The results of this study show that one type of environmental disclosure positively affects R&D investment, namely, corporations that disclose GHG emissions of scope 31 are more likely to invest in R&D. First, it sheds light on the relationship between environmental disclosure and innovation activity, which is not. Therefore, this study can provide an original insight into the impact of environmental disclosure on innovation activity.
A number of studies show that environmental disclosure can bring advantages to corporations, as explained in the next section, but in addition, this study finds that domain 3 disclosure is important for encouraging innovation activity. Studies such as Brouhle and Khanna (2007) show that environmental disclosure can also improve product quality. As shown by these simple examples, environmental discovery can be related not only to environmental innovation, but also to other types of innovation.
The relationship between environmental disclosure and innovation is not clear, but it is interesting to explore because there is still little research examining this relationship. Furthermore, environmental data disclosure can improve communication between companies and external actors such as investors and shareholders.
Model
The dependent variable in this study can also be influenced by previous achievements; thus, it is essential to include the lagged variable in the set of explanatory variables. First, it is assumed to consist of endogenous variables that can correlate with the error term due to the bidirectional causality between variables. Because the lagged dependent variable is correlated with the error term, the OLS estimator is inconsistent.
Based on these econometric problems, I therefore focus on estimation methods that can be used for explanatory variables or instruments that are not strictly exogenous. These models incorporate lags of the dependent variables as covariates and include unobserved individual effects. To eliminate individual effects, GMM uses the difference Eq. 1) and adopts previous observations of the endogenous variables and a lagged dependent variable as instruments.
This GMM estimator is based on the assumption that the error term is not serially correlated and that the explanatory variables are not correlated with future realizations of the error term (Roodman, 2006). However, this difference GMM also has limitations; for example, the lagged levels can become weak instruments for first differences when the explanatory variables are persistent over time, which can lead to a large final sample bias (Blundell and Bond, 1998). In this study, certain explanatory variables are persistent over time, and thus there is the possibility that this may lead to bias and inaccuracy.
To address this problem and to generate consistent and efficient estimates, I choose the system GMM estimator ( Blundell and Bond, 1998 ) as an extended version of the difference GMM estimator. One is the difference Cf. 2), which adopts appropriate lagged levels as instruments, and the second is Eq. 1), which is the comparison in levels and uses appropriate lagged differences of the explanatory variables as instruments. A misspecification test for second-order serial correlation in the first-difference error term is also performed.
If we cannot reject the null hypothesis that there is no second-order serial correlation in the differentiated residual, then the error term (in levels) is not serially correlated at order 1.
Data description
On behalf of institutional investors, the CDP requests information on greenhouse gas emissions, energy use and the risks and opportunities of climate change from thousands of the world's largest corporations. Both the quantity and quality of the data disclosed by corporations have improved significantly, and the number of corporations responding has grown since the first CDP report in 2003. collected climate change data is now used as evidence for.
This data has been used in practice to monitor research and development in the EU, but has not yet been fully explored in academia. Each company's CSR reports are also used in this study to supplement the data when information was not available in the CDP and R&D investment data. It is possible that the companies responding to the CDP are those that are already active in addressing climate change issues, which could strengthen the relationship between environmental disclosure and R&D in this study.
The variables have the values 1 if the corporation has implemented or engaged in the following actions: if the corporation discloses the total cost of its energy consumption from fossil fuels and electricity (ENERGYCOST); if the corporation discloses emissions of field 3 GHGs (EMISION3); and whether any of the disclosed information has been externally verified/secured in whole or in part (INFO_VERIF). The following variables related to corporate characteristics are also included: "lnPROFIT", "lnMRKTCPTL" and "lnEMPLO". Market capitalization (lnMRKTCPTL) not only shows the economic performance, but also explains the overall valuation of a corporation in the market.
