The Effects of Firm Size and Experience on Safety and Environmental Performance in the Oil and Gas Industry, Part I: A Proposed Treatment for Sample Selection In Detection-Controlled Estimation Models

2014 ◽  
Author(s):  
Christopher Jablonowski
Keyword(s):  
Firm Size ◽  
Environmental Performance ◽  
Oil And Gas ◽  
Sample Selection ◽  
Oil And Gas Industry ◽  
Gas Industry ◽  
Estimation Models

scholarly journals SIZE, AGE AND LEVERAGE OF NIGERIA QUOTED OIL AND GAS CORPORATIONS

2021 ◽  
Vol 3 (6) ◽  
pp. 51-60
Author(s):  
Onipe Adabenege Yahaya ◽  
Bilyaminu Tijjani
Keyword(s):  
Firm Size ◽  
Oil And Gas ◽  
Empirical Studies ◽  
Oil And Gas Industry ◽  
Financial Leverage ◽  
Firm Level ◽  
Gas Industry ◽  
User Data ◽  
Oil And Gas Firms ◽  
Oil And Gas Companies

Firm size and age influence firm-level leverage. The extent of such influence on the oil and gas industry is not known in Nigeria. There are very few empirical studies that interrogate the effects of firm size and listing age on leverage in Nigeria. This study examines the impacts of firm size and listing age on firm-level financial leverage of listed oil and gas companies in Nigeria. It was non-experimental research and correlational in nature. Data were extracted from annuals and accounts of 8 firms over a period of 13 years (2007-2019) and subjected to descriptive statistics (number of observations, mean, standard deviations, mean, minimum and maximum means) and inferential statistics (multiple regression analysis). The findings show that firm size has a negative and significant impact on firm-level financial leverage. Firm age has a positive and significant effect on firm-level leverage. In this paper, we contribute to the literature by examining the presence and direction of firm size and listing age to financial leverage user data from listed oil and gas firms in Nigeria. Our study is the first to address the adverse implications of Modeling with firm size and listing age on firm-level financial leverage.

Best Available Techniques Applied to the Offshore Oil and Gas Industry

2014 ◽  
Vol 2014 (1) ◽  
pp. 388-399 ◽  
Author(s):  
Valentin Vandenbussche ◽  
Emma Karlstrøm Thylander ◽  
Daniel Millet
Keyword(s):  
Environmental Performance ◽  
Oil And Gas ◽  
Pollution Prevention ◽  
Oil And Gas Industry ◽  
Gas Industry ◽  
Site Specific ◽  
Best Available Techniques ◽  
Eu Directive ◽  
Offshore Industry ◽  
Offshore Oil

ABSTRACT Best Available Techniques (BAT) is a principle originally defined in the EU directive on Integrated Pollution Prevention and Control (IPPC). The overall ambition of the directive is to reduce emissions and impacts on the environment as a whole. The purpose of a BAT assessment is to identify the technique with the best environmental performance among all available techniques for a certain industrial application. Such assessment should also take into account technical and economic constraints. A wide variety of industries fall under the scope of the IPPC requirement for BAT in Europe. The BAT approach is more and more applied in countries outside of EU, and adopted by private organisations as a best practice. In the offshore Oil & Gas industry in Norway, for instance, the BAT approach is now applied to many systems, such as power generation, produced water management, VOC recovery, or, more recently, leak detection and remote sensing. The particularity of the site-specific constraints as well as a lifecycle perspective, typical of the offshore Oil & Gas industry, makes the application of the BAT approach challenging for this sector. Best Available Techniques for offshore applications are therefore site-specific, and require a case by case assessment. In addition, in countries such as Norway, there is no guideline or directive describing how to perform a BAT assessment, which hence needs interpretation and adjustment for each individual application. DNV has developed a methodology for BAT assessments specifically for the offshore industry. This methodology is based on a ranking of the environmental performance as well as technical feasibility, reliability and costs of available industrial concepts. The approach is applicable to various stages of offshore Oil & Gas projects. This paper will describe the BAT methodology for the offshore Oil & Gas industry, and give relevant examples of its application to various systems commonly found on offshore facilities. Challenges and future opportunities will also be presented and discussed.

