Government subsidies and green innovation in chinese enterprises based on the synergy of executive incentives

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Asian Journal of Technology Innovation ISSN: (Print) (Online) Journal homepage: www.tandfonline.com/journals/rajt20 Government subsidies and green innovation in Chinese enterprises-based on the synergy of executive incentives Hu Liu, Xiaoxuan Yu & Yijun Peng To cite this article: Hu Liu, Xiaoxuan Yu & Yijun Peng (2023) Government subsidies and green innovation in Chinese enterprises-based on the synergy of executive incentives, Asian Journal of Technology Innovation, 31:3, 534-555, DOI: 10.1080/19761597.2022.2131586 To link to this article: https://doi.org/10.1080/19761597.2022.2131586 Published online: 10 Oct 2022 Submit your article to this journal Article views: 254 View related articles View Crossmark data Citing articles: View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=rajt20 ASIAN JOURNAL OF TECHNOLOGY INNOVATION 2023, VOL 31, NO 3, 534–555 https://doi.org/10.1080/19761597.2022.2131586 Government subsidies and green innovation in Chinese enterprises-based on the synergy of executive incentives Hu Liu, Xiaoxuan Yu and Yijun Peng International Business School, Shaanxi Normal University, Xi’an, People’s Republic of China ABSTRACT KEYWORDS Government subsidies; green Based on the micro data of China’s heavily polluting enterprises innovation; China’s heavy from 2010 to 2019, this article analyzes the synergistic effect of pollution enterprise; government subsidies and executive incentives on green compensation incentive; innovation It is found that government subsidies significantly equity incentive promote the output of innovation results, and this effect has a time lag Executive compensation incentives will weaken the current policy effect, and the benefit convergence effect produced by equity incentives can reverse executives’ short- sighted thinking Although the current impact of equity incentives is not significant, it can play a substantial synergistic effect in the first and second lag periods It is proved that the green innovation of heavy pollution enterprises can not only consider the impact of exogenous policy but ignore the perfection of internal governance mechanism Introduction and literature review According to the ‘2021 Interim Report on the State of the Global Climate’ released by the World Meteorological Organization (WMO), the frequency and intensity of global climate extremes are rising rapidly, which may form a ‘dangerous compound effect’ with the impact of the epidemic and economic recession The problem of environmental degradation deserves the vigilance of all countries in the world After more than 40 years of rapid development of reform and opening up, China’s environmental carrying capacity is gradually approaching the upper limit, and ecological governance is immi- nent China’s 2060 carbon neutrality strategy emphasises the importance of technology in improving climate and environmental change, and clarifies that emission reduction needs to shift from end-to-end governance to source control, and the growth model from factor-driven to innovation-driven Therefore, green innovation has received a lot of attention from Chinese academia Regarding green innovation, there is currently no generally accepted definition in academia Early scholars mostly believed that green innovation is a new technology or new product with the premise of protecting the eco- logical environment and the pursuit of economic benefits With the extension and devel- opment of the concept of green innovation, green management innovation (such as green marketing, green supply chain, etc.) is gradually included in the category of CONTACT Hu Liu liuhusnnu@163.com Shaanxi Normal University, International Business School, 620 West Chang’an Street, Xi’an 710062, People’s Republic of China © KOSIME, ASIALICS, STEPI 2022 ASIAN JOURNAL OF TECHNOLOGY INNOVATION 535 green innovation However, considering the research purpose of this article, the green innovation referred to in this article is more inclined to green technology innovation Green equipment innovation, green product innovation, and green production material innovation all belong to the category of green technology innovation Compared with general innovation, green innovation pays more attention to environmental benefits, that is, whether the damage to the environment can be reduced or avoided From the perspective of life cycle, green innovation should include the whole process from idea formation to market launch Green R&D is the capital invested for green inno- vation activities, and it is the beginning of enterprise green innovation activities Accord- ing to Hamamoto’s (2006) research and combined with the data of the ‘China Science and Technology Statistical Yearbook’, the green R&D investment in China from 2000 to 2019 can be calculated, as shown in Figure The green R&D investment generally shows an upward trend, with an average annual growth rate of 15.27% The annual growth rate of general R&D investment is 18.41%, which is slightly higher than that of green R&D investment, but there is a large order of magnitude difference between the two At this stage, China’s green R&D investment seriously underinvested Although green innovation is considered to be the first driving force to lead high-quality economic development and enterprise transformation (Guo et al., 2019a), the dual externalities of green innovation and the profit-seeking nature of capital lead to the fact that enterprises tend to prefer economies of scale and short-term economic benefits while ignoring the environment protection in the process of development, lack of enthusiasm and initiative to increase green R&D investment In addition, the lack of scientific research personnel, technology and funds also hinders the improvement of enterprises’ green governance and innovation capabilities Since this article pays more attention to the results of enter- prise green innovation activities and the feasibility of measurement indicators, the number of green patents is selected to reflect the level of green innovation in Figure The reason for not using green R&D is that the greater the number of green R&D does not mean the more green patents According to statistics, the average annual growth rate of green patents in China from 2000 to 2019 is 24.07%, which is higher Figure Trend chart of R&D investment for green innovation in China 536 H LIU ET AL Figure Trend chart of green innovation and other types of innovations in China than that of common patents The number of green patents in 2019 is about 60 times that of 2000 However, there is still a big gap with leading countries such as the United States, Japan and Germany To solve environmental problems, China has formed a governance system led by the government, dominated by enterprises, and