Production and Hedging under Smooth Ambiguity Preferences

This paper examines the optimal production and hedging decisions of the competitive firm facing ambiguous price and background risk. Ambiguity is modeled by a second-order probability distribution that captures the firm's uncertainty about which of the subjective beliefs govern the price and background risk. Ambiguity preferences are modeled by the (second-order) expectation of a concave transformation of the (first-order) expected utility of profit conditional on each plausible subjective joint distribution of the price and background risk. When the background risk is additive in nature, we show that the separation theorem holds in that the firm's optimal production decision depends neither on the firm's attitude towards ambiguity nor on the incident of the underlying ambiguity. We derive necessary and sufficient conditions under which the firm's optimal forward position is completely characterized. When the background risk is multiplicative in nature, we derive sufficient conditions under which the firm reduces its optimal output level and opts for an under-hedge. Contrary to the conventional wisdom, we show that the behavior of the firm is affected by the introduction of ambiguity even when the firm is ambiguity neutral.postprin

The European Carbon Market in Action: Lessons from the First Trading Period Interim Report

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).The European Union Emissions Trading Scheme (EU ETS) is the largest greenhouse gas market ever established. The European Union is leading the world's first effort to mobilize market forces to tackle climate change. A precise analysis of the EU ETS's performance is essential to its success, as well as to that of future trading programs. The research program "The European Carbon Market in Action: Lessons from the First Trading Period," aims to provide such an analysis. It was launched at the end of 2006 by an international team led by Frank Convery, Christian De Perthuis and Denny Ellerman. This interim report presents the researchers' findings to date. It was prepared after the research program's second workshop, held in Washington DC in January 2008. The first workshop was held in Paris in April 2007. Two additional workshops will be held in Prague in June 2008 and in Paris in September 2008. The researchers' complete analysis will be published at the beginning of 2009.The research program “The European Carbon Market in Action: Lessons from the First Trading Period” has been made possible thanks to the support of: Doris Duke Charitable Foundation, BlueNext, EDF, Euronext, Orbeo, Suez, Total, Veolia

Decoupling farm policies: how does this affect production?

This paper studies the extent to which decoupled income support measures in agriculture can have production implications both at the extensive and intensive margins. We develop a theoretical framework that analyzes production responses of agricultural producers to apparently decoupled payments, by explicitly considering risk attitudes and uncertainty. We use farm-level data collected in Kansas to estimate the model. Technology and risk preference parameters are jointly estimated. Results show that though lump sum payments are not fully decoupled in the presence of risk and uncertainty, their effects on agricultural production are likely to be of a very small magnitude.Agricultural and Food Policy,

Stochastic utility-efficient programming of organic dairy farms

Opportunities to make sequential decisions and adjust activities as a season progresses and more information becomes available characterise the farm management process. In this paper, we present a discrete stochastic two-stage utility efficient programming model of organic dairy farms, which includes risk aversion in the decision maker’s objective function as well as both embedded risk (stochastic programming with recourse) and non-embedded risk (stochastic programming without recourse). Historical farm accountancy data and subjective judgements were combined to assess the nature of the uncertainty that affects the possible consequences of the decisions. The programming model was used within a stochastic dominance framework to examine optimal strategies in organic dairy systems in Norway

The Effects of Foreign Price Uncertainty on Australian Production and Trade

This paper provides a framework for the empirical analysis of the role of uncertain international prices for the Australian economy’s production sector and its international trade. We model the movement of traded goods prices via a bivariate GARCH model and embed this within an expected utility maximizing model of the production sector. We find that the empirical results are consistent with expected utility maximization and that the hypothesis of risk neutrality is soundly rejected. Estimates of the effects of changes in expected prices and volatility of traded goods prices upon production decisions and the return to capital are presented and discussed, as are the impacts of changes in output growth of Australia’s major trading partners. The overall conclusion is that price uncertainty matters for the Australian production sector.Price uncertainty, production under risk, expected utility maximization, international trade

A Forward Looking Version of the MIT Emissions Prediction and Policy Analysis (EPPA) Model

