Fostering Sustainable Development: How Local Fiscal Sustainability Enhances High-Quality Corporate Innovation in China

Abstract

High-quality corporate innovation serves as a critical driver for achieving corporate sustainable development. This study bridges the gap between macroeconomic fiscal sustainability and microeconomic innovation quality. Specifically, this paper investigates the influence of local fiscal sustainability on high-quality corporate innovation, examining the underlying mechanisms and heterogeneous effects. Methodologically, data were collected using Python-based retrieval and web-scraping techniques. A multi-dimensional index of local fiscal sustainability was constructed, comprising five key dimensions to quantitatively map provincial fiscal sustainability across China. Corporate innovation quality was measured using patent citation metrics. Employing panel data from A-share listed companies over the 2015–2023 period, we implemented a two-way fixed-effects model for rigorous empirical econometric analysis. The findings indicate a significant positive relationship between local fiscal sustainability and high-quality corporate innovation. This result remains robust after a battery of robustness tests, including the use of instrumental variable (IV) methods. Mechanism analysis reveals that the resource compensation effect is the primary channel. Furthermore, our analysis identifies heterogeneity across varying innovation environments, economic regions, and industry characteristics. The positive influence is particularly pronounced in provinces with stronger intellectual property protection, firms located in the eastern regions, and High-Tech Enterprises. Collectively, the conclusions drawn from this research offer valuable policy implications for strengthening local fiscal sustainability and enhancing high-quality corporate innovation.

1. Introduction

In recent years, the emphasis on sustainable development has grown significantly. Innovation plays a crucial role in enabling firms to maintain their competitive advantage and achieve long-term growth. More precisely, it is high-quality corporate innovation that allows firms to keep pace with technological progress, and gain initiative in highly competitive environments [1]. On the one hand, innovation embodies a process of ‘creative destruction’, highlighting the inherent costs and uncertainties associated with innovation. On the other hand, high-quality corporate innovation generates positive externalities, benefiting not only individual enterprises but also wider economic ecosystems. Due to these spillover effects, market mechanisms and firms’ own resources alone are often insufficient to achieve breakthrough innovations. Therefore, how to better leverage government guidance to facilitate high-quality corporate innovation and sustainable corporate development has become an urgent issue that requires further examination. Hence, optimizing government guidance to foster high-quality corporate innovation and promote sustainable development demands immediate scholarly investigation.

Concurrently, fiscal sustainability serves as a critical determinant of both economic sustainability and fiscal health. Since 2019, the COVID-19 pandemic has exerted profound adverse effects globally, while population aging and government debt repayment challenges have further strained fiscal sustainability worldwide. In emerging economies like China, where the government leadership plays a dominant role, public authorities remain the pivotal arbiter of resource allocation and economic guidance. The 2023 Central Economic Work Conference in China highlighted that years of large-scale tax reduction and fee exemption policies have led to an expanding fiscal deficit, escalating government debt, and intensifying fiscal imbalances. The 2023 Government Work Report emphasized the urgency of enhancing fiscal sustainability, necessitating a strategic transition from an investment-driven growth model to an innovation-driven development paradigm in China. Existing research has indicated that Chinese corporate innovation outcomes are predominantly reflected in quantitative metrics rather than qualitative dimensions [2]. Nevertheless, few studies have directly examined the impact of local fiscal sustainability on high-quality corporate innovation.

Consequently, this raises several fundamental research questions. Can local fiscal sustainability enhance high-quality corporate innovation? If such causality exists, what are the underlying mechanisms driving this relationship? How does the impact of local fiscal sustainability on corporate innovation quality vary across heterogeneous contexts? Given the unique institutional characteristics of the Chinese fiscal system, as well as its economic structure and socioeconomic challenges, empirical research within this specific context is warranted. A comprehensive examination of how local fiscal sustainability influences high-quality corporate innovation carries significant theoretical and practical implications.

The determinants of corporate innovation quality have long been a prominent focus in the academic literature. These determinants span two broad dimensions. At the firm level, key determinants include enterprise size and R&D investment intensity. At the macroeconomic level, influential factors encompass fiscal and tax policies as well as government debt levels [3]. Although prior research has demonstrated that local fiscal sustainability significantly promotes corporate green technology innovation [4], these studies predominantly rely on patent application counts as proxies for innovation performance. Quantitative increases in innovation output do not inherently translate into qualitative improvements. Critically, this quantitative approach presents an inherent limitation by potentially overlooking the value-driven dimensions of innovation quality (e.g., technological novelty, commercial relevance), which fundamentally underpin high-quality corporate innovation. Within the literature on macroeconomic drivers of innovation quality, several lines of inquiry are particularly pertinent. The existing research has identified specific fiscal instruments that influence corporate innovation quality. For instance, studies have shown that government procurement [5] and fiscal decentralization [6] can significantly promote corporate innovation quality.

However, these studies typically concentrate on singular fiscal policy tools. They often overlook a more holistic assessment of fiscal health, which would incorporate multifaceted aspects, such as fiscal revenue, fiscal expenditure, fiscal risk, budgetary execution, and development objective. Unlike isolated metrics, the concept of fiscal sustainability captures the overall resilience and viability of public finance, which is fundamental to ensuring fiscal security and effective policy implementation. Meanwhile, local governments may prioritize short-term economic targets, potentially implementing policies that compromise long-term corporate interests, which consequently suppresses innovation. Consistent with this concern, expansions in local government debt have a significant negative effect on the quality of corporate innovation [3]. Given these conflicting theoretical arguments and empirical findings, the net impact of local fiscal sustainability on high-quality corporate innovation remains ambiguous and empirically unresolved. This research gap thus presents a compelling opportunity for rigorous empirical investigation.

To address this gap, this study employs Python-based (version 3.0) retrieval and web-scraping techniques to compile a comprehensive dataset. Diverging from previous studies, which focused narrowly on tax policies or debt levels as singular measures of local fiscal sustainability, this study constructs a multidimensional index system to comprehensively assess local fiscal sustainability. This index system integrates five core dimensions, encompassing fiscal revenue, fiscal expenditure, fiscal risk, budgetary execution, and development objective. To measure high-quality corporate innovation, we utilize patent citation data, which provides a more nuanced assessment than simple patent counts. This framework enables us to construct a matched panel dataset linking macro-level fiscal sustainability with micro-level innovation quality.

Our findings demonstrate that higher levels of local fiscal sustainability significantly enhance high-quality corporate innovation. We further examine the underlying mechanism by employing the resource compensation effect framework, which elucidates how local fiscal sustainability creates institutional incentives for corporate innovation activities. Additional analyses reveal heterogeneous effects across different innovation environments, economic regions, and industry characteristics. Building on the empirical findings, our study contributes to both empirical knowledge and practical governance by elucidating the economic impact of local fiscal sustainability on corporate high-quality innovation.

This study offers three principal contributions to the existing literature. Firstly, we advance the conceptual framework of macro–micro linkages through integrating two hitherto disconnected research domains: macro-level local fiscal sustainability and micro-level high-quality corporate innovation. Whereas the existing literature has predominantly neglected the economic consequences of local fiscal sustainability, this study pro-vides a systematic analysis of how local fiscal sustainability functions as an institutional driver for corporate innovation quality. Our approach not only broadens the research perspective on local fiscal sustainability, but also addresses a critical gap in the literature by linking macro-level fiscal sustainability to micro-level innovation quality.

Secondly, our study expands the theoretical framework concerning the drivers of high-quality corporate innovation. Whereas the prior research has predominantly concentrated on the effects of isolated fiscal policies, often lacking a comprehensive perspective that integrates overall local fiscal sustainability, our research tackles this gap by employing a comprehensive analytical framework that examines local fiscal sustainability as a multidimensional systemic construct. Specifically, we identify and validate the resource compensation effect, providing robust empirical evidence of how macro-level fiscal sustainability shapes micro-level sustainable development. Furthermore, this study enriches the literature on innovation determinants by introducing local fiscal sustainability as a novel analytical dimension, thereby significantly extending the theoretical and empirical boundaries of the field.

