Neural network DEA for measuring the efficiency of mutual funds

Efficiency in the mutual fund (MF), is one of the issues that has attracted many investors in countries with advanced financial market for many years. Due to the need for frequent study of MF's efficiency in short-term periods, investors need a method that not only has high accuracy, but also high speed. Data envelopment analysis (DEA) is proven to be one of the most widely used methods in the measurement of the efficiency and productivity of decision making units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper uses neural network back-ropagation DEA in measurement of mutual funds efficiency and shows the requirements, in the proposed method, for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of a large set of MFs. Copyright © 2014 Inderscience Enterprises Ltd.

Power industry restructuring and eco-efficiency changes:a new slacks-based model in Malmquist-Luenberger Index measurement

Measuring variations in efficiency and its extension, eco-efficiency, during a restructuring period in different industries has always been a point of interest for regulators and policy makers. This paper assesses the impacts of restructuring of procurement in the Iranian power industry on the performance of power plants. We introduce a new slacks-based model for Malmquist-Luenberger (ML) Index measurement and apply it to the power plants to calculate the efficiency, eco-efficiency, and technological changes over the 8-year period (2003-2010) of restructuring in the power industry. The results reveal that although the restructuring had different effects on the individual power plants, the overall growth in the eco-efficiency of the sector was mainly due to advances in pure technology. We also assess the correlation between efficiency and eco-efficiency of the power plants, which indicates a close relationship between these two steps, thus lending support to the incorporation of environmental factors in efficiency analysis. © 2014 Elsevier Ltd.

Technical efficiency determinants within a dual banking system:a DEA-bootstrap approach

The purpose of this study is to provide a comparative analysis of the efficiency of Islamic and conventional banks in Gulf Cooperation Council (GCC) countries. In this study, we explain inefficiencies obtained by introducing firm-specific as well as macroeconomic variables. Our findings indicate that during the eight years of study, conventional banks largely outperform Islamic banks with an average technical efficiency score of 81% compared to 95.57%. However, it is clear that since 2008, efficiency of conventional banks was in a downward trend while the efficiency of their Islamic counterparts was in an upward trend since 2009. This indicates that Islamic banks have succeeded to maintain a level of efficiency during the subprime crisis period. Finally, for the whole sample, the analysis demonstrates the strong link of macroeconomic indicators with efficiency for GCC banks. Surprisingly, we have not found any significant relationship in the case of Islamic banks.

A linear relational DEA model to evaluate two-stage processes with shared inputs

Two-stage data envelopment analysis (DEA) efficiency models identify the efficient frontier of a two-stage production process. In some two-stage processes, the inputs to the first stage are shared by the second stage, known as shared inputs. This paper proposes a new relational linear DEA model for dealing with measuring the efficiency score of two-stage processes with shared inputs under constant returns-to-scale assumption. Two case studies of banking industry and university operations are taken as two examples to illustrate the potential applications of the proposed approach.

Carbon efficiency evaluation:an analytical framework using fuzzy DEA

Data Envelopment Analysis (DEA) is a powerful analytical technique for measuring the relative efficiency of alternatives based on their inputs and outputs. The alternatives can be in the form of countries who attempt to enhance their productivity and environmental efficiencies concurrently. However, when desirable outputs such as productivity increases, undesirable outputs increase as well (e.g. carbon emissions), thus making the performance evaluation questionable. In addition, traditional environmental efficiency has been typically measured by crisp input and output (desirable and undesirable). However, the input and output data, such as CO2 emissions, in real-world evaluation problems are often imprecise or ambiguous. This paper proposes a DEA-based framework where the input and output data are characterized by symmetrical and asymmetrical fuzzy numbers. The proposed method allows the environmental evaluation to be assessed at different levels of certainty. The validity of the proposed model has been tested and its usefulness is illustrated using two numerical examples. An application of energy efficiency among 23 European Union (EU) member countries is further presented to show the applicability and efficacy of the proposed approach under asymmetric fuzzy numbers.

A methodological framework for modeling pavement maintenance costs for projects with performance-based contracts

Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.

A Methodological Framework for Modeling Pavement Maintenance Costs for Projects with Performance-based Contracts

Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.