scholarly journals Legitimacy in Green: Pollution vs. Profit in Canadian Oil Refineries

2007 ◽  
Vol 1 (1) ◽  
pp. 54 ◽  
Author(s):  
Vanessa Magness
Keyword(s):  
Environmental Performance ◽  
Oil And Gas ◽  
New Technologies ◽  
Petroleum Refinery ◽  
External Environment ◽  
Oil And Gas Industry ◽  
Gas Industry ◽  
Oil Refineries ◽  
Cost Efficiencies ◽  
Societal Expectations

This paper examines the correlation of financial and environmental performance in the petroleum refinery sector. Emissions fell while profits<br />rose over a ten-year period. Ongoing efforts to legitimize companies in<br />light of changing societal expectations have created an external environment that encourages the development of new technologies that promote cost efficiencies and good environmental performance simultaneously.  Russo and Fouts (1997) argued that industries subject to rapid technological advance are well suited to respond to these changes in the external environment. The findings of this paper suggest that the petroleum refinery sector of the oil and gas industry may be meeting the challenge of the environmental movement.<br /><br />

An integrative environmental performance index for benchmarking in oil and gas industry

2016 ◽  
Vol 133 ◽  
pp. 1190-1203 ◽  
Author(s):  
Alejandro Germán Frank ◽  
Nathalie Dalle Molle ◽  
Wolfgang Gerstlberger ◽  
João Augusto Bonzanini Bernardi ◽  
Danilo Cuzzuol Pedrini
Keyword(s):  
Performance Index ◽  
Environmental Performance ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Gas Industry ◽  
Environmental Performance Index

An Analysis of the Trends in US Offshore Oil and Gas Safety and Environmental Performance

2019 ◽  
Author(s):  
Jeremy M. Gernand
Keyword(s):  
Random Forest ◽  
Environmental Performance ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Time Of Day ◽  
Gas Production ◽  
Gas Industry ◽  
Oil And Gas Production ◽  
Offshore Oil And Gas ◽  
Offshore Oil

Abstract The production of oil and gas in the offshore waters of the United States continues to be a major part of US energy extraction activities amounting to just less than a third of total US oil and gas production. However, this industry has been marked by occasional safety and environmental disasters including most famously the Deepwater Horizon explosion and oil spill that resulted in the deaths of 11 workers and the release of more than 130 million gallons of oil in to the Gulf of Mexico. In response, the Bureau of Safety and Environmental Enforcement (BSEE) was created in 2011 to separate enforcement activities from federal lease management activities and reduce the possibility for conflicts of interests and regulatory capture. This paper presents an analysis of the safety and environmental performance of the US offshore oil and gas industry in the years before and after the creation of the BSEE to quantify the changes in the industry record and the level of risk that remains. Recorded events including fires and explosions, spills, and gas releases, collisions, and injuries and fatalities are included in the analysis. The overall level of exposure is estimated based on rig counts and oil and gas production quantities since detailed employment records by facility are not available. Data is sourced from the BSEE, Bureau of Labor Statistics (BLS), and the Energy Information Agency (EIA). In addition to linear regression analysis of trends, this paper presents the results of a random forest-based machine learning investigation of the characteristics of safety and environmental incidents to evaluate the most significant contributors that remain, especially those amenable to control through engineering system design. Facility type, water depth, distance to shore, and time of day or year in the relevant incident reports were included in the input dataset for the random forest model. Results indicate that the overall oil and gas industry has become safer in recent years, though significant risks remain. It is yet unclear whether the BSEE approach bears any responsibility for this change as the data are not yet sufficient to declare the post-2011 period as statistically significantly improved from prior years, though additional data in line with 2016–2017 level of performance would satisfy this condition. The random forest model indicates that increased risk is associated with time of day, quarter of the year, water depth, and distance to shore. Data quality concerns remain present as minor incidents and injuries may be under-reported. BSEE enforcement does not appear to be a direct cause of the noted improvements.

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