Thirdly, we advance the literature methodologically by employing more precise and comprehensive indicators, thereby directly redressing the measurement limitations that plague existing studies. Previous research on innovation quality has often relied on patent application counts or R&D expenditures, which capture innovation input or quantity rather than quality. Similarly, local fiscal sustainability has frequently been oversimplified to single indicators like fiscal deficit or debt ratios. To overcome these shortcomings, we employ more granular and robust measures: patent citation data to capture enterprise innovation quality and a multi-dimensional index system for local fiscal sustainability. This enhanced methodological rigor allows for a more accurate and robust estimation of the underlying mechanisms and heterogeneous effects, thereby significantly deepening the relevance and precision of related research.

The remainder of this paper proceeds as follows: Section 2 develops the theoretical analysis and research hypotheses, followed by empirical predictions. Section 3 describes the research design, including the sample and data, variables, and method. Section 4 presents the main results and robustness tests. Section 5 conducts a mechanism validation and multidimensional heterogeneity analyses. Section 6 synthesizes the empirical findings, discusses theoretical and policy implications, acknowledges methodological limitations, and proposes directions for future research.

2. Literature Review and Research Hypothesis

2.1. Local Fiscal Sustainability

Advanced economies worldwide have maintained sustained focus on fiscal sustainability. Countries including the United States, the United Kingdom, Canada, and Australia regularly publish Fiscal Sustainability Reports, projecting future fiscal revenue, expenditure, and sustainability condition. Fiscal sustainability is intrinsically linked to fiscal security, effective government functioning, and the achievement of national strategic development objectives. Consequently, it has garnered increasing attention from both policymakers and academic researchers. Buiter [7] was the first to define fiscal sustainability as the enduring capacity of public finance. He argued that it should be evaluated through an integrated assessment of fiscal operations and debt dynamics, with specific emphasis on financing capacity, solvency, and maintenance of dynamic fiscal equilibrium. The existing literature on local fiscal sustainability has primarily focused on four research domains: conceptual foundations, measurement methodologies, determinant factors, and economic implications.

Contemporary scholarship on the conceptual foundations of local fiscal sustainability has converged around three core areas: fiscal equilibrium, financing capacity, and solvency. The first perspective emphasizes fiscal revenue–expenditure equilibrium. Proponents of this view posit that government debt is sustainable if economic growth consistently enables fiscal balance across all periods [8]. The second perspective focuses on debt financing capacity. This approach argues that local fiscal sustainability persists as long as governments retain access to new borrowing channels in capital markets [9]. The third perspective centers on solvency risk. According to this view, sustainability is achieved when governments can service their debt obligations on schedule without triggering default events. Adopting a broad perspective, local fiscal sustainability reflects a dynamic process encompassing fiscal risk, fiscal space, and fiscal philosophy [10]. The definition of local fiscal sustainability adopted in this study aligns with this broad conceptual perspective, encompassing five interrelated dimensions: fiscal revenue, fiscal expenditure, fiscal risk, budgetary execution, and development objective. Specially, this multidimensional construct emphasizes the capacity to maintain long-term dynamic fiscal equilibrium in revenue and expenditures, thereby ensuring the uninterrupted delivery of essential government functions.

Additionally, regarding the measurement of local fiscal sustainability, scholars have developed diverse methodological approaches that can be broadly categorized into several streams. The single-indicator approach employs straightforward metrics such as fiscal revenue–expenditure ratios, government debt-to-GDP rates, and government financing gaps to quantify local fiscal sustainability. The fiscal reaction function approach utilizes nonlinear regression techniques to evaluate sustainability [11]. Dynamic Stochastic General Equilibrium (DSGE) models capture the complex interactions between fiscal policy, economic fluctuations, and sustainability constraints under uncertainty [12]. Furthermore, researchers have constructed early warning systems by developing multi-dimensional indicator frameworks. These systems employ various weighting schemes and analytical techniques, including factor analysis, cluster analysis, hierarchical analysis, and entropy methods. Such composite approaches attempt to capture the multifaceted nature of local fiscal sustainability beyond what single metrics can provide.

Moreover, scholars have investigated the determinants of local fiscal sustainability from multiple perspectives, including tax revenue sharing, fiscal incentives, digital economy, and population aging [13]. The value-added tax (VAT) revenue-sharing reforms significantly enhance local fiscal sustainability [14]. A research consensus has emerged that technological advancement and economic digitalization exert a significant positive effect on local fiscal sustainability [15].

Lastly, the existing research has revealed a notable gap in the understanding of the economic consequences of local fiscal sustainability. A limited body of literature has examined how local fiscal sustainability affects the provision of public goods, such as infrastructure investments and educational expenditure [16]. More specifically, the extant literature lacks a systematic investigation into how local fiscal sustainability mechanistically influences corporate innovation behavior. Hence, this paucity of empirical evidence at the micro-level constitutes a critical research gap.

2.2. High-Quality Corporate Innovation

High-quality corporate innovation serves as a fundamental pillar for enhancing firms’ core competitiveness and achieving sustainable development. Moreover, it functions as a critical driver of broader socioeconomic growth and technological advancement. Haner [17] pioneered the conceptualization of innovation quality by proposing a three-dimensional evaluation framework encompassing product innovation, management innovation, and process innovation. Subsequent research on innovation quality has primarily concentrated on refining measurement methodologies and identifying determinant factors of innovation quality.

In recent years, numerous measurement methods for innovation quality have been proposed from various perspectives. Prior research has proposed quantifying innovation quality through indicators such as the number of invention patents, design patents, and utility model patents [18]. However, the evaluation of innovation performance extends beyond quantitative volumes to encompass qualitative dimensions, as significant heterogeneity exists in the importance and economic value of individual patents. Consequently, relying solely on patent counts fails to capture the complete spectrum of innovation. To address this limitation, patent citation analysis has emerged as a more nuanced metric for evaluating patent quality and innovative value [19]. Further research has refined this approach by developing a composite innovation quality index integrating three core dimensions: knowledge breadth (measuring technological breadth), forward citation (tracing patent impact), and exploratory patent ratio (identifying technological breakthrough).

Simultaneously, the factors influencing corporate innovation quality have attracted considerable attention in academia. At the micro-level, firm-specific characteristics significantly influence innovation quality. These include firm size [20], R&D investment [21], ownership structure, corporate governance [22], executive compensation [16], financing constraints, and digital transformation [23]. Empirical evidence has confirmed that larger firms tend to possess more innovation resources, thereby positively influencing innovation performance [20]. In addition, at the macro-level, government governance mechanisms shape corporate innovation quality through various channels. Key factors include government debt [3], tax incentives, industrial policies, innovation ecosystems, and legal frameworks. Notably, government subsidies play a particularly crucial role in determining innovation quality [21], while fiscal and tax policies effectively stimulate corporate technological innovation. Furthermore, strengthened patent law and intellectual property protection significantly impact innovation quality [24].

However, a significant research gap persists. Although the existing literature has extensively investigated drivers of high-quality corporate innovation at the macro-level, much of this research predominantly focuses on the impact of individual policies. Nevertheless, the impacts of different policies exhibit substantial heterogeneity, and government debt sustainability does not equate to fiscal sustainability [25]. Consequently, there is a lack of comprehensive analysis from the perspective of local fiscal sustainability. Therefore, this paper seeks to examine whether and how local fiscal sustainability influences high-quality corporate innovation.

2.3. Hypotheses Development

The global economy is grappling with a challenging environment characterized by the “low growth, low interest rates, high debt” conundrum, which has heightened fiscal sustainability risks and constrained government’s ability to implement proactive fiscal policies. Enhancing corporate innovation quality is crucial for promoting high-quality economic development, and such innovation relies heavily on sustainable local fiscal support [26]. The Chinese government has increasingly prioritized technological innovation, implementing a series of strategic policies such as the innovation-driven development strategy. Local governments demonstrate a growing propensity to engage in innovation-based competition rather than purely development-oriented growth [27]. The Chinese innovation landscape has now entered a new phase, transitioning from a focus on quantity to a focus on quality. Consequently, a pivotal question arises: Does local fiscal sustainability enhance high-quality corporate innovation? The academic community has yet to reach a consensus on this issue.

