects of external shocks and has a positive effect on enhancing urban economic resilience. This conclusion will be further verified in the subsequent econometric analysis.

Figure 1

Figure 1. Economic resilience of cities in the control group and the experimental group from 2013 to 2022.

4 Empirical result analysis

4.1 Baseline regression analysis

According to the regression results in Table 3, column (1) represents the model without control variables, while columns (2) to (6) show the results after gradually adding control variables. “Broadband China” policy (BC) consistently demonstrates a significant and stable positive impact on urban economic resilience (ER), indicating that government science and technology policies can significantly enhance urban economic resilience, and this effect may stem from technological innovation incentives and industrial structure upgrading. The overall material capital stock (pcs) has a significant negative impact on urban economic resilience, especially in models (2) and (3), which may reflect the decline in efficiency due to excessive reliance on material resources. Urban size (cs) also shows a significant negative effect, suggesting that large cities are more susceptible to economic shocks, possibly due to resource concentration and increased management complexity. Human capital (hc) does not reach a significant level, but the direction is positive, indicating that its promoting effect is not yet obvious. Government intervention (gov) and foreign direct investment (FDI) have a positive impact on resilience, but statistically not significant. Overall, government science and technology policies are the core force for enhancing urban economic resilience, while the expansion of material capital and urban size may weaken this resilience.

Table 3

Table 3. Baseline regression.

4.2 Mechanism of action verification

In the previous empirical analysis, we found that the “Broadband China” policy (BC) has a significant positive impact on urban economic resilience (ER). This section will further explore through which pathways the Broadband China policy affects urban economic resilience. This part constructs the following mechanism model for identification. Specifically, on the basis of Model 1, two additional recursive models are added, as follows:

$ME{D}_{it}={\delta }_0+{\delta }_{1}B{C}_{it}+\phi X_{it}+{\mu }_i+{\nu }_t+{\epsilon }_{it}(2)$

$E{R}_{it}={\gamma }_0+{\gamma }_{1}B{C}_{it}+{\gamma }_{2}ME{D}_{it}+\phi X_{it}+{\mu }_i+{\nu }_t+{\epsilon }_{it}(3)$

Among them, MED represents a series of mediating variables. Model 2 examines the impact of the “Broadband China” policy on the mediating variables, while Model 3 investigates the role of the mediating variables in the quality of urban economic growth. By comparing the significance and coefficients of the main variables, the existence of the mediating effect can be determined. To ensure conceptual clarity, the mediating variables are defined and theoretically justified as follows. Fiscal Expenditure Bias (FEB) refers to the proportion of local government science and technology expenditures in total fiscal expenditures. It captures the degree to which government fiscal resources are reallocated toward technological innovation and information infrastructure following the implementation of the “Broadband China” policy. This shift reflects the government’s strategic emphasis on digital infrastructure and innovation capacity as a means to strengthen urban resilience. According to the theory of innovation-driven development, targeted fiscal investment in science and technology can stimulate knowledge diffusion, promote industrial upgrading, and enhance the capacity of cities to absorb external shocks (Bezpalov et al., 2019). Digital Financial Inclusion (DFI), on the other hand, measures the accessibility, coverage, and usage of digital financial services enabled by broadband networks. It reflects the extent to which information infrastructure facilitates financial innovation, reduces transaction costs, and improves financial inclusiveness. As digital platforms expand financial access for small and medium-sized enterprises and residents, they enhance liquidity, risk diversification, and overall economic flexibility—key components of urban economic resilience (Du et al., 2023). Data for FEB are obtained from the China Statistical Yearbook and China City Statistical Yearbook, while DFI is derived from the Peking University Digital Finance Research Center’s city-level index. Both variables are standardized using the min-max method, and DFI is constructed from sub-indicators of coverage, usage, and depth. To address potential endogeneity of DFI, we use its one-year lag in the mediation models and conduct robustness checks with instrumental variables such as regional internet penetration and local broadband investment. Regarding Hypothesis 2, this study analyzes the mechanism by which government science and technology policies affect the resilience of the urban economy from two dimensions: fiscal expenditure bias (FEB) and digital financial inclusion index (DFI). Fiscal expenditure bias (FEB) is represented by the ratio of local government science and technology expenditures to general fiscal expenditures, reflecting that resources are more allocated to information infrastructure and technological innovation after policy implementation, thereby promoting industrial upgrading and enhancing resilience to shocks. The digital financial inclusion index (DFI) reflects that the “Broadband China” policy promotes digital finance and infrastructure construction, improves financial accessibility and efficiency, enabling enterprises and residents to more flexibly respond to economic shocks.

