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This study investigates how government policies affect firm-level innovation. To empirically test this relationship, we use panel data for the Korean renewable energy technology firms. Taking into account the results of various panel framework tests and sample size, we establish a panel vector autoregressive model in the first difference, and use a bias-corrected least squares dummy variable estimator to test complex dynamic relationships between public subsidies, firm heterogeneities (size, age, and slack), industry dynamic competition, and innovation. Based on the estimations, we find that there is a positive bidirectional causal relationship between firms’ innovation and each of the following: research and development (R&D) subsidy, available organizational slack, and industry dynamic competition. Non-R&D subsidy, firm size, and age do not have significant direct effects on firm-level innovation. However, non-R&D subsidy is involved in the relationship between R&D subsidy and firms’ innovation. We discuss some implications based on the findings of this study.

Renewable energy technology (RET) firms are key economic entities in the export of RET-related products and components, in which RET firms’ exports are affected largely by policy and market. Nonetheless, the effects of policy and market factors on RET firm-level export have never received attention from researchers. This study aims to fill the gap by taking a political economy approach to establish a structural equation model to analyze the path of political-economic factor-firms’ market orientation-based export. This study reveals that RET firms’ market-orientation-based export enhancement depends entirely on political forces. Particularly, two government intervention instruments, environmental policy and export promotion policy, were highlighted. However, the effects of renewable energy policies on the exports of RET firms through market orientation are negative and statistically significant. This study proves that the effects of inter-firm competition and market attractiveness on RET firms’ exports through their market orientation are negative and statistically significant and insignificant, respectively. Further, this study demonstrates that RET firms’ market orientation has a significant positive effect on their export performance. We conclude that in order to improve RET-related policy effectiveness and efficiency, it will be useful to consider firms’ heterogeneity in response to external factors. Additionally, a full mediation model in the academic investigation of the effects of various external factors, including public policies and market factors, on firm-level export, and the implementation of firm-level export-induced policy, taking into account firms’ managerial interpretations to external factors, should be considered.

We empirically investigate whether government subsidies result in firms' overinvestment using unbalanced panel data from 61 renewable energy technology firms in Korea between 1991 and 2018. Considering the diagnostic test results, we build a panel vector autoregression model and test how overinvestment is influenced by research and development and non-research and development government subsidies and the interactions between subsidies, leverage, and free cash flow. We find that these subsidies do not significantly induce overinvestment by firms. In addition, non-research and development subsidies affect overinvestment positively through leverage and affect it negatively through free cash flow interactions. We also find that leverage and free cash flow do not affect overinvestment in Korea's renewable energy technology sector directly; however, firms with positive free cash flow tend to overinvest. One factor that drives renewable energy technology firms in Korea to overinvest is external growth opportunities. We suggest various policy implications based on this study's results.

Numerous issues, such as technological and market uncertainty, and financial role-players’ avoidance of long-run investment in renewable energy technologies, have deterred investments in innovation. Therefore, we investigate the direct and indirect (inter-firm spillover) effects of government support and firm heterogeneity on productivity. Using panel data concerning Korean solar energy technology manufacturers, the significance of firm heterogeneity in improving productivity is found. Specifically, the positive impact of physical capital and organizational slack on productivity in the short and long run, and the positive spillover effect of intellectual capital on productivity in the long run are established. Additionally, productivity increases only when government support interacts with firm heterogeneity. This increase relates to short- and long-run direct effects of the interaction between intellectual capital and non-R&D (Research and Development) subsidy, and organizational slack and R&D subsidy, and long-run spillover effect via the interaction between non-R&D subsidy and organizational slack. Lastly, for the solar energy technology industry, the policy and strategic repercussions for firm-level productivity enhancement are deliberated based on the findings of this study.

This study explores how inflows of foreign direct investment (FDI) affect a country’s carbon dioxide (CO2) emission levels. To investigate this relationship, we use panel data (2002–2015) from the 28 subsectors of the Chinese manufacturing sector. We also perform panel framework analysis to verify the characteristics of the panel data before establishing the panel estimator meant to test the relationships between carbon dioxide emissions, FDI inflows, industrial GDP, industry openness, net domestic fixed capital stock and cleaner production. The results of the panel framework analysis suggest the need to eliminate dynamic panel bias and produce more efficient and consistent parameter estimates. To do so, we use System Generalized Method of Moments (GMM) estimators with time dummies. Ultimately, the results of the analysis show that FDI is a positive predictor of environmental quality in the host country, which serves as evidence of the halo effect that FDI reduces CO2 emission levels. The study also finds evidence that industrial GDP and cleaner production improve environmental quality. However, the domestic capital stock has a negative effect on environmental quality. By showing that past carbon dioxide emissions significantly influence current emissions, our findings demonstrate the importance of consistency and persistence in efforts to reduce those emissions. Accordingly, we discuss some policy implications based on these results.