Elevated local fiscal sustainability may potentially facilitate high-quality corporate innovation. An improvement in local fiscal sustainability reflects a healthier fiscal condition, enabling local governments to fulfill their responsibilities more effectively and support long-term economic development [28]. On the one hand, local governments may increase fiscal expenditures to strengthen industrial policy support. Empirical studies demonstrate that government procurement uniquely combines administrative and market functions, thereby alleviating corporate financial constraints and boosting R&D investments [29]. On the other hand, the existing literature has revealed that local governments utilize fiscal and taxation instruments during investment promotion. Specifically, these policy tools, such as tax incentives and fiscal rebates, effectively alleviate corporate cash flow constraints, thereby stimulating innovation activities within firms.

Hence, to examine this proposition, the following hypothesis is formulated:

Hypothesis 1a: 

Local fiscal sustainability positively stimulates high-quality corporate innovation.

From another perspective, local fiscal sustainability may not exert a significant positive impact on corporate innovation quality. The extant literature has indicated that information asymmetry may lead to government failures during policy implementation [30]. Furthermore, under the Yardstick Competition framework, central governments guide local governments toward prioritizing growth competition through relative performance evaluations. This dynamic is driven by related economic and fiscal incentives, such as achieving higher economic growth and expanding fiscal revenue [31]. Additionally, rent-seeking incentives create a misalignment of priorities, where local governments may engage in rent-seeking behaviors [32]. These practices may crowd out innovation investment and weaken the foundation for high-quality corporate innovation, for example, through favoring politically connected firms or prioritizing immediate fiscal targets.

While under tight fiscal constraints, local authorities tend to prioritize economic growth, tolerating resource misallocation in pursuit of short-term economic gains. Empirical evidence has showed that Chinese local governments exhibit a pronounced preference for production-oriented investment while neglecting innovation, thereby reducing factor inputs into R&D [4]. Consequently, firms may shift their focus from long-term technological advancement to short-term survival strategies [33], undermining sustainable innovation investments and ultimately degrading the corporate innovation ecosystem. Conversely, in order to address fiscal deficits, local governments may intensify rigor regarding tax collection and enhance penalty enforcement. Enhanced tax enforcement raises corporate effective tax burdens, compresses profit margins, diminishes internal financing capacity, and consequently constrains the cash flow available for research and development activities. Some studies have argued that expansions in local government debt have a significant negative effect on corporate innovation quality [3].

Thus, to test this prediction, the research hypothesis was established as follows:

Hypothesis 1b: 

Local fiscal sustainability may not significantly stimulate high-quality corporate innovation.

Innovation, inherently characterized by high risk, substantial costs, and uncertain returns, requires sustainable investments in both human and financial resources. Consequently, firms face persistent external financing pressures for research and development. Empirical research has demonstrated that governments can effectively support and stimulate corporate innovation through mechanisms such as subsidies and tax incentives [34], thereby promoting technological advancement and achieving sustainable innovation. Elevated local fiscal sustainability signifies greater governmental financial resources, enabling the expansion of government subsidy programs and increasing the probability of firms receiving government support. This mechanism operates through two complementary pathways. Figure 1 presents the logic diagram of the mechanism test, illustrating the hypothesized pathways between local fiscal sustainability and high-quality corporate innovation.

First, government subsidies directly provide financial resources for innovative activities. By augmenting innovation resource endowments, these subsidies reduce marginal R&D costs, expand innovation scales, and ultimately improve innovation performance [35]. Second, government subsidies indirectly function as credibility guarantees [36]. The subsidies transmit positive security assurances to market investors [37], mitigating perceived investment risks in innovation projects and alleviating financing constraints. Consequently, local fiscal sustainability enhances high-quality corporate innovation through the resource compensation effect and signaling transmission effect. This mechanism transforms innovation from a short-term financial burden into a sustainable long-term strategic activity, thereby strengthening corporate intrinsic motivation to pursue high-quality corporate innovation and ultimately elevating innovation quality.

Therefore, this study advances the following hypothesis:

Hypothesis 2: 

Local fiscal sustainability enhances high-quality corporate innovation through government subsidies, exhibiting a resource compensation effect.

The positive effect of local fiscal sustainability on high-quality corporate innovation may exhibit heterogeneity depending on the strength of the intellectual property protection. Robust intellectual property protection encompasses optimized procedures for patent examination, trademark review, and copyright registration [38]. A well-developed intellectual property protection system institution safeguards the legitimate rights of innovators, thereby stimulating enterprises’ self-driven motivation and long-term commitment to high-quality corporate innovation [39].

Initially, intellectual property protection establishes a protective innovation institutional environment for innovation by mitigating the risks of intellectual property infringement. A higher level of intellectual property protection ensures the legality and exclusivity of innovation outcomes, reduces the potential risks of technology leakage and talent drain, and maximizes the value realization of high-quality corporate innovation [40]. Furthermore, intellectual property protection empowers corporate innovation capabilities through multidimensional monitoring and punitive measures against infringement. By providing legal mechanisms for economic compensation, it offers robust support for enterprises to pursue legal remedies, thereby stimulating the vitality of research and development.

Corporate innovation outcomes necessitate protection, and an intellectual property protection system creates a favorable innovation environment, mitigates the risks of innovation, and encourages high-quality innovative activities. Therefore, this paper formulates the following hypothesis:

Hypothesis 3a: 

In regions with stronger intellectual property protection, the positive effect of local fiscal sustainability on high-quality corporate innovation is more pronounced compared to other regions.

The effect of local fiscal sustainability on corporate innovation quality may vary across different regions due to disparities in resource endowments and development stages. In China, local fiscal sustainability levels exhibit significant heterogeneity, particularly when categorized by geographical area. According to the classification by the National Bureau of Statistics, mainland China is divided into four major regions: the eastern, northeastern, central, and western regions. On the one hand, local governments in the central, western, and northeastern regions face intense catch-up pressure and prioritize rapid economic growth over innovation investment [26]. This developmental gap often leads to a substantial allocation of resources toward infrastructure and production, while reducing expenditures on enterprise innovation activities [41]. On the other hand, eastern regions demonstrate higher levels of marketization and economic development, and a higher research capacity, compared to other regions [27]. This enables eastern local governments to better support corporate innovation, thereby amplifying the promotional effect of local fiscal sustainability on innovation quality. In consequence, this synergy helps to align local fiscal policy with national innovation strategies and regional sustainable development objectives. Thus, this paper proposes the following hypothesis:

Hypothesis 3b: 

The positive effect of local fiscal sustainability on high-quality corporate innovation is more pronounced in the eastern regions compared to other regions.

Considering the substantial heterogeneity in innovation demands across industries, the effect of local fiscal sustainability on corporate innovation quality varies significantly by sector. High-Tech Enterprises, as pivotal drivers of technological innovation, play a crucial role in implementing the national innovation-driven development strategy. Compared to traditional firms, High-Tech Enterprises possess more essential and adequate conditions for high-quality corporate innovation, including highly skilled talent, sophisticated equipment, and cutting-edge technologies [42]. Consequently, the facilitative effect of local fiscal sustainability on high-quality corporate innovation may exhibit notable variations depending on whether firms are certified as High-Tech Enterprises.

Firstly, High-Tech Enterprises exhibit increased innovation demands compared to firms in other industries, making them more reliant on external innovation support from local governments [43]. Additionally, in pursuit of innovation objectives and sustainable development, the inherent innovation advantages of High-Tech Enterprises serve as a catalyst for local governments to intensify policy interventions and stimulate corporate innovation quality [20]. Ultimately, High-Tech Enterprises are particularly sensitive to financial constraints, which can be effectively mitigated by proactive fiscal and policy support from local authorities [44].

Collectively, these dynamics suggest that local fiscal sustainability exerts a stronger positive effect on innovation quality in High-Tech Enterprises relative to other industries. Therefore, the following hypothesis is advanced in this paper:

Hypothesis 3c: 

The positive effect of local fiscal sustainability on high-quality corporate innovation is more pronounced in High-Tech Enterprises than in other industries.

