Direct Tax Burden, Financing Constraints, and Innovation-Based Output

Abstract

Tax and fee reductions serve as pivotal instruments in the deepening of structural reforms on the supply side and constitute a significant element of China’s proactive fiscal policy. Although China’s tax regime encompasses both direct and indirect tax burdens, the direct tax burden directly impacts the operational costs of firms and remains non-transferable. As such, it holds significant influence over corporate growth trajectories. A decrease in the direct tax burden alleviates financing constraints for firms, subsequently reducing their exposure to business risks. Focusing on the innovative output capabilities of firms, this study analyzes A-share-listed companies on the Shanghai and Shenzhen stock exchanges from 2010 to 2021. It aims to ascertain the influence of direct tax burden reductions on innovation output within the tax and fee reduction framework. The findings indicate that lessening the direct tax burden ameliorates financing constraints, thereby enhancing a firm’s innovative output capabilities. A deeper analysis reveals that non-state-owned enterprises benefit more significantly from this dynamic than their state-owned counterparts, underscoring the potential for targeted tax and fee reduction policies to bolster enterprise innovation. Furthermore, the government should recognize enterprise differentiation and drive broader economic growth through tailored strategies. Notably, the positive impact of mitigating financing constraints on innovation is more pronounced in firms with suboptimal corporate governance structures. While this mechanism notably influences non-invention patent applications, its effect on invention patent applications is comparatively muted. Post-outbreak, the interplay between tax burdens and innovative outputs has intensified, becoming more pronounced than in pre-outbreak times.

1. Introduction

In today’s intricate and evolving international market landscape, publicly listed enterprises grapple with unparalleled challenges. Factors such as capital chain disruptions, information blockages, and shortages in resources and talent can deal significant blows to enterprises. Such setbacks often deprive these businesses of the essential conditions required for innovation, potentially hindering their sustainable growth. Taxation, while influencing operational costs, also significantly impacts the free cash flow within enterprises. Consequently, to mitigate potential risks, several enterprises adopt conservative investment strategies. The tax burden in China is divided into direct and indirect categories. Notably, direct tax burdens are non-transferable, amplifying the fiscal strain on enterprises [1]. Furthermore, relative to indirect tax burdens, direct tax strains more profoundly jeopardize corporate survival and considerably influence profit margins. Hence, when the government alleviates direct tax burdens, enterprises become more attuned to opportunities, thereby fostering innovative pursuits. Existing research corroborates that policy direction can notably bolster corporate innovation. Specifically, direct tax relief emerges as a pivotal policy instrument for enhancing corporate innovative performance [2]. Exorbitant direct tax burdens not only impede corporate investment and reproduction but can also instigate capital flight and overseas profit transfers. Given the backdrop of global economic integration, nations are circumspect about levying high taxes on corporate capital. This caution is evident in the declining global trend of direct corporate tax burdens.

In recent years, China’s policies have been increasingly supportive of corporate technological innovation. The country has employed strategies such as expanding the scope and intensity of accelerated depreciation and R&D expense deduction policies, aiming to continually lessen the direct tax burden on enterprises and bolster innovation. Yet, according to the Organization for Economic Cooperation and Development’s (OECD) Annual Income Statistics Report 2021, when examining income tax—a prominent component of direct tax—it is evident that China’s nominal tax rate stands at 25%. This rate contributes to 18.1% of global tax revenue, inclusive of social insurance revenue. This figure surpasses the current OECD average of 10% and exceeds the Latin American countries’ average by 3 percentage points, indicating that while the enterprise income tax burden in China is progressively decreasing, further reductions are plausible.

In 2020, China’s corporate income tax revenue constituted 3.59% of its GDP, surpassing figures from several developed nations such as the United States (0.96%), the United Kingdom (2.49%), Germany (2.01%), and France (2.24%). As per the “Fiscal Revenue and Expenditure in 2022” report released by the Ministry of Finance in January 2023, income tax represented 65% of the total direct tax burden. When compared to corporate income tax, other forms of direct tax burdens appear insubstantial. Although corporate income tax experienced a modest increase in 2022, marking a year-on-year growth of 3.9%, its overarching trend is declining. Notwithstanding its growth, when juxtaposed with OECD members, there remains potential to further reduce China’s income tax burden. To ameliorate the economic distress induced by the pandemic and foster high-caliber development, China must unwaveringly pursue a technologically-driven strategy. Tax incentives emerge as potent tools to invigorate corporate innovation, highlighting opportunities for further alleviation of China’s corporate income tax burden.

Furthermore, the 14th Five-Year Plan underscores a tax system transformation, pivoting from a direct tax emphasis to an indirect tax focus. As fiscal and taxation reforms intensify, there has been a marked enhancement in the tax system’s architecture. The proportion of direct taxes swelled from 28.4% in 2011 to 36% in 2021. Such systemic refinements bolster enterprise innovation impetus and facilitate the conversion of technological achievements. Evidently, China’s commitment to direct taxation is on an upward trajectory.

Existing literature posits that, from a macro perspective, tax burden alleviation not only fosters stable and robust employment growth in China [3], but also augments the efficacy of government spending [4]. Tax burden policy evaluations should encompass both macro perspectives and the tangible economy’s development nuances. Direct tax reductions can amplify corporate cash flows, mitigate financing constraints, rejuvenate ente.rprise vitality, and diminish associated risks. A lowered direct tax burden significantly bolsters corporate profitability, decreases capital and labor relative prices, and enhances enterprises’ R&D input-output dynamics [5,6]. Nevertheless, comprehensive examinations delving into the influence of direct tax burdens on enterprise innovation, considering varied paths and heterogeneities, remain scarce, necessitating the in-depth exploration presented in this paper.

Following the issuance of the “Opinions on the Key Work of Deepening the Economic System Reform” by the Development and Reform Commission of the State Council in 2010, there has been a discernible shift toward a primary trajectory in China’s forthcoming tax reforms, namely, an incremental emphasis on direct taxation. This study, leveraging A-share-listed companies from the Shanghai and Shenzhen stock exchanges spanning 2010 to 2021 as its research subjects, delves into the nexus between direct tax burdens and innovation outputs. The findings illuminate that diminishing the direct tax burden can efficaciously assuage enterprises’ financing constraints, particularly cash flow deficiencies and informational asymmetries, culminating in augmented innovation outputs. To substantiate the robustness of these outcomes, the conclusions retain their validity even after incorporating endogeneity tests, modifying variable measurements, amplifying control variables, and adjusting sample dimensions. A more granular analysis reveals that this trajectory not only bolsters the number of invention patent applications but also escalates the count of non-invention patent submissions. Intriguingly, when juxtaposed against invention patent applications, the augmentative impact on non-invention patent applications appears more pronounced. To dissect the heterogeneity underpinning the interplay between direct tax burdens, financing impediments, and innovation outputs, the study segregates entities based on proprietary rights and governance standards. The analysis discerns that the relationships between innovation output, financing constraints, and direct tax burdens are more pronounced for non-state-owned enterprises compared to their state-owned counterparts. Furthermore, entities characterized by lower governance standards manifest a more tangible relationship between innovation outputs, financing constraints, and corporate tax burdens than those with elevated governance benchmarks. Notably, post-pandemic, the linkage between direct tax burdens and corporate innovation has grown more salient.

While a plethora of prior research has shed light on the influence of the comprehensive tax burden on corporate R&D and innovation, scant attention has been given to the nexus between direct tax burdens, enterprise innovation outputs, and their underlying mechanisms. This study not only elucidates the relationship between a firm’s direct tax burden and its innovation output but also delineates the channels through which it operates. Our findings corroborate that by mitigating a firm’s financing constraints, a reduction in direct tax burdens can address issues of cash flow insufficiency and information asymmetry, thereby fostering heightened innovation outputs. Delving deeper, this paper discerns variances in the effects of direct tax burden reduction on diverse innovation output types via this mechanism, as well as differential impacts under varying proprietary rights and corporate governance standards. Furthermore, in light of contemporary events, this study evaluates the repercussions of the pandemic on this established pathway. The derived conclusions augment our understanding of the economic outcomes of tax and fee reductions, offering empirical grounding for policymakers to further expedite tax alleviation measures.

