Search results

This study uncovers how government interventions, in terms of stringency and support, shape coronavirus disease 2019's (COVID-19) detrimental impact on organizations' performance. Specifically, this paper studies whether stringency and support play complementary or substitutive roles in lowering COVID-19's impact on organizations' performance.

The authors gathered primary data from USA manufacturing companies and combined this with secondary data from the Oxford COVID-19 Government Response Tracker (OxCGRT) to test the proposed model with structural equation modeling (SEM).

The results show that the stringency approach increases the detrimental impact on both operational and financial performance, while economic support (to households) and fiscal spending (to organizations) work differently on lowering the impacts of COVID-19. Further, these combinative effects only influence the firm's operational performance, albeit in opposite directions.

This study advances the knowledge of government interventions by examining stringency and support's direct and interaction effects on firm performance as a result of the COVID-19 pandemic. The findings contribute to the literature by uncovering the unique roles of both supportive policies, thus differentiating economic support (to individuals/households) from fiscal spending (to organizations) and providing important academic, managerial and policy insights into how government should best initiate and blend stringency and support policies during the COVID-19 pandemic.

The purpose of this paper is to examine firms’ knowledge-sourcing behavior in green technology development with respect to the home country’s market- vs nonmarket environmental policy stringency.

This paper empirically analyzes the effects of market and nonmarket environmental policy stringency on firms’ knowledge sourcing activity with patent data from OECD countries during 1991–2010, across five categories of green technologies.

When a nation establishes more stringent market environmental policies, firms likely source more international knowledge rather than domestic knowledge about green technology, up to a point. After that level, this balance shifts (inverted U-shaped curve) due to the risks associated with greater investment costs and commerciality. Nonmarket environmental policies instead should exhibit a positive, linear relationship with international relative to domestic knowledge sourcing. This study also reveals the dynamic roles of a firm’s green technological capability with market-based environmental policy stringency and a substitutive role of the capability with nonmarket-based environmental policy stringency.

This study shows the effect of market and nonmarket environmental policy stringency on firms’ knowledge sourcing. The findings provide meaningful implications for policymakers regarding the optimal levels of market and nonmarket environmental policy stringency that will enhance their countries’ green technology development.

This paper enriches the literature of environmental policy and knowledge sourcing and offers the direction of future research of how environmental policy stringency influences a firm’s knowledge sourcing for green technology development.

Trade of environmentally sensitive goods (ESGs) is often exposed to countries with less stringent regulations suggesting that those countries have comparative advantage in the polluting sector. The Group of Twenty (G20) members are among the highest polluters, globally. Different stringency policies are enacted time to time in G20 to control environment pollution. However, the impact of policy stringency on export performance of ESGs is seldom examined. The paper aims to address some of the issues concerning this matter.

The present study aims to address the short run and long-run association between Revealed Comparative Advantage of ESGs and Environmental Policy Stringency Index for the period of 1990–2019 in G20. Periodic fluctuations and time adjustment mechanism are also studied. Second Generation Panel Cointegration, Vector Error Correction, Impulse Response Function and Variance Decomposition methods are employed to address the objectives.

Result is evident that more exposure to stringent environmental regulations reduces the comparative advantage of ESGs in the long run. But there is no evidence of the short-run relationship between the variables. The possible reason could be that new regulations enacted prove fruitful in the long run.

The novelty of the study is to focus on inter linkages between stringency and global export competitiveness in G20, almost nonexistent in the past studies. The study also provides a road map to policymakers to find out potential ways for sustainable development by balancing environmental stringency measures and international trade.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2022-0560

The purpose of this paper is to examine the role of activism in determining the identity of the “green” median voter and the influence of the green voter on environmental regulatory stringency in the US states.

Regulatory stringency is measured using output weighted abatement spending and an industry concentration adjusted index of state environmental compliance costs for the period 1989-1994. Activism measures include environmental initiatives, median support for pollution standards and voter ideology. Fixed-effects panel methodology is used in empirical estimation.