3. Methodology and Sample

3.1. Empirical Model

Following Huang et al. [45], this paper constructs the following multiple regression model to reveal the relationship between local fiscal sustainability and high-quality corporate innovation, as shown in Equation (1):

$$HIN{N}_{i,t}={\alpha }_i+\beta LF{S}_{p,t}+\gamma Control\_Va{r}_{i,t}+{\delta }_i+{\mu }_t+{\epsilon }_{i,t}$$

(1)

where HINN_i,t is the dependent variable of high-quality corporate innovation; LFS_p,t is the independent variable of local fiscal sustainability; β is the coefficient of interest, which represents the effect of local fiscal sustainability on high-quality corporate innovation; α_i denotes the intercepted item; Control_Var_i,t represents the enterprise-level control variables, such as SIZE, AGA, LEV, ROA, TANG, TOP1, DUAL, and IND; γ denotes the coefficient of the control variables; i, p and t represent industry, province and year, respectively; δ_i and u_t are the industry and year fixed-effect; ε_i,t is a normally distributed random error vector. As previously discussed, if higher local fiscal sustainability enhances high-quality corporate innovation, we expect the regression coefficient β to be statistically significant and positive.

3.2. Variable Measurement

3.2.1. Dependent Variable

Following the methodology of Hasan et al. [46], and Kong et al. [47], we measure high-quality corporate innovation as the natural logarithm of one plus the total number of cumulative citations received by the enterprise’s invention-type patents in the subsequent year (HINN_i,t).

While the existing literature has proxied innovation quality with the number of invention patent applications, this quantitative metric may not accurately evaluate innovation quality and fail to distinguish between low-impact and high-impact innovations. In contrast to patent counts, which represent innovation breadth, patent citations are widely recognized as a more reliable indicator of the depth and quality of innovation. They reflect the technological impact, market recognition, and widespread application of corporate inventive outcomes. Consequently, a higher value of our chosen variable indicates a greater level of corporate innovation quality.

To further strengthen the validity of our findings, we constructed an alternative measure for robustness checks, taking the natural logarithm of one plus the cumulative number of invention patents, excluding self-citations. This adjustment approach helps to ensure that our findings are not skewed by self-referential citations.

3.2.2. Independent Variable

Currently, China has not established an official, dedicated database on fiscal sustainability. Existing measurement approaches face notable limitations. Single-indicator approaches often fail to comprehensively and systematically capture the complex and multidimensional nature of local fiscal sustainability. While the fiscal reaction function methods are susceptible to systemic bias stemming from data-quality deficiencies and misspecification of structural parameters.

To address these limitations, our study adopts a composite index approach, following the methodology of Zhang et al. [48]. We used the longitudinal and cross-sectional data envelopment analysis method to assign weights to underlying indicators. This technique provides a more accurate reflection of inter-regional differences in local fiscal sustainability by enabling both vertical and horizontal comparisons, thereby ensuring that our indicator system is both systematic and comprehensive. While parsimonious, these indicators provide initial assessments of fiscal health.

Grounded in conceptual definition and the fiscal function, we measured local fiscal sustainability along five key dimensions: fiscal revenue, fiscal expenditure, fiscal risk, budgetary execution, and the development objective [10]. These five dimensions are interrelated, collectively forming an integrated framework for assessing local fiscal sustainability. This framework not only addresses explicit fiscal operational challenges but also incorporates implicit fiscal risks. Furthermore, it strengthens the dynamic regulatory capacity through the management and objective dimensions, thereby aligning with the dual imperatives of short-term equilibrium and long-term resilience. Hence, a higher value of the constructed index indicates a stronger local fiscal sustainability at the provincial level.

Table 1. Definitions of local fiscal sustainability (LFS) index system.

Primary Indicator	Secondary Indicator	Definitions	Direction
Fiscal Revenue	Fiscal Revenue Growth Rate	(Current year’s general public budget revenue—previous year’s general public budget revenue)/previous year’s general public budget revenue	+
	Per Capita Fiscal Revenue	General public budget revenue/total population	+
	Major Tax Share	(Value-added tax + corporate income tax + personal income tax)/total tax revenue	+
	Tax Revenue Ratio	Tax revenue/general public budget revenue	+
Fiscal Expenditure	Fiscal Expenditure Growth Rate	(Current year’s general public budget expenditure—previous year’s general public budget expenditure)/previous year’s general public budget expenditure	+
	Public Welfare Spending Ratio	(Social security and employment expenditure + health and medical expenditure + education expenditure)/general public budget expenditure	+
	Science and Technology Expenditure Ratio	Science and technology expenditure/general public budget expenditure	+
	Administrative Management Expenditure Ratio	General public service expenditure/general public budget expenditure	−
Fiscal Risk	Fiscal Deficit-to-GDP Ratio	(Local government expenditure—local government revenue)/GDP	−
	Local Government Debt Burden Ratio	Urban investment bond balance/GDP	−
	Land Fiscal Dependence	Land transfer revenue/general public budget revenue	−
	Social Security Burden Ratio	Population aged 65 and above/population aged 15–64	−
Budgetary Execution	Revenue Budget Deviation	(Final fiscal revenue—budgeted fiscal revenue)/budgeted fiscal revenue	−
	Expenditure Budget Deviation	(Final fiscal expenditure—budgeted fiscal expenditure)/budgeted fiscal expenditure	−
Development Objective	Economic Growth Rate	(Current year’s GDP—previous year’s GDP)/previous year’s GDP	+

Note: “+” indicates a positive association between the indicator and local fiscal sustainability, meaning a higher value of the indicator is conducive to stronger local fiscal sustainability. Conversely, “−” indicates a negative association, meaning a higher value of the indicator is less favorable to local fiscal sustainability.

presents the complete local fiscal sustainability index system, including indicator definitions, directions, and measurement units. The detailed measurement methodology is as follows.

Step 1: Data Normalization

We standardize and normalize all base indicators to a uniform positive orientation. This process transforms the raw data, denoted as $X_{pj}$, into a consistent format for aggregation.

Step 2: Weight Determination

To determine the optimal weights vector $W_j$ for the comprehensive evaluation function, $y_p\left(K_t\right)={\sum }_{j=1}^m{W}_j{X}_{p{j}^{\text{'}}}\left(K_t\right)$, we represent the differences among the evaluation objects using the sum of squares of the total deviations, as shown in Equation (2):

$${\sigma }^2=\sum _{t=1}^N\sum _{p=1}^n{\left(y_p\left(k_t\right)-\overline{y}\right)}^2=\sum _{t=1}^N\left(w^T{H}_{t}w\right)=w^T \sum _{t=1}^N{H}_{t}w=w^{T}Hw$$

(2)

$H={\sum }_{t=1}^N{H}_t$ is a symmetric matrix of order $m \times m$, and $H_t=A_t^T{A}_t$. It can be mathematically proven that the maximum value of ${\sigma }^2$ is achieved when $W_j$ is the eigenvector corresponding to the largest eigenvalue of matrix $H$. Assuming $w>0$, the weight vector $w$ is then computed by solving the linear programming problem in Equation (3):

$$max{w}^{T}Hw s.t. ‖w‖=1 w>0$$

(3)

This formulation ensures that weights are empirically derived based on inter-provincial heterogeneity in fiscal performance, rather than arbitrarily assigned.

Step 3: Weighted Synthesis

After obtaining the weight vector $W_j$, we calculate the overall local fiscal sustainability score for province p in the year t. By using a linear weighted method and the comprehensive evaluation function, the final LFS index is valued in Equation (4):

$$LT{S}_{pt}=\sum _{p=1}^n{W}_j{X}_{pj}\left(kt\right)$$

(4)

The resulting LFS score reflects the relative level of local fiscal sustainability, with higher values indicating stronger fiscal resilience and greater capacity for long-term sustainability.