participated by social organisations and the public The government has been revising and promulgating laws, regulations, and policy measures for a long time, so as to incorporate environmental factors into the production function of enterprises, and encourage or force green transformation of enterprises Gov- ernment subsidies and environmental taxes are the two main means of current govern- ment intervention See Table for details In order to alleviate the financing constraints faced by enterprises and reduce the negative impact of ‘market failure’, the Chinese central government and local govern- ments have widely adopted fiscal and taxation policies to intervene in innovation entities Table Comparative analysis table of government subsidies and environmental taxes Type Government subsidies Environmental tax-independent taxes in China Mechanism Resource Supplement Punitive pushback Responsible Finance Department Tax Department Department Wide range of objects Enterprises, institutions and other producers and Subsidy object operators that directly discharge taxable There is information asymmetry between the pollutants into the environment Challenge government and enterprises, and it is difficult for the government to directly supervise the Under the ever-increasing environmental use of government subsidy funds by protection supervision, in recent years, there enterprises, and it is even difficult to determine has been a ‘one-size-fits-all’ approach in whether the enterprises that receive environmental supervision and law government subsidies really have the enforcement, such as companies shutting corresponding qualifications down polluting production activities to deal with the behaviour of the inspectors ASIAN JOURNAL OF TECHNOLOGY INNOVATION 537 Government subsidies are free funds allocated by governments at all levels to enterprises They are an ex-ante incentive for enterprises, and their smoothing effect on innovation has also been questioned by many academic circles Scholars of the incentive view believe that the signalling effect of government subsidies makes enterprises more favoured by the capital market (Xia & He, 2020), easy to obtain external input, reduce financing con- straints (Li et al., 2019; Montmartin & Herrera, 2015), and higher expected returns enhance their innovation willingness (Yu et al., 2021a); secondly, the ‘leverage effect’ hypothesis believes that the various review and evaluation mechanisms formulated by the government around the subsidy policy are also conducive to improving the R&D investment and economic performance of enterprises, and alleviating the opportunism of enterprises in innovation incentives (Ding & Xie, 2021; Yu et al., 2021b); furthermore, the government allocates the risk of innovation failure through R&D funds, affects the allocation of innovation resources, and then promotes R&D innovation (Du & Zhang, 2020; Hu & Deng, 2019) Scholars who hold the inhibition view believe that the horizon- tal competition of local governments can easily lead to enterprise policy arbitrage, which leads to policy failure and waste of public resources The serious ‘patent bubble’ problem also makes government subsidies and enterprise innovation choices fall into the ‘prison- er’s dilemma’ (Hu & Jin, 2021) The influx of a large number of government subsidies will also reduce the risk-taking spirit of entrepreneurs and inhibit innovation performance There are also differences in the investment goals of the government and enterprises, and the funds used for green R&D activities may be misappropriated or directly crowded out of enterprises self-owned R&D funds (Liu et al., 2019) Different from the resources allocated by other market mechanisms, subsidies lack corresponding value appeals and are ‘inactive’ in innovation activities (Jourdan & Kivleniece, 2017) From the perspective of market supply, the increase in financial subsidies may also lead to an increase in resource prices, a decline in marginal benefits, and an adverse impact on innovation output The promotion and inhibition of government subsidies and green innovation may occur successively (Huang et al., 2016; Wang & Wang, 2020b; Wu & Zhang, 2021; Zhang, 2020), property rights (Jin et al., 2018), scale (Pere, 2013), type of government subsidies (Lou et al., 2021), system quality (Bianchini et al., 2019), the policy attention of enterprises will also cause differences in research results (Fu & Gao, 2021) In fact, the output of green innovation not only depends on the resource endowment of enterprises, but also is affected by differences in internal governance of enterprises From the principle of the dialectical relationship between internal and external causes, we can see that the internal cause is the fundamental cause of the development of things, the external cause is the condition of change, which acts through the internal cause Therefore, only relying on external policies cannot fundamentally improve the green innovation performance of enterprises and promote the ‘greening’ process of enterprises In recent years, scholars have also begun to pay attention to the impact of internal governance differences on green innovation For example, the shareholding of state-owned enterprises can promote the green governance of private heavily polluting enterprises (Wang et al., 2022), and non-state-owned equity participation in state- owned enterprises also plays a positive role (Zhao et al., 2022); the stronger the execu- tives’ dual environmental awareness, the better at identifying and grasping the market opportunities brought by green innovation, they also actively reflect on the shortcomings 538 H LIU ET AL of the enterprise’s own green development, and implement a green innovation strategy (Xi & Zhao, 2022); influenced by morality and ethics, green investors are willing to reduce interest demands, which can prompt enterprises to implement green actions, increase green expenditures, and improve green governance performance (Jiang et al., 2021) In modern enterprises, senior executives hold a large part of the management rights of the enterprise and become the makers and implementers of enterprise decision-making In the case of information asymmetry, the existence of agency pro- blems makes executives more likely to focus on arbitrage for personal gain when making decisions Risk aversion, high innovation failure costs, and lack of innovation compensation mechanisms further weaken executives’ green innovation tendency Com- pared with stimulating innovation, stimulating green innovation is a more challenging proposition How to use the executive incentive mechanism to enable enterprise man- agers to actively carry out green innovation activities, improve the policy effect of govern- ment subsidies, and realise the ‘green’, ‘ecological’ and ‘innovative’ of enterprise, has both theoretical and practical significance Therefore, this