Characterization of wood biochar and evaluation of its adsorption potential for removal of sulphate from produced water in offshore oil and gas industry

This thesis analyses the potential of wood biochar as an adsorbent in removal of sulphate from produced water. In worldwide offshore oil and gas industry, a large volume of waste water is generated as produced water. Sulphur compounds present in these produced water streams can cause environmental problems, regulatory problems and operational issues. Among the various sulphur removal technologies, the adsorption technique is considered as a suitable method since the design is simple, compact, economical and robust. Biochar has been studied as an adsorbent for removal of contaminants from water in a number of studies due to its low cost, potential availability, and adsorptive characteristics. In this study, biochar produced through fast pyrolysis of bark, hardwood sawdust, and softwood sawdust were characterized through a series of tests and were analysed for adsorbent properties. Treating produced water using biochar sourced from wood waste is a two-fold solution to environmental problems as it reduces the volume of these wastes. Batch adsorption tests were carried out to obtain adsorption capacities of each biochar sample using sodium sulphate solutions. The highest sulphur adsorption capacities obtained for hardwood char, softwood char and bark char were 11.81 mg/g, 9.44 mg/g, and 7.94 mg/g respectively at 10 °C and pH=4. The adsorption process followed the second order kinetic model and the Freundlich isotherm model. Adsorption reaction was thermodynamically favourable and exothermic. The overall analysis concludes that the wood biochar is a feasible, economical, and environmental adsorbent for removal of sulphate from produced water.

A study of methods used to analyze total oil and polycyclic aromatic hydrocarbons in produced water: steps towards the validation of molecularly imprinted polymers for use in marine environmetns

Produced water is a by-product of offshore oil and gas production, and is released in large volumes when platforms are actively processing crude oil. Some pollutants are not typically removed by conventional oil/water separation methods and are discharged with produced water. Oil and grease can be found dispersed in produced water in the form of tiny droplets, and polycyclic aromatic hydrocarbons (PAHs) are commonly found dissolved in produced water. Both can have acute and chronic toxic effects in marine environments even at low exposure levels. The analysis of the dissolved and dispersed phases are a priority, but effort is required to meet the necessary detection limits. There are several methods for the analysis of produced water for dispersed oil and dissolved PAHs, all of which have advantages and disadvantages. In this work, EPA Method 1664 and APHA Method 5520 C for the determination of oil and grease will be examined and compared. For the detection of PAHs, EPA Method 525 and PAH MIPs will be compared, and results evaluated. APHA Method 5520 C Partition-Infrared Method is a liquid-liquid extraction procedure with IR determination of oil and grease. For analysis on spiked samples of artificial seawater, extraction efficiency ranged from 85 – 97%. Linearity was achieved in the range of 5 – 500 mg/L. This is a single-wavelength method and is unsuitable for quantification of aromatics and other compounds that lack sp³-hybridized carbon atoms. EPA Method 1664 is the liquid-liquid extraction of oil and grease from water samples followed by gravimetric determination. When distilled water spiked with reference oil was extracted by this procedure, extraction efficiency ranged from 28.4 – 86.2%, and %RSD ranged from 7.68 – 38.0%. EPA Method 525 uses solid phase extraction with analysis by GC-MS, and was performed on distilled water and water from St. John’s Harbour, all spiked with naphthalene, fluorene, phenanthrene, and pyrene. The limits of detection in harbour water were 0.144, 3.82, 0.119, and 0.153 g/L respectively. Linearity was obtained in the range of 0.5-10 g/L, and %RSD ranged from 0.36% (fluorene) to 46% (pyrene). Molecularly imprinted polymers (MIPs) are sorbent materials made selective by polymerizing functional monomers and crosslinkers in the presence of a template molecule, usually the analytes of interest or related compounds. They can adsorb and concentrate PAHs from aqueous environments and are combined with methods of analysis including GC-MS, LC-UV-Vis, and desorption electrospray ionization (DESI)- MS. This work examines MIP-based methods as well as those methods previously mentioned which are currently used by the oil and gas industry and government environmental agencies. MIPs are shown to give results consistent with other methods, and are a low-cost alternative improving ease, throughput, and sensitivity. PAH MIPs were used to determine naphthalene spiked into ASTM artificial seawater, as well as produced water from an offshore oil and gas operation. Linearity was achieved in the range studied (0.5 – 5 mg/L) for both matrices, with R² = 0.936 for seawater and R² = 0.819 for produced water. The %RSD for seawater ranged from 6.58 – 50.5% and for produced water, from 8.19 – 79.6%.