Investors' and other stakeholders' decisions are one of the most important external factors influencing corporate actions. Finally, to consider the impact of the EU ETS, a dummy variable "EUETS" and the interaction terms of "EUETS" and dummy variables of environmental disclosure actions are added in Models 2 and 4. The sign of this variable can be positive because corporations under the EU-ETS are more likely to consider their climate change strategy as part of their EU-ETS compliance.
For instruments, the models use sufficiently lagged levels and sufficiently lagged differences of the explanatory variables.
Results and discussion
This variable shows that companies with a large number of employees (i.e. larger companies) are more likely to increase their R&D investments than smaller companies. The variables of sectors 4 (chemicals and pharmaceuticals), 6 (industrial machinery and high-tech) and 7 (automobiles, auto parts and other manufacturing goods) are significantly positive at the 1%, 5% and 5% level, respectively. These results indicate that firms in these industries are more likely to encourage R&D investments than those in other industries.
Investment in Research and Development (log) Investment in R&D (log) Investment in R&D/net sales Ratio of investment in R&D/net sales (Robust Std. This result implies that corporations that disclose scope 3 GHG emissions have more likely to increase their investments in R&D. ENERGYCOST" is significantly negative at the 10% level, indicating that corporations that disclose energy costs are less likely to encourage investment in research and development.
In contrast, the interaction term of “EUETS” and “ENERGYCOST” is significantly positive at the 10% level, indicating that firms covered by the EU ETS and disclosing energy costs are more likely to invest in R&D. The variables for sectors 3 (paper and forest products) and 5 (food, beverages and tobacco) are significantly negative at the level of 1% and 5%, respectively. These unexpected results suggest that corporations in these sectors are less likely to promote R&D investment.
In Model 3, the estimated coefficient of the lagged dependent variable (ratio of R&D investment to net sales) is positive and statistically significant at the 1% level. The result implies that corporations that disclose scope 3 GHG emissions tend to increase their ratio of R&D investment to net sales. EUETS” and environmental disclosure actions dummy variables in Model 3, the estimated coefficient of the lagged dependent variable is positive and statistically significant at the 1% level.
This result means that companies that disclose GHG emissions in scope 3 are more likely to increase their share of R&D investment than other companies.
Conclusion
Findings in this study show that one type of environmental disclosure action positively affects R&D investment. Corporations can become aware of the importance of innovation activity through this commitment, which can lead to improved R&D investment. The coefficient of the interaction terms of "EUETS" and "ENERGYCOST" is 0.105 higher than that of "ENERGYCOST".
The results show that “INFO_VERIF”, a dummy variable that takes a value of 1 when any of the disclosed information has been fully or partially externally verified/assured, is not significant in all models. Given the characteristics of the CDP and the fact that when corporations disclose their environmental performance to the CDP, the information will be rigorously scrutinized by institutional investors, whether it is externally verified may not be particularly important to corporations. This study is unique in that it explains the relationship between environmental disclosure and innovation activity; however, the results should also be treated with caution due to the issue of potential response bias, which assumes that corporations with environmentally conscious managers are more likely to respond to the CDP questionnaire than other corporations.
The corporations responding to the CDP may be those already active in addressing climate change, and there is a possibility that the environmental disclosure-R&D relationship may be slightly inflated. Moreover, the estimation methods can be further improved. does not prove the direct impact of the EU-ETS on innovation, I would like to investigate this using different methods. First, this study can provide original insights into the relationship between environmental disclosure and innovation activity.
In particular, this study is unique in that it presents an interesting impact of discovering GHG emissions in Area 3 on innovation activity. Environmental disclosure can increase the transparency of corporate risk management attitudes regarding environmental issues and financial liabilities, which can enable investors to consider their investment strategy. In addition, environmental disclosure can help corporations communicate with consumers and improve their brand image and/or legitimacy.
Based on the mutual influences between these actors, it is clear that environmental disclosure can improve communication between actors and ultimately encourage innovation activity. The implication of this finding is that in order to enjoy the benefits of environmental disclosure, it is essential to construct a system in which environmental disclosure is. It is also essential to provide incentives to corporations to sustainably engage in environmental disclosure.