article takes heavily polluting enterprises as samples to explore the relationship between government subsidies and green innovation and the moderating effect of executive incentives on the two It may enrich and deepen the existing research in the following aspects: (1) The empirical research conclusions on the effect of government subsidies are quite different, and the existing literature on government subsidies and enter- prise green innovation is still relatively small, the effect of government subsidies in heavily polluting enterprises needs more evidence to support (2) ‘The Suggestions of the Central Committee of the Communist Party of China on Formulating the Fourteenth Five-Year Plan for National Economic and Social Development and the Long-term Goals for 2035’ pointed out that the green transformation of key industries and key areas should be pro- moted in the future Therefore, this article takes the heavily polluting enterprises as the research object, and considers the macro-policy perspective (government subsidies) and the micro-perspective of enterprises (executive incentives) to study the green innovation of enterprises, which can provide some enlightenment for how to promote the construction of ecological civilisation in China by improving the coordination of internal and external mechanisms (3) This article analyzes the effect of government subsidies under different executive incentive methods, which will help relevant government departments to effectively identify enterprises before subsidies are issued, so as to reduce supervision costs and trans- action costs, and reduce the possibility of enterprises breaking the invisible contract Theoretical analysis and research hypothesis 2.1 Government subsidies and green innovation Dual externalities are the main reason for the low enthusiasm for green innovation in the current heavily polluting enterprises From the externality theory, it can be known that in economic activities, if enterprises cannot enjoy all the benefits of decision-making or needs to bear all the costs of decision-making, externalities will occur Knowledge and technology have positive externalities, the green innovation achievements of heavily pol- luting enterprises are also prone to spillover, leading to the widespread phenomenon of ‘free riders’ in the industry If competitors quickly imitate and reproduce at low cost, it ASIAN JOURNAL OF TECHNOLOGY INNOVATION 539 will greatly shorten the time for the enterprise to enjoy the technological advantages, market position and high economic returns brought by the green innovation achieve- ments, and even cannot make up for the enterprise’s early innovation investment, which greatly dampen the enterprise’s enthusiasm for green innovation This phenom- enon will become more prominent when the mechanism is relatively weak The negative externality of environmental pollution means that the pollution costs incurred by enter- prises in the production and operation process are not fully borne by the enterprises themselves Without being punished, enterprises lack the initiative to adopt green tech- nologies It can be deduced from this that without corresponding policy incentives and institutional constraints, the development and use of green technologies will be uneco- nomical for heavily polluting enterprises that are currently rational economies In addition, innovation activities require stable financial support, but the endogenous financing of heavily polluting enterprises is generally difficult to meet innovation needs (Cao et al., 2021) China’s financial market is also seriously lagging behind indus- trial development, and the allocation of market resources has failed Therefore, govern- ment departments need to effectively intervene in the innovation activities of enterprises by using government subsidies as an innovative resource supplement mechanism Based on the resource-based view, government subsidies, as an ‘ex-ante incentive’ measure, can provide enterprises with certain resources and directly alleviate the financing constraints of enterprises in a way of nearly zero financing costs, which is con- ducive to enhancing the green innovation ability and willingness of enterprises to inno- vate, leading them to increase the intensity of innovation investment, manage R&D activities in a refined manner, and accelerate the innovation process From the perspec- tive of ‘signaling’ and ‘authentication effect’, government subsidies can reduce the nega- tive effects of information asymmetry In order to maintain a competitive advantage and prevent the leakage of core secrets, enterprises will strictly control the leakage of infor- mation before the final results are formed The complexity and opacity of the innovation process make it impossible for outside investors to judge the expected return of project investment, resulting in increased financing constraints (Hall & Lerner, 2010) Govern- ment subsidy is equivalent to sending a signal to the market as an intermediary, that is, the enterprise is recognised and focused by the government, which is conducive to enhancing investor confidence, expanding enterprise financing channels, ensuring the necessary capital investment for green innovation activities, reducing the marginal cost of R&D activities, and preventing the crowding of normal operating cash flow From the perspective of cost and risk sharing, local governments use government subsi- dies to provide financial support for R&D activities, and share the risk of innovation failure with enterprises Enterprises in the initial stage of transformation may need to some preparations for R&D activities, such as purchasing certain new equipment, hiring scientific researchers, and forming R&D teams Government subsidies are used to reduce the sunk costs of enterprises and ease the pressure on capital flow In the process of ‘learning by learning’ and ‘learning by doing’, the knowledge reserve of enter- prises increases dynamically and improves the possibility of successful innovation activi- ties in the future For enterprises that have already carried out R&D activities, government subsidies can reduce the marginal cost of enterprises, encourage more R&D investment, compensate for losses caused by technology spillovers, bridge the gap between private benefits and social benefits At the same time, it helps enterprises 540 H LIU ET AL share the risks of innovation activities and reduces the probability of bankruptcy of enter- prises after innovation fails In addition, the government will strengthen the regulation and supervision of enterprises that receive subsidies, further improving the efficiency of innovation output of enterprises (Wang et al., 2017) Based on this, the first research hypothesis of this article is put forward: H1: Government subsidy plays a positive role in promoting green innovation of heavy pol- lution enterprises 2.2 Moderating