Essays on energy economics : markets, investment and production

textMy dissertation consists of three distinct but related chapters on Energy Economics and Finance. My first chapter is an empirical evaluation of market conduct in global crude oil markets. "Hotelling rule" states that even in competitive equilibrium, price of an "exhaustible resource" exceeds its marginal cost due to the opportunity cost of depleting the non-renewable resource. This cost is called "scarcity rent". Oil price exceeds its marginal extraction cost significantly. This can be attributed to two different sources: effect of scarcity of oil on prices or exercising market power by OPEC (collusion). In this paper, I use Porter (1983) approach considering the possibility of "scarcity rent" component involved in the gap between price and marginal extraction cost in the oil market. The novelty of my approach is to empirically estimate scarcity rent using data on cost of production of oil. Two benchmark cases, where scarcity rent is either zero (non-exhaustible resources hypothesis (Adelman 1990)) or equal to minimum price-cost margin are considered. The results show that in both cases OPEC failed to cooperate effectively and in second case, market conduct estimated is closer to Cournot behavior. In the second chapter of my dissertation, we employ a real options approach to evaluate oil and gas companies' investment decisions in an empirical setup. We develop a theoretical model to derive testable predictions. A unique measure of investment costs is obtained from energy industry data vendors. This novel dataset contains details of contract terms and pricing for offshore drilling equipment, which constitute the major share of investment costs in offshore oil field development. The investment database is combined with financial and macroeconomic data, which enables us to perform a panel data analysis of investments' response to variations in investment costs and market variables such as the slope of futures curve, firms' past earnings, cost of capital and implied oil price volatility. Our results show that the larger firms, facing less financial friction, are more forward looking while the smaller firms, who have less access to capital markets, are more dependent on their past earnings. The third chapter of my dissertation is about the effect of recent natural gas production boom on U.S. manufacturing. Natural gas production in North America has increased significantly over the past decade causing the prices to plunge during past 5 years. The purpose of this research is to investigate the effect of low natural gas prices on energy intensive U.S. manufacturing industries using market data. I empirically evaluate the stock market reactions of publicly traded companies in energy intensive industries to arrival of new information about the unexpected price shocks in natural gas futures markets. My results show that the stock market does not react significantly to innovations in the expected price of natural gas, proxied for by monthly changes in natural gas futures contracts with a fixed maturity date. I then split the sample into two groups based on their expenditure on natural gas as a ratio of their total production value. The stock market valuation of companies in high "natural gas intensity" industries were positively affected by unexpected downward shocks in natural gas prices and the results are significant.Economic

The study of the interactive effect of culture and e-commerce in Iran

In this study, it has been tried to identify cultural factors influencing on understanding, acceptance and replacing older methods with electronic commerce and through a basic hypothesis(there is a significant relationship between the culture and e-commerce) and five sub-hypotheses(examining the relationship between learning English, teaching how to use computers and search engines, traditional shopping ways, the impact of thoughts and attitudes of reference groups, friends, relatives, family and competitive phenomena and finally the distance between the class and e-commerce). As it is found from the research topic, research scope was related to the whole parts of Iran but since the culture of tendency toward e-commerce does not exist in a large amount in Tehran, therefore, we consider only Tehran as our population and statistical sample obtained through the cluster sampling method. The primary and secondary data were collected through library method and questionnaire as a survey method of research was distributed in computer sales centers in Tehran like Computer Center of Raza, capital, Ala al-Din, Shahrake Ekbatan, Shahrake Gharb, café nets and some major computer sales centers in different parts of Tehran. Among them, people having computers and information about computer and computer science were regarded as the main participants. Finally, the results of this research indicated that there is a significant relationship between culture and e-commerce

The study of the interactive effect of culture and e-commerce in Iran

In this study, it has been tried to identify cultural factors influencing on understanding, acceptance and replacing older methods with electronic commerce and through a basic hypothesis(there is a significant relationship between the culture and e-commerce) and five sub-hypotheses(examining the relationship between learning English, teaching how to use computers and search engines, traditional shopping ways, the impact of thoughts and attitudes of reference groups, friends, relatives, family and competitive phenomena and finally the distance between the class and e-commerce). As it is found from the research topic, research scope was related to the whole parts of Iran but since the culture of tendency toward e-commerce does not exist in a large amount in Tehran, therefore, we consider only Tehran as our population and statistical sample obtained through the cluster sampling method. The primary and secondary data were collected through library method and questionnaire as a survey method of research was distributed in computer sales centers in Tehran like Computer Center of Raza, capital, Ala al-Din, Shahrake Ekbatan, Shahrake Gharb, café nets and some major computer sales centers in different parts of Tehran. Among them, people having computers and information about computer and computer science were regarded as the main participants. Finally, the results of this research indicated that there is a significant relationship between culture and e-commerce