2. Literature Review and Research Hypotheses

The influence of the tax burden on enterprise innovation output predominantly stems from both tax policies and the intrinsic characteristics of the enterprises.

2.1. Research on Tax Policy and Innovation

Tax reduction policies primarily aim to invigorate market dynamism, alleviate corporate burdens, and diminish business risks. Given China’s current trajectory of moderated economic growth, corporate tax has emerged as a pivotal tool for governmental intervention in business operations. Consequently, tax policies significantly shape future corporate activities. Foundational theories on tax reduction, whether classical, Keynesian, or supply-side, all converge on the overarching objective of ensuring economic stability via tax cuts. Their divergence is rooted in the distinct tax reduction policies employed at various times to address specific challenges. While Keynesians leverage tax reductions to spur demand, supply-siders employ them to enhance supply. China’s ongoing slew of supply-side structural reforms predominantly targets diminishing production costs, refining the supply structure, catalyzing reform, and fostering innovation on the supply side to realize economic growth. In the recent past, China has consistently escalated its tax and fee reduction measures. The 2018 Government Work Report highlighted an annual tax reduction amounting to 1.3 trillion yuan. As the momentum of supply-side structural reforms gained pace, the tax and fee reduction scope for 2019 broadened to nearly 2 trillion yuan. Notably, even amidst the 2020–2021 pandemic, China further augmented tax and fee cuts. Such measures were designed to alleviate operational strains, retain more funds within companies, ease financing constraints, and thereby champion sustained innovation and corporate growth.

In the recent past, China has consistently escalated its tax and fee reduction measures. The 2018 Government Work Report highlighted an annual tax reduction amounting to 1.3 trillion yuan. As the momentum of supply-side structural reforms gained pace, the tax and fee reduction scope for 2019 broadened to nearly 2 trillion yuan. Notably, even amidst the 2020–2021 pandemic, China further augmented tax and fee cuts. Such measures were designed to alleviate operational strains, retain more funds within companies, ease financing constraints, and thereby champion sustained innovation and corporate growth. The relationship between tax policy and enterprise innovation remains a contested terrain, with scholarly opinions bifurcating into two predominant schools of thought. Firstly, a significant body of literature posits that tax policies can serve as a catalyst for enterprise innovation. As elucidated by [7,8], and others, tax relief measures can bolster anticipated earnings for listed companies, diminish capital costs, and amplify innovation investments, cumulatively fostering a conducive environment for innovative activities. Empirical analyses, such as those undertaken by [9] using Turkish and Polish corporate samples, underscore that governmental research and development incentives can escalate innovation expenditures and the propensity to introduce novel products. Furthermore, Ref. [10] studies emphasize the potential of income tax reforms and the shift from business to value-added tax policies to galvanize innovative endeavors among enterprises. Conversely, the second perspective argues that tax policies fail to kindle innovation in enterprises. As per [1], while preferential tax treatments might bolster profitability for small-scale enterprises, they remain inconsequential in driving their innovative endeavors. Ref. [11] concurs, positing that tax incentives cannot redress the innovation market’s intrinsic incentive deficiencies. While the pendulum of academic consensus tends to lean toward the former viewpoint, certain nuances merit consideration. Scholars such as [12] posit that after tax reduction policies, enterprises might adopt measures tailored to these policies, potentially curbing their innovation behavior.

Scholars categorize the ramifications of taxation on enterprise innovation into two distinct classifications: strategic and substantive. It is generally accepted that only substantive innovations significantly contribute to enterprise development. However, Ref. [13] postulates that a majority of enterprises primarily engage in strategic innovation. Under such circumstances, the stimulative effects of tax policies on genuine innovative activities could be considerably diminished. Some enterprises even resort to manipulating R&D expenditures to align with tax incentives, an approach that potentially curtails market performance enhancement and dilutes the positive correlation between innovation investments and patent applications [14]. Despite these contrasting viewpoints, the prevailing academic consensus suggests that tax burden reductions predominantly benefit, rather than inhibit, enterprise innovation output.

2.2. Research on Tax Burden and Innovation Output

Contemporary research concerning the nexus between tax burden and innovation output can be parsed into three thematic categories: 1. The impact of a comprehensive tax burden on innovation output; the impact of tax structure on innovation activities; the perspective of individual tax system classification. Existing literature bifurcates into two predominant views. The first underscores a significant inverse relationship between tax burden and innovation output. This perspective contends that reducing tax burdens invariably augments innovation output, as evidenced by studies from [15,16], and others. Such reductions ostensibly foster enhanced enterprise productivity [2]. Conversely, the second viewpoint argues that high tax burdens do not necessarily impede enterprise innovation. Ref. [17] discovered that if R&D expenditures are factored into enterprise income tax calculations, the tax’s detrimental impact on innovation becomes negligible. Similarly, Ref. [18] observed that despite the substantial tax cuts during US President Bush’s tenure aimed at alleviating enterprise tax burdens, these measures failed to significantly catalyze innovative behaviors within enterprises.

The Central Committee of the Communist Party of China, in its proposal for the 14th Five-Year Plan for National Economic and Social Development and the Long-term Goals for 2035, underscored the imperative of optimizing tax structures. Consequently, a burgeoning body of literature has emerged examining the influence of tax structures on enterprise innovation. Ref. [19] was among the earliest to classify tax structures, defining those taxes that could be calibrated based on individual taxpayer characteristics as direct taxes. By this definition, traditional income taxes fall under the direct tax category, while taxes imposed on transactions are categorized as indirect taxes. A subset of scholars further delineates tax burdens into direct and indirect, assessing their respective impacts on enterprise innovation. Ref. [14] argue that diminishing direct tax burdens can enhance R&D investments, subsequently boosting enterprise innovation outputs. Ref. [20], utilizing data from 11 provinces within the Yangtze River Basin, and [21], employing panel data from 31 provincial administrative regions in China spanning 2007 to 2018, both concludes that reductions in direct tax burdens are favorable for enterprise innovation outputs. Ref. [22], analyzing patent authorization data from prefecture-level cities, posits that easing direct tax burdens can invigorate enterprise innovation enthusiasm and elevate their innovation outputs.

However, in the above literature, it can be found that while the existing literature underscores the role of reducing direct tax burdens in augmenting enterprise innovation outputs, two notable gaps emerge: 1. Sample Selection and Focus: Many studies select specialized samples, and the direct tax burden is not always their primary research objective. 2. Heterogeneity and Path Mechanism: There is an evident dearth of research on the variances and the underlying mechanisms connecting direct tax burden to innovation output. Though some studies delve into the relationship between R&D input and enterprises’ direct tax burden, it is imperative to note that innovation input does not necessarily translate to innovation output due to inherent risks. This distinction will be the pivotal focus of this paper.

2.3. Direct Tax Burden, Financing Constraints, and Innovation Output

Financing constraints refer to the challenges enterprises face during financing. Pioneering works by [23] highlighted that in imperfect capital markets, issues such as information asymmetry and agency problems will culminate in financing constraints for enterprises. This means that enterprise investment behaviors are influenced not just by investment demands but also by their capital availability. These constraints, therefore, have significant implications for how tax burdens affect corporate innovation activities. Ref. [24], utilizing the 2005 World Bank survey data on Chinese enterprises, demonstrated that financing constraints considerably impede innovation, particularly for small to medium-sized enterprises, private entities, and those that are capital-intensive. Concurrently, other studies echo these findings, suggesting that financing constraints curtail enterprise innovation activities [25]. Conversely, easing these constraints can bolster innovation outputs [26]. Additionally, alleviating financing constraints aids enterprises in safeguarding their human capital, especially pivotal innovators and decision-makers, thereby enhancing innovation efficiency and both the volume and quality of innovation outputs [27,28].