effects of executive incentive The incentive mechanism of executives stems from the first type of principal-agent problem The income function of enterprise executives and shareholders is not consist- ent Shareholders can diversify their shares to diversify risks and obtain benefits The wealth accumulation and career prospects of senior management depend on the success or failure of the enterprise If the incentive contract cannot provide enough incentives to offset the negative impact of the failure of green innovation activities, execu- tives may be ‘lazy’ and ‘inaction’ in innovation activities due to career concerns Because the value-creating effect of green innovation is difficult to translate into observable per- formance of enterprises in the short term, executives’ ‘short-sightedness’ and lack of awareness of green innovation will also affect enterprises’ decision-making choices and investment rankings How to implement effective incentives for senior management has always been a hot topic in the theoretical and practical circles If the internal incentive mechanism of the enterprise is ineffective, the implementation and operation costs of government subsidies will be increased, and it is difficult to achieve the best ‘greening’ effect Innovation may even become a tool for executives to capture resources and pursue self-interest (Tong et al., 2014) According to existing research, executive incen- tives are mainly divided into compensation incentives and equity incentives The adjust- ment effects of different incentive methods are as follows 2.2.1 The moderating effect of compensation incentives The executive compensation incentive mechanism is to establish executive compensation on the basis of certain performance standards At present, Chinese executives are in the stage of wealth accumulation Compensation incentives link executives’ monetary returns with the short-term interests of the enterprise, and are believed to satisfy execu- tives’ wealth needs and curb their risk aversion tendencies, so that executives can perform their duties diligently, make scientific and effective business decisions (Wang & Wang, 2020a), stimulate enthusiasm for work, and concentrate on strengthening the manage- ment of R&D activities of enterprises Ultimately, the efficiency of using government sub- sidies is improved, while the ‘crowding out’ effect on the original R&D funds of enterprises is weakened, and the probability of successful green innovation activities is increased Although green innovation activities are beneficial to enterprises, it has large investment scale, long payback period and high risk, and cannot generate cash flow during the tenure of senior executives, which may have a negative impact on com- pensation incentives based on short-term performance The preference of executives for short-term benefits such as salary and bonuses will reduce their risk tolerance, and even ASIAN JOURNAL OF TECHNOLOGY INNOVATION 541 stick to conservative investment decisions in order to maintain the existing monetary income, and the development of core technologies will be locked back to low-end orien- tation Secondly, green innovation activities will increase the current cost of enterprises and reduce investment in productive and profitable projects When business perform- ance declines, stakeholders such as shareholders will question the operational capabilities of executives, and the career prospects and personal reputation of the executives will also be damaged As a result, executives may respond negatively to the green innovation activities of the company In the absence of strong support from senior executives, the internal green innovation power of enterprises is insufficient, project operations lack planning, and innovation efficiency is low Therefore, the role of government subsidies in promoting green innovation in enterprises is weakened Accordingly, the second research hypothesis of this article is put forward: H2: The executive compensation incentive policy plays a significant negative role in regulat- ing the relationship between government subsidy and green innovation 2.2.2 The moderating effect of equity incentives It is generally believed that equity incentives enable executives to obtain the distribution rights of residual income through shareholding, resulting in a convergence effect of inter- ests The long-term value of the enterprise and the personal value of the executives are unified, which enhances the sense of protagonist of the executives, encourages the execu- tives to reduce adverse choices in strategic decision-making, and make strategic decisions that are in line with the sustainable development of the enterprise Due to information asymmetry, it is difficult for the government subsidy support mechanism to rely on exter- nal orders to carry out orderly development The green innovation funds given to enter- prises by government departments may be misappropriated to other projects, or have a ‘crowding out’ effect on the enterprise’s own R&D investment Even if there is external supervision, the use of subsidy funds and the management of green innovation activities are difficult to achieve an effective state, which increases the cost of supervision and reduces the efficiency of government subsidies When there is a reasonable equity incen- tive contract within the enterprise, it will increase the executives’ tolerance for short-term green innovation failures, and give incentive objects generous remuneration in the long run, so that executives have strong green innovation motivation and strong willingness to green governance Not only government subsidies are used for green innovation activi- ties, but additional R&D investment will be added Therefore, under the synergy of equity incentives, the positive effect of government subsidies on green innovation of enterprises is magnified In recent years, environmental policies have become increasingly strict, and the new Environmental Protection Law has introduced information disclosure mechan- isms for public supervision, which has improved the transparency of enterprise environ- mental information and significantly reduced the opportunistic behaviour of enterprises to conceal environmental information (Wang et al., 2020) Local governments have also tightened penalties for environmental violations Because the frequent exposure of enter- prise violation information will accelerate the depreciation of executives’ human capital, executives can make strategic choices to maintain enterprise reputation out of risk aver- sion considerations At the same time, the accumulation of negative environmental news has led to a rising risk of stock price collapse (Yu & Bi, 2021) In order to increase stock 542 H LIU ET AL Figure Theoretical hypothetical framework prices to achieve asset preservation and appreciation, executives will be more proactive in carrying out