Valuation of Biodiversity Benefits (OECD)

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present the same benefit estimates, but expressed in relative terms: as a percentage of the benefits ofthe same programme when estimated in isolation. These provide a clearer idea of the rising magnitudeof substitution effects as we go on further in the sequence, i.e.: as more and more programmes arealready included in the mix.Table 5.3 Point estimates of sequential values of programmes for the Pennine Dales ESA schemewhen valued in different valuation sequences aProgrammeInitial policy mix(0, 0, 0) (1, 0, 0) (0, 1, 0) (0, 0, 1) (1, 1, 0) (1, 0, 1) (0, 1, 1)P1 56.42(100.0)– 46.09(81.7)36.33(64.4)– – 26.00(46.1)P2 57.78(100.0)47.45(82.1)– 27.31(47.3)– 16.98(29.4)–P3 59.15(100.0)39.07(66.1)28.68(48.5)– 8.60(14.5)– –Note: a values in £ per household per year; values in parenthesis are expressed as percentage of the value of thecorresponding programme when valued in isolation.The next stage is to estimate the sequential costs of programmes, which was done elsewhere[Santos (1997)]. Then, sequential benefits for each programme (dependent on policy mix) are dividedby costs to provide sequential benefit/cost ratios. These are presented in Table 5.4, using upper-boundsocial cost estimates. IVS results (that is: using non-sequential, IVS, values for benefits), which do notaccount for substitution effects (and are, thus, biased), are presented in parentheses. The objective is toillustrate the sensitivity of results and policy recommendations to the IVS bias when selecting anoptimal policy mix.From Table 5.4, we conclude that all programmes pass the cost-benefit test whatever theevaluating sequence we adopt. Therefore, from a strict social-welfare perspective, the optimal mixshould include all programmes. Of course, this is not the case if available budget for policy is notsufficient for this mix. (The criterion to use in this case is described above).Table 5.4 Sequential benefit/cost ratios for conservation programmes in the Pennine Dales ESA,when evaluated in different valuation sequences(that is: with different initial policy mixes)ProgrammeInitial policy mix(0, 0, 0) (1, 0, 0) (0, 1, 0) (0, 0, 1) (1, 1, 0) (1, 0, 1) (0, 1, 1)P1 3.89(3.89) a – 4.35(5.32)P2 3.35(3.35)P3 113.08(113.08)3.55(4.32)2.51(3.90)– 1.58(3.34)74.69(113.08)54.83(113.08)– 16.44(113.08)Note: a ratios in parenthesis were estimated using IVS benefit estimates.– – 2.45(5.31)– 1.27(4.32)–– –For an example of an evaluating sequence, consider the sequence P3®P1®P2. Theappropriate ratio for P3 is 113.08, which obviously passes the benefit-cost test. The ratio for P1 when88
P3 is already in the mix is 2.51, still well over 1.00, and hence P1 also passes the cost-benefit test.Eventually, the ratio for P2 when P1 and P3 are already in the mix is 1.27. This is still over 1.00, butthe difference may not be statistically significant (in fact, this is actually the case). Hence, therecommendation to include P2 is subject to a non-trivial risk of error.However, using the IVS benefit-cost ratio (that is: 4.32), analysts would be very confident inrecommending the inclusion of P2 in this sequence. Here the IVS result does not change the averagepolicy recommendation (it would change if we used lower limits of 95% confidence intervals ratherthan averages for benefit estimation), but leads us to be overconfident about this recommendation.In other studied cases, IVS actually leads to recommendations of the wrong policy mix[Santos (1997)]. This wrong mix will be broader than the optimal one, if substitution betweenprogrammes prevails; it will be stricter if complementarity is the prevailing relationship betweenprogrammes. The practical conclusion is, therefore, to use, when possible, the modelling approachproposed in this paper for benefit estimation, which accounts for substitution effects, and hence is notprone to IVS bias. In cases where a model such as this cannot be estimated (e.g. where benefits are tobe transferred from previous studies), it would be wise to adjust biased estimates to correct for the IVSeffect. This leads us to strongly recommend the promotion of further research on substitution effectsunder the most diverse circumstances, using the proposed modelling approach, so that the properadjustment factors can be developed for a broad range of valuation settings.Other practical application problems exist with the proposed sequential approach to optimalpolicy mix, such as the path-dependency of the optimum. These problems are discussed and solutionsproposed in Santos (1998).89
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«ENVIRONMENTValuation ofBiodiversi
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ORGANISATION FOR ECONOMIC CO-OPERAT
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TABLE OF CONTENTSPART 1 ...........
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PART 4 ............................
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Why value biodiversity?There are th
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Figure 1.1 Total economic value: us
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from biodiversity at the local leve
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in the database and also for undert
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in the policy context. This is high
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Table 1.3 Policy Options for the Cl
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Box 1.2 Value of Turkey’s Forests
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of the most important implications
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Additionally, valuation does not ju
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value is the habitat, many differen
Page 31 and 32: are very modest. More recently, new
Page 33 and 34: Table 2.2 Estimates of the Medicina
Page 35 and 36: The importance of indirect use valu
Page 37 and 38: pharmaceutical use, although the li
Page 39 and 40: McAllister, D., (1991). Estimating
Page 41 and 42: Simpson, D and Craft, A.. (1996).
Page 43 and 44: practice, the overlap between these
Page 45 and 46: aimed at giving more precise quanti
Page 47 and 48: structural values. There are a numb
Page 49 and 50: Reid (forthcoming) discusses the po
Page 51 and 52: Ecotourism as a Way to Generate Loc
Page 53 and 54: endangered Indian rhino and other t
Page 55 and 56: ReferencesBann, C., and M. Clemens
Page 57 and 58: PART 261
Page 59 and 60: many European countries, CBA has a
Page 61 and 62: (1) Cost and time constraintsThe co
Page 63 and 64: activity day, there is greater vari
Page 65 and 66: added independent variable C s= cha
Page 67 and 68: error in valuing respiratory sympto
Page 69 and 70: ReferencesArrow, K.J., R. Solow, E.
Page 71 and 72: OECD (1995). The Economic Appraisal
Page 73 and 74: CHAPTER 5:by José Manuel LIMA E SA
Page 75 and 76: linkages usually lead to diverse co
Page 77 and 78: A discrete choice approach to quest
Page 79 and 80: Table 5.2 Model-based point estimat
Page 81: is potentially very large for multi