The results in Table 4 indicate that the “Broadband China” policy (BC) significantly enhances urban economic resilience (ER) through multiple intermediary mechanisms. Among them, the fiscal expenditure bias (FEB) and the digital financial inclusion index (DFI) are the two main transmission paths. Firstly, the fiscal expenditure bias mechanism shows that after the policy implementation, local governments have a greater inclination in fiscal resource allocation towards information infrastructure and technological innovation fields, thereby promoting the optimization of the industrial structure and the enhancement of innovation capabilities. This resource reallocation not only strengthens the city’s innovation-driven foundation but also enhances its resilience and adaptability to external economic shocks. Secondly, the digital finance mechanism reveals that the “Broadband China” policy has improved the accessibility and efficiency of financial services by promoting the construction of digital infrastructure and the development of internet finance. The popularization of digital finance enables enterprises and residents to be more flexible in financing and consumption, helping to maintain the liquidity and market vitality of the economy during economic fluctuations, thereby enhancing the stability and resilience of the overall economic system.

Table 4

Table 4. Mechanism of action verification.

4.3 Heterogeneity analysis

To reveal the mechanism of the “Broadband China” policy, this study conducts heterogeneity analysis from three dimensions: province, city size, and business environment. The results show that the policy has significant differences in its impact on economic resilience (ER) under different city sizes and business environments (see Table 5). In terms of city size, the policy can significantly enhance resilience in both large cities and small cities, but the paths are different: large cities rely on well-established infrastructure to strengthen their resilience; small cities, on the other hand, make up for their development shortcomings through broadband construction. Specifically, broadband expansion in small cities improves the connectivity of local industries and reduces information asymmetry, allowing enterprises to integrate more easily into regional and national value chains. By facilitating access to e-commerce platforms, remote services, and digital public management systems, broadband construction enables small cities to overcome geographical constraints and limited market size. It also promotes human capital upgrading through online education and training, and attracts external investment by improving the transparency and efficiency of government services. These channels jointly enhance the innovation potential, market participation, and adaptability of small cities, thereby compensating for their original disadvantages in physical infrastructure and capital accumulation. The physical capital in small cities significantly promotes resilience, while its effect is not significant in large cities, indicating that the sources of resilience are different. This suggests that in small cities, physical investment and digital infrastructure are complementary—broadband construction amplifies the productivity effects of physical capital—whereas in large cities, diminishing returns to physical capital make innovation and technological upgrading the dominant drivers of resilience. In terms of the business environment, the policy effect is stronger in cities with excellent environments, and the institutional and market conditions have a magnifying effect; while in areas with poor environments, broadband construction can still enhance the ability to resist risks to a certain extent. This is because the improvement of digital infrastructure reduces transaction costs and strengthens the resilience of supply chains even where institutional support is weak. In contrast, in cities with favorable business environments, broadband acts as a catalyst for innovation clustering and efficient resource allocation, leading to a stronger cumulative effect on economic resilience. In addition, in cities with a favorable business environment, physical capital shows a negative impact, mainly due to the decline in efficiency caused by excessive capital accumulation. Such cities, due to their institutional advantages and strong market vitality, are more likely to attract a large amount of investment. However, if the speed of capital input exceeds the simultaneous improvement of labor skills, technological innovation and industrial structure upgrading, the new capital will be difficult to be fully absorbed, thus resulting in diminishing marginal output (Solow, 1956). Furthermore, capital is more likely to cause resource misallocation and inefficient investment in such cities, such as redundant construction or investment in low-return industries, resulting in a decline in overall utilization rate (Hsieh and Klenow, 2009). The combined effect of the above-mentioned mechanisms may lead to a negative impact of physical capital on economic resilience in cities with a favorable business environment.

Table 5

Table 5. Heterogeneity analysis.

4.4 Robustness test

4.4.1 Parallel trend test

When analyzing the impact of the “Broadband China” policy on economic resilience, it is crucial to verify whether the multi-period DID model satisfies the parallel trend assumption. This assumption requires that the economic growth trends of the treatment group and the control group should be basically the same before the implementation of the policy, in order to ensure the reliability of the identification of the policy effect. Therefore, this paper constructs the following Model 4 for test:

$E{R}_{it}=\alpha +u_i+{\lambda }_t+\delta \left(trea{t}_i\times pos{t}_{it}\right)+\beta x_{it}+{ϵ}_{it}(4)$

Here, $u_i$ represents the city fixed effect, and ${\lambda }_t$ represents the time fixed effect. $\delta$ denotes the impact coefficient of the “Broadband China” policy on urban economic resilience. For the years following the policy implementation, a variable $pos{t}_{it}$ is constructed for city i in year t to capture the policy effects across different years. $\beta x_{it}$ represents a series of control variables, and ${ϵ}_{it}$ is the random error term.