Firstly, from the perspective of internal firm dynamics, enterprises require ample capital investment when engaging in innovation activities, especially high-risk ventures. Ref. [29] posited that the more disposable free cash flows a firm possesses, the greater its propensity to undertake spontaneous innovative activities, thereby enhancing its innovative outputs. Conversely, if a firm’s disposable cash flow is limited, embarking on innovative activities might exacerbate the risk of capital chain disruption. Under such circumstances, it might not be a prudent decision for firms to pursue innovation. Instead, they might prioritize maintaining the stability of their capital chain over innovation. The pecking order theory suggests that firms prefer internal, lower-cost financing methods when innovating. By decreasing the direct tax burden, enterprises can augment their free disposable cash flows, mitigating internal financing constraints and thereby invigorating innovation output [26,30].

Ref. [31] also revealed that the enactment of tax reduction policies, such as the US Job Creation Act, tempered market competition. This is attributed to the fact that excessive tax burdens can exacerbate financing constraints through the mechanism of product market competition, thereby depriving firms of the necessary funds for innovation. The competition in the product market acts as a conduit that magnifies the repercussions of tax burden changes. This influence is pivotal as it counteracts the benefits derived from free cash flow. Therefore, by slashing enterprises’ direct tax burdens, one can elevate the discretionary cash flows available to internal managers, alleviate internal financing constraints, and catalyze innovative activities [32,33,34,35,36]. This strategy simultaneously mitigates business risks.

Secondly, from an external enterprise perspective, relying solely on internal financing for innovation amplifies its associated uncertainties and risks. It is evident that Chinese firms predominantly turn to financial institutions such as banks or venture investors for external financing [37]. As [38] highlighted, when bank credit tightens, riskier loans are often curtailed to maintain a balanced risk profile across the loan portfolio. Given the inherently high risk of innovative ventures, such banking behaviors undoubtedly impose external financing constraints on firms and transmit negative signals externally. However, when the government introduces tax policies aligned with innovation activities, tax reductions enhance firms’ post-tax returns. This not only sends a positive signal but also mitigates the information asymmetry inherent in innovation [14,39,40]. By broadening external financing avenues, the adverse impacts of reduced bank lending are neutralized, enabling firms to overcome potential innovation stagnation due to funding shortages, subsequently amplifying innovation output [41,42]. Thus, decreasing the direct tax burden can also bolster enterprise innovation output by alleviating external financing constraints.

Drawing from the analysis above, reducing the direct tax burden empowers companies to augment their discretionary cash flow, project a positive external image, and diminish internal information asymmetry and agency dilemmas. These factors collectively enhance the firm’s innovation output by easing financing constraints [43,44].

The direct tax burden’s influence on innovation output varies based on factors such as property rights, corporate governance, and marketization levels. State-owned enterprises and non-state-owned enterprises experience different impacts due to these variations. Given the disparities in size, debt capacity, growth potential, resources, strategy, and culture across companies, their developmental capacities differ. Companies with robust corporate governance levels react differently to the direct tax burden compared to those with weaker governance structures, with the latter experiencing a more pronounced influence on their innovation trajectory. Consequently, companies possess diverse stances toward innovation when confronted with identical tax policies [45].

In summary, the influence of direct tax burden reduction on mitigating corporate financing constraints can be discerned from two distinct viewpoints: 1. Internal Financing Constraints: From an internal vantage point, enhancing a firm’s internal cash flow and mitigating the intensified market competition due to funding shortages can alleviate the company’s internal financing constraints. 2. External Financing Constraints: Viewing from an external perspective, reducing the direct tax burden projects a positive image externally, easing the enterprise’s information asymmetry and bolstering investor confidence. This can counteract the negative ramifications of diminished bank credits, thereby relaxing external financing constraints for companies. With reduced financing constraints, firms possess augmented disposable funds. This capital can be channeled to retain innovative talents, curtail innovation stagnation due to financial costs, and lessen innovation risks stemming from principal-agent issues. The ultimate objective is to elevate the enterprise’s innovative output. This mechanism is delineated in Figure 1.

Drawing from the preceding analysis, the paper posits the following research hypotheses:

Hypothesis 1. 

A significant inverse relationship exists between direct tax burden and innovation output.

Hypothesis 2. 

Diminishing the direct tax burden alleviates firms’ financing constraints, thereby enhancing their innovative output.

3. Research Design

3.1. Samples and Data

For this study, A-share primary board-listed companies in Shanghai and Shenzhen from 2010 to 2021 are the primary samples. The dataset undergoes a filtering process based on the subsequent criteria: (1) Exclusion of companies that were ST and PT listed during the period, (2) financial sector firms are omitted due to their unique financial statements, which differ from those of other industries. (3) removal of samples with missing pivotal data (4) to curtail the influence of extreme values on regression outcomes, all variables underwent a 1% and 99% quantile winsorization. After this rigorous filtration, the study comprises 1707 listed firms, resulting in 11,000 observational data points. Aside from the corporate governance index, the CSMAR database is the primary data source for this paper.

3.2. Variable Definitions

3.2.1. Dependent Variable (Innovation Output)

The emphasis of this paper is on the implications of tax and fee reductions on corporate innovation, necessitating the selection of an index that aptly gauges corporate innovation. The present literature predominantly employs two metrics for enterprise innovation: innovation input [46] and innovation output [47]. Given the intrinsic uncertainty and elevated failure rate characterizing enterprise innovation activities, the number of patent applications a company files offers a more accurate depiction of its innovation level than innovation inputs do [47]. Consequently, in alignment with [48], this study adopts the count of patent applications as the metric for assessing innovation output levels.

3.2.2. Independent Variable (Direct Tax Burden)

Recent data indicate that the corporate income tax constitutes the primary component of an enterprise’s direct tax burden, accounting for over 65% of it. This paper, therefore, utilizes the corporate income tax burden as a representation of the direct tax burden enterprises shoulder. In accordance with [49,50], the direct tax burden of enterprises is quantified by the ratio of direct tax to business revenue. A higher value suggests a steeper direct tax burden for the company.

3.2.3. Mediating Variables

Contemporary research offers three standard measures for financing constraints: the SA index [51], the KZ index [52], and the WW index [53]. The SA index, in comparison to the WW and KZ indices, has the advantage of sidestepping potential measurement errors by employing a model with two distinctly exogenous factors: firm age and firm size. To probe the mechanics of financing constraints, this study, in line with [54,55], employs the SA index to gauge the degree of financing constraints. The computation formula is delineated as follows:

$$\mathrm{S}\mathrm{A}=-0.737\mathrm{S}\mathrm{i}\mathrm{z}\mathrm{e}+0.043\mathrm{S}\mathrm{i}\mathrm{z}\mathrm{e}2-0.04\mathrm{A}\mathrm{g}\mathrm{e}$$

(1)

Size represents the firm’s scale, while age denotes the company’s age. A lower financing constraint for a company suggests greater ease in procuring financing. When the SA index is negative and its absolute value is substantial, it signifies heightened financing constraints for the enterprise (as per [54]).

3.2.4. Control Variables

Drawing from studies on enterprise innovation output [2], this research considers the following control variables: company age (Age), government subsidy (Size), company size (Growth), price-to-earnings ratio (MB), debt-to-asset ratio (Lev), corporate free cash flow (Fcf), stock return (Rate), proportion of independent directors (Dr), managerial position (Dual), largest shareholder’s shareholding ratio (Top1), proportion of intangible assets (LAR), and return on total assets (Roa). This study incorporates year- and industry-fixed effects into the regression model to mitigate potential omitted variable bias. Please see

Table A1. Variable Definitions.