green innovation activities Therefore, the third research hypothesis of this article is proposed: H3: Executive equity incentive policy plays a significant positive role in regulating the relationship between government subsidy and green innovation Based on the above theoretical analysis and research hypotheses, a research frame of the relationship is constructed in Figure 3 Research and design 3.1 Sample selection and data source This article selects 2010–2019 A-share listed companies in China’s Shanghai and Shenzhen stock markets with heavy pollution industries as the research object, and the heavy pol- lution enterprises are defined according to the sixteen subdivided industries such as thermal power, iron and steel involved in the Guide to Environmental Information Disclos- ure of Listed Companies issued by the Ministry of Environmental Protection in 2010 According to the division standard of the Guidance of Industry Classification of Listed Companies issued by the CSRC in 2001, the corresponding secondary industries are com- pared, and then whether the listed companies have the attribute of heavy pollution industry is judged In order to ensure the quality of the research data, the article further screened the samples as follows: (1) Exclude enterprise samples that were ST and *ST during the sample period; (2) Exclude the enterprise samples listed in 2011 and later; (3) Exclude enterprise sample with missing financial data After the above treatment, this article finally obtained 536 heavy pollution listed enterprises 5360 balance panel data The green patent application data of listed companies comes from CNRDS, and other enterprise governance and financial data come from CSMAR At the same time, in order to avoid the influence of out- liers on the research conclusions, this article conducts Winsorize at the upper and lower 1% level for all continuous variables The data was processed using Excel2010 and Stata16.0 3.2 Variable design 3.2.1 Dependent variable Green innovation activities of enterprises include green innovation input and green inno- vation output Most researches on green innovation use energy consumption or new ASIAN JOURNAL OF TECHNOLOGY INNOVATION 543 product output value to measure However, this method cannot accurately meet the need for research on the level of green innovation at the microcosmic individual level of enterprises (Xiao et al., 2021) The cost of green R&D input has not been measured and disclosed in the financial report, and it is difficult to separate from the R&D input of enterprises Therefore, this article selects the number of green patent applications to represent the green innovation capability of enterprises In the process of data collation, this article can distinguish green patents and non-green patents by checking whether keywords such as ‘energy saving’ and ‘emission reduction’ appear in documents such as corporate annual reports and patent appli- cation materials The reason for not choosing the number of green patent grants is that cur- rently a patent usually takes 1–2 years from application to grant, and it is easily affected by external interference during the granting process, which is unstable In comparison, the enterprise green patent application process has already indicated that the enterprise is carry- ing out innovation activities So, the number of patent applications will more timely and reliably reflect the real green innovation level of enterprises than the number of patent grants This article uses the sum of the current green invention patents and green utility patents of enterprises to measure green innovation, and adds to the number of green patent applications in the regression model to take the logarithm 3.2.2 Independent and moderator variables (1) Independent variables In this article, the total amount of government subsidy disclosed in the annual report of listed companies is used to measure the subsidy intensity (2) Moderator variables For compensation incentive, this article draws on the method of Guo et al (2019b), and uses the ratio of the total compensation of the top three executives to the total compensation of all executives Due to the generally low share- holding level of executives in some listed companies, the total number of shares held by executives is added by and the natural logarithm is taken to measure equity incentives (Yin et al., 2018) 3.2.3 Control variables (Table 2) Table Variable definition table Type Name Symbol Definition Gpatent Dependent Green innovation LN(1 + The number of green patent applications in the variable Subsidy current period) Government subsidies Independent Payinc LN(1+ Total amount of government subsidies for the current variable Compensation incentive period) Shainc Moderator Equity incentive Roa Top three executive payroll/Executive payroll variable Rate of return on total RD LN(1 + Total number of shares held by executives) Control variable assets Age Net profit/Total asset balance R&D input Business Age Soe R&D input/Operating income The number of years from the enterprise’s founding period Nature of property right TobinQ to the sample period Ability to grow Virtual variable: for state-owned enterprises and for non- state-owned enterprises (Stock market value + Net debt)/Total assets 544 H LIU ET AL 3.3 Model design In order to test the relationship between government subsidy and enterprise green inno- vation, and the moderating effect of executive incentive on the relationship, under the condition of controlling the main influencing factors of enterprise green innovation, the following regression model is constructed in sequence: Gptentit = a0 + a1Subsidyit + a2Xit + mi + gt + 1it (1) Gptentit = b0 + b1Subsidyit + b2Subsidyit × Payincit + b3Payincit +b4Xit + mi + gt + 1it Gptentit = l0 + l1Subsidyit + l2Subsidyit × Shaincit + l3Shaincit +l4Xit + mi + gt + 1it Among them, subscript i represents enterprise, t represents year; Gpatent represents the enterprise green innovation variable, Subsidy represents the government subsidy variable, Payinc and Shainc represent executive compensation incentives and equity incentive variables, respectively X are a set of control variables, μ, γ, and ε represent firm fixed effects, year fixed effects, and stochastic disturbance term The key parameters of this article are α1, β2 and λ2, which reflect the specific impact of government subsidies on green innovation and the moderating role of executive incentive Empirical results 4.1 Descriptive statistics Descriptive statistics of the primary variables for this article are presented in Table The average value of green innovation is 3.100, the standard deviation is 9.500, the minimum value and the median value are zero, indicating that more than half of the sample enter- prises not carry out substantial green innovation activities, resulting in a generally low green patent output level and a large degree of