The Cumulative Impact of Health, Environmental, and Safety Concerns on the Chemical Industry during the Seventies

Hoerger, Fred D.; Beamer, William H.; Hanson, James S.

doi:10.2307/1191558

Cited by 11 publications

(3 citation statements)

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“…Also increases in regulation may lead firms to become less certain about future regulatory policies. This in turn could lead firms them to delay investment (Viscusi [1983]), the development of new products (Hoerger, Beamer, and Hanson [1983]), or research on new production technologies. We would expect similar effects to result if firms have limited budgets for research and development, and regulation requires them to invest in the development of new pollution abatement or cleaner technologies rather than more efficient ones.…”

Section: Environmental Regulation and Productivitymentioning

confidence: 99%

Pollution abatement expenditures and plant-level productivity: A production function approach

Shadbegian

Gray

2005

Ecological Economics

186

104

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In this paper we investigate the impact of environmental regulation on productivity using a Cobb-Douglas production function framework. Estimating the effects of regulation on productivity can be done with a top-down approach using data for broad sectors of the economy, or a more disaggregated bottom-up approach. Our study follows a bottom-up approach using data from the U.S. paper, steel, and oil industries. We measure environmental regulation using plant-level information on pollution abatement expenditures, which allows us to distinguish between productive and abatement expenditures on each input. We use annual Census Bureau information (1979-1990) on output, labor, capital, and material inputs, and pollution abatement operating costs and capital expenditures for 68 pulp and paper mills, 55 oil refineries, and 27 steel mills. We find that pollution abatement inputs generally contribute little or nothing to output, especially when compared to their 'productive' equivalents. Adding an aggregate pollution abatement cost measure to a Cobb-Douglas production function, we find that a $1 increase in pollution abatement costs leads to an estimated productivity decline of $3.11, $1.80, and $5.98 in the paper, oil, and steel industries respectively. These findings imply substantial differences across industries in their sensitivity to pollution abatement costs, arguing for a bottom-up approach that can capture these differences. Further differentiating plants by their production technology, we find substantial differences in the impact of pollution abatement costs even within industries, with higher marginal costs at plants with more polluting technologies. Finally, in all three industries, plants concentrating on change-in-production-process abatement techniques have higher productivity than plants doing predominantly end-of-line abatement, but also seem to be more affected by pollution abatement operating costs. Overall, our results point to the importance using detailed, disaggregated analyses, even below the industry level, when trying to model the costs of forcing plants to reduce their emissions.

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Section: Environmental Regulation and Productivitymentioning

confidence: 99%

Pollution abatement expenditures and plant-level productivity: A production function approach

Shadbegian

Gray

2005

Ecological Economics

186

104

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“…Furthermore, environmental regulation increases the uncertainty faced by firms. Such uncertainties may potentially hinder investment decisions and adversely affect the development of new products and production processes [10,11]. However, the perspective of compliance cost theory is relatively static.…”

Section: Introductionmentioning

confidence: 99%

Environmental Regulations and Urban Technological Innovation: China’s Two Control Zones Policy as Evidence

Zhu,

Zhou

2024

Sustainability

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In China, the Two Control Zones (TCZ) policy is an important practice in promoting sustainable development. This study aimed to investigate whether the TCZ policy promotes urban technological innovation. In this research, a DID model was built with the TCZ policy as an exogenous shock using panel data covering over 223 Chinese cities from 1995 to 2003. The empirical outcomes indicate that the TCZ policy is beneficial for augmenting urban technological innovation. Through heterogeneity analysis, it is further observed that the promotional effects of technological innovation resulting from the TCZ policy are highest in the Western region, followed by the Eastern region, and finally the Central region, and higher in cities with a higher proportion of state-owned enterprises than in cities with a higher proportion of non-state-owned enterprises. The findings of this paper align with Porter’s hypothesis and hold significant importance for other countries in devising appropriate environmental regulation policies to facilitate sustainable development.

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“…Early efforts into sustainability focused on the economic optimization of production processes: using less material, generating less waste, and utilizing less hazardous materials. 3,4 Eventual efforts began to incorporate the product itself in the creation of materials which by their own action or by their contrast to existing materials are less harmful to (or actively beneficial for) the environment. 5,6 Irrespective of the final product, there is an opportunity to make materials discovery and process development research themselves more sustainable.…”

Section: Introductionmentioning

confidence: 99%

Engineering a Sustainable Future: Harnessing Automation, Robotics, and Artificial Intelligence with Self-Driving Laboratories

Sadeghi,

Canty,

Mukhin

et al. 2024

ACS Sustainable Chem. Eng.

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The accelerating depletion of natural resources undoubtedly demands a radical reevaluation of research practices addressing the escalating climate crisis. From traditional approaches to modern-day advancements, the integration of automation and artificial intelligence (AI)-guided decision-making has emerged as a transformative route in shaping new research methodologies. Harnessing robotics and high-throughput automation alongside intelligent experimental design, self-driving laboratories (SDLs) offer an innovative solution to expedite chemical/materials research timelines while significantly reducing the carbon footprint of scientific endeavors, which could be utilized to not only generate green materials but also make the research process itself more sustainable. In this Perspective, we examine the potential of SDLs in driving sustainability forward through case studies in materials discovery and process optimization, thereby paving the way for a greener and more efficient future. While SDLs hold an immense promise, we discuss the challenges that persist in their development and deployment, necessitating a holistic approach to sustainability in both design and implementation.

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The Cumulative Impact of Health, Environmental, and Safety Concerns on the Chemical Industry during the Seventies

Cited by 11 publications

References 0 publications

Pollution abatement expenditures and plant-level productivity: A production function approach

Pollution abatement expenditures and plant-level productivity: A production function approach

Environmental Regulations and Urban Technological Innovation: China’s Two Control Zones Policy as Evidence

Engineering a Sustainable Future: Harnessing Automation, Robotics, and Artificial Intelligence with Self-Driving Laboratories

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