It can be seen from Figure 2 that the “Broadband China” policy has a significantly positive impact on the urban economy of the Yangtze River Delta. Before the implementation of the policy (−3 to −1 year), the estimates are close to zero, and the confidence interval contains zero, indicating that the economic trends of the treatment group are consistent with those of the control group, in line with the parallel trend hypothesis. After the implementation of the policy, the effect continues to rise and reaches the peak in the third year, indicating that the broadband construction significantly promotes the economic growth of the demonstration cities, especially in the expansion stage of infrastructure and information investment in the early stage of the policy. Since then, the effect has gradually declined but is still positive, reflecting the marginal diminishing of the policy and the influence of external economic factors. In general, the policy has significantly improved urban economic resilience and growth in the years after its implementation.

Figure 2

Figure 2. Parallel trend test.

4.4.2 Placebo test

In order to exclude the interference of random factors, this paper conducts a placebo test to verify the robustness and causality of the “Broadband China” policy on economic resilience. First of all, referring to the research of Liu et al. (2024), O'Garra et al. (2025), the counterfactual test is conducted 2 years ahead of the policy implementation time. Secondly, a number of cities are randomly selected from the 27 sample cities, which are assumed to become demonstration cities in different virtual years, and the DID model is used to repeat the random regression 300 times. The kernel density distribution of the spurious policy effect is close to normal, indicating that the random factors do not lead to significant spurious effects, and verifying the robustness of the policy impact.

The placebo test results (as shown in Figure 3) indicate that the average value of the 300 false regression coefficients is close to zero, and the kernel density distribution is approximately standard normal. The false policy effects are concentrated around zero and are not significant. Most p-values are far above 0.05, indicating that no significant effect was produced when random years and cities were set. Thus, it can be seen that the actual impact of the “Broadband China” policy was not caused by random factors, and its causal relationship is robust and reliable.

Figure 3

Figure 3. Placebo test.

4.4.3 Other robust tests

To ensure the robustness of the conclusion, this paper conducted robustness tests from three perspectives: Firstly, the propensity score matching - difference-in-differences (PSM-DID) method was adopted to reduce sample selection bias and endogeneity, and the results were consistent with the main regression, showing a significantly positive policy effect. Secondly, provincial capitals and municipalities directly under the Central Government were excluded to eliminate the estimation bias caused by resource concentration, and the policy impact remained significant. Thirdly, the policy lag period was introduced, and the results indicated that the policy effect remained significant in the lag period of one period and was persistent. Table 6 shows that the coefficients of the policy variables in the three tests are all significant at the 1% level, verifying the robust and positive effect of the “Broadband China” policy on economic growth and economic resilience improvement.

Table 6

Table 6. Other Robustness tests.

5 Conclusion and suggestion

5.1 Conclusion

This study takes the Yangtze River Delta urban agglomeration as the sample and systematically analyzed the impact of the “Broadband China” policy on the economic resilience of cities. Through multi-dimensional empirical research such as baseline regression, mechanism analysis, heterogeneity analysis, and robustness tests, the results showed that government-led technological policies have a significant positive effect in enhancing cities' resilience against external shocks, promoting economic recovery and continuous evolution. After controlling for factors such as physical capital, human capital, city size, government intervention, and foreign investment, the empirical results indicated that the policy significantly improved the economic resilience (ER) of cities, indicating that the improvement of digital infrastructure can enhance the stability and adaptability of the urban economic system and provide support for regional high-quality development. The mechanism analysis showed that the policy achieved resilience enhancement through three paths: first, improving information infrastructure to enhance resource allocation efficiency and information circulation speed; second, promoting digital technological innovation to optimize the industrial structure and accumulate technological factors; third, expanding the space for information governance to enhance structural risk resistance capacity. The heterogeneity analysis indicated that the policy effect varies by city type: provincial capitals and economically strong cities benefited more significantly, while small and medium-sized cities made up for their development shortcomings through digital construction and achieved “digital empowerment” resilience growth. The institutional environment and business conditions also have a moderating effect on the policy effect, indicating that the implementation of the policy needs to be matched with the local development stage. The economic growth analysis further showed that after the implementation of the policy, urban per capita GDP, the number of industrial enterprises, and transportation volume all significantly increased, presenting a “growth - resilience” synergy effect. Through parallel trend tests, placebo tests, and various robustness analyses (including PSM-DID matching, excluding provincial capitals and lagged regression), the robustness and causality of the research conclusions were verified.

In conclusion, this study demonstrates that government science and technology policies possess the “dual rationality” characteristic in the urban economic system: they not only reflect the role of scientific rationality in optimizing the economic structure, but also highlight the institutional power of governance rationality in addressing complex risks and promoting long-term resilient development. The “Broadband China” policy, as a model combining scientific rationality and governance rationality, provides empirical evidence for understanding the governance philosophical connotation of digital infrastructure policies.