3.2.3. Control Variables

To mitigate potential biases arising from confounding characteristics, we included several control variables commonly employed in corporate innovation studies. Following Chu et al. [49], we constructed the following control variables. Firm size (SIZE) is measured as the natural logarithm of the firm’s total assets. Firm age (AGE) is represented by the natural logarithm of one plus the number of years since the firm’s incorporation. The leverage (LEV) is calculated as the ratio of a firm’s total liabilities to total assets. Return on assets (ROA) is defined as net profit divided by total assets. Capital intensity (TANG) refers to the ratio of a firm’s fixed assets to total assets. The largest shareholder ownership (TOP1) represents the shareholding ratio of total shares owned by the largest shareholder in a firm. CEO–chairman duality (DUAL) is a dummy variable coded as 1 if the CEO and the chairman of the board roles are held by the same person. Independent directors proportion (IND) is the ratio of independent directors to the number of total board members, serving as a measure of board independence and oversight quality. The paper also controls for industry and year fixed effects. All variable definitions and computational specifications are summarized in

Table 2. Definitions of variables.

	Variables	Definition
Dependent variable	HINN	The natural logarithm of one plus the total number of cumulative citations received by a firm’s invention-type patents in the subsequent year.
Independent variable	LFS	The value of Local Fiscal Sustainability Index at the end of period t.
Control variables	SIZE	The natural logarithm of the total assets of the firm at the end of period t.
	AGE	The natural logarithm of one plus the number of years since the firm’s incorporation at the end of period t.
	LEV	Total liabilities deflated by total assets at the end of period t.
	ROA	Net profit deflated by total assets at the end of period t.
	TANG	Fixed assets deflated by total assets at the end of period t.
	TOP1	Shareholding ratio of the firm’s largest shareholder at the end of period t.
	DUAL	Dummy variable, equal to 1 if the firm’s chairman of the board also serves as the CEO at the end of period t, 0 otherwise.
	IND	The proportion of independent directors on the board at the end of period t.

.

3.3. Sample and Data

This study explores the relationship between local fiscal sustainability and high-quality corporate innovation by using a unique panel dataset that integrates both macro-level provincial fiscal data and micro-level corporate financial and patent data. Methodologically, the Python-based (version 3.0) web scraping and data retrieval techniques were employed for systematic data collection.

Provincial-level data were obtained from the WIND database and CEIC database, as well as various statistical yearbooks, including the China Statistics Yearbook, Finance Yearbook of China, China Taxation Yearbook, and the China Land and Resources Statistical Yearbook. Missing data were supplemented by manual compilation from the Final Accounts of the General Public Budget for Chinese provinces, autonomous regions, and municipalities.

Firm-level data were sourced from the CSMAR database and the Chinese Research Data Services Platform (CNRDS). Corporate patent data were acquired from the China National Intellectual Property Administration (CNIPA) and Google Patents. Specifically, we first obtained patent publication numbers for all patents held by A-share listed companies (Shanghai and Shenzhen) and their subsidiaries in China from the CNIPA website. These publication numbers were then used to query Google Patents, retrieving detailed patent citation records, including forward citations, grant dates, and technological classifications. After a meticulous data processing procedure, we compiled a comprehensive dataset of patent citations.

The initial sample comprised A-share listed companies, with firm-level data precisely matched to provincial-level fiscal statistics based on corporate registration locations. The analysis focused on the period from 2015 to 2023, coinciding with China’s implementation of the new Budget Law in 2015, which introduced stringent requirements for local government debt management.

To ensure the reliability and validity of our empirical results, we applied rigorous data screening and preprocessing steps: (1) firms in the financial industry were excluded to avoid industry-specific biases; (2) firms with ST, * ST, or PT status were removed to mitigate financial abnormality effects; (3) observations with missing key variables were dropped; (4) firms that changed their primary industry classification during the sample period were excluded to prevent potential selection bias; (5) samples from Tibet, Hong Kong, Macao, and Taiwan were excluded due to data completeness issues; and (6) all continuous variables were winsorized at the upper and the lower 1% levels to minimize outlier influence. Following this rigorous procedure, we ultimately constructed a balanced panel dataset containing 14,586 firm-year observations across 30 provinces in Mainland China.

4. Empirical Results and Analyses

4.1. Descriptive Statistics

Table 3. Descriptive statistics.

Variables	Obs	Mean	Sd	Min	Max
HINN	14,586	2.528	1.574	0	10.143
LFS	14,586	1.838	0.143	1.048	2.713
SIZE	14,586	22.273	1.247	20.071	26.498
AGE	14,586	2.842	0.336	1.742	3.974
LEV	14,586	0.398	0.197	0.054	0.941
ROA	14,586	0.041	0.064	−0.231	0.264
TANG	14,586	0.227	0.132	0.001	0.809
TOP1	14,586	0.341	0.139	0.045	0.873
DUAL	14,586	0.311	0.463	0	1
IND	14,586	0.378	0.053	0.333	0.572

Note: This table shows the summary statistics of firm-year observations of variables for the period from 2015 to 2023.

presents the descriptive statistics for all variables used in this study. The mean value of high-quality corporate innovation (HINN) is 2.528, with a standard deviation of 1.574. These statistics are consistent with the findings of Hu et al. [50], indicating considerable heterogeneity in the innovation quality among Chinese listed companies. The relatively low mean value, coupled with a large standard deviation, suggests that while some firms achieve high-quality corporate innovation, the overall level is not high. For local fiscal sustainability (LFS), the mean value is 1.838 and the standard deviation is 0.143. These values are similar to those reported by Peng et al. [4], confirming that there is meaningful inter-provincial variation in local fiscal sustainability. The maximum value is 2.713, which further indicates a wide range of fiscal health and a substantial potential for improvement. This result highlights the necessity for provinces to actively strengthen their local fiscal sustainability. The descriptive statistics for the main control variables are largely consistent with the findings from the existing literature, providing further confidence in the validity and comparability of our dataset.

4.2. Baseline Regression

Table 4. Baseline results.

	(1)	(2)
	HINN	HINN
LFS	1.413 ***	1.381 ***
	(3.015)	(4.237)
SIZE		0.483 ***
		(8.102)
AGE		0.647 ***
		(3.616)
LEV		−0.018
		(−0.047)
ROA		−0.291 **
		(−2.242)
TANG		0.018
		(0.135)
TOP1		−0.000
		(−0.912)
DUAL		0.014
		(0.632)
IND		−0.084
		(−0.174)
Controls	0.755 ***	2.891 ***
	(3.960)	(6.995)
Industry FE	YES	YES
Year FE	YES	YES
N	14,586	14,586
Adjust R2	0.151	0.177

Note: Robust t-statistics are reported in parentheses. **, and *** indicate the 5%, and 1% significance levels, respectively. Industry and year fixed effects are included.

presents our baseline regression results. Column (1) shows a positive and statistically significant relationship between local fiscal sustainability (LFS) and high-quality corporate innovation (HINN), which provides initial evidence in support of Hypothesis 1a and rejection of Hypothesis 1b. This specification only includes fixed effects for firm and year, without any additional control variables. In column (2), the coefficient for local fiscal sustainability is 1.381, which remains significant at the 1% level. This finding confirms Hypothesis 1a, demonstrating that local fiscal sustainability can indeed enhance high-quality corporate innovation. Column (2) incorporates all control variables, capturing corporate-specific characteristics. Regarding the control variables, firm size (SIZE) and firm age (AGE) show a significantly positive relationship with innovation quality at the 1% level, suggesting that larger and older firms tend to have higher-quality innovation. In contrast, the coefficient for return on assets (ROA) is significantly negative at the 5% level, which indicates that firms with higher profitability may allocate fewer marginal resources toward risky and long-term R&D activities. The results for all other control variables are consistent with the existing literature.

4.3. Endogenous Tests

4.3.1. Instrumental Variable Estimation

The baseline regression results may be subject to endogeneity bias due to potential reverse causality. To mitigate this concern, we conducted a robustness check using the instrumental variables two-stage least squares (IV-2SLS) approach. Specifically, following Yu et al. [51], we designed an instrumental variable (IV) based on the perspective of local government competition: the number of prefecture-level cities within the firm’s province of origin. Existing research indicated that within pyramidal hierarchical structures, officials face significant promotion pressure and intense peer competition. Consequently, enhancing local fiscal sustainability occupies a critical criterion in the evaluation metrics for official promotion. Given the limited number of promotion positions, a higher count of prefecture-level cities intensifies competition among local officials. This heightened competition, in turn, incentivizes local governments to improve local fiscal sustainability, thus establishing a positive correlation between the number of prefecture-level cities and local fiscal sustainability.