Variable Types	Variable Name	Variable Definitions
Explained Variable	Patent	Ln (1+ Total number of patent applications)
Explanatory Variables	D_Taxburden	Direct tax burden, income tax expense/operating income
Mediating Variable	SA	−0.737Size + 0.043Size2 – 0.04Age
Control Variables	Age	The natural logarithm of a company’s years on the market
	Subsidy	Ln (1+ government subsidy)
	Size	The natural logarithm of total assets of the company
	Growth	Total revenue growth rate of the company
	MB	Stockholders’ equity/market value of the company
	Lev	The ratio of total liabilities to total assets of the company
	Fcf	Enterprise free cash flow
	Rate	Stock return, the annual stock return, considering cash dividends reinvested
	Dr	Proportion of independent directors, the proportion of independent directors
	Dual	Dummy variable, 1 if chairman and general manager are the same person; otherwise it is 0.
	Top1	The shareholding ratio of the largest shareholder
	LAR	Intangible assets/total assets
	Roa	(Total profit + Financial expenses)/Total assets
	Year	Year dummy variable
	Industry	Industry dummy variable
	Pro	Province dummy variable
Grouping variables	SOE	Nature of property right of listed company, 1 for state-owned enterprises; otherwise it is 0.
	CorGovindex	Corporate governance level is 1 if it is higher than the industry average; otherwise, it is 0.

.

3.3. Model Settings

Drawing from the preceding discourse, this study proposes the following model (2) to empirically evaluate the association between the direct tax burden and innovation output, thereby verifying Hypothesis 1:

$${\mathrm{P}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{t}}_{i,t}={\beta }_0+{\beta }_1{\mathrm{D}\_\mathrm{T}\mathrm{a}\mathrm{x}\mathrm{b}\mathrm{u}\mathrm{r}\mathrm{d}\mathrm{e}\mathrm{n}}_{i,t}+{\beta }_2{Controls}_{i,t}+\sum \mathrm{Y}\mathrm{e}\mathrm{a}\mathrm{r}+\sum \mathrm{I}\mathrm{n}\mathrm{d}+\sum \mathrm{P}\mathrm{r}\mathrm{o}+{\epsilon }_{i,t}$$

(2)

In Model (2), the dependent variable, patent applications (Patent_(_i,t)), signifies the company’s innovation output, while the independent variable D_Taxburden depicts the enterprise’s tax burden level. Besides the previously mentioned control variables, this research integrates year- and industry-fixed effects into the regression model to counteract the effects of omitted variables. The Hausman test is employed to determine the most appropriate effect (fixed or random) for the panel selection, yielding a test result of 1311.77. Given this outcome, we reject the null hypothesis, opting for the fixed effect model.

Within Model (2), the coefficient of direct tax burden, represented by β1, is of primary interest. If β1 is statistically significant and negative, it indicates that a reduction in the enterprise’s direct tax burden augments the number of patent applications. In other words, a pronounced negative correlation exists between the direct tax burden and innovation output.

To scrutinize the mediating effect of financing constraints in the relationship between corporate tax burden and innovation output, this paper introduces Models (3) and (4). Specifically, Model (3) is deployed to ascertain if a reduction in the direct tax burden can substantially mitigate corporate financing constraints, representing the initial phase of the mediation effect. A significantly negative coefficient β1 for financing constraint (SA) in Model (3) implies that with a decrease in the direct tax burden shouldered by the company, the financing constraint also diminishes. Model (4), which incorporates both the direct tax burden and financing constraint into the regression equation, represents the subsequent phase to corroborate the mechanism’s effect. In conjunction with Model (4), a significantly negative β1 combined with a significantly positive α2 reveals that financing constraints exert a mediating influence on the tax burden’s effect on innovation output. That is, the reduction in corporate tax burden facilitates enhanced innovation output by alleviating internal financing constraints.

$${\mathrm{D}\_\mathrm{T}\mathrm{a}\mathrm{x}\mathrm{b}\mathrm{u}\mathrm{r}\mathrm{d}\mathrm{e}\mathrm{n}}_{i,t}={\beta }_0+{\beta }_1{\mathrm{S}\mathrm{a}}_{i,t}+{\beta }_2{Controls}_{i,t}+\sum \mathrm{Y}\mathrm{e}\mathrm{a}\mathrm{r}+\sum \mathrm{I}\mathrm{n}\mathrm{d}+\sum \mathrm{P}\mathrm{r}\mathrm{o}+{\epsilon }_{i,t}$$

(3)

$${\mathrm{P}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{t}}_{i,t}={\alpha }_0+{\alpha }_1{\mathrm{D}\_\mathrm{T}\mathrm{a}\mathrm{x}\mathrm{b}\mathrm{u}\mathrm{r}\mathrm{d}\mathrm{e}\mathrm{n}}_{i,t}+{\alpha }_2{\mathrm{S}\mathrm{a}}_{i,t}+{\alpha }_3{Controls}_{i,t}+\sum \mathrm{Y}\mathrm{e}\mathrm{a}\mathrm{r}+\sum \mathrm{I}\mathrm{n}\mathrm{d}+\sum \mathrm{P}\mathrm{r}\mathrm{o}+{\epsilon }_{i,t}$$

(4)

4. Empirical Findings and Discussion

4.1. Descriptive Statistics and Correlation Analysis

Table 1. Descriptive Statistics of Variables.

	VAR	Ave	Median	sd	Min	Max	Size
Explained Variable	Patent	4.2920	4.4310	1.8940	0.0000	9.8390	11,000
Explanatory Variable	D_Taxburnden	0.0190	0.0120	0.0230	−0.0280	0.1990	11,000
Intermediary Variable	Sa	−3.8370	−3.8530	0.2620	−4.5560	−2.6710	11,000
Control Variable	Age	2.3820	2.7080	0.8780	0.0000	3.3670	11,000
	Subsidy	0.0050	0.0030	0.0070	0.0000	0.0530	11,000
	Size	22.7400	22.5600	1.3900	19.9100	27.5500	11,000
	Growth	0.1680	0.1010	0.4400	−0.5440	5.5400	11,000
	MB	0.6700	0.6830	0.2580	0.0720	1.2850	11,000
	Lev	0.4830	0.4890	0.1980	0.0670	0.9500	11,000
	Fcf	0.0100	0.0190	0.0910	−0.4420	0.2810	11,000
	Rate	0.0940	0.0040	0.4560	−0.6330	2.7260	11,000
	Dr	0.3740	0.3330	0.0550	0.2860	0.6000	11,000
	Dual	1.8180	2.0000	0.3860	1.0000	2.0000	11,000
	Top1	0.3700	0.3540	0.1540	0.0640	0.7890	11,000
	LAR	0.0510	0.0350	0.0600	0.0000	0.4930	11,000
	Roa	0.0560	0.0500	0.0570	−0.2250	0.3010	11,000
Grouping Variables	SOE	0.5960	1.0000	0.4910	0.0000	1.0000	11,000
	CorGovindex	0.5180	1.0000	0.5000	0.0000	1.0000	11,000

presents the descriptive statistics of the variables. Notably, the patent applications variable has a mean value of 4.292 and a median of 4.431, with its range spanning from a minimum of 0 to a maximum of 9.8390, and a standard deviation of 1.894. The variable D_Taxburden exhibits an average and median of 0.019 and 0.012, respectively. This suggests that the mean direct tax burden for the sampled listed companies constitutes 1.9% of their operational income. The Financing Constraints (SA) variable has a mean and median of −3.837 and −3.8530, respectively. Furthermore, the descriptive statistical outcomes for other control variables align well with existing research findings.

Table 2. Correlation Coefficient Test of Main Variables.

