- 學位論文
應用實質選擇權方法於環保投資與環境政策管理之決策分析
Enhancement of Decision-making for Environmental Investment and Environmental Policy Management using Real Option Analysis
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摘要
政府的環境政策及企業因應環保之投資策略影響未來之環境品質及企業之永續發展至鉅。然而環境問題的不確定性，包括技術的與環境的，在數量上相較以前增加了許多，尤其因應地球暖化與能源環境政策的問題，使得企業經營的風險暴露程度升高。因此政府在制定各種環境管制政策或標準時，必需將未來環境的不確定性因素考慮在內，才不致造成企業對於進行環保投資的延遲，亦或過度的投資，而造成不經濟之結果。 傳統上無論政府的環境政策之制定方法或企業因應之環保投資策略決策方法，大多未能以量化之方法納入環境不確定性分析，造成決策需承擔未來較大的風險。經由文獻回顧顯示，實質選擇權分析(ROA)方法自1980年代開始，就逐漸被應用於評估天然資源開採及R&D等涉及高度不確定性的投資計畫，並自1990年代末期被應於許多環境議題相關之決策分析。本論文應用實質選擇權方法於四個能源環境相關之投資與策略分析。 首先，實質選擇權方法被應用於評估一個廢棄物資源化工廠的投資策略，由於本項投資面臨未來廢棄物處理服務費收入、回收產品出售價格、及處理成本等不確定性因素，因此以二項式實質選擇權法進行評價，並與淨現值法(NPV)比較。評析結果，在投資者同時擁有放棄及擴張選擇權之情況下，計畫現值與淨現值較NPV法分別增加了9.2%及52.4%，顯示管理彈性對計畫具有相當的策略性價值。進行敏感度分析的結果，亦顯示出影響計畫現值及投資報酬之主要因素。依據評價結果畫出的策略地圖，可供經理人在未來不同時間點上決策之參考依據。 第二個案例是評估一個使用水銀電解槽法生產鹼氯之工廠，在面臨環境成本的增加及汞污泥廢棄物所需承擔的環境風險下，應在何時轉換為離子薄膜法的清潔生產製程。分析結果顯示，由於目前的環境成本尚不高，且法規亦不夠嚴格，因此尚無足夠的誘因促使業者進行清潔製程的轉換。但是基於水銀法製程造成的歷久性環境污染問題，業者應從企業社會責任的觀點，加速製程的轉換。 第三個案例應用連續的隨機實質選擇權模型於企業因應CO2排放管制之決策。企業在因應地球暖化之溫室氣體排放管制時，可以選擇裝置節能減碳設備，或減少產量以降低CO2排放總量，或接受政府的罰款，亦或購買碳權。但是因為裝置節能減碳設備涉及巨大的資本支出，且為不可回復的，而碳排放權之價格有隨時間變動之不確定性，因此應用實質選擇權分析方法可以決定(1)應投資計畫價值之門檻值(critical value) V*(受CO2排放權之交易價格影響)及(2)應進行投資設置減碳設備之時點。 最後一個案例是分析電力業者在面臨國家清潔能源管制目標及未來電力需求與CO2排放權價格的不確定性下，如何採取最適的因應策略。由於清潔能源結構的調整涉及重大的資本支出及規劃興建期，因此策略的決定必需考慮前導期(lead time)。本研究發展出一個「改良式序列二項式複合實質選擇權評價模式」，可供業者應用於具有前導期的決策分析。研究結果亦發現，在二項樹(binomial lattice)的一些決策點上，其最適之清潔能源策略是與二項樹的發展路徑相依的，這是與標準的序列複合選擇權模型顯著的差異。此模型亦可加以一般化以應用於許多具有前導期的政府政策或資本投資評估上。 由本論文的實證研究結果顯示，相較於傳統的資本預算方法，實質選擇權分析法更能處理具有高度不確定性的決策問題，是值得政府在制定環境政策與企業評估因應策略時採用的重要工具。
並列摘要
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.
參考文獻
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