Concurrently, the number of prefecture-level cities within a province remains relatively stable over time and exhibited minimal variation during our sample period. Theoretically, this stability implies that the quantity of prefecture-level cities does not exhibit a correlation with high-quality corporate innovation, thereby satisfying the exogeneity requirement for an instrumental variable. To strengthen the instrument’s robustness, we combined this variable with an exogenous time dummy. This methodological approach effectively captures temporal dynamics while preserving the instrumental variable’s validity.

Table 5. Estimation results of endogenous tests.

	(1)	(2)	(3)
	First-Stage	Second-Stage	One-Period Lag Test
	LFS	HINN	HINN
LFS		1.371 ***
		(4.153)
IV	0.001 ***
	(2.6174)
LFSt−1			1.264 ***
			(2.697)
Controls	YES	YES	YES
Industry FE	YES	YES	YES
Year FE	YES	YES	YES
N	14,586	14,586	14,586
Adjust R2			0.088
Cragg-Donald Wald F-Statistics	121.632

Note: Robust t-statistics are reported in parentheses. *** indicate the 1% significance levels, respectively. Industry and year fixed effects are included.

reports the estimation results of the two-stage least squares (2SLS) regression. Column (1) presents the first-stage regression results, where the instrument variable (IV) enters with a significantly positive coefficient, as expected. The Cragg–Donald Wald F-statistic is 175.427, which exceeds the Stock–Yogo weak identification test’s 10% critical value of 16.380. This result allows us to confidently reject the null hypothesis of a weak instrument, thereby confirming that our instrumental variable satisfies the relevance condition. Column (2) reports the second-stage regression results. The coefficient remains positive and statistically significant at the 1% level, indicating that our main conclusions remain robust after addressing endogeneity.

4.3.2. Lagged Variable

To account for the potential time lag in the impact of local fiscal sustainability on high-quality innovation, we further performed an additional robustness check. We included the one-period lag of the dependent variable (LFS_t−1) in the model to address reverse causality. More specifically, higher innovation quality at the firm level may attract greater attention from local governments, leading to increased access to preferential policies and financial subsidies. Thus, there is a bidirectional causality between local fiscal sustainability and high-quality corporate innovation. As shown in Column (3) of Table 5, the regression coefficient is 1.264, with a t-value of 2.697, which remains positive and statistically significant at the 1% level. This finding confirms that the positive incentive effect of local fiscal sustainability on high-quality corporate innovation is robust after accounting for dynamics, mitigating reverse causality.

4.4. Robustness Tests

Several potential issues, such as measurement error, model misspecification, and omitted variable bias, may threaten the validity of our baseline regression results. In light of these concerns, we conducted a series of robustness checks to verify the reliability of the baseline regression results. The specific methods are outlined in the following sections.

4.4.1. Alternative Measurement of Independent Variable

We conducted a robustness check by employing an alternative measure of local fiscal sustainability to ensure our results were not sensitive to the choice of proxy variable. Specifically, following the methodology of Lv et al. [10], we used the China Provincial Fiscal Development Index (FDI), which was developed and released by the Institute of Fiscal Sciences at Renmin University of China, as a substitute for our primary independent variable. As reported in Column (1) of

Table 6. Estimation results of alternative measurement and subsample analysis.

	(1)	(2)	(3)
			Subsample
	HINN	HINN’	HINN
LFS		1.317 ***	1.389 ***
		(4.985)	(4.241)
FDI	0.732 ***
	(4.657)
Controls	YES	YES	YES
Industry FE	YES	YES	YES
Year FE	YES	YES	YES
N	14,586	14,586	10,097
Adjust R2	0.195	0.241	0.179

Note: Robust t-statistics are reported in parentheses. *** indicate the 1% significance levels, respectively. Industry and year fixed effects are included.

, the estimated coefficient is 0.732 and statistically significant at the 1% level, indicating that the baseline conclusion is not contingent on the measurement choice for local fiscal sustainability.

4.4.2. Alternative Measurement of Dependent Variable

To ensure that our results are not sensitive to the specific measurement of the dependent variable, we conducted a robustness check using an alternative indicator (HINN’) for high-quality corporate innovation. Consistent with the prior literature [52], self-citations were excluded so that only citations from external parties were counted. For our regression, we used the natural logarithm of the number of HINN’ as the dependent variable. The results, presented in Column (2) of Table 6, show that the regression coefficient for local fiscal sustainability remains positive and statistically significant at the 1% level. This finding confirms that the positive influence of local fiscal sustainability on high-quality corporate innovation is not driven by idiosyncrasies in the measurement method.

4.4.3. Subsample Analysis

The COVID-19 pandemic exerted a profound and widespread influence, particularly from 2020 onwards. To mitigate potential interference from this public emergency on the estimation of our core effects, we conducted a robustness check by excluding data from 2020 to 2022. Consistent with our baseline findings, the coefficient for local fiscal sustainability in Column (3) of Table 6 remains positive and significant at the 1% level. The regression results indicate a significant positive correlation between local fiscal sustainability and high-quality corporate innovation. Critically, this positive effect persists even after removing data from this three-year period, thereby underscoring the robustness of the conclusions.

4.4.4. Addressing Competing Hypotheses

The merger of State Tax Bureau (STB) and Local Tax Bureaus (LTBs) in 2018 aimed to enhance tax authority independence, strengthen tax enforcement, and improve tax services. These reforms may have influenced corporate innovation behaviors by altering tax administration intensity [53]. To preclude alternative explanations for our findings, we constructed a dummy variable (Merger). This variable is assigned a value of 1 for the year of the STB-LTBs merger and all subsequent years, and 0 otherwise. This dummy variable was incorporated into Model (1) for regression analysis. The results, presented in Column (1) of

Table 7. Estimation results of competing hypotheses and higher-level fixed effects.

	(1)	(2)	(3)
		Higher-Level Fixed Effects
	HINN	HINN	HINN
LFS	1.383 ***	1.384 ***	1.384 ***
	(4.239)	(3.339)	(3.336)
Merger	0.004 *
	(1.701)
Controls	YES	YES	YES
Industry FE	YES	YES	YES
Year FE	YES	YES	YES
Industry × Year FE	NO	YES	NO
Province × Year FE	NO	NO	YES
N	14,586	14,586	14,586
Adjust R2	0.177	0.157	0.157

Note: Robust t-statistics are reported in parentheses. *, and *** indicate the 10%, and 1% significance levels, respectively. Industry and year fixed effects are included.

, reveal a statistically significant positive correlation between local fiscal sustainability and high-quality corporate innovation. Crucially, even after controlling for the confounding effects of the STB-LTBs merger reform, the competitive policy has no significant effect on the benchmark regression results. This finding effectively rules out the alternative competitive hypothesis and thereby confirms the robustness of the baseline findings.

4.4.5. Higher-Level Fixed Effects

Improvements in corporate innovation quality may be driven by unobserved factors that evolve over time at the industry or provincial level. To address this concern, we re-estimated the model with additional controls for industry fixed effects, province fixed effects, and their interactions with year fixed effects. As reported in Columns (2) and (3) of Table 7, the estimated coefficient remains positive and statistically significant at the 1% level. This indicates that the results are consistent with our previous conclusion and remain robust to the inclusion of these additional controls.