Previous studies have investigated how government policies on renewable energy technology (RET) affect economic performance at the industrial level. However, each firm in the RET industry is heterogeneous in terms of their capacities, resources, and the amount of public subsidies they receive. Considering the context in which public subsidies are provided to firms, this study econometrically investigates the effects of government policies on firms&rsquo, financial performance using panel data from the Korean RET industry. We consider the results of various panel framework tests, establish a panel vector autoregressive model in first differences, and test the dynamic relationships between firms&rsquo, financial performance, government subsidies (R&amp, D- and non-R&amp, D-related), firm size and age, and organizational slack, using a bias-corrected least squares dummy variable estimator. We find that R&amp, D-related subsidies positively affect firms&rsquo, financial performance in the long run. In the short run, there are bidirectional positive causal relationships between firms&rsquo, financial performance and organizational slack (and non-R&amp, D-related subsidy), and firm size and non-R&amp, D-related subsidy. A positive short-run relationship runs from R&amp, D-related subsidy to firms&rsquo, financial performance, from firm age to non-R&amp, D-related subsidy, and from firm size to firm age. Further, there are dynamic effects in all estimations, demonstrating that the dependent variables of the previous period enhance their values in the current period. The results provide some policy and strategic implications.

This study explores the definition of the industrial use of genetically modified organisms (GMOs), factors that affect it, and how it influences a firm’s economic performance to understand who drives market access for GMOs and GM products, considering the two premises related to sustainable development: 1) the continuing use of GMOs is one of the most prominent driving forces behind a bio-based economy’s growth, and 2) social system members seek protection from the potential risks of GMOs. The results show compelling evidence of a structural relationship between sociopolitical/economic pressures and economic performance. Additionally, these pressures vary by industry, and activities to secure both social and economic legitimacy due to these pressures have a positive impact on overall firm performance.

With regard to the survey data of Korean researchers using genetic resources from three genebanks administered by the Korea Research Institute of Bioscience and Biotechnology, we conducted conjoint and cluster analyses to estimate the relative importance of genetic resource (microbial, plant and animal) attributes among the researchers. Our results indicate that Korean researchers view price (cost of acquiring an accession), high new functionality (functional properties of germplasms for specific applications and uses) and completely uncovered genomic information (about mutation, genetic transformation, genomic function and pathways) as far more important in decision-making about R&D use of microbial, plant and animal genetic resources, respectively, than other attributes. Furthermore, this study shows that researchers conducting R&D in the microbial and plant genetic resource sectors especially prefer resources from specific domestic environments and Korean indigenous species, respectively. The study also sheds light on different patterns of researcher segments in terms of utilities of attributes and subgroups of researchers who have common needs in the three genetic resource sectors. We proposed some policy and strategic implications based on the results of this study.

Using panel data from Korean manufacturing firms, this study empirically investigates how knowledge assets impact the relationship between exports and productivity. We consider a scenario in which firms are situated in a globally competitive, knowledge-based environment. We establish a dynamic panel vector autoregressive model by considering the outcomes of various panel framework tests. A generalized method of moments estimator is employed to test the dynamic relationships among the variables, and a post-estimation test, Granger causality test, and impulse response test are performed. Our findings indicate the existence of a learning-by-exporting effect on the enhancement of total factor productivity (TFP). The result show that TFP can be improved by interacting with exports and knowledge assets, and that firms&rsquo, knowledge assets significantly and positively affect their exports. However, industry competition, as an external force, does not contribute to boosting firms&rsquo, productivity. We highlight the importance of continuously upgrading productivity, exports, knowledge assets, and industry competition by demonstrating that the present levels of these elements serve as the main source of their own future values. Finally, the implications of our results are outlined.