The evaluation of the effect of E-banking service quality on customers’ commitment of Parsian Bank of Tehran

This study investigates the impact of e-banking service quality on customers’ satisfaction and commitment. The design of the present study isexperimental, and for conducting this study, 384 customers of Parsian Bank of Tehran who have had the experience of using the electronic services of this bank were randomly selected by cluster sampling and data of this study were collected by using of questionnaire tool. The nature of the study is descriptive-survey and descriptive-analytical statistical techniques were used to analyze the data. In the descriptive analysis level, demographic data were analyzed and in the analytical analysis level, data were analyzed by structural equation modeling to confirm or reject the hypotheses. The results of this study indicated that all three hypotheses were confrmed. The perceived quality of e-banking services has positive impact on customers’ satisfaction. Finally, the satisfaction of the perceived quality of e-banking services has a positive impact on customers’ commitment

The evaluation of the effect of E-banking service quality on customers’ commitment of Parsian Bank of Tehran

This study investigates the impact of e-banking service quality on customers’ satisfaction and commitment. The design of the present study isexperimental, and for conducting this study, 384 customers of Parsian Bank of Tehran who have had the experience of using the electronic services of this bank were randomly selected by cluster sampling and data of this study were collected by using of questionnaire tool. The nature of the study is descriptive-survey and descriptive-analytical statistical techniques were used to analyze the data. In the descriptive analysis level, demographic data were analyzed and in the analytical analysis level, data were analyzed by structural equation modeling to confirm or reject the hypotheses. The results of this study indicated that all three hypotheses were confrmed. The perceived quality of e-banking services has positive impact on customers’ satisfaction. Finally, the satisfaction of the perceived quality of e-banking services has a positive impact on customers’ commitment

Faults in Deep Reinforcement Learning Programs: A Taxonomy and A Detection Approach

A growing demand is witnessed in both industry and academia for employing Deep Learning (DL) in various domains to solve real-world problems. Deep Reinforcement Learning (DRL) is the application of DL in the domain of Reinforcement Learning (RL). Like any software systems, DRL applications can fail because of faults in their programs. In this paper, we present the first attempt to categorize faults occurring in DRL programs. We manually analyzed 761 artifacts of DRL programs (from Stack Overflow posts and GitHub issues) developed using well-known DRL frameworks (OpenAI Gym, Dopamine, Keras-rl, Tensorforce) and identified faults reported by developers/users. We labeled and taxonomized the identified faults through several rounds of discussions. The resulting taxonomy is validated using an online survey with 19 developers/researchers. To allow for the automatic detection of faults in DRL programs, we have defined a meta-model of DRL programs and developed DRLinter, a model-based fault detection approach that leverages static analysis and graph transformations. The execution flow of DRLinter consists in parsing a DRL program to generate a model conforming to our meta-model and applying detection rules on the model to identify faults occurrences. The effectiveness of DRLinter is evaluated using 15 synthetic DRLprograms in which we injected faults observed in the analyzed artifacts of the taxonomy. The results show that DRLinter can successfully detect faults in all synthetic faulty programs

Automatic Fault Detection for Deep Learning Programs Using Graph Transformations

Nowadays, we are witnessing an increasing demand in both corporates and academia for exploiting Deep Learning (DL) to solve complex real-world problems. A DL program encodes the network structure of a desirable DL model and the process by which the model learns from the training dataset. Like any software, a DL program can be faulty, which implies substantial challenges of software quality assurance, especially in safety-critical domains. It is therefore crucial to equip DL development teams with efficient fault detection techniques and tools. In this paper, we propose NeuraLint, a model-based fault detection approach for DL programs, using meta-modelling and graph transformations. First, we design a meta-model for DL programs that includes their base skeleton and fundamental properties. Then, we construct a graph-based verification process that covers 23 rules defined on top of the meta-model and implemented as graph transformations to detect faults and design inefficiencies in the generated models (i.e., instances of the meta-model). First, the proposed approach is evaluated by finding faults and design inefficiencies in 28 synthesized examples built from common problems reported in the literature. Then NeuraLint successfully finds 64 faults and design inefficiencies in 34 real-world DL programs extracted from Stack Overflow posts and GitHub repositories. The results show that NeuraLint effectively detects faults and design issues in both synthesized and real-world examples with a recall of 70.5 % and a precision of 100 %. Although the proposed meta-model is designed for feedforward neural networks, it can be extended to support other neural network architectures such as recurrent neural networks. Researchers can also expand our set of verification rules to cover more types of issues in DL programs

Preventive behaviors in recurrent kidney stone and barriers to performing these behaviors

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