5. Further Analysis

5.1. Mechanism Test of Resource Compensation Effect

To examine whether local fiscal sustainability enhances high-quality corporate innovation through a resource compensation channel, we estimate the mechanism model specified in Equations (5) and (6).

$$SU{B}_{i,t}={\alpha }_i+\beta LF{S}_{p,t}+\gamma Control\_Va{r}_{i,t}+{\delta }_i+{\mu }_t+{\epsilon }_{i,t}$$

(5)

$$HIN{N}_{i,t}={\alpha }_0+{\alpha }_{1}LF{S}_{p,t}+{\alpha }_{2}Ln{SUB}_{i,t}+{\alpha }_{3}LF{S}_{p,t}\times Ln{SUB}_{i,t}+\gamma Control\_Va{r}_{i,t}+{\delta }_i+{\mu }_t+{\epsilon }_{i,t}$$

(6)

In this specification, government subsidies serve as the proxy for the resource compensation effect. In Equation (5), we employ two distinct methods to measure government subsidies. First, we use a continuous variable (LnSUB), defined as the natural logarithm of one plus the annual amount of government subsidies received by the listed firm in a given year. Second, we use a binary indicator (SUB), which takes a value of 1 if a listed firm receives any government subsidy in a given year, and 0 otherwise. In Equation (6), we incorporate an interaction term between local fiscal sustainability (LFS) and government subsidies (LnSUB). The coefficient, denoted as ${\alpha }_3$, associated with the interaction term is utilized to empirically investigate the presence of a resource compensation effect between local fiscal sustainability and high-quality corporate innovation. A positive and significant coefficient ${\alpha }_3$ suggests that elevated levels of local fiscal sustainability enable firms to more readily secure government subsidies, consequently supporting Hypothesis 2. The data for government subsidies are sourced from the ‘non-operating income’ line item disclosed in listed firms’ annual reports. All other variables are defined consistently with those in Equation (1), and the regression also controls for industry and year fixed effects.

Table 8. Mechanism test results of resource compensation effect.

	(1)	(2)	(3)
	LnSUB	SUB	HINN
LFS	2.413 ***	0.732 ***	1.107 ***
	(5.915)	(3.257)	(4.681)
LnSUB			0.424 *
			(1.721)
LFS × LnSUB			0.017 **
			(2.052)
Controls	YES	YES	YES
Industry FE	YES	YES	YES
Year FE	YES	YES	YES
N	14,586	14,586	14,586
Adjust R2	0.256	0.155	0.199

Note: Robust t-statistics are reported in parentheses. *, **, and *** indicate the 10%, 5%, and 1% significance levels, respectively. Industry and year fixed effects are included.

reports the regression results for the resource compensation effect. Column (1) shows that the coefficient for the interaction between government subsidies (LnSUB) and local fiscal sustainability is positive and statistically significant at the 1% level. This result implies that higher local fiscal sustainability expands local governments’ disposable fiscal resources and increases the scale of government subsidies awarded to firms. Furthermore, to investigate how local fiscal sustainability affects the likelihood of firms receiving subsidies, we further assessed the extensive margin using the dummy variable SUB. The results shown in Column (2) also remain positive and statistically significant at the 1% level. Furthermore, the regression results in Column (3) reveal that the coefficient ${\alpha }_3$ of the interaction term is positive and statistically significant at the 5% level. Concurrently, the coefficients of LFS and LnSUB are also positive and statistically significant. These findings collectively suggest the existence of a resource compensation effect, wherein higher local fiscal sustainability amplifies the positive relationship between the availability of government subsidies and corporate innovation incentives. The results are highly consistent with the prediction of Hypothesis 2. Hence, improvements in local fiscal sustainability strengthen governmental fiscal support and increase both the amount and the probability of firms receiving government subsidies. By alleviating R&D financing constraints via the resource compensation channel, this enhanced financial support effectively promotes high-quality corporate innovation.

5.2. Heterogeneity Analyses

5.2.1. Heterogeneity Analysis of Innovation Environment

Well-functioning intellectual property protection institutions and effective enforcement procedures may foster a favorable innovation environment, thereby sustaining incentives to innovation activities. Accordingly, we assess a measure for the strength of provincial intellectual property protection (IPP). This indicator is based on the number of intellectual property cases concluded by the courts in each province, normalized by the provincial GDP. The calculation method for this variable is specified in Equation (7):

$$\mathrm{I}\mathrm{P}\mathrm{P}={\displaystyle \frac{\mathrm{L}\mathrm{o}\mathrm{c}\mathrm{a}\mathrm{l} \mathrm{I}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{l}\mathrm{l}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{u}\mathrm{a}\mathrm{l} \mathrm{P}\mathrm{r}\mathrm{o}\mathrm{p}\mathrm{e}\mathrm{r}\mathrm{t}\mathrm{y} \mathrm{C}\mathrm{a}\mathrm{s}\mathrm{e}\mathrm{s} \mathrm{C}\mathrm{l}\mathrm{o}\mathrm{s}\mathrm{u}\mathrm{r}\mathrm{e} \mathrm{N}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r}}{\mathrm{L}\mathrm{o}\mathrm{c}\mathrm{a}\mathrm{l} \mathrm{G}\mathrm{D}\mathrm{P}}}/{\displaystyle \frac{\mathrm{N}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{a}\mathrm{l} \mathrm{I}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{l}\mathrm{l}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{u}\mathrm{a}\mathrm{l} \mathrm{P}\mathrm{r}\mathrm{o}\mathrm{p}\mathrm{e}\mathrm{r}\mathrm{t}\mathrm{y} \mathrm{C}\mathrm{a}\mathrm{s}\mathrm{e}\mathrm{s} \mathrm{C}\mathrm{l}\mathrm{o}\mathrm{s}\mathrm{u}\mathrm{r}\mathrm{e} \mathrm{N}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r}}{\mathrm{N}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{a}\mathrm{l} \mathrm{G}\mathrm{D}\mathrm{P}}}$$

(7)

Specifically, we partition the entire sample into two subsamples based on the annual median of our intellectual property protection (IPP), forming a higher IPP group and a lower IPP group. The heterogeneity results are reported in

Table 9. Estimation results of environment heterogeneity.

	(1)	(2)	(3)	(4)
	Higher IPP	Lower IPP	Higher IPP	Lower IPP
	HINN	HINN	HINN	HINN
LFS	1.161 **	0.231	1.132 **	0.134
	(2.022)	(1.608)	(2.037)	(1.683)
Controls	NO	NO	YES	YES
Industry FE	YES	YES	YES	YES
Year FE	YES	YES	YES	YES
N	6892	7114	6892	7114
Adjust R2	0.058	0.011	0.062	0.020

Note: Robust t-statistics are reported in parentheses. ** indicate the 5% significance levels, respectively. Industry and year fixed effects are included.

. As shown, the regression coefficients in Columns (1) and (3) are positive coefficients that are statistically significant at the 5% level, whereas the coefficients in Columns (2) and (4) are positive but not statistically significant. These findings indicate that the positive effect of local fiscal sustainability on high-quality corporate innovation is significant only in the subsample with stronger intellectual property protection, thereby supporting Hypothesis H3a.

When intellectual property protection is insufficient, corporate innovation outcomes face higher risks of misappropriation and imitation, alongside relatively high litigation and enforcement costs. These factors weaken corporate innovation incentives, thereby rendering the promotional effect of local fiscal sustainability insignificant. Conversely, a high level of intellectual property protection fosters a fair and equitable innovation environment. By safeguarding innovators’ returns, mitigating infringement risk, and reducing losses from innovation spillovers, well-developed intellectual property protection actively encourages high-quality corporate innovation.

5.2.2. Heterogeneity Analysis of Economic Region

Table 10. Estimation results of region heterogeneity.

	(1)	(2)	(3)	(4)
	Eastern Regions	Northeastern Regions	Central Regions	Western Regions
	HINN	HINN	HINN	HINN
LFS	1.161 ***	0.497	0.973	0.412
	(5.912)	(0.821)	(1.287)	(0.795)
Controls	YES	YES	YES	YES
Industry FE	YES	YES	YES	YES
Year FE	YES	YES	YES	YES
N	9773	583	2188	2042
Adjust R2	0.287	0.016	0.040	0.014

Note: Robust t-statistics are reported in parentheses. *** indicate the 1% significance levels, respectively. Industry and year fixed effects are included.

presents the regional heterogeneity in the effect of local fiscal sustainability on high-quality innovation. Consistent with the regional classifications established by the National Bureau of Statistics of China, we divide our full sample into the eastern, northeastern, central, and western regions. Columns (1)–(4) correspond to these regions, respectively. As shown, only the coefficient for the eastern regions in Column (1) is positive and statistically significant at the 1% level, with a coefficient of 1.161. The regression results for all other regions are not statistically significant. These findings confirm Hypothesis H3b.