This study examines how various actors influence the transition to a renewable-energy economy. We employ a conceptual framework derived from a literature review and text-mining analysis and establish a panel data model for an empirical test using unbalanced panel data from 25 member countries of the Organization for Economic Co-operation and Development (OECD), for the period from 1990 to 2014. We establish a panel vector autoregressive (VAR) model in the first differences and use a bias-corrected least squares dummy variable (LSDVC) estimator to test complex dynamic relationships between government, the public, markets, the traditional energy sector (i.e., the sector that uses nuclear power, oil, coal and natural gas as sources for electricity) and the contribution of renewables to the total energy supply. We also perform Wald tests on the coefficients of variables estimated by LSDVC estimator to determine causal relationships between the variables. The results of this study reveal that government and markets directly promote the transition to renewable energy, whereas the traditional energy sector negatively and directly affects the transition. By contrast, the public does not directly influence the transition to a renewable-energy economy. This study also shows that the government and public have positive indirect effects on the transition, by interacting with the market. We also find convincing evidence of significant dynamic-path dependence in all estimations. Finally, we discuss some implications based on the findings of this study.

This study examines how the dynamic efficiency of public policy influences the export performance of bioenergy technologies in the short and long run using panel data over the 1995–2012 period for 16 countries that are members of the OECD. Various dynamic panel framework tests to check data characteristics are performed. The study found evidence of co-movement among the series, and set up the panel vector error correction mechanism to evaluate the short- and long-run Granger-causality between the following variables: dynamic efficiency of public policy, export, and environmental policy stringency. This study highlighted positive effects of the dynamic efficiency of public policy and environmental policy efforts on exports in both the short and long run. This study proposes policy considerations based on its results.

This study investigates the effects of public policy supports on the export performance of bioenergy technologies; it uses panel data from 18 countries from the 1992 to 2008 period. Panel unit-root and cointegration tests are applied, taking into account the results of structural-break tests for each time series and testing for the presence in the panel of cross-sectional dependence. Time-series data on public supports and exports are integrated and cointegrated. The results of dynamic ordinary least squares indicate that in the long term, public R&D expenditures have a positive effect on the exports, the contribution of bioenergy to the total energy supply has a negative effect on the exports, and GDP has a positive effect on the exports. The contribution of bioenergy to total energy supply responds to deviations in the previous period from the long-term equilibrium. Additionally, Blundell–Bond system generalized methods of moments estimations are made, to determine dynamic causality in a panel vector error correction mechanism setting. Evidence of a positive strong and short-term relationship from exports to R&D expenditures, and of a positive short-term causality from exports to the contribution of bioenergy to total energy supply, is found. A positive strong bidirectional relationship between GDP and exports is also uncovered. There is a positive strong, bidirectional, and short-term relationship between GDP and the contribution of bioenergy to total energy supply. Finally, some policy implications based on the results of this study are offered.

This study explores the long- and short-term dynamic relationships between government policies and exports of renewable energy technologies (RETs) at the subsector level (biomass, wind, and solar energy technologies). This allows a more robust exploration of the relationships, in which differences in cost structures and maturity levels exist for different RETs, without losing the generality of the results. Dynamic panel econometric techniques are employed to analyze the relationships, using data of annual measures for 18 countries during 1992–2008. The vector error correction mechanism (VECM) is used to test the dynamic relationships among government policies, exports, and gross domestic product (GDP) for biomass and wind energy technologies, and the vector auto-regression (VAR) model, for solar energy technologies. The study indicates that each subsector has a unique path-dependent process, showing the presence of different positive feedback mechanisms based on interactions among technology-push policy, market-pull policy, exports, and/or GDP in the short and long run. We suggest some policy implications based on the results of this study.

The industrial use of genetically modified organisms (GMOs) has been highly controversial for many reasons. The controversies lead to a gap between societal needs and expectations of the potential benefits and risks related to the industrial use of GMOs. This gap has been imposing society-specific political-economic pressures on firms. These pressures derive from the external stakeholders' needs and expectations that GMOs will assume an important role in creating business opportunities for and damaging the social reputations of firms. This paper, by drawing upon the literature on managerial interpretations of issues, investigates the way sociopolitical-economic forces and managerial interpretations influence firms' intentions for the industrial use of GMOs in the Korean context. It uses a structural equation modeling (SEM) approach. Results based on survey data from 145 manufacturing companies indicate that social acceptance, and managerial interpretation influenced mainly by market attractiveness, will both make a significant contribution to the prediction of firms' industrial use intentions of GMOs. Market attractiveness was not a significant factor affecting the use intentions of GMOs directly. Some insights into what governments should do to promote sustainable use of GMOs in their countries are proffered.

This paper investigates the relationships among environmental regulation, export performance, and factor intensity, using panel data from South Korea's manufacturing sector (1991–2009). A panel vector autoregression (VAR) model in first differences tests the relationships among the variables, while considering the results of heterogeneous panel unit root and cointegration tests. Generalized Method of Moments (GMM) estimations help determine dynamic series relationships, and panel-causality tests are run based on the results of GMM estimations. There is evidence of a positive short-run linear causal relation running from environmental regulation to export performance, suggesting that environmental-protection expenditure may constitute a comparative advantage. The short-run linear causal relation from export performance to investment in activities related to environmental protection is insignificant.

This article investigates the causal relationship between public policies and exports of renewable energy technologies using panel data from 18 countries for the period 1991–2007. A number of panel unit root and cointegration tests are applied. Time series data on public policies and exports are integrated and cointegrated. The dynamic OLS results indicate that in the long run, a 1% increase in government R&D expenditures (RAD) increases exports (EX) by 0.819%. EX and RAD variables respond to deviations from the long-run equilibrium in the previous period. Additionally, the Blundell–Bond system generalized methods of moments (GMM) is employed to conduct a panel causality test in a vector error-correction mechanism (VECM) setting. Evidence of a bidirectional and short-run, and strong causal relationship between EX and the contribution of renewable energy to the total energy supply (CRES) is uncovered. CRES has a negative effect on EX, whereas EX has a positive effect on CRES. We suggest some policy implications based on the results of this study.

각국의 바이오에너지 산업의 성장과 수출은 주로 기술지향 및 수요견인 정책을 통해 유도되고 있다. 이들 정책의 주요 목표가 기술 혁신인점을 감안하면 기술 역량은 곧 산업과 수출을 성장시키는 주요 요인이 된다. 이러한 사실에도 불구하고, 바이오에너지 산업에 있어서의 수출 경쟁력과 기술 역량 사이의 동태적 관계를 분석하고 있는 실증 연구는 없다. 이에 본 연구는 20개 OECD 국가에 대한 패널 자료를 구축하여 바이오에너지 산업에 있어서의 수출 경쟁력과 기술 역량 간 관계를 분석하였다. 먼저, 각 시계열에 있어서의 구조적 변화와 횡단면 사이의 상호의존성에 대한 검정을 실시하였으며, 이 결과에 기초하여 데이터의 정상성과 장기 균형의 존재 여부를 검정하였다. 패널 단위근 및 패널 공적분 검정결과, 데이터가 안정적이지 않은 것으로 나타났으며, 시계열 사이에 공적분이 있는 것으로 나타났다. 이에 본 연구는 패널 VECM을 설정하고 1단계 차분 GMM 추정을 통해 양자간 관계를 분석하였다. 분석결과, 단기적으로 수출경쟁력은 기술역량에 정(+)의 영향을 미치고 있으며, 이들 양자는 오차수정항과 작용하여 상호 영향을 미치는 것으로 나타났다. 장기적으로는 기술역량의 강화가 오차수정항을 통해 수출경쟁력에 정(+)의 영향을 미치는 것으로 나타났다. 본 연구의 결과는 바이오에너지 공공정책의 입안과 수행이 수출경쟁력에 대한 긍정적인 정책탄력성을 유발할 수 있도록 장기적인 차원에서 접근해야할 필요성을 제기하고 있다.

This study investigates how the eco-efficiency of government policy—continuously implementing innovation-friendly policy based on both environmental and economic considerations—affects the export performance of bioenergy technologies, using panel data from 16 countries during 1995–2012. Various heterogeneous panel framework tests are conducted. Our panel unit root and co-integration tests, which allow for cross-sectional dependence in the panel, show that the time series data on the eco-efficiency of public support, exports, and gross domestic product (GDP) are integrated and co-integrated. We set up a panel vector error correction model (VECM) to empirically test the casual relationship among the variables examined. The long-term parameters of the variables were calculated using dynamic ordinary lease squares (DOLS). Panel difference generalized method of moments (GMM) estimations were conducted to test the short-term relationship among the variables. The results of this study therefore show that the eco-efficiency of government policy positively influences export performance in the long run, but not in the short run. The presented findings also indicate that efficiently implemented government policy plays a crucial role in achieving environmentally sound and sustainable development, showing path dependence among the eco-efficiency of government policy, exports, and GDP. We finally suggest policy implications based on the results.