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).This paper documents a forward looking multi-regional general equilibrium model developed from the latest version of the recursive-dynamic MIT Emissions Prediction and Policy Analysis (EPPA) model. The model represents full inter-temporal optimization (perfect foresight), which makes it possible to better address economic and policy issues such as borrowing and banking of GHG allowances, efficiency implications of environmental tax recycling, endogenous depletion of fossil resources, international capital flows, and optimal emissions abatement paths among others. It was designed with the flexibility to represent different aggregations of countries and regions, different horizon lengths, as well as the ability to accommodate different assumptions about the economy, in terms of economic growth, foreign trade closure, labor leisure choice, taxes on primary factors, vintaging of capital and data calibration. The forward-looking dynamic model provides a complementary tool for policy analyses, to assess the robustness of results from the recursive EPPA model, and to illustrate important differences in results that are driven by the perfect foresight behavior. We present some applications of the model that include the reference case and its comparison with the recursive EPPA version, as well as some greenhouse gas mitigation cases where we explore economic impacts with and without inter-temporal trade of permits.This research was supported by the U.S Department of Energy, U.S. Environmental Protection Agency, U.S. National Science Foundation, U.S. National Aeronautics and Space Administration, U.S. National Oceanographic and Atmospheric Administration; and the Industry and Foundation Sponsors of the MIT Joint Program on the Science and Policy of Global Change: Alstom Power (USA), American Electric Power (USA), A.P. Møller-Maersk (Denmark), Cargill (USA), Chevron Corporation (USA), CONCAWE & EUROPIA (EU), DaimlerChrysler AG (USA), Duke Energy (USA), Electric Power Research Institute (USA), Electricité de France, Enel (Italy), Eni (Italy), Exelon Power (USA), ExxonMobil Corporation (USA), Ford Motor Company (USA), General Motors (USA), Iberdrola Generacion (Spain), J-Power (Japan), Merril Lynch (USA), Murphy Oil Corporation (USA), Norway Ministry of Petroleum and Energy, Oglethorpe Power Corporation (USA), RWE Power (Germany), Schlumberger (USA),Shell Petroleum (Netherlands/UK), Southern Company (USA), StatoilHydro (Norway), Tennessee Valley Authority (USA), Tokyo Electric Power Company (Japan), Total (France), G. Unger Vetlesen Foundation (USA)

Farmers' behavior and the provision of public goods: towards an analytical framework

The new CAP reform aims to stimulate the role of agriculture as provider of public goods. An analytical framework is developed to model farmers’ decision making and to gain insight into farmers’ behavior in response to a number of policy instruments. The framework integrates characteristics of farm, farmer, market, as well as the policy instruments. Theoretical analysis suggests that attitudes, off-farm employment opportunities, non-pecuniary benefits and expectations of future developments can play important roles in farmer’s decision making regarding the provision of public goods. Empirical research is needed to test the hypothesis

Vertical integration and firm boundaries : the evidence

Since Ronald H. Coase's (1937) seminal paper, a rich set of theories has been developed that deal with firm boundaries in vertical or input–output structures. In the last twenty-five years, empirical evidence that can shed light on those theories also has been accumulating. We review the findings of empirical studies that have addressed two main interrelated questions: First, what types of transactions are best brought within the firm and, second, what are the consequences of vertical integration decisions for economic outcomes such as prices, quantities, investment, and profits. Throughout, we highlight areas of potential cross-fertilization and promising areas for future work

Foresighted Demand Side Management

We consider a smart grid with an independent system operator (ISO), and distributed aggregators who have energy storage and purchase energy from the ISO to serve its customers. All the entities in the system are foresighted: each aggregator seeks to minimize its own long-term payments for energy purchase and operational costs of energy storage by deciding how much energy to buy from the ISO, and the ISO seeks to minimize the long-term total cost of the system (e.g. energy generation costs and the aggregators' costs) by dispatching the energy production among the generators. The decision making of the entities is complicated for two reasons. First, the information is decentralized: the ISO does not know the aggregators' states (i.e. their energy consumption requests from customers and the amount of energy in their storage), and each aggregator does not know the other aggregators' states or the ISO's state (i.e. the energy generation costs and the status of the transmission lines). Second, the coupling among the aggregators is unknown to them. Specifically, each aggregator's energy purchase affects the price, and hence the payments of the other aggregators. However, none of them knows how its decision influences the price because the price is determined by the ISO based on its state. We propose a design framework in which the ISO provides each aggregator with a conjectured future price, and each aggregator distributively minimizes its own long-term cost based on its conjectured price as well as its local information. The proposed framework can achieve the social optimum despite being decentralized and involving complex coupling among the various entities

Improving the quality of the industrial enterprise management based on the network-centric approach

The article examines the network-centric approach to the industrial enterprise management to improve the ef ciency and effectiveness in the implementation of production plans and maximize responsiveness to customers. A network-centric management means the decentralized enterprise group management. A group means a set of enterprise divisions, which should solve by joint efforts a certain case that occurs in the production process. The network-centric management involves more delegation of authority to the lower elements of the enterprise’s organizational structure. The industrial enterprise is considered as a large complex system (production system) functioning and controlled amidst various types of uncertainty: information support uncertainty and goal uncertainty or multicriteria uncertainty. The information support uncertainty occurs because the complex system functioning always takes place in the context of incomplete and fuzzy information. Goal uncertainty or multicriteria uncertainty caused by a great number of goalsestablished for the production system. The network-centric management task de nition by the production system is formulated. The authors offer a mathematical model for optimal planning of consumers’ orders production with the participation of the main enterprise divisions. The methods of formalization of various types of uncertainty in production planning tasks are considered on the basis of the application of the fuzzy sets theory. An enterprise command center is offered as an effective tool for making management decisions by divisions. The article demonstrates that decentralized group management methods can improve the ef ciency and effectiveness of the implementation of production plans through the self-organization mechanisms of enterprise divisions.The work has been prepared with the financial support from the Russian Ministry of Education and Science (Contract No. 02.G25.31.0068 of 23.05.2013 as part of the measure to implement Decision of the Russian Government No. 218)