	Patent	D_Taxburnden	Sa
Patent	1.0000	−0.1150 ***	0.0043
D_Taxburnden	−0.1820 ***	1.0000	−0.0432 ***
Sa	0.0824 ***	−0.0346 ***	1.0000

Note: The bottom (left) and top (right) sections depict the results of the Pearson and Spearman correlation coefficient tests, respectively. ***, denotes significance at the 1% level.

presents the Pearson and Spearman correlation coefficients between the principal variables. The lower triangle depicts the Pearson correlation coefficient results, while the upper triangle represents the outcomes of the Spearman correlation coefficient test. The correlation matrix reveals a notable negative correlation between direct tax burden and the number of patent applications. Furthermore, there exists a significant positive correlation between the degree of financing constraints and the number of patent applications, aligning with our initial expectations. While the relationship between innovation output capacity and financing constraints is not significant in the Spearman correlation coefficient test, a thorough regression analysis is required to delve into the precise impact mechanism. Moreover, concerning the correlation coefficients, the coefficients among the primary variables are all significantly below 0.5, indicating the absence of severe multicollinearity among these variables.

4.2. Multiple Regression Analysis

In this research, regression tests for Models (2) to (4) utilize annual industry panel data from 2010 to 2021. The regression outcomes are displayed in Table 4. Specifically, Column (1) represents the regression results of Model (2). The coefficient for the direct tax burden (D_Taxburden) stands at −3.461 and is statistically significant at the 1% level. This suggests that as enterprises experience a reduction in the direct tax burden, they accumulate more free cash flow. Consequently, they encounter enhanced opportunities to engage in innovative activities laden with uncertain risks, thereby amplifying their innovation output (as supported by [42,56]). Thus, Hypothesis 1 (H1) is validated. In terms of economic significance, a tax reduction amounting to 1% of the operational revenue translates to a 3.556% surge in innovation output.

Columns (2) and (3) of

Table 3. Direct Tax Burden, Financing Constraints, and Firm Innovation Output.

VAR	(1)	(2)	(3)
	Patent	D_Taxburden	Patent
D_Taxburden	−3.461 ***		−3.269 ***
	(−5.224)		(−4.993)
Sa		−0.005 ***	0.794 ***
		(−2.967)	(5.003)
Controls	Yes	Yes	Yes
	(0.428)	(−0.284)	(0.712)
Constant	−7.462 ***	−0.031 ***	−3.653 ***
	(−10.310)	(−2.815)	(−3.532)
Annual effect	Yes	Yes	Yes
Industry effect	Yes	Yes	Yes
Obs	11,283	11,283	11,283
R-squared	0.567	0.567	0.511

Note: *** denotes significance at the 1% level. Values in parentheses represent either t-statistics or z-statistics corresponding to the coefficient.

detail the regression results for models (3) and (4), respectively. The coefficient for D_Taxburden in column (2) is −0.005 and is statistically significant at the 1% level. This underscores that a reduction in the direct tax burden leads to diminished financing constraints for enterprises. The alleviation of the direct tax burden mitigates both internal and external financing constraints. This is achieved by sending positive signals externally, buffering against the negative repercussions of diminished bank credit, and amplifying internal cash flow and profit margins. In column (3), the coefficient for the financing constraint (Sa) is positive and statistically significant at the 1% level. Considering this alongside the regression results from column (2), it becomes evident that financing constraints present a significant impediment to enterprise innovation. Easing these constraints fosters enterprise innovation output by curbing financing expenses and safeguarding human capital (as cited in [26]). Hypothesis 2 (H2) is thus validated. By directly diminishing the tax burden and consequently reducing corporate financing constraints, issues such as cash flow shortages, innovation stagnation, human capital deficits, and information asymmetry are substantially mitigated. This, in turn, bolsters the enhancement of innovation output.

4.3. Robustness Test

To validate the dependability of our findings, subsequent robustness tests will be undertaken.

4.3.1. Endogeneity Test

Beyond the challenges posed by potential omitted variables and measurement errors, which can instigate endogeneity issues, ref. [57] identified that firms with heightened innovation propensities are more inclined to engage in tax evasion. Such behavior introduces the risk of reverse causality, potentially undermining the credibility of the study’s conclusions. The instrumental variable (IV) approach serves as a robust solution to the aforementioned endogeneity concerns. Drawing inspiration from the methodologies of [2], this paper employs the average comprehensive tax burden of firms within the same city and industry as an instrumental variable for the tax burden. For an instrumental variable to be valid, it must satisfy two key conditions: exogeneity and relevance. Exogeneity: The average tax burden of firms operating within the same city and industry is predominantly influenced by macro-level determinants, including the overarching tax regime, intrinsic industry attributes, and the rigor of local tax enforcement mechanisms. Given that these factors remain largely unaffected by micro-level firm-specific characteristics, the instrument’s exogeneity criterion is deemed satisfied. Relevance: There exists a meaningful correlation between a firm’s individual tax burden and the overarching average tax burden characteristic of its city and industry. This relationship affirms the instrument’s relevance criterion.

Table 4. Endogeneity Testing: An Instrumental Variable Approach.

VAR	(1)	(2)	(3)
	First Stage	Second Stage
	D_Taxburden	Patent	Patent
IV	0.691 ***
	(22.900)
D_Taxburden		−8.259 **	−8.259 **
		(−2.425)	(−2.425)
Controls	Yes	Yes	Yes
Annual effect	Yes	Yes	Yes
Industry effect	Yes	Yes	Yes
Provincial effect	Yes	Yes	Yes
Constant	−0.075 ***	−13.462 ***	−13.462 ***
	(−3.701)	(−18.509)	(−18.509)
Obs	11,283	11,283	11,283
R-squared	0.536	0.568	0.568
Weak identification test	524.4

Note: ***, **, denote significance at the 1% and 5% levels, respectively. The values enclosed in parentheses represent the corresponding t-statistics or z-statistics for each coefficient.

presents the two-stage regression outcomes derived from the instrumental variable approach. In the table, column (1) displays the results from the first-stage regression. The coefficient of the instrumental variable (IV) stands at 0.691, significant at the 1% level. This indicates a strong correlation between the IV and the direct tax burden (D_Taxburden). At the base of the table, the Cragg–Donald Wald F-statistic, used for testing the weakness of the instrumental variable, is reported at 524.4. This value surpasses the critical threshold posited by [58]. Consequently, the null hypothesis, which suggests weak instrumental variables, is rejected, further validating the appropriateness of the selected instrumental variable. Column (2) presents the second-stage regression results. Here, the coefficient of the tax burden is −8.259, which is significant at the 5% level. This indicates a clear relationship: as the direct tax burden decreases, there is a significant enhancement in the innovation output level. This, in essence, leads to an increase in the number of patent applications submitted by enterprises. Column (3) showcases the outcomes of a straightforward regression. The ensuing results, detailed in

Table 5. Impact of Direct Tax Burden, Financing Constraints, and Patent Grant.

VAR	(1)	(2)	(3)
	Patent_A	D_Taxburden	Patent_A
D_Taxburden	−2.190 ***		−2.053 ***
	(−3.151)		(−2.970)
Sa		−0.010 **	0.570 ***
		(−2.224)	(2.653)
Controls	Yes	Yes	Yes
Constant	−8.622 ***	−0.051 **	−5.827 ***
	(−10.575)	(−1.989)	(−5.180)
Annual effect	Yes	Yes	Yes
Industry effect	Yes	Yes	Yes
Provincial effect	Yes	Yes	Yes
Obs	11,283	11,283	11,283
R-squared	0.3588	0.270	0.3525

Note: ***, **, denote significance at the 1% and 5% levels, respectively. Parenthesized values are the corresponding t-statistics or z-statistics for each coefficient.

, reinforce the paper’s main conclusions, affirming their robustness even when accounting for omitted variables, measurement inaccuracies, and potential reverse causality.