dispersion The maximum value of gov- ernment subsidy is 849741992 RMB (about US$126,016,737.41), the minimum value is zero, the mean value and median value are 49273866 RMB (about US$7,307,314.33) and 13028658 RMB (about US$1,932,149.98) respectively, which indicates that the subsidy amount obtained by different sample enterprises varies greatly The minimum value of executive compensation incentive is 0.22, the maximum value is 0.89, and the standard deviation is 13.600 The minimum and median of senior executives’ equity Table Descriptive statistics of main variables Variable name Sample size Mean Median Standard deviation Min Max Green innovation 5360 3.100 9.500 72 13028658 118339666 849741992 Government subsidies 5360 49273866 22 44.300 13.600 89 Compensation incentive 5360 46.300 66613486 −0.238 404612837 Equity incentive 5360 24303059 0.037 0.065 4.170 0.227 0.010 0.022 0.107 Rate of return on total assets 5360 0.041 5.460 0.870 30.400 18 0.500 R&D input 5360 0.019 1.390 1.650 8.430 Business Age 5360 17.800 Nature of property right 5360 0.522 Ability to grow 5360 2.120 ASIAN JOURNAL OF TECHNOLOGY INNOVATION 545 incentive are all zero It can be seen that there are relatively few listed enterprises in the heavy pollution industry implementing equity incentive, the average value of variable is 24303059, and the standard deviation is 66613486, indicating that the number of senior executives’ equity incentive is generally low and there is obvious difference among different enterprises All other variables are within the reasonable value range, and details are not described herein 4.2 Regression analysis 4.2.1 Regression analysis results of government subsidy on green innovation of enterprises Table reports the regression results of government subsidy and enterprise green inno- vation, columns (1) and (2) report the estimation results of fixed effect and random effect models respectively, and column (3) reports the model regression results of two-way fixed effect According to the Hausman test, the corresponding P value is 0.000, so the fixed effect model is selected Then, the individual fixed effect and time fixed effect are constructed by F statistics It is found that the corresponding P value is 0.000, and the goodness of fitting of the model with the two-way fixed effect is better, so the two-way fixed effect model is finally selected for analysis The regression coefficient of government subsidies is 0.007, and it is significant at the significance level of 10%, which indicates that government subsidies play a significant role in promoting enterprise green innovation Thus hypothesis H1 is verified This shows that government subsidies, as an important supplementary mechanism of innovation resources, can share innovation risk for enter- prises and enhance their willingness to innovate green At the same time, because gov- ernment subsidies play the role of ‘signal transmission’ in capital market, it can effectively widen the external financing channel of enterprises and reduce the degree Table Regression analysis of government subsidies to enterprise green innovation Variable (1) (2) (3) Gpatent Gpatent Gpatent FE RE FE Subsidy 0.008** 0.022*** 0.007* (0.004) (0.004) (0.004) Roa 0.242 0.285* 0.192 (0.171) (0.170) (0.169) RD 2.280*** 3.493*** 2.559*** (0.754) (0.684) (0.747) Age 0.059*** 0.042*** −0.067 (0.003) (0.003) (0.044) Soe 0.157** 0.166*** 0.179*** (0.069) (0.047) (0.068) TobinQ −0.023** −0.043*** −0.030*** (0.009) (0.009) (0.010) Constant term −0.659*** −0.572*** 1.038* (0.092) (0.088) (0.595) R2 0.095 0.088 0.134 F 84.50 49.52 Firm fixed effect Control No control Control Year fixed effect No control No control Control Number of samples 5360 5360 5360 Note: Standard errors in parentheses; ***, **, * represent significance levels of 1%, 5%, and 10%, respectively 546 H LIU ET AL of financing constraint In addition, the heavy pollution enterprises’ heavy dependence on government subsidies also restricts the possible arbitrage behaviour of enterprises Considering that government subsidies may have a lag and cumulative effect on green innovation activities of enterprises, based on model (1), this article regresses gov- ernment subsidies and all control variables with a lag of one and two periods, respect- ively The regression coefficient of government subsidies in the first lag period is 0.008, which is significant at the significance level of 5% The regression coefficient of govern- ment subsidies in the second lag period is 0.007, which did not pass the significance test This shows that, for the heavy pollution enterprises, the promotion of government subsidies to the green innovation of enterprises, not only has a certain time-delay characteristics, but also has a stronger influence coefficient and a higher significance level, that is, the government subsidies obtained in the current period significantly improve the green innovation level of enterprises in the current and next period The lagging effect of government subsidies may be because enterprises often need to go through a certain period from R&D investment to patent output, on the other hand, because the policy can play a certain guiding role, the local government’s support for green innovation will enhance the confidence of enterprises, encourage heavily polluting companies to allocate more resources to innovation activities later Therefore, hypothesis H1 is further validated (Table 5) 4.2.2 The analysis of the moderating effect of executive incentive The differential effects of executive compensation incentive and equity incentive on the moderating effect of government subsidies and enterprise green innovation are shown in Table The first column is the empirical results of the moderating effect of execu- tive compensation incentives The regression coefficient of the interaction term between compensation incentive and government subsidies is −0.019, which passed the significance test at the level of 5% It shows that the compensation incentive restrains the positive influence of government subsidies on the green innovation of enterprises Because the final effect of green innovation activity is difficult to reflect on the financial performance in a short time, the compensation incentive based on short-term performance evaluation will enhance the motivation of executives to pursue private interests and strengthen the short-sightedness effect, so that they divert the fund originally used for innovation to some quick profitable projects to achieve the effect of smooth performance, resulting in the crowding out of R&D invest- ment The highly uncertain and risky results of green innovation activities also enhance executives’ awareness of risk aversion, resulting in the failure of compensation incen- tives to effectively resolve the mismatch between executives’ risk-taking and benefit acquisition To sum up, it is assumed that H2 is supported The second