Enhancement of Decision-making for Environmental Investment and Environmental Policy Management using Real Option Analysis
Date Issued
2012
Date
2012
Author(s)
Cheng, Ching-Tsung
Abstract
Government environmental policy and enterprise environmental investment will significantly affect the environmental quality and the enterprise sustainability. The future environmental uncertainties, derived especially from climate change, have increased the enterprise risk exposure. These uncertainties should be considered in developing environmental policies and standards to prevent discouraging investment and/or causing overinvestment in environmental facility.
Owing to their static and nonflexible characteristics, traditional investment valuation methods such as net present value (NPV), internal rate of return (IRR), and so on suffer from flaws when making decisions under uncertainty. The discounted cash flow (DCF) appraisal does not account for the inherent strategic value of the project. The real options analysis (ROA) theory developed in the 1980s has been recognized as an alternative for investment under uncertainty. Theory of real options that underlies real assets is extended from the mathematical technique of financial options.
In this study, the real options analysis method is applied to four case studies related to environmental investment and/or policy decision. The first case concerns an investment of waste recovery plant that faces significant uncertainties of future waste treatment service fee, revenue of product sales, and operating costs. The analytical results show that the project value and net present value increased by 9.2% and 52.4%, respectively if the strategic value of the project is considered. Sensitivity analysis highlights the major factors that influences on the project net present value and return. The optimal decision resulting from the ROA is also sketched as a strategic roadmap that the decision maker can follow.
Increasing concerns over the release of mercury into the environment call for a cleaner production process in the chlor-alkali industry. Based on real option theory, the study develops an evaluation model for estimating the threshold and timing that trigger a process retrofit project under environmental uncertainty. After conducting numerical and sensitivity analyses on significant factors that affect corporate process retrofit behavior, the result shows that in the current environment and under current regulations, there are insufficient incentives to encourage firms to retrofit the mercury cell process, other than a significant increase in the environmental costs and/or strict enforcement of the current environmental policy. For a process that persistently emits toxic pollutants, it would be hoped that companies take a more socially responsible approach when considering the option of a process retrofit.
A continuous real option model developed by Dixit and Pindyck (1994) is applied to model the greenhouse gas reduction strategies for industries. Companies have options to invest in CO2 mitigation project, purchase carbon credits, reduce carbon emission by lowering production capacity, and suffer penalties for non-compliance. Considering the large irreversible capital investment in CO2 mitigation project and the uncertainties about future product and carbon credit market, the real options analysis will figure out the threshold project value and timing that will trigger the investment.
The energy industry, accounts for the largest portion of CO2 emissions, is facing the issue of compliance with the national clean energy policy. The methodology for evaluating the energy mix policy is crucial because of the characteristics of lead time embedded with the power generation facilities investment and the uncertainty of future electricity demand. In this study, a modified binomial model based on sequential compound options which may account for the lead time and uncertainty as a whole is established, and a numerical example on evaluating the optional strategies and the strategic value of the cleaner energy policy is also presented. It is found that the optimal decision at some nodes in the binomial tree is path dependent which is different from the standard sequential compound option model with lead time or time lag concept. The proposed modified binomial sequential compound real options model can be generalized and extensively applied to solve the general decision problems that deal with the long lead time of many government policies as well as capital intensive investments.
The empirical case studies show that real options analysis can well take account of uncertainties associated with environmental policy and corresponding strategies. The discrete-time model, compared to continuous-time model, is easier to the practitioners in government as well as in industry.
Subjects
environmental uncertainty
managerial flexibility
cleaner production
clear energy
real options
lead time
Type
thesis
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