Environmental Impacts of the Deep-Water Oil and Gas Industry : A Review to Guide Management Strategies

The authors would like to thank the leadership of the Deep Ocean Stewardship Initiative (DOSI), including Lisa Levin, Maria Baker, and Kristina Gjerde, for their support in developing this review. This work evolved from a meeting of the DOSI Oil and Gas working group supported by the J.M. Kaplan Fund, and associated with the Deep-Sea Biology Symposium in Aveiro, Portugal in September 2015. The members of the Oil and Gas working group that contributed to our discussions at that meeting or through the listserve are acknowledged for their contributions to this work. We would also like to thank the three reviewers and the editor who provided valuable comments and insight into the work presented here. DJ and AD were supported by funding from the European Union's Horizon 2020 research and innovation programme under the MERCES (Marine Ecosystem Restoration in Changing European Seas) project, grant agreement No 689518. AB was supported by CNPq grants 301412/2013-8 and 200504/2015-0. LH acknowledges funding provided by a Natural Environment Research Council grant (NE/L008181/1). This output reflects only the authors' views and the funders cannot be held responsible for any use that may be made of the information contained therein.

Local fiscal effects of oil and gas development in eight states

Oil and gas production in the United States has increased dramatically in the past 10 years. This growth has important implications for local governments, which often see new revenues from a variety of sources: property taxes on oil and gas property, sales taxes driven by the oil and gas workforce, allocations of state revenues from severance taxes or state and federal leases, leases on local government land, and contributions from oil and gas companies to support local services. At the same time, local governments tend to experience a range of new costs such as road damage caused by heavy industry truck traffic, increased demand for emergency services and law enforcement, and challenges with workforce retention. This report examines county and municipal fiscal effects in 14 oil- and gas-producing regions of eight states: AK, CA, KS, OH, OK, NM, UT, and WV. We find that for most local governments, oil and gas development—whether new or longstanding—has a positive effect on local public finances. However, effects can vary substantially due to a variety of local factors and policy issues. For some local governments, particularly those in rural regions experiencing large increases in development, revenues have not kept pace with rapidly increased costs and demand for services, particularly on road repair.

Innovation in the pharmaceutical industry: New estimates of R&D costs.

The research and development costs of 106 randomly selected new drugs were obtained from a survey of 10 pharmaceutical firms. These data were used to estimate the average pre-tax cost of new drug and biologics development. The costs of compounds abandoned during testing were linked to the costs of compounds that obtained marketing approval. The estimated average out-of-pocket cost per approved new compound is $1395 million (2013 dollars). Capitalizing out-of-pocket costs to the point of marketing approval at a real discount rate of 10.5% yields a total pre-approval cost estimate of $2558 million (2013 dollars). When compared to the results of the previous study in this series, total capitalized costs were shown to have increased at an annual rate of 8.5% above general price inflation. Adding an estimate of post-approval R&D costs increases the cost estimate to $2870 million (2013 dollars).

A Study of Environmental Disclosures in the European Oil and Gas Industry : With Reference to the Global Reporting Initiative