list is the empirical result of senior executives’ equity incentive moderating function The regression coefficient of the interaction term between equity incentives and govern- ment subsidies is 0.095, but it has not passed the significance test This may be because the feedback of equity incentive effect also needs a certain time and cannot be reflected in the current period Because it has been confirmed that there is a time lag in the effect of government sub- sidies, this article believes that it is necessary to further explore the long-term and short- term effects of different executive incentives On the basis of the models (2) and (3), the ASIAN JOURNAL OF TECHNOLOGY INNOVATION 547 Table Regression analysis of lag effect Variable (1) (2) Gpatent Gpatent Subsidyt−1 0.008** 0.007 (0.004) (0.005) Roat−1 0.240 0.336* (0.184) (0.203) RDt−1 1.772** −0.073 (0.817) (0.891) Aget−1 −0.083 −0.093 (0.056) (0.068) Soet−1 0.121 0.117 (0.075) (0.081) TobinQt−1 −0.036*** −0.032*** (0.010) (0.011) Subsidyt−2 1.597* 1.360* (0.919) Roat−2 (0.760) 0.105 0.118 RDt−2 33.73 40.70 Control Aget−2 Control Control Control 4288 Soet−2 4824 TobinQt−2 Constant term R2 F Firm fixed effect Year fixed effect Number of samples Note: Standard errors in parentheses; ***, **, * represent significance levels of 1%, 5%, and 10%, respectively government subsidies, executive incentive and all control variables are regressed in the first and second phases, respectively The regressive results are shown in Table Accord- ing to column (1) and column (2), the regression coefficients of the reciprocal items of compensation incentive and government subsidy are negative, but both failed the signifi- cance test This shows that the compensation incentive is a kind of short-term incentive, and the short-term pressure will only crowd out the government subsidies in the current period According to the empirical results of column (3) and column (4), the regression coefficient of the interaction term between equity incentives and government subsidies in the first lag period is 0.023, and it is significant at the 10% significance level; the regression coefficient of the interaction term in the second lag period is 0.035, which is significant at the 5% significance level This shows that equity incentive is a long- term incentive mechanism, and its profit-driven effect reverses the short-sighted thinking of executives, enhances the green innovation power of executives, and then promotes the allocation of enterprise resources to innovation activities Since the substantial synergy of equity incentives also amplifies the signalling function and certification effect of govern- ment subsidies, heavily polluting enterprises will attract more external capital injections Hence, this mechanism makes the policy effect closer to the expectations of the local gov- ernment H3 is verified 548 H LIU ET AL Table Regression analysis of incentive moderating effect of senior executives Variable (1) (2) Gpatent Gpatent Subsidy 0.010** 0.009** (0.004) (0.004) Subsidy × Payinc −0.019** (0.008) 0.018 Payinc −0.002** (0.013) (0.001) −0.003 Subsidy × Shainc (0.003) 0.199 0.209 Shainc (0.169) (0.169) 2.507*** 2.529*** Roa (0.747) (0.748) −0.073* −0.067 RD (0.044) (0.044) 0.168** 0.173** Age (0.068) (0.068) −0.0291*** −0.031*** Soe (0.010) (0.010) 1.176** 1.029* TobinQ (0.600) (0.595) 0.136 0.135 Constant term R2 44.36 43.95 F Control Control Firm fixed effect Control Control Year fixed effect 5360 5360 Number of samples Note: Standard errors in parentheses; ***, **, * represent significance levels of 1%, 5%, and 10%, respectively 4.3 Robustness test 4.3.1 Instrumental variable method In practice, enterprises may get government subsidies because of green innovation activi- ties Although this article has delayed the variables by one and two periods to avoid the endogenous problems of mutual causality, it may still face endogenous problems such as missing variables Therefore, the industry mean of government subsidies excluding the enterprise itself is selected as the instrumental variable, and the endogenous influence is excluded by 2SLS See Table for the regression results The Cragg-Donald Wald F statistic in Table shows that there is no weak instrumental variable in the instrumental variable, and the regression result of the instrumental variable is basically consistent with that of the baseline model, that is, there is a significant positive correlation between gov- ernment subsidies and green innovation of enterprises, which further illustrates the robustness of the regression result in this article 4.3.2 Replacing regression model Because the median of green patent is zero, there is a large proportion of zero value in the data, which forms a mixed distribution of ‘zero value accumulation’ and ‘continuous positive value’ coexistence Referring to the research of Tong et al (2018), this article uses Tobit model to re-examine the main basic regression Table reports the regression results of Tobit model After replacing the regression model, this article finds that ASIAN JOURNAL OF TECHNOLOGY INNOVATION 549 Table Hysteresis regression analysis of senior executive incentive moderating effect Variable (1) (2) (3) (4) Gpatent Gpatent Gpatent Gpatent Subsidyt−1 0.009** 0.007 0.011** 0.010** Subsidyt−1* Payinct−1 (0.005) (0.005) (0.004) (0.005) Payinct−1 −0.006 −0.003 Subsidyt−1×Shainct−1 (0.009) (0.010) 0.023* 0.035** Shainct−1 −0.001 0.001 (0.014) (0.015) Roat−1 (0.001) (0.001) −0.002 −0.001 RDt−1 (0.003) (0.003) Aget−1 0.241 0.341* 0.260 0.356* Soet−1 (0.184) (0.204) (0.185) (0.203) TobinQt−1 1.757** −0.064 1.735** −0.149 Subsidyt−2 (0.817) (0.891) (0.817) (0.891) Subsidyt−2* Payinct−2 −0.086 −0.093 −0.082 −0.093 Payinct−2 (0.056) (0.068) (0.056) (0.068) Subsidyt−2×Shainct−2 0.115 0.118 0.116 0.112 Shainct−2 (0.075) (0.082) (0.075) (0.081) Roat−2 −0.035*** −0.033*** −0.038*** −0.034*** RDt−2 (0.010) (0.011) (0.010) (0.011) Aget−2 1.567* 1.546* Soet−2 1.453* (0.924) 1.335* (0.919) TobinQt−2 (0.765) 0.105 (0.760) 0.106 Constant term 0.118 0.119 R2 29.23 29.67 F 35.76 Control 35.89 Control Firm fixed effect Control Control Control Control Year fixed effect Control 4288 Control 4288 Number of samples 4824 4824 Note: Standard errors in parentheses; ***, **, * represent significance levels of 1%, 5%, and 10%, respectively government subsidies still play a significant role in promoting the green innovation of enterprises in the heavy pollution industry, and the compensation incentive still plays a significant negative moderating role in it, while the moderating role of equity incentive is not significant The results verify the consistency of the main conclusions in this article 4.3.3 Replacing variable In order to prevent the problem of collinearity, this article excludes the influence of financial subsidies on the profitability, adjusts the total net interest rate of assets, 550 H LIU ET AL