Several factors may account for this pattern. First and foremost, the eastern region possesses more ample fiscal resources and a more developed innovation ecosystem, enabling local governments to provide more generous government subsidies for corporate innovation activities. Hence, this effectively translates local fiscal sustainability into improvements in corporate innovation quality [6]. Subsequently, the eastern regions face less pressure to prioritize short-term economic growth targets, and thus place greater strategic emphasis on innovation-driven, sustainable development. Last but not least, the eastern regions benefit from stronger innovation-supporting endowments, including superior infrastructure investment, robust scientific research support, and favorable pilot policy programs.

By contrast, in the central, western, and northeastern regions, catch-up pressures tend to orient local governments toward rapid economic growth objectives, which can lead to a more constrained and less flexible approach to fiscal support for firm innovation. Consequently, the eastern governments are better positioned to leverage local fiscal sustainability to promote high-quality corporate innovation than those elsewhere.

5.2.3. Heterogeneity Analysis of Industry Characteristic

High-Tech Enterprises derive their core competitiveness primarily from innovation, especially relative to traditional firms. Accordingly, we partitioned the sample into two sub-groups based on High-Tech Enterprise certification status: High-Tech Enterprises and Non-High-Tech Enterprises. The regression results of this sub-sample analysis are presented in

Table 11. Estimation results of industry heterogeneity.

	(1)	(2)	(3)	(4)
	High-Tech Enterprise	Non-High-Tech Enterprise	High-Tech Enterprise	Non-High-Tech Enterprise
	HINN	HINN	HINN	HINN
LFS	1.761 ***	1.156	1.732 ***	1.263
	(4.238)	(1.387)	(4.239)	(1.566)
Controls	NO	NO	YES	YES
Industry FE	YES	YES	YES	YES
Year FE	YES	YES	YES	YES
N	8731	5855	8731	5855
Adjust R2	0.178	0.097	0.180	0.099

Note: Robust t-statistics are reported in parentheses. *** indicate the 1% significance levels, respectively. Industry and year fixed effects are included.

. Columns (1) and (3), which represent the High-Tech Enterprise group, show that the coefficient for local fiscal sustainability is positive and statistically significant at the 1% level, regardless of the inclusion of control variables. Conversely, the coefficients for the Non-High-Tech Enterprise group in Columns (2) and (4) are not statistically significant. These findings indicate that local fiscal sustainability has a significant positive effect on the innovation quality of High-Tech Enterprises, while its influence on the innovation level of Non-High-Tech Enterprises is not significant. These findings support Hypothesis H3c.

This observed industry heterogeneity may be attributed to systematic variations in corporate strategy and responsiveness to policy incentives. Under the government’s innovation-driven development strategy, High-Tech Enterprises are more responsive to policy incentives. This facilitates accelerated research and development, thereby enhancing innovation quality. In comparison, Non-High-Tech Enterprises rely less on innovation and exhibit weaker innovation incentives, with their development strategies focusing on asset investment over R&D. Consequently, the promotional effect of local fiscal sustainability on high-quality corporate innovation demonstrates significant heterogeneity across these two types of firms.

6. Discussion and Conclusions

High-quality corporate innovation is essential for ensuring both competitive advantages and sustainable development among firms. In this context, local fiscal sustainability serves not only as an internal requirement for fiscal security but also a crucial pillar for promoting sustainable economic development. This paper delves into the enhancing effect, underlying mechanisms, and heterogeneous impacts of local fiscal sustainability on high-quality corporate innovation. To bridge the gap between macro-level fiscal sustainability and micro-level innovation quality, we conducted empirical analyses using fixed-effects models and instrumental variable approaches on panel data, supplemented by rigorous robustness checks. Methodologically, data were collected and processed using Python-based (version 3.0) retrieval and web-scraping techniques. A multi-dimensional index of local fiscal sustainability was constructed, comprising five key dimensions to quantitatively capture local fiscal sustainability across Chinese regions.

The empirical analysis reveals three key results. First, local fiscal sustainability significantly promotes high-quality corporate innovation. This conclusion remains robust across various robustness tests, including instrumental variable estimations, alternative variable specifications, and model modifications. Second, mechanism analysis provides evidence that resource compensation effect serves as the primary channel through which local fiscal sustainability enhances high-quality corporate innovation. Third, heterogeneous effects are pronounced across innovation environments, economic regions, and industry characteristics. The positive effect is significantly more pronounced in provinces with robust intellectual property protection, which provides a more conducive innovation environment. Moreover, compared to other regions and industries, local fiscal sustainability demonstrates greater efficacy in enhancing innovation quality among firms in eastern regions and for those operating within the High-Tech Enterprise sector. Building on the empirical findings, our study contributes to both empirical knowledge and practical governance by elucidating the economic impact of local fiscal sustainability on corporate high-quality innovation.

Correspondingly, this paper has some policy implications. First and foremost, local governments should strengthen local fiscal sustainability to promote sustainable enterprise development. Establishing sound fiscal governance systems, embedding a sustainability-oriented fiscal philosophy, and reinforcing fiscal risk prevention mechanisms may safeguard long-term local fiscal sustainability; in this way, these measures may fully leverage the resource compensation effect to drive high-quality corporate innovation.

Subsequently, establishing a differentiated innovation incentive can empower high-quality corporate innovation. Our results reveal that the positive effect of local fiscal sustainability on high-quality corporate innovation exhibits significant regional and industrial heterogeneity. Therefore, local governments should formulate and implement tailored fiscal and industrial policies, with prioritized support for High-Tech Enterprises and firms in the eastern regions. This will foster a durable, sustainable mechanism for corporate innovation development.

Ultimately, local governments should cultivate a conducive innovation environment and improve intellectual property protection. By strengthening the effective protection of the legal rights attached to innovation outputs, governments may prevent technology leakage and infringement. This, in turn, will incentivize firms to increase R&D investment, bolster confidence in pursuing high-quality innovation, and ultimately create a supportive environment for corporate innovation.

While our study provides policy implications for strengthening local fiscal sustainability and promoting high-quality corporate innovation, six aspects warrant caution when interpreting the results. First, we focus exclusively on innovation quality rather than innovation types or strategies, and specifically, the distinction between breakthrough versus incremental innovation. Future studies could extend this work by examining how local fiscal sustainability influences innovation pathway selections. Furthermore, innovation outputs are tradable, and patent transfers often generate spatial spillovers of technological knowledge. Subsequent studies could incorporate spatial econometric models to capture how local fiscal sustainability contributes to knowledge sharing and collaborative innovation across regions. Last but not least, although our analysis relies on provincial-level fiscal data, city-level fiscal statistics may more precisely reflect the mechanisms through which local fiscal sustainability enhances high-quality corporate innovation. We plan to deepen this research beyond emerging economies like China by expanding the study’s geographical scope. Collecting and processing subnational fiscal data from diverse countries represents a valuable avenue for future investigation.

Furthermore, although scientific methodologies were employed, limitations were identified within the indicator system. These challenges include potential multicollinearity and the omission of macro-level indicators, such as measures for the industrial structure rationalization, industrial structure upgrading, and urbanization rates. Future research will address these shortcomings by employing alternative weighting methodologies (e.g., equal weighting or entropy weighting) and conducting sensitivity analyses. Additionally, future research could expand the scope to explore the influence pathways and effects of other macro fiscal policies on high-quality corporate innovation, such as transfer payments, government subsidies and government procurement, with a particular focus on government innovation subsidies. Additionally, given the potential constraints of data quality and time span in a single-country study, we plan to extend this research beyond emerging economies like China by expanding the geographical scope. Collecting and processing subnational fiscal data from diverse countries represents a valuable avenue for future investigation.