The authors find that activism increases stringency in regulating overall as well as media-specific pollution. The results particularly highlight the nuances of different approaches to activism and their varied impact across pollution media.

A drawback of the empirical estimation is the lack of continuous historical abatement spending data. A longer panel with alternative stringency measure(s) would add explanatory power to activism, especially since some activism measures capture slow-changing institutional factors.

The study identifies the conditions under which activism can have the most impact on a society's environmental outcomes since pollution varies in damages, hence abatement costs, across pollution media.

The paper adds to the existing literature by incorporating three alternative measures of environmental activism to systematically investigate its impact on environmental stringency within a fixed-effects regression design. It also promotes a deeper understanding of the efficacy of the activism process by deconstructing policy stringency across pollution media to show that activism and its impacts are more nuanced than previously studied.

To construct an index (index of environmental sensitivity performance) to be used in a cross‐country trade model in order to analyze the effect of various degrees of environmental stringency on the trade patterns, and especially on the export performance of the countries.

The gravity model of trade is used in order to find the effects of environmental stringency on the variation in trade flows.

The study shows that environmental stringency has an important impact on the export of the countries. The impact of the degree of environmental stringency on the exports is significantly negative suggesting an inverse relationship between export values and relative environmental sensitivity performance of the nations.

This study supports the argument that the environmental stringency level differential between developing and developed nations is a crucial criteria in terms of explaining shifts in the trade patterns and international specialization of the countries.

Textile, listed as one of the highly environmentally sensitive goods, its trade is susceptible to be influenced by the implementation of stringent environmental policies. This paper aims to investigate the long-run relationship between revealed comparative advantage (RCA) and Environmental Policy Stringency Index (EPSI) for textile exports of G20 countries in panel data setup.

Apart from trend analysis, the authors have employed Pedroni and Westerlund panel cointegration method and fully modified ordinary least square (FMOLS) method to study the long-run relationship between RCA and EPSI in presence of cross-sectional dependence.

A strong link between trade and environmental stringency is observed for textile in the present study. For G20 countries, slight evidence of the Pollution Haven Hypothesis has also been witnessed in the study. Correspondingly, the results reveal the presence of long-run association between the variables under study, implying that stringent environmental policies reduce RCA for some countries, whereas some countries witness the Porter hypothesis.

The results imply that policy formulation should not aim at limiting the efforts of connecting RCA to environmental stringency but to set trade policies in a wider framework, considering environmental concerns, as these are inseparable subjects. However, this study also provides relevant real-world implications that can support further research.

The present study has important implications for textile exporters such as green innovations. The Porter hypothesis can be a beneficial tool for G20 exporters in enhancing their export performance, especially for the ones dealing in environmentally sensitive goods. This study offers relevant policy implications and provides directions for future research on global trade and environment nexus.

This study deals in a debatable area of research that evaluates the interlinkages between environmental stringency and global trade flows in the G20 countries. An important observation of the study is the asymmetrical nature of policy stringency across different countries and its impact on trade. The unavailability of updated data is the limitation of the present study.

The stringency policy and economic support policy in response to and to address the coronavirus disease 2019 have become a significant concern since the end of 2019. The motivation that led to this study is that, the selection of the stringency policy and the economic support policy appear to have brought about the opposite effects of the environmental costs of carbon dioxide emissions. The study's objective is to examine the contradictory impacts of these stringency and economic support policies on carbon dioxide emissions.

This study applies panel data for the top four countries responsible for carbon dioxide emission, namely China, the United States of America, India and Russia. A fully modified ordinary least squares estimator and dynamic ordinary least squares estimator are employed to determine the long-run parameters.

The results indicate that the effect of reduced carbon dioxide emissions due to a one-unit increase in the stringency policy is greater than the effect of increased carbon dioxide emissions caused by a one-unit increase in the economic support policy. Hence, if the two policies are implemented simultaneously, a positive net effect on environmental costs will be gained.