Background and Problem: Sustainability reporting is a growing trend in the society. One of the most exposed industries to environmental matters is the oil and gas industry, which commit to sustainability reporting in order to deal with the industry’s destructive operations. The Global Reporting Initiative (GRI) provides voluntary guidelines in sustainability reporting, which increase transparency for the company’s stakeholders. However, it is controversial that the oil and gas industry put a great effort into sustainability reporting even though the industry is environmentally destructive. This gap is interesting to investigate and will contribute to the academic discussion. Therefore, this thesis will focus on the sustainability reporting in the oil and gas industry and to what extent the industry actually discloses material environmental information about their operations. Purpose: The purpose of this thesis is to examine how the sustainability reporting has changed in the oil and gas industry in Europe. This is performed from a stakeholder perspective. Further, it aims to investigate how oil and gas companies have followed the GRI guidelines and how the reporting has changed over time. Method: A quantitative method is used in order to answer the research questions. The data sample is based on oil and gas companies reporting according to the GRI framework during year 2012 to year 2014. The empirical data is gathered from the studied companies’ environmental category in their sustainability reports. Further, a content analysis technique, with a coding scheme, was set up to interpret and analyse the information. To enable an easy overview of the findings, the relevant data is presented in tables and diagrams. Empirical Findings and Conclusion: The majority of the studied companies have increased their level of compliance in the environmental category. Although, the majority of the companies have increased their reporting, the compliance level differs between the companies. The most reported sectors are the; “Water”, “Biodiversity”, “Emissions”, “Effluents and Waste”, “Compliance”, and “Overall”. Further, the empirical findings show that there is an overall increase in the amount of disclosed information per indicator. The conclusion of this thesis is that the environmental disclosures have increased in the oil and gas industry from year 2012 to 2014.

Effects of IFRS adoption on the financial statements of Nigerian listed entities: the case of oil and gas companies

On 28 July 2010, the Nigerian Federal Executive Council approved January 1, 2012 as the effective date for the convergence of Nigerian Statement of Accounting Standards (SAS) or Nigerian GAAP (NG-GAAP) with International Financial Reporting Standards (IFRS). By this pronouncement, all publicly listed companies and significant public interest entities in Nigeria were statutorily required to issue IFRS based financial statements for the year ended December, 2012. This study investigates the impact of the adoption of IFRS on the financial statements of Nigerian listed Oil and Gas entities using six years of data which covers three years before and three years after IFRS adoption in Nigeria and other African countries. First, the study evaluates the impact of IFRS adoption on the Exploration and Evaluation (E&E) expenditures of listed Oil and Gas companies. Second, it examines the impact of IFRS adoption on the provision for decommissioning of Oil and Gas installations and environmental rehabilitation expenditures. Third, the study analyses the impact of the adoption of IFRS on the average daily Crude Oil production cost per Barrel. Fourth, it examines the extent to which the adoption and implementation of IFRS affects the Key Performance Indicators (KPIs) of listed Oil and Gas companies. The study further explores the impact of IFRS adoption on the contractual relationships between Nigerian Government and Oil and Gas companies in terms of Joint Ventures (JVs) and Production Sharing Contracts (PSCs) as it relates to taxes, royalties, bonuses and Profit Oil Split. A Paired Samples t-test, Wilcoxon Signed Rank test and Gray’s (Gray, 1980) Index of Conservatism analyses were conducted simultaneously where the accounting numbers, financial ratios and industry specific performance measures of GAAP and IFRS were computed and analysed and the significance of the differences of the mean, median and Conservatism Index values were compared before and after IFRS adoption. Questionnaires were then administered to the key stakeholders in the adoption and implementation of IFRS and the responses collated and analysed. The results of the analyses reveal that most of the accounting numbers, financial ratios and industry specific performance measures examined changed significantly as a result of the transition from GAAP to IFRS. The E&E expenditures and the mean cost of Crude Oil production per barrel of Oil and Gas companies increased significantly. The GAAP values of inventories, GPM, ROA, Equity and TA were also significantly different from the IFRS values. However, the differences in the provision for decommissioning expenditures were not statistically significant. Gray’s (Gray, 1980) Conservatism Index shows that Oil and Gas companies were more conservative under GAAP when compared to the IFRS regime. The Questionnaire analyses reveal that IFRS based financial statements are of higher quality, easier to prepare and present to management and easier to compare among competitors across the Oil and Gas sector but slightly more difficult to audit compared to GAAP based financial statements. To my knowledge, this is the first empirical research to investigate the impact of IFRS adoption on the financial statements of listed Oil and Gas companies. The study will therefore make an enormous contribution to academic literature and body of knowledge and void the existing knowledge gap regarding the impact and implications of IFRS adoption on the financial statements of Oil and Gas companies.