Nevertheless, this study also acknowledges several limitations that should be interpreted with caution. First, although regional heterogeneity is partly explored through subgroup analysis, the Yangtze River Delta represents a highly developed and institutionally advanced region, which may limit the generalizability of the findings to less developed areas. Second, potential macroeconomic shocks—such as trade fluctuations, major public health events, or cyclical downturns—may overlap with the policy period, and although robustness tests mitigate endogeneity concerns, fully isolating these shocks remains challenging. Third, concurrent national strategies (e.g., innovation-driven development, smart city initiatives, and industrial upgrading policies) may interact with the Broadband China policy, creating policy bundles whose effects cannot be entirely separated within the DID framework. Addressing these issues in future research—through multi-policy interaction models, higher-frequency data, or quasi-experimental designs using micro-level indicators—will help provide a more comprehensive understanding of how digital infrastructure influences long-term urban resilience.

5.2 Suggestion

Based on research findings and theoretical analysis, the following policy recommendations are proposed, with the framework of “technological rationality - governance rationality - resilient governance” to promote high-quality and sustainable urban development. First, the inclusiveness and balance of digital infrastructure should be strengthened. At the national level, a hierarchical layout and regional coordination mechanism can be established. Through fiscal transfer payments, special funds, and policy-based financial tools, infrastructure can be extended to small and medium-sized cities, resource-based cities, and underdeveloped regions to prevent the expansion of the digital divide and achieve a balanced distribution of information flow, technology flow, and capital flow, providing a foundation for regional overall resilience. Specifically, in less developed or smaller cities, policymakers should prioritize improving broadband accessibility and affordability to enhance basic connectivity, while in large metropolitan areas, more emphasis should be placed on upgrading network quality, cybersecurity, and intelligent infrastructure to support high-value innovation activities.

Second, the systematic integration of science and technology policies and the innovation ecosystem should be promoted. Deepen the collaborative governance of science and technology policies and industrial policies, and build an innovation ecosystem centered on data elements, intellectual property rights, and research networks. Optimize the allocation of research funds, improve innovation incentives, encourage industry-university-research collaboration, make digital infrastructure the “driver” of scientific and technological innovation, and enhance the adaptability and evolutionary power of the economic system through innovation diffusion. For cities at different development stages, differentiated innovation strategies should be adopted: developing cities should focus on cultivating digital skills and application-oriented innovation, while advanced cities should promote frontier technologies and platform-based collaborative R&D.

Third, an interactive mechanism for digital governance and institutional resilience should be constructed. Digital infrastructure should be incorporated into the core of urban governance. Through data-driven public management, smart governance, and emergency decision-making platform construction, the government’s perception, response, and learning capabilities can be enhanced, achieving a leap from “technological resilience” to “institutional resilience”, making science and technology policies an effective tool for improving governance capabilities and public rationality. In practice, local governments can establish digital governance pilot zones or cross-department data-sharing mechanisms to improve policy coordination and transparency, which are essential for differentiated resilience governance among cities.

Fourth, a feedback and evaluation system for digital policies should be improved. Establish a closed-loop mechanism of planning - implementation - evaluation - feedback. Utilize big data and artificial intelligence to monitor policy performance in real time, dynamically adjust policies, and achieve the coordinated unity of goals, means, and social value, avoiding structural risks caused by short-term performance orientation. Policymakers should also develop city-level digital resilience assessment indicators to identify the strengths and weaknesses of each region, enabling targeted improvement strategies.

Fifth, regional digital collaboration and resilience co-construction should be promoted. At the Yangtze River Delta level, a unified digital standard and information sharing platform should be constructed, promoting cross-city data interconnection, technology co-research, and industrial linkage, establishing a digital governance collaboration mechanism among governments, and enhancing the overall ability of the region to cope with external shocks, forming a “multi-center governance, resilience symbiosis” digital development pattern. For less developed cities within the region, participation in joint digital projects with core cities can accelerate knowledge spillover and infrastructure upgrading.

In conclusion, the experience of the “Broadband China” policy indicates that the integration of technological rationality and governance rationality is the core logic for building urban resilience. Future policy implementation should consider differentiated development paths—balancing efficiency, inclusiveness, and security—to ensure that both large and small cities can benefit from digital transformation. With the governance philosophy of technological empowerment as the guide, a sustainable urban resilience governance system should be constructed to achieve the coordinated development of economic growth and social stability.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

Author contributions

XC: Formal Analysis, Methodology, Software, Writing – original draft, Writing – review and editing. LL: Conceptualization, Formal Analysis, Methodology, Writing – review and editing. YZ: Data curation, Resources, Software, Writing – review and editing. LX: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Writing – review and editing. CZ: Conceptualization, Investigation, Software, Writing – review and editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This research was supported by Major Decision-making Consultation Project of the Shanghai Municipal Government Development Research Center (The person receiving the funding is XC); grant number: (2025-AZ-17).

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

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