An Investment Criterion Incorporating Real Options

Investment in infrastructure such as the information and communication technology sector requires large, substantial amounts, most of which are sunk or irreversible. Uncertainty of market demand, competition, costs and public policy complicates the investment decision process. This paper provides an investment decisionmaking criterion under uncertainty using (deferred) real options methodology to evaluate if an investment should be made immediately, cautiously, deferred (wait-and-watch), or foregone. A decision-making index d is developed, which is equal to the expectation of net present value (NPV) normalized by its standard deviation. Under a lognormal assumption of the distribution of NPV discounted by risk-free rate, we find the "break-even point" at which the NPV equals the real option value (ROV): d = D* = 0.276. Using the absolute value of D*, one can make sophisticated decisions considering opportunity losses. This new decision index, d, provides a criterion to make investment decisions to capture underlying uncertainty. When making a decision, a manager only has to observe three parameters: expectation of future cash flow, its uncertainty as measured by its standard deviation, and the magnitude of investment. We discuss examples using this criterion and show its value. The criterion is particularly useful when NPV lies near zero or uncertainty is large.Real Options, Decision, Investment, Economic Methodology; Statistical Decision Theory, Criteria for Decision-Making under Risk and Uncertainty.

Optimal Technology Choice and Investment Timing: A Stochastic Model of Industrial Cogeneration vs. Heat-Only Production

In this paper we develop an economic model that explains the decision-making problem under uncertainty of an industrial firm that wants to invest in a process technology. More specifically, the decision is between making an irreversible investment in a combined heat-and-power production (cogeneration) system, or to invest in a conventional heat-only generation system (steam boiler) and to purchase all electricity from the grid. In our model we include the main economic and technical variables of the investment decision process. We also account for the risk and uncertainty inherent in volatile energy prices that can greatly affect the valuation of the investment project. The dynamic stochastic model presented allows us to simultaneously determine the optimal technology choice and investment timing. We apply the theoretical model and illustrate our main findings with a numerical example that is based on realistic cost values for industrial oil- or gas-fired cogeneration and heat-only generation in Switzerland. We also briefly discuss expected effects of a CO2 tax on the investment decision.Cogeneration, Irreversible investment, Risk, Uncertainty, Real options

Three essays on institutional design for voluntary water conservation

2017 Fall.Includes bibliographical references.This dissertation is a compilation of three essays on institutional issues inherent in water conservation decision making by agricultural producers. Chapter 1 includes summaries of the three papers I intend to defend and introduces some ideas and concepts visited throughout the dissertation. Chapter 2 presents the results of a multidisciplinary study on managing selenium pollution in the Lower Arkansas River Basin in Southeastern Colorado titled, "Institutional Constraints on Cost-Effective Water Management: Selenium Contamination in Colorado's Lower Arkansas River Valley." The study presents the cost-effectiveness of various management practices to mitigate selenium pollution flows simulated over twenty years using regional scale groundwater and reactive solute transport models. Social institutions, such as rules on water conservation, serve to influence decision making and alter the economic feasibility of conservation efforts. The third chapter, "Uncertainty and Technology Adoption: Lessons from the Arkansas River Valley," extends the property rights institutional concerns introduced in chapter 2 and looks specifically to how use-based property rights influence decision making for conservation irrigation technology. When an irreversible investment is made under uncertainty, there is often a delay in investment that would not be seen under the traditional Marshallian framework for investment. This study advances the literature by exploring how property rights further exacerbate this option value hurdle which serves to further delay investment under uncertain water supplies. An empirical section explores how property rights are being applied in the Arkansas River Basin and discusses the implications for future conservation efforts. Finally, the last chapter, "An Experimental Approach to Resolving Uncertainty in Water Quality Trading Markets," uses experimental economics to explore the impacts of resolving uncertainty in water quality trading market design. This paper looks at whether non-point sources would take an opportunity to resolve environmental uncertainty if there is a water quality trading market in place. Additionally, it explores the interactions between a pollution market and voluntary abatement with and without a voluntary-threat regulation