4.3.2. Replacement of Variable Measurement

To offset potential distortions arising from variable measurement errors in our conclusions, we adjusted the measurement methodologies of both the dependent and mediator variables and then reran models (2) through (4). For the dependent variables, we took cues from existing literature. Adhering to the methods used by [10], we substituted the number of patent applications with the number of patents granted as an indicator of a firm’s innovative output capacity. A higher count implies a more robust, innovative output capacity. Notably, patent grants, in contrast to patent applications, undergo stringent national evaluations, underscoring their higher quality and credibility. This substitution is captured in Model (5) as follows:

Pantent_A = ln (1 + Number of patents granted)

(5)

The regression outcomes in Table 5, after altering the dependent variable’s measurement method, indicate that the D_Taxburden coefficient in column (1) is −2.190, significant at the 1% level. This reaffirms the inverse relationship between direct tax burden and innovation output. The cumulative insights from columns (2) and (3) further underscore that by mitigating D_Taxburden, firms can bolster their innovative output by alleviating financing constraints. Hence, our findings remain robust even after adjusting the dependent variable’s measurement methodology.

Regarding the mediator variables, we turned to Whited and Wu (2006) and adopted the WW index to gauge financing constraints. This index offers a more comprehensive view as it encompasses not just a firm’s financial attributes but also industry-level external traits. To augment accuracy, we excluded Tobin’s Q value. The specific methodology is elucidated in Model 6.

$${\mathrm{W}\mathrm{W}\mathsf{\lambda }}_{\mathrm{i},\mathrm{t}}={\mathsf{\beta }}_1{\mathrm{T}\mathrm{L}\mathrm{T}\mathrm{D}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\beta }}_2{\mathrm{D}\mathrm{I}\mathrm{V}\mathrm{P}\mathrm{O}\mathrm{S}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\beta }}_3{\mathrm{S}\mathrm{i}\mathrm{z}\mathrm{e}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\beta }}_4{\mathrm{S}\mathrm{G}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\beta }}_5{\mathrm{I}\mathrm{S}\mathrm{G}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\beta }}_6{\mathrm{C}\mathrm{F}}_{\mathrm{i},\mathrm{t}}$$

(6)

where, ${TLTD}_{i,t}$ represents the ratio of long-term liabilities to total assets; ${DIVPOS}_{i,t}$ represents a virtual variable when dividends are distributed, and if dividends are distributed, ${DIVPOS}_{i,t}$ is 1; ${Size}_{i,t}$ represents the natural logarithm of total assets; ${SG}_{i,t}$ represents the growth rate of sales in the industry; ${CF}_{i,t}$ represents the ratio of cash flows to assets. The coefficient vector $\beta$ is defined by Whited and Wu (2006). A higher value indicates a more pronounced financing constraint faced by the enterprise.

Table 6. Modified Mediator Variable.

VAR	(1)	(2)	(3)
	Patent	D_Taxburden	Patent
D_Taxburden	−3.902 ***		−9.501 ***
	(−5.385)		(−12.197)
WW		0.024 ***	−1.585 ***
		(4.177)	(−3.496)
Controls	Yes	Yes	Yes
Constant	−7.468 ***	−0.012 ***	−12.988 ***
	(−9.756)	(−3.007)	(−39.100)
Annual effect	Yes	Yes	Yes
Industry effect	Yes	Yes	Yes
Provincial effect	Yes	Yes	Yes
Obs	10,133	10,133	10,133
R-squared	0.576	0.511	0.576

Note: *** denotes significance at the 1% level. The values in parentheses are the corresponding t-statistics or z-statistics for each coefficient.

showcases the regression results when employing this alternative measure for financing constraints. Notably: The coefficient for direct tax burden (D_Taxburden) in column (1) is −3.902, significant at the 1% level. Column (2) examines the relationship between the direct tax burden and financing constraints, where both the D_Taxburden and the financing constraint (WW) coefficients are positive and significant at the 1% level. Upon amalgamating insights from columns (2) and (3), it becomes evident that even after altering the financing constraint measurement approach, the positive impact of a reduced direct tax burden on easing corporate financing constraints and bolstering innovation output remains unaltered. Thus, the study’s conclusion retains its robustness.

4.3.3. Method of Changing Sample Size

To mitigate the influence arising from variable measurement inaccuracies, this study ventured into sample size modifications to ascertain the result’s robustness. Post-2013, China embarked on extensive reforms, with tax reform deepening and yielding significant strides. This prompted improvements in the local tax system, an increased emphasis on direct taxes, and elevated the prominence of direct taxes. Consequently, the sample was refined to span from 2010 to 2013. The regression outcomes in

Table 7. Changing Sample Size.

VAR	(1)	(2)	(3)
	Patent	D_Taxburden	Patent
D_Taxburden	−1.737 ***		−1.705 **
	(−2.589)		(−2.554)
Sa		−0.004 **	0.473 ***
		(−2.462)	(3.552)
Controls	Yes	Yes	Yes
Constant	−13.096 ***	−0.025 ***	−11.977 ***
	(−17.702)	(−4.081)	(−18.179)
Annual effect	Yes	Yes	Yes
Industry effect	Yes	Yes	Yes
Provincial effect	Yes	Yes	Yes
Obs	10,630	10,630	10,630
R-squared	0.570	0.511	0.570

Note: ***, **, denote significance at the 1% and 5% levels, respectively. Values in parentheses represent the corresponding t-statistics or z-statistics for each coefficient.

confirm the paper’s findings remain robust after the sample size is changed.

5. Further Analysis

5.1. Difference Analysis

To further delve into the nuanced effects of direct tax alterations on varying patent categories, our research, inspired by the methodologies of [59,60,61], bifurcates the overall patent applications into two distinct segments: Invention patent applications and non-invention patent applications. Here, non-invention patent applications encompass the collective sum of utility model patents and design patents. Intriguingly, compared to invention patents, the ripple effects of direct tax cuts might be more pronounced for non-invention patent applications. This assumption finds its roots in the inherent complexity and stringent standards associated with invention patents. The rigorous review process and elevated benchmarks inevitably translate to richer technological content within invention patents relative to their non-invention counterparts. Consequently, invention patent applications, due to their potential to shape the enterprise’s future trajectory, are more coveted. In scenarios where reduced direct tax burdens alleviate financing constraints, enterprises striving for breakthroughs and sustainable growth are predisposed toward pursuing invention patents, given their elevated technological stature and prospective long-term benefits. Given these dynamics, the sensitivity of patent applications (be they inventions or non-inventions) to direct tax fluctuations might exhibit variations. In light of this hypothesis, we embark on regression analyses, individually assessing the interplay between direct tax burdens and the two patent types.

Table 8. Patent grouping result.

VAR	(1)	(2)	(3)	(4)	(5)	(6)
	Patent_i	D_Tax	Patent_i	Patent_p	D_Tax	Patent_p
	Application for Invention Patent			Non-Invention Patent Application
D_Taxburden	−3.479 ***		−3.276 ***	−3.313 ***		−3.205 ***
	(−5.118)		(−4.881)	(−4.310)		(−4.170)
Sa		−0.010 **	0.858 ***		−0.010 **	0.465 **
		(−2.217)	(5.467)		(−2.217)	(2.127)
Controls	Yes	Yes	Yes	Yes	Yes	Yes
Annual effect	Yes	Yes	Yes	Yes	Yes	Yes
Industry effect	Yes	Yes	Yes	Yes	Yes	Yes
Provincial effect	Yes	Yes	Yes	Yes	Yes	Yes
Constant	−7.932 ***	−0.046 **	−3.748 ***	−10.022 ***	−0.046 **	−7.763 ***
	(−10.312)	(−1.990)	(−3.523)	(−10.987)	(−1.990)	(−5.560)
Observations	11,283	11,283	11,283	11,283	11,283	11,283
R-squared	0.410	0.271	0.426	0.243	0.271	0.233
SUR	3.89 **
	(0.0486)

