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Brazilian Government has proposed a change in the current fiscal regime because of the recent discoveries of large oil reserves in Brazilian pre-salt areas, from royalty/tax system to production-sharing contracts. Implementing the production-sharing system, the government believes that this is the best policy to increase gains to be transferred to society. Although, the production-sharing system is not currently clearly defined in Brazil, some debates among companies and government are occurring. Some questions may arise when comparing royalty/tax and production-sharing contracts under the company's point of view: 1) Are the appropriate oil exploitation strategy different for each fiscal model regarding configuration of wells? 2) What are the risk and return created by each fiscal regime for companies? The aim of this paper is to present a comparative analysis considering risk and return of the optimum exploitation strategy for both systems, regarding number of injectors and producers and their allocation in the reservoir. The methodology consists of: (1) selection of a typical oil field from pre-salt area; (2) optimization of an oil exploitation strategy through reservoir simulation aiming to maximize company NPV for a single deterministic scenario for each fiscal system; (3) modeling of uncertainty in oil price, capital and operating costs etc. (4) Monte Carlo simulation and quantification of risk and return (Expected Monetary Value, EMV) of royalty/tax and production-sharing systems (5) sensitivity analysis of parameters of major interest. Results indicate that the optimal production strategy to maximize NPV is different for each fiscal system. The uncertainties in the economic scenario considered in this work influence the EMV significantly. Moreover, it is also important the cost structure of the oil field and how production is shared between the parts involved over time.

Algorithms are increasingly involved in making decisions that affect human lives. Prior work has explored how people believe algorithmic decisions should be made, but there is little understanding of which individual factors relate to variance in these beliefs across people. As an increasing emphasis is put on oversight boards and regulatory bodies, it is important to understand the biases that may affect human judgements about the fairness of algorithms. Building on factors found in moral foundations theory and egocentric fairness literature, we explore how people's perceptions of fairness relate to their (i) demographics (age, race, gender, political view), and (ii) personal experiences with the algorithmic task being evaluated. Specifically, we study human beliefs about the fairness of using different features in an algorithm designed to assist judges in making decisions about granting bail. Our analysis suggests that political views and certain demographic factors, such as age and gender, exhibit a significant relation to people's beliefs about fairness. Additionally, we find that people beliefs about the fairness of using demographic features such as age, gender and race, for making bail decisions about others, vary egocentrically : that is they vary depending on their own age, gender and race respectively.

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Healthy adult women did not present with central stimulation of appetite or binge eating disorder in their first year after starting use of DMPA. This study reinforces the use of the contraceptive DPMA and the need for guidance related to living a healthy lifestyle for women who attribute the increase of body weight to the use of the method.

Portfolio selection of oil and gas assets is a fundamental subject of capital budgeting in the energy sector. Traditional methods of portfolio selection are index ranking, zero-one programming, and utility functions. However, none of these methods mentions the value of option timing when the firm is selecting the desired combination of projects. This paper compares results of portfolio selection of non-developed reserves using both traditional approaches and option timing. Key Words: real options, portfolio management, uncertainty, timing. Introduction Oil and gas companies have the difficult task of portfolio selection from a large number of competing exploration and production projects for immediate or future operation under limited amount of investments. Typically, capital budgeting refers to allocation of resources among projects for which there are not well-established markets and that requires discrete lump of cash. Differently, the term portfolio selection is more devoted to a set of financial assets that are easily traded and divisible. The principles and fundaments of portfolio selection can be used to compare strategies of investments, so that firms get maximum returns. Usually there are more available opportunities than capital, so that the firm's manager may use economic indicators as an efficient way of capital allocation in constructing portfolios. These indicators include net present value (NPV), internal rate of return (IRR) and period of payback (PPB), among others. The problem of capital budgeting arises when a firm has several proposed competing projects with different scale, cash requirements, and benefits. For example, even if all projects gives positive benefits, they can't be selected because of budget limitation. In such circumstances, the manager needs to use a mixture of art and scientific tools in order to find a vector of assets whose associated cash stream produces the maximum worth for shareholders. There are many challenges in implementing oil and gas portfolios. In particular, the risk and return of individual projects within the portfolio must be characterized in a consistent manner in order to achieve a minimum-risk and a maximum-return. Clearly, it is important to use economic evaluation techniques to characterize these risks and impacts on company performance and long-term value. Traditional methods based upon discounted cash flow (DCF) reported in the finance literature are always based upon static assumptions - no mention about the value of embodied managerial options. For the case of mutually exclusive projects as those to develop oil and gas reserves, DCF rule tends to favor those with higher NPV values but also may demand proportional investment. An attempt to enrich the decision-making is the use of hurdle rates but there is no clear theoretical trigger value to accept or reject opportunities. However, in practice many corporate managers overrule passive net present value (NPV) analysis by using intuition and executive judgment to take future managerial flexibility into assets values (Trigeorgis, 1993). Confirming this tendency, an empirical study carried out by Summers (1987) found that 94% of participant firm uses DCF at the same discount rate, independently of risk; 23% uses discount rate in excess of 19%. This behavior suggests that firm's portfolio selection is based on hurdle-rates and NPV rules, not accounting the embodied flexibilities such as that of postponement or anticipation, suspension, etc.