Making, buying and concurrent sourcing: implications for operating leverage and stock beta

We present a real options model of a firm’s make-or-buy decision under demand uncertainty. “Making” is subject to decreasing returns to scale, fixed costs, and capital investment. “Buying” happens at a fixed price and requires no investment. Three distinct procurement regimes endogenously arise: buying, making, or concurrent sourcing for, respectively, low, intermediate, and high demand. Capital constraints encourage buying or concurrent sourcing. Operating leverage peaks when the firm switches between buying and making, and it is lowest (and negative) at the switch between making and concurrent sourcing. This non-monotonic pattern mirrors and drives the behavior of the firm’s beta.Lambrecht and Pawlina thank the ESRC (grant RES-062-23-0078) and Teixeira thanks Portuguese Foundation for Science and Technology (BD/12193/2003) for financial support

Investment decision-making in clean energy under uncertainties: A real options approach

International commitments on emission reduction and the deterioration of fossil energy resources have caused more research attention to clean energy production. Getting the optimal investment portfolio in infrastructure for energy supply and consumption is a minimum requirement to enable the transition towards a sustainable energy system. Due to their environmental benefits, advanced biofuel and clean power generation are expected to play an important role in the future in transportation sector and electricity sector, respectively. In this dissertation, a real options approach is adopted for valuating clean technology investment portfolios under uncertainty, exploring managerial insights, and examining policy implications. The dissertation consists three parts discussing problems on clean energy investment. Biofuel production investment, motivated by consumption volume mandates in revised Renewable Fuel Standard, is a long-term irreversible investment facing revenue uncertainty given volatile fuel market. Iowa, rich in agricultural residues like corn stover, is a major player in the fulfillment of the cellulosic biofuels mandate. In this first part, we aim to answer the question: Is now a good time for Iowa to start investing in cellulosic biofuels? Using a fast pyrolysis facility as an example, we present a real options approach for valuating the investment of a new technology for producing cellulosic biofuels subject to construction lead time and uncertain fuel price. We conduct a case study, in which the profitability of the project, optimal investment timing, and the impact of project lead time are investigated. The second part extended the previous work by incorporating supply risk and dual sourcing. While corn stover is an abundant source of feedstock for biofuels production in Iowa, there is a potential supply risk due to the following reasons: (1) lack of market; (2) low percentage of farm participation; and (3) yield uncertainty due to the changing weather conditions. The decision maker would consider investing in a land to grow his own feedstock, in addition to the investment of biofuel facility. Land option with the growing of dedicated energy crops has a value-adding effect when operating with the fast pyrolysis facility. And with dual sourcing, the impact from supply uncertainty could be mitigated. A real options approach is used to analyze the optimal investment timing and benefits of the dual sourcing. Risk-aversion has an unexpected effect on investment decision-making, which may cause the investment decision of the value-adding option can be very sensitive to the primary underlying uncertainty, and the immediate action towards land investment can no longer be described with a single fuel price threshold. Policy is deemed as one of the top decisive external factor that impacts the interest of a power producer. All energy projects are prone to policy risk, yet such eventualities are difficult to predict and therefore expensive to insure. In the third part of the study, we extend the uncertainty to the scope of government policy, in addition to considering the critical uncertainty of commodity prices. In this work, we want to examine the timing that an owner of a traditional coal-fired generator adopts in a clean technology when facing two realistic policy uncertainty cases: risk of repealing an existing policy, and risk of a policy change. The investment of a natural gas generator is considered in order to meet the load obligation while maximizing its expected long-run profit with regulated emission-related costs considered. The price uncertainties in electricity, natural gas, and carbon emission, together with policy uncertainty jointly affect profitability and decision-making of the clean technology adoption. A real options approach is applied to investigate the optimal investment decision. The producers are risk avoiding when facing uncertain future policy environment; and this reflects in delaying investment plan and creating a future investment plan that is stubborn to current carbon price. To a risk-neutral price-taking power producer, emission trading is a more effective instrument compared to carbon tax, and shifting from carbon tax to emission permits could more effectively inducing immediate investment in clean technology