Note: ***, **, signify that the estimated coefficient is statistically significant at the 1% and 5% levels, respectively. Parenthesized values represent the pertinent t-statistics or F-statistics for each coefficient.

presents the regression outcomes detailing how a reduced direct tax burden, by mitigating financing constraints, influences various patent types. From columns (1) and (3), the coefficient associated with the direct tax burden (D_Taxburden) stands at −3.479 and is statistically significant at the 1% level. This implies that diminishing the direct tax burden considerably bolsters the number of invention patent applications (Patent_i) by firms. Drawing insights from columns (2) and (3) reveals that the enhancement in patent applications arises primarily due to the alleviation of corporate financing constraints stemming from a reduced tax burden. Using the criterion established by [62] to assess the magnitude of the channel effect, the juxtaposition of product coefficients in columns (2), (3), (5), and (6) suggests a pronounced influence on elevating the submission of invention patent applications by enterprises. This heightened effect can be attributed to the inherent superiority of invention patents in terms of their technological depth and potential future contributions to firms, especially when compared to non-invention patents. As direct tax burdens decrease and, consequently, financing constraints relax, companies, striving to navigate existing challenges and foster sustainable growth, show a pronounced inclination toward pursuing invention patents, which harbor advanced technological nuances and promise long-term developmental prospects.

To further discern whether the impact of a reduced direct tax burden on innovative output varies significantly across diverse patent application types, this study employs the Seemingly Unrelated Regression (SUR) test to evaluate coefficient disparities within the samples. The obtained p-value stands at 0.0486. This result suggests that, in comparison to non-invention patent applications, the efficacy of diminishing the direct tax burden—through the mechanism of easing financing constraints—is particularly salient in amplifying the number of enterprise invention patent applications.

5.2. Heterogeneity Analysis

5.2.1. Regression by Nature of Property Right Grouping

Relative to non-state-owned enterprises, state-owned entities typically shoulder a lighter direct tax burden. Consequently, the potential for enhancing innovation output through the easing of financing constraints may be less pronounced for state-owned enterprises. This distinction can be attributed to the fact that Chinese state-owned enterprises, unlike their non-state counterparts, prioritize government directives over profit-making in their operational strategies. Such a stance ensures that irrespective of the prevailing tax burden, state-owned enterprises remain committed to innovation.

In light of this, state-owned enterprises, by virtue of their alignment with government objectives, are privy to more favorable policies. They benefit from “soft budget constraints” and inherent resource advantages, which collectively enable them to register higher innovative outputs. The dual factors of primary governmental objectives and “soft” budgetary constraints underscore this trend. Given these considerations, it is plausible to assume that in the Chinese context, the responsiveness of innovation output, financing constraints, and reductions in the direct tax burden varies between state-owned and non-state-owned enterprises. To investigate this, we segment all enterprises in the sample based on their property rights and proceed with a grouped regression analysis.

Table 9. Results Grouped by Nature of Property Rights.

VAR	(1)	(2)	(3)	(4)
	State-Owned Enterprise		Non-State-Owned Enterprise
	D_Taxburden	Patent	D_Taxburden	Patent
D_Taxburden		−3.491 ***		−1.707 *
		(−4.145)		(−1.717)
Sa	−0.002	0.998 ***	−0.005 ***	0.474 **
	(−0.992)	(4.273)	(−2.623)	(2.379)
Controls	Yes	Yes	Yes	Yes
Constant	−0.007	−5.104 ***	−0.054 ***	−3.820 ***
	(−0.514)	(−3.237)	(−3.844)	(−3.277)
Annual effect	Yes	Yes	Yes	Yes
Industry effect	Yes	Yes	Yes	Yes
Provincial effect	Yes	Yes	Yes	Yes
Obs	6722	6722	4561	4561
R-squared	0.299	0.242	0.298	0.223
Chow Test	6.37 ***
	(0.000)

Note: ***, **, *, denote that the estimated coefficient is statistically significant at the 1%, 5%, and 10% levels, respectively. Values in parentheses represent the t-statistics or z-statistics corresponding to the coefficient.

presents the regression outcomes segmented by property-right nature. Observing column (1), the coefficient for the financing constraint (Sa) of state-owned enterprises stands at −0.002, which is not statistically significant. In contrast, column (3) displays a coefficient of −0.005 for financing constraints, significant at the 1% level. This coefficient is notably larger than the one in column (1). Moreover, the coefficient for the direct tax burden in column (2) (D_Taxburden) surpasses its counterpart in column (4) (D_Taxburden). Such findings suggest that, for non-state-owned enterprises, a reduction in the direct tax burden can enhance innovation output by alleviating financing constraints. To ascertain whether the mitigating effect of a reduced direct tax burden on enterprise innovation output—achieved by easing financing constraints—varies significantly between enterprises with differing property rights, a Chow test was conducted. The test aimed to discern inter-group coefficient disparities. Results revealed a P-value of 0, underscoring that the alleviating impact of reducing the direct tax burden on non-state-owned enterprises, achieved through the financing constraint pathway, is more pronounced than in state-owned enterprises. One plausible explanation for this disparity is the “soft budget constraints” inherent in state-owned enterprises. Such enterprises face milder financing constraints and consequently have access to increased disposable cash flows compared to non-state-owned entities. Given the absence of “soft constraints” related to primary objectives and budgets in non-state-owned enterprises, these entities encounter more pronounced financing constraints than their state-owned counterparts. Hence, the potential of direct tax burden reductions to bolster innovation output by mitigating financing constraints is considerably stronger for non-state-owned enterprises than for state-owned ones.

5.2.2. Regression by Corporate Governance Level Grouping

Corporate governance levels of publicly traded companies can influence their innovative outputs. Firms with superior governance levels are likely to have diminished innovation deficits arising from issues such as information asymmetry and agency problems. Earlier findings suggest that a decrease in the direct tax burden not only conveys a positive signal to external entities but also helps stakeholders comprehend a firm’s tax relief situation and specific capital flow nuances via related policies. This, in turn, can alleviate financing constraints engendered by a company’s information asymmetry. In a competitive landscape, stakeholders might advocate for the firm to allocate this capital toward innovation. A reduced direct tax burden transmits an optimistic financial signal externally. Comparatively, firms with a lower governance level suffer from pronounced financial challenges and diminished innovation output due to information asymmetry and agency issues. Therefore, with a decrease in the direct tax burden, stakeholders, being privy to a company’s tax relief status and particular capital flow dynamics, can mitigate these challenges. They might then encourage such low-governance firms to prioritize innovation in a fiercely competitive environment. Consequently, the impact of tax relief on amplifying innovation output may be more palpable among samples with lower corporate governance levels.

To investigate this, the study segregated samples based on high and low corporate governance levels, using them as control groups. The grouped regression was applied to model (1) to test if the governance level influences the efficacy of tax reductions on enterprise investment. Adhering to methodologies from [63], seven factors were chosen to gauge corporate governance levels. These include: dual roles of chairman and general manager (DUAL); natural logarithm of board size (BOARD). 3. Proportion of independent directors (DR); cumulative compensation of the top three executives (Mana_Pay); ownership percentage of executives (Mana_Share); shareholding proportion of the second to tenth largest stakeholders relative to the dominant shareholder (Share_Balance); institutional investor ownership (Inst_Share). The principal component analysis method was employed to craft the corporate governance level index (GOVER). A higher GOVER value denotes superior corporate governance. Samples were bifurcated into two groups, high and low governance levels, based on the median, and underwent group testing.

The regression results in

Table 10. Regression Results by Corporate Governance Level.

VAR	(1)	(2)	(3)	(4)
	High Level of Corporate Governance		Low Level of Corporate Governance
	D_Taxburden	Patent	D_Taxburden	Patent
D_Taxburden		−2.455 ***		−4.612 ***
		(−3.203)		(−4.162)
Sa	−0.004 **	0.549 ***	−0.006 ***	0.895 ***
	(−2.111)	(2.923)	(−3.385)	(4.437)
Controls	Yes	Yes	Yes	Yes
Constant	−0.033 ***	−5.389 ***	−0.039 ***	−4.344 ***
	(−3.045)	(−4.651)	(−3.005)	(−2.890)
Annual effect	Yes	Yes	Yes	Yes
Industry effect	Yes	Yes	Yes	Yes
Provincial effect	Yes	Yes	Yes	Yes
Obs	6218	6218	5065	5065
R-squared	0.214	0.443	0.306	0.494
Chow Test	2.61 ***
	(0.000)

Note: ***, **, indicates significance levels at 1% and 5%, respectively. Values in parentheses are t-statistics or z-statistics corresponding to the coefficients.

reveal a significant negative correlation between the direct tax burden and financing constraint (Sa) across both groups. Furthermore, the financing constraint is positively linked with enterprise innovation output. This suggests that regardless of a firm’s corporate governance level—be it high or low—a reduction in the direct tax burden enhances innovation output by mitigating financing constraints. Notably, the coefficient for the financing constraint (Sa) is larger in the low governance group than in the high governance group. To further discern coefficient differences between these groups, a Zou test was conducted. The resulting joint F-statistic of 2.61 substantiates that, within the low governance sample, the impact of a reduced direct tax burden on bolstering innovation output—via the alleviation of financing constraints—is more pronounced.

5.3. Analysis of the Epidemic’s Influence on the Direct Tax Burden-Innovation Output Dynamic

The COVID-19 epidemic profoundly impacted China’s economic landscape, introducing unprecedented challenges to enterprise operations and growth [64]. To sustain operations, several firms resorted to measures such as extended layoffs and deferring innovation investments, potentially endangering their long-term viability [65]. To counteract these adversities, China unveiled a suite of tax relief measures, such as extending the maximum carry-over period, advocating for corporate rental reductions, cutting corporate value-added taxes, and progressively lowering corporate income taxes. These initiatives considerably alleviated firms’ tax obligations, solidifying their financial foundation for future innovative pursuits. Existing research suggests two potential dynamics influencing the direct tax burden-innovation output relationship during the epidemic. First, companies might intensify their innovation activities to navigate pandemic-induced challenges [49]. Thus, a reduced direct tax burden could further catalyze firms’ innovative endeavors during this period. Alternatively, companies, grappling with survival pressures, might strategically innovate or adjust research and development efforts to align with tax incentives. Such maneuvers aim to capitalize on tax benefits, possibly attenuating the inverse relationship between direct tax burdens and innovation output [66]. To delve deeper into the pandemic’s ramifications on this relationship, this study, inspired by [67], introduces a dummy variable, COVID. This variable is set to 0 for the period 2010–2018 and 1 for 2019–2021. The ensuing regression models are:

$${\mathrm{P}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{t}}_{i,t}={\beta }_0+{\beta }_1{\mathrm{D}\_\mathrm{T}\mathrm{a}\mathrm{x}\mathrm{b}\mathrm{u}\mathrm{r}\mathrm{d}\mathrm{e}\mathrm{n}}_{i,t}+{\beta }_2{\mathrm{C}\mathrm{O}\mathrm{V}\mathrm{I}\mathrm{D}\_\mathrm{T}\mathrm{A}\mathrm{X}}_{i,t}+{\alpha }_3{Controls}_{i,t}+\sum \mathrm{Y}\mathrm{e}\mathrm{a}\mathrm{r}+\sum \mathrm{I}\mathrm{n}\mathrm{d}+\sum \mathrm{P}\mathrm{r}\mathrm{o}+{\epsilon }_{i,t}$$

(7)

$${\mathrm{C}\mathrm{O}\mathrm{V}\mathrm{I}\mathrm{D}\_\mathrm{T}\mathrm{A}\mathrm{X}}_{i,t}={\mathrm{C}\mathrm{O}\mathrm{V}\mathrm{I}\mathrm{D}}_{i,t}*{\mathrm{D}\_\mathrm{T}\mathrm{a}\mathrm{x}\mathrm{b}\mathrm{u}\mathrm{r}\mathrm{d}\mathrm{e}\mathrm{n}}_{i,t}$$

(8)

Table 11. Direct Tax Burden, the COVID-19 Outbreak, and Innovation Output.

VAR	Patent
	(1)	(2)
D_Taxburden	−9.061 ***	−8.366 ***
	(−6.298)	(−6.511)
COVID_TAX		−5.187 ***
		(−3.767)
Controls	Yes	Yes
Annual effect	Yes	Yes
Industry effect	Yes	Yes
Provincial effect	Yes	Yes
Constant	−13.260 ***	−15.483 ***
	(−18.655)	(−19.811)
Observations	11,283	11,283
R-squared	0.567	0.457

Note: ***, indicates significance level at 1%. Parenthetical values are t-statistics or F-statistics corresponding to the coefficients.

presents the regression outcomes. The direct tax burden (D_Taxburden) and innovation output (Patent) exhibit a significant negative association. Furthermore, the interaction term (COVID_TAX) is negatively significant at the 1% level. This suggests that the onset of COVID-19 attenuates the negative correlation between direct tax burden and enterprise innovation output. This likely stems from the pressing challenges posed by the pandemic and the survival crisis. Consequently, some enterprises might prioritize strategic innovation activities over genuinely beneficial innovation efforts that sustain regular production and operations.

6. Research Conclusions

Utilizing Shanghai and Shenzhen A-share main board-listed companies from 2010 to 2021 as samples, this study, set against China’s tax and fee reduction policy backdrop, examines the repercussions of a reduced direct tax burden on corporate innovative output. It scrutinizes the mediating role of financing constraints and delves into three core areas: (1) the influence of direct tax burden fluctuations on diverse patent outputs; (2) the heterogeneous impacts of property rights and corporate governance on innovation output; and (3) the ramifications of the pandemic on the interplay between direct tax burden and enterprise innovation. Key findings include: (1) Tax reduction policies significantly bolster innovative enterprise output by alleviating financing constraints. This assertion holds under various robustness checks, such as adjustments in explanatory and intermediary variable measurements, sample size modifications, instrumental variable applications, and the inclusion of provincial dummy variables. (2). Reducing direct tax burdens retains more discretionary cash flow within enterprises, eases financing constraints, and amplifies both invention and non-invention patent applications. However, the effect is more pronounced for invention patent applications. (3). Non-state-owned enterprises exhibit a more pronounced relationship between direct tax burden, financing constraints, and innovation output than their state-owned counterparts. (4). Enterprises with lower corporate governance levels display a more significant relationship between direct tax burden, financing constraints, and innovation output than those with higher governance levels. (5). The advent of COVID-19 considerably weakens the nexus between direct tax burden and innovation output.

This paper discusses several implications for further implementing tax reduction. Firstly, ensuring the sustainable development of enterprises is crucial for achieving high-quality economic growth in China. The findings of this study affirm the positive impact of tax reduction policies at China’s current developmental stage. This can serve as a valuable reference for companies seeking to utilize tax reduction policies to bolster sustainable development. In addition, the paper suggests that increasing tax cuts for non-state-owned enterprises could significantly enhance economic growth. By lessening the tax burden on these enterprises, internal demand can effectively expand, further empowering the development of non-state-owned enterprises.

However, a limitation of this study is its exclusive focus on income tax as the sole measurement index of the direct tax burden, excluding other taxes. Despite income tax accounting for over 65% of the direct tax burden, the study acknowledges the potential impact of other taxes, albeit their dispersed nature and relatively small proportion. This limitation highlights the need for future research to employ a more comprehensive approach to measuring the direct tax burden for a more accurate assessment.