Table Regression results for instrumental variables Variable Column A Gpatent Instrumental variable First-order lag term Subsidy 0.1408*** (0.054) Roa −0.0257 RD (0.030) 0.9793* Age (0.510) −0.2139 Soe (0.274) 0.2325*** TobinQ (0.079) 0.0115 Firm fixed effect (0.0154) Year fixed effect Control Cragg-Donald Wald F statistics Control Number of samples 34.99 5220 Note: Standard errors in parentheses; ***, **, * represent significance levels of 1%, 5%, and 10%, respectively measures the total net asset interest rate with ‘(net profit-financial subsidy)/average total asset’, and tests it with the basic regression model The regression results are shown in Table As can be seen from Table 10, the regression results did not materially change, so the hypothesis in this article is considered to be robust Main research conclusions and enlightenment 5.1 Main research conclusions How to lead the green production and operation of enterprises and get rid of the tra- ditional development path of high pollution and high energy consumption has become an important issue that cannot be ignored in the process of promoting eco- logical civilisation construction and economic transformation China has tried to use government subsidies to drive green innovation of enterprises, but the effect of the policy is controversial This article takes heavily polluting enterprises as research samples to study the relationship between government subsidies and green innovation, and analyzes the coordination between executive incentives and government subsidies in the process of influencing enterprise green innovation The research results show that: First, government subsidies significantly promote green innovation in heavily polluting companies Second, executive compensation incentives are not an effective way to enhance the role of government subsidies in promoting green innovation, but significantly weaken the positive relationship between them Compensation incen- tives cannot balance the risk-taking and benefit-acquisition of green innovation activi- ties, and the risk aversion tendency of executives is still strong, which reduces the effect of government subsidies Third, executive equity incentives have formed a posi- tive synergy effect on government subsidies Although the moderating effect of equity incentives in the current period is not significant, but after the first and second periods lag, it is found that government subsidies can produce more green innovation ASIAN JOURNAL OF TECHNOLOGY INNOVATION 551 Table Regression results of tobit model Variable (1) (2) (3) Gpatent Gpatent Gpatent Subsidy 0.016*** 0.020*** 0.017*** Subsidy × Payinc (0.005) (0.006) (0.005) `Payinc −0.029*** Subsidy × Shainc 0.229 (0.009) 0.018 Shainc (0.156) −0.003*** (0.013) Roa 2.064*** (0.001) −0.005* RD (0.745) (0.003) Age −0.022** 0.238* 0.252 Soe (0.009) (0.132) (0.164) TobinQ 0.255*** 1.986** 2.110*** Constant term (0.063) (0.863) (0.716) Sigma_u −0.044*** −0.021*** −0.024*** Sigma_e (0.010) (0.007) (0.008) Firm fixed effect 0.299** 0.237*** 0.237*** Year fixed effect (0.148) (0.055) (0.058) Number of samples 0.708*** −0.042*** −0.046*** (0.039) (0.008) (0.007) 0.593*** 0.371*** 0.334** (0.013) (0.138) (0.148) Control 0.698*** 0.707*** Control (0.044) (0.046) 0.593*** 0.593*** 5360 (0.016) (0.013) Control Control Control Control 5360 5360 Note: Standard errors in parentheses; ***, **, * represent significance levels of 1%, 5%, and 10%, respectively results It can be seen that even in heavily polluting enterprises, equity incentives are still an effective way to combine the personal interests of executives with the long- term development of the company, which reverses the short-sighted thinking of executives and helps to improve the positive effect of government subsidies on green innovation 5.2 Research enlightenment First, the financing constraints of heavily polluting enterprises are still serious, and insufficient funds have delayed the green innovation process of enterprises Govern- ments at all levels should strengthen financial support for heavily polluting enterprises, ease the cost pressure on enterprises, and strengthen enterprises’ willingness to inno- vate green At the same time, we will eliminate discrimination in the financial industry and guide more social funds to be injected into enterprises Second, the financial departments of governments at all levels should strengthen the evaluation of enter- prises before issuing government subsidies, and can consider whether the enterprise implements the executive equity incentive mechanism that is conducive to the output of green innovation as an evaluation criterion This will improve the accuracy and effectiveness of fund allocation, reduce the problem of adverse selection between government subsidies and green innovation to a certain extent, and prevent 552 H LIU ET AL Table 10 Regression results for substituted variables Variable (1) (2) (3) Gpatent Gpatent Gpatent Subsidy 0.008* 0.011** 0.010** (0.004) (0.004) (0.004) Subsidy × Payinc −0.019** 0.014 (0.008) 0.018 Payinc (0.068) −0.002** (0.013) 2.520*** (0.001) −0.003 Subsidy × Shainc (0.747) (0.003) −0.066 0.019 0.022 Shainc (0.044) (0.068) (0.068) 0.177*** 2.468*** 2.489*** Adjustroa (0.068) (0.746) (0.747) −0.030*** −0.072* −0.066 RD (0.010) (0.044) (0.044) 1.030* 0.166** 0.171** Age (0.595) (0.068) (0.068) 0.133 −0.028*** −0.031*** Soe (0.010) (0.010) 49.10 1.172* 1.022* TobinQ Control (0.600) (0.595) Control 0.135 0.133 Constant term 5360 R2 43.99 43.55 F Control Control Firm fixed effect Control Control Year fixed effect 5360 5360 Number of samples Note: Standard errors in parentheses; ***, **, * represent significance levels of 1%, 5%, and 10%, respectively enterprises from using green innovation as a gimmick to defraud more external funds Third, governments at all levels should introduce supporting measures related to gov- ernment subsidies After the subsidy funds are released, relevant departments should not only strengthen supervision to ensure that the use of funds is compliant and reasonable, but also require enterprises to improve internal governance Relying solely on the direct supervision of government departments is too costly, and both internal and external approaches can more effectively promote the construction of China’s ecological civilisation Fourth, relevant government departments should estab- lish a dynamic assessment system and increase the proportion of green innovation in the assessment system to encourage enterprises to introduce green innovation as a performance goal into the executive incentive mechanism Disclosure statement No potential conflict of interest was reported by the author(s) Funding This work was supported by Shannxi Province Social Science Fund Program [grant numbers 2020D017, 2022HZ0540]; “Rural Revitalization” Special scientific research Project of Shaanxi Normal University [grant number 22XCZX08]