The study investigates in a general scope, the impact these response policies have on the environment. Future researchers may enhance the research on environmental impact in different sectors due to the implementation of both policies to enrich the analytical perspective.

The results have provided implications for policymakers to emphasize more on stringency-oriented policies while giving economic support to the low-income or unemployed households in order to reduce carbon dioxide emissions.

Despite the foreseen effects of the stringency policy and economic support policy, there has hardly been any studies that have explored empirically the nexus between both policies with carbon dioxide emissions in one empirical model. Furthermore, the paper uses the high-frequency data in determining the contradictory impacts of stringency policy and economic support policy on CO₂ emissions.

The increased focus on sustainability has led firms to incorporate a range of sustainability practices in their products, processes and supply chains. Because these practices are typically difficult to observe, firms often seek an independent verification and adopt voluntary environmental and social standards and eco-labels such as ISO 14000, FSC, USDA Organic or Fairtrade. The purpose of this paper is to study several factors linked to their adoption.

Drawing on existing theory, the authors hypothesize that environmental and social standards will be more widely adopted if they are better-governed, less stringent and more favorably covered in the media. The authors collect data on 41 eco-labels from multiple data sources.

The authors find that the better-governed labels are more widely adopted, but that more stringent labels within the sample are not less widely adopted. More favorable media coverage is not associated with wider adoption.

The study focuses on the diffusion of a sample of well-established eco-labels. To establish causal links, longitudinal data on governance, stringency, adoption and media coverage would be needed.

Managers deciding which eco-label to adopt need not be concerned that a more stringent label will inevitably yield less business value due to the label being less widely adopted. However, they should care whether a label is seen to be well-governed. Managers cannot use the way a label is portrayed in the media as a predictor for adoption.

Past research has often ignored how characteristics of environmental and social standards impact their diffusion. The work contributes to the growing literature on diffusion of voluntary standards and eco-labels by adding a quantitative and multi-sectoral perspective.

Maximum residue limits (MRLs) on pesticides and veterinary drugs in plant and animal products are established to promote food safety and animal and plant health. In practice, however, they are often accused of creating unnecessary trade barriers. The controversy is more prominent when a given MRL is stricter than the corresponding international standard developed by Codex. Using the score indices constructed by Li and Beghin (2012), we empirically assess the implications of stringency in MRLs in plant and animal products, relative to Codex levels, for Canadian and US trade performance. We find little evidence that US imports are influenced by domestic stringency or those imposed by its trading partners. However, US exports are negatively affected by stringency in destination markets. Canada’s stringent MRLs facilitate its exports of plant and animal products and these exports do not seem to be impeded by MRL stringency in destination markets. Canada’s imports do not appear to be systematically influenced by either its own or its trading partners’ MRL stringency. We draw implications for the potential harmonization of MRLs between the two countries.

This study aims to examine the impact of the stringency of COVID-19 protocols on the volatility of sectoral indices during the period 03:2020–05:2021. Specifically, this study investigates the role of economic disturbances on sectoral volatility by applying a range of conditional volatility techniques.

For this analysis, two approaches were adopted. The first approach considers COVID stringency as a factor in the conditional variance equation of sectoral indices. In contrast, the second approach considers the stringency indicator as a possible determinant of their estimated conditional volatility.

Results show that the stringency of the protocols throughout the pandemic phase led to an instantaneous spike followed by a gradual decrease in estimated volatility of all the sectoral indices except pharma and health care. Specific sectors such as bank, FMCG, consumer durables, financial services, IT, media and private banks respond to protocols expeditiously compared to other sectors.

The key contribution of this study to the existing literature is the innovative approach. The inclusion of the COVID stringency index as a regressor in the variance equation of the conditional volatility techniques was a distinctive approach for assessing the volatility dynamics with the stringency of COVID protocols. Furthermore, this study also adopts an alternative approach that estimates the conditional volatility of the indices and then tests the effect of the stringencies on estimated volatility in a regression framework.