Electricity Generation and Emissions Reduction Decisions under Policy Uncertainty: A General Equilibrium Analysis

The electric power sector, which accounts for approximately 40% of U.S. carbon dioxide emissions, will be a critical component of any policy the U.S. government pursues to confront climate change. In the context of uncertainty in future policy limiting emissions, society faces the following question: What should the electricity mix we build in the next decade look like? We can continue to focus on conventional generation or invest in low-carbon technologies. There is no obvious answer without explicitly considering the risks created by uncertainty. // This research investigates socially optimal near-term electricity investment decisions under uncertainty in future policy. It employs a novel framework that models decision-making under uncertainty with learning in an economy-wide setting that can measure social welfare impacts. Specifically, a computable general equilibrium (CGE) model of the U.S. is formulated as a two-stage stochastic dynamic program focused on decisions in the electric power sector. // In modeling decision-making under uncertainty, an optimal electricity investment hedging strategy is identified. Given the experimental design, the optimal hedging strategy reduces the expected policy costs by over 50% compared to a strategy derived using the expected value for the uncertain parameter; and by 12-400% compared to strategies developed under a perfect foresight or myopic framework. This research also shows that uncertainty has a cost, beyond the cost of meeting a policy. Results show that uncertainty about the future policy increases the expected cost of policy by over 45%. If political consensus can be reached and the climate science uncertainties resolved, setting clear, long-term policies can minimize expected policy costs. // Ultimately, this work demonstrates that near-term investments in low-carbon technologies should be greater than what would be justified to meet near-term goals alone. Near-term low-carbon investments can lower the expected cost of future policy by developing a less carbon-intensive electricity mix, spreading the burden of emissions reductions over time, and helping to overcome technology expansion rate constraints—all of which provide future flexibility in meeting a policy. The additional near-term cost of low-carbon investments is justified by the future flexibility that such investments create. The value of this flexibility is only explicitly considered in the context of decision-making under uncertainty.The authors gratefully acknowledge the financial support for this work provided by the U.S. Department of Energy, Office of Science under grants DE-PS02-09ER09-26, DE-FG02-94ER61937, DE-FG02-08ER64597, DE-FG02-93ER61677, DE-SC0003906, DE-SC0007114, XEU-0-9920-01; the U.S. Environmental Protection Agency under grants XA-83240101, PI-83412601-0, RD-83427901-0, XA-83505101-0, XA-83600001-1, and subcontract UTA12-000624; and a consortium of government, industrial and foundation sponsors

Electricity generation and emissions reduction decisions under uncertainty : a general equilibrium analysis

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 169-183).The electric power sector, which accounts for approximately 40% of U.S. carbon dioxide emissions, will be a critical component of any policy the U.S. government pursues to confront climate change. In the context of uncertainty in future policy limiting emissions and future technology costs, society faces the following question: What should the electricity mix we build in the next decade look like? We can continue to focus on conventional generation or invest in low-carbon technologies. There is no obvious answer without explicitly considering the risks created by uncertainty. This research investigates socially optimal near-term electricity investment decisions under uncertainty in future policy and technology costs. It employs a novel framework that models decision-making under uncertainty with learning in an economy-wide setting that can measure social welfare impacts. Specifically, a computable general equilibrium (CGE) model is formulated as a two-stage stochastic dynamic program focused on decisions in the electric power sector. The new model is applied to investigate a number of factors affecting optimal near-term electricity investments: (1) policy uncertainty, (2) expansion rate limits on low-carbon generation, (3) low-carbon technology cost uncertainty, (4) technological learning (i.e., near-term investment lowers the expected future technology cost), and (5) the inclusion of a safety valve in future policy which allows the emissions cap to be exceeded, but at a cost. In modeling decision-making under uncertainty, an optimal electricity investment hedging strategy is identified. Given the experimental design, the optimal hedging strategy reduces the expected policy costs by over 50% compared to a strategy derived using the expected value for the uncertain parameter; and by 12-400% compared to strategies developed under a perfect foresight or myopic framework. This research also shows that uncertainty has a cost, beyond the cost of meeting a policy. In the experimental design used here, uncertainty in the future policy increases the expected cost of policy by over 45%. If political consensus can be reached and the climate science uncertainties resolved, setting clear, long-term policies can minimize expected policy costs. In addition, this work contributes to the learning-by-doing literature by presenting a stochastic formulation of technological learning in which near-term investments in a technology affect the probability distribution of the future cost of that technology. Results using this formulation demonstrate that learning rates lower than those found in the literature can lead to significant additional near-term investment in low-carbon technology in order to lower the expected future cost of the technology in case a stringent policy is adopted.Ultimately, this dissertation demonstrates that near-term investments in low-carbon technologies should be greater than what would be justified to meet near-term goals alone. Near-term low-carbon investments can lower the expected cost of future policy by developing a less carbon-intensive electricity mix, spreading the burden of emissions reductions over time, helping to overcome technology expansion rate constraints, and reducing the expected future cost of low-carbon technologies-all of which provide future flexibility in meeting a policy. The additional near-term cost of low-carbon investments is justified by the future flexibility that such investments create. The value of this flexibility is only explicitly considered in the context of decision-making under uncertainty.by Jennifer Faye Morris.Ph.D

Measuring the capacity of a port system : a case study on a Southeast Asian port

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 172-177).As economies develop and trade routes change, investment in port infrastructure is essential to maintain the necessary capacity for an efficiently functioning port system and to meet expected demand for all types of cargo. However, these largescale, expensive investments in long-term infrastructure assets must be made despite a variety of future uncertainties that may potentially influence a port's performance. By using a Southeast Asian multi-purpose port as a case study, this thesis paper enhances the investment decision-making process for port infrastructure through the successful application and modification of two existing methodologies and the development of both an investment tool and a framework for selecting an optimal investment strategy to address capacity constraints within a port system. Applied at the case study port, the research evaluates a modification of an existing methodology for the measurement of port capacity, developed by Lagoudis and Rice, to identify bottlenecks within the port system. The research then examines a modification of an existing methodology, developed by de Neufville and Scholtes, for the evaluation of potential investment strategies under uncertainty. A simulation screening model is developed to forecast expected profitability under uncertainty for potential investment strategies, including strategies with flexible options, and to determine the optimal strategy. The thesis concludes with the presentation of a decision-making process for port infrastructure investment and recommended refinements to the existing methodologies.by Jason Bryan Salminen.M.Eng.in Logistic

Valuation of defer and relocation options in photovoltaic generation investments by a stochastic simulation-based method

Risk management is crucial when committing investments in electricity markets. Investment projects for the generation of electricity are capital-intensive, in large part irreversible and future performance is subject to high uncertainty. Fortunately, most power generation projects have strategic flexibility for handling uncertainty and for mitigating risks under unfavorable scenarios. Modern corporate finance recognizes Real Option analysis (ROA) as the correct way to value investment projects with these characteristics. Due to both, environmental concerns and escalation of fuel prices, electricity generation from renewable sources has grown dramatically worldwide over the last decade. Renewable investment projects share many of the features mentioned. As such, option valuation methods should be applied to estimate the monetary value of flexibility in renewable energy investments. This work presents an appropriate methodology for assessing the economic value of a photovoltaic power plant under uncertainties. ROA is applied to determine the value of delaying the investment decision while waiting for better market information that would reduce acquisition costs due to progress in solar technology. The flexibility of relocating the solar facility in the future upon the appearance of a more attractive site in terms of cost, network accessibility or regulatory policies is also valued. The problem of option valuation is solved through stochastic simulation combined with recursive approximate dynamic programming techniques. The methodology developed might be used by investors for more efficient decision-making and by regulatory agencies for designing adequate support policies that encourage investment in renewable energy generation.Fil: Pringles, Rolando Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Olsina, Fernando Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Penizzotto Bacha, Franco Victor. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentin