1、Designation: E 1369 072Standard Guide forSelecting Techniques for Treating Uncertainty and Risk inthe Economic Evaluation of Buildings and BuildingSystems1This standard is issued under the fixed designation E 1369; the number immediately following the designation indicates the year oforiginal adopti
2、on or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. Asuperscript epsilon () indicates an editorial change since the last revision or reapproval.1NOTEFootnotes updated editorially in August 2007.2NOTESection 2.2 and Footnote 5 were
3、 editorially corrected and Section 12 was editorially added in January 2009.1. Scope1.1 This guide covers techniques for treating uncertainty ininput values to an economic analysis of a building investmentproject. It also recommends techniques for evaluating the riskthat a project will have a less f
4、avorable economic outcome thanwhat is desired or expected.21.2 The techniques include breakeven analysis, sensitivityanalysis, risk-adjusted discounting, the mean-variance criterionand coefficient of variation, decision analysis, and simulation.1.3 The techniques can be used with economic methods th
5、atmeasure economic performance, such as life-cycle cost analy-sis, net benefits, the benefit-to-cost ratio, internal rate of return,and payback.2. Referenced Documents2.1 ASTM Standards:3E 631 Terminology of Building ConstructionsE 833 Terminology of Building EconomicsE 917 Practice for Measuring Li
6、fe-Cycle Costs of Buildingsand Building SystemsE 964 Practice for Measuring Benefit-to-Cost and Savings-to-Investment Ratios for Buildings and Building SystemsE 1057 Practice for Measuring Internal Rate of Return andAdjusted Internal Rate of Return for Investments in Build-ings and Building SystemsE
7、 1074 Practice for Measuring Net Benefits and Net Sav-ings for Investments in Buildings and Building SystemsE 1121 Practice for Measuring Payback for Investments inBuildings and Building SystemsE 1185 Guide for Selecting Economic Methods for Evalu-ating Investments in Buildings and Building Systems2
8、.2 Adjuncts:Discount Factor Tables, Adjunct to Practices E 917, E 964,E 1057, E 1074, and E 112143. Terminology3.1 DefinitionsFor definitions of terms used in this guide,refer to Terminologies E 631 and E 833.4. Summary of Guide4.1 This guide identifies related ASTM standards and ad-juncts. It descr
9、ibes circumstances when measuring uncertaintyand risk may be helpful in economic evaluations of buildinginvestments. This guide defines uncertainty, risk exposure, andrisk attitude. It presents nonprobabilistic and probabilistictechniques for measuring uncertainty and risk exposure. Thisguide descri
10、bes briefly each technique, gives the formula forcalculating a measure where appropriate, illustrates the tech-niques with a case example, and summarizes its advantagesand disadvantages.4.2 Since there is no best technique for measuring uncer-tainty and risk in every economic evaluation, this guidec
11、oncludes with a discussion of how to select the appropriatetechnique for a particular problem.4.3 This guide describes in detail how risk exposure can bemeasured by probability functions and distribution functions(see Annex A1). It also describes how risk attitude can beincorporated using utility th
12、eory and other approaches (seeAnnex A2).5. Significance and Use5.1 Investments in long-lived projects such as buildings arecharacterized by uncertainties regarding project life, operation1This guide is under the jurisdiction of ASTM Committee E06 on Performanceof Buildings and is the direct responsi
13、bility of Subcommittee E06.81 on BuildingEconomics.Current edition approved April 1, 2007. Published April 2007. Originallyapproved in 1990. Last previous edition approved in 2002 as E 1369 02.2For an extensive overview of techniques for treating risk and uncertainty, seeMarshall, Harold E.Technique
14、s for Treating Uncertainty and Risk in the Eco-nomic Evaluation of Building Investments, National Institute of Standards andTechnology, Special Publication 757, 1988.3For referenced ASTM standards, visit the ASTM website, www.astm.org, orcontact ASTM Customer Service at serviceastm.org. For Annual B
15、ook of ASTMStandards volume information, refer to the standards Document Summary page onthe ASTM website.4Available from ASTM International Headquarters. Order Adjunct No.ADJE091703.1Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United States.and
16、 maintenance costs, revenues, and other factors that affectproject economics. Since future values of these variable factorsare generally not known, it is difficult to make reliableeconomic evaluations.5.2 The traditional approach to project investment analysishas been to apply economic methods of pr
17、oject evaluation tobest-guess estimates of project input variables as if they werecertain estimates and then to present results in single-value,deterministic terms. When projects are evaluated withoutregard to uncertainty of inputs to the analysis, decision makersmay have insufficient information to
18、 measure and evaluate therisk of investing in a project having a different outcome fromwhat is expected.5.3 Risk analysis is the body of theory and practice that hasevolved to help decision makers assess their risk exposures andrisk attitudes so that the investment that is the best bet for themcan b
19、e selected.NOTE 1The decision maker is the individual or group of individualsresponsible for the investment decision. For example, the decision makermay be the chief executive officer or the board of directors.5.4 Uncertainty and risk are defined as follows. Uncertainty(or certainty) refers to a sta
20、te of knowledge about the variableinputs to an economic analysis. If the decision maker is unsureof input values, there is uncertainty. If the decision maker issure, there is certainty. Risk refers either to risk exposure orrisk attitude.5.4.1 Risk exposure is the probability of investing in aprojec
21、t that will have a less favorable economic outcome thanwhat is desired (the target) or is expected.5.4.2 Risk attitude, also called risk preference, is the will-ingness of a decision maker to take a chance or gamble on aninvestment of uncertain outcome. The implications of decisionmakers having diff
22、erent risk attitudes is that a given investmentof known risk exposure might be economically acceptable toan investor who is not particularly risk averse, but totallyunacceptable to another investor who is very risk averse.NOTE 2For completeness, this guide covers both risk averse and risktaking atti
23、tudes. Most investors, however, are likely to be risk averse. Theprinciples described herein apply both to the typical case where investorshave different degrees of risk aversion and to the atypical case where someinvestors are risk taking while others are risk averse.5.5 No single technique can be
24、labeled the best technique inevery situation for treating uncertainty, risk, or both. What isbest depends on the following: availability of data, availabilityof resources (time, money, expertise), computational aids (forexample, computer services), user understanding, ability tomeasure risk exposure
25、 and risk attitude, risk attitude ofdecision makers, level of risk exposure of the project, and sizeof the investment relative to the institutions portfolio.6. Procedures6.1 The recommended steps for carrying out an evaluationof uncertainty or risk are as follows:6.1.1 Determine appropriate economic
26、 measure(s) forevaluating the investment (see Guide E 1185).6.1.2 Identify objectives, alternatives, and constraints (seePractices E 917, E 964, E 1057, E 1074, and E 1121).6.1.3 Decide whether an uncertainty and risk evaluation isneeded, and, if so, choose the appropriate technique (seeSections 5,
27、7, 8, and 10).6.1.4 Compile data and establish assumptions for the evalu-ation.6.1.5 Determine risk attitude of the decision maker (seeSection 7 and Annex A2).6.1.6 Compute measures of worth5and associated risk (seeSections 7 and 8).6.1.7 Analyze results and make a decision (see Section 9).6.1.8 Doc
28、ument the evaluation (see Section 11).7. Techniques: Advantages and Disadvantages7.1 This guide considers in detail three nonprobabilistictechniques (breakeven analysis, sensitivity analysis, and risk-adjusted discounting) and three probabilistic techniques (mean-variance criterion and coefficient o
29、f variation, decision analy-sis, and simulation) for treating uncertainty and risk.This guidealso summarizes several additional techniques that are usedless frequently.7.2 Breakeven Analysis:7.2.1 When an uncertain variable is critical to the economicsuccess of a project, decision makers frequently
30、want to knowthe minimum or maximum value that variable can reach andstill have a breakeven project; that is, a project where benefits(savings) equal costs. For example, the breakeven value of aninput cost variable is the maximum amount one can afford topay for the input and still break even compared
31、 to benefitsearned. A breakeven value of an input benefit variable is theminimum amount the project can produce in that benefitcategory and still cover the projected costs of the project.NOTE 3Benefits and costs are treated throughout this guide on adiscounted cash-flow basis, taking into account ta
32、xes where appropriate.(See Practice E 917 for an explanation of discounted cash flows consid-ering taxes.)7.2.2 To perform a breakeven analysis, an equation isconstructed wherein the benefits are set equal to the costs for agiven investment project, the values of all inputs except thebreakeven varia
33、ble are specified, and the breakeven variable issolved algebraically.7.2.3 Suppose a decision maker is deciding whether or notto invest in a piece of energy conserving equipment for agovernment-owned building. The deviation of the formula forcomputing breakeven investment costs for the equipment is
34、asfollows:S 5 C (1)C 5 I 1 O or acombination might include optimistic values for some vari-ables in conjunction with pessimistic or expected values forothers. Examining different combinations is required if theuncertain variables are interrelated.7.3.3 The following illustration of sensitivity analy
35、sis treatsan accept/reject decision. Consider a decision on whether ornot to install a programmable time clock to control heating,ventilating, and air conditioning (HVAC) equipment in abuilding. The time clock reduces electricity consumption byturning off that part of the HVAC equipment that is not
36、neededduring hours when the building is unoccupied. Using thebenefit-to-cost ratio (BCR) as the economic method, the timeclock is acceptable on economic grounds if its BCR is greaterthan 1.0. The energy reduction benefits from the time clock,however, are uncertain.They are a function of three factor
37、s: theinitial price of energy, the rate of change in energy prices overthe life cycle of the time clock, and the number of kilowatthours saved. Assume that the initial price of energy and thenumber of kilowatt-hours saved are relatively certain, and thatthe sensitivity of the BCR is being tested wit
38、h respect to thefollowing three values of energy price change: a low rate ofenergy price escalation (slowly increasing benefits from energysavings); a moderate rate of escalation (moderately increasingbenefits); and a high rate of escalation (rapidly increasingbenefits). These three assumed values o
39、f energy price changemight correspond to our projections of pessimistic, expected,and optimistic values. Three BCR estimates result from repeat-ing the BCR computation for each of the three energy priceescalation rates. For example, BCRs of 0.8, 2.0, and 4.0 mightresult. Whereas a deterministic appr
40、oach might have generateda BCR estimate of 2.0, now it is apparent that the BCR couldbe significantly less than 2.0, and even less than 1.0. Thusaccepting the time clock could lead to an inefficient outcome.7.3.4 There are several advantages of sensitivity analysis.First, it shows how significant a
41、single input variable is indetermining project outcomes. Second, it recognizes the un-certainty associated with the input. Third, it gives informationabout the range of output variability. And fourth, it does all ofthese when there is little information, resources, or time to usemore sophisticated t
42、echniques.7.3.5 Disadvantages of sensitivity analysis in evaluatingrisk are that it gives no explicit probabilistic measure of riskexposure and it includes no explicit treatment of risk attitude.The findings of sensitivity analysis are ambiguous. How likelyis a pessimistic or expected or optimistic
43、value, for example,and how likely is the corresponding outcome value? Sensitivityanalysis can in fact be misleading if all pessimistic assumptionsor all optimistic assumptions are combined in calculatingeconomic measures. Such combinations of inputs are unlikelyin the real world.7.3.6 Sensitivity re
44、sults can be presented in text, tables, orgraphs. One type of graph that is useful in showing thesensitivity of project worth to a critical variable is illustrated inFig. 1. Net benefits (NB) for Projects A and B decrease as thediscount rate increases. The slopes of the functions show thatNB is more
45、 sensitive to discount rate changes for Project Athan for Project B, assuming other variables remain unchanged.These functions also help in making comparisons as to whichproject is more cost effective.At a discount rate below 7 %, forexample, Project A has the greater NB. At a rate above 7 %,Project
46、 B yields the greater NB. And at 7 %, the two projectsprovide identical NB.7.3.7 Note that the functions indicate the potential values ofNB if different values of the discount rate occur. If decisionmakers have some idea as to the likelihood of specific discountrates, the graph will help them evalua
47、te the NB implications forE13690723these two projects. The sensitivity graph in this sense contrib-utes to an implicit description of risk exposure. Yet the graphfails to provide a quantitative measure of the probability of anygiven NB occurring.7.3.8 Another special graph for sensitivity analysis t
48、hatpresents a snapshot of potential impacts of uncertain inputvariables on project outcomes is the spider diagram. The oneillustrated in Fig. 2 shows for a prospective commercialbuilding investment the sensitivity of the adjusted internal rateof return (AIRR) to three variables: operation, maintenan
49、ce,and replacement costs (OM project life (PL); and thereinvestment rate (RR). Each variable is represented by alabeled function that shows what AIRR values would resultfrom different values of the uncertain variable. For example,the downward-sloping OM that is, as future benefitsbecome more uncertain, the RADR technique requires raisingthe discount rate to make the project look less desirable. Forcost streams, AR1 and AR2 are adjusted downwards asperceived risk increases; that is, as future costs become moreuncertain, the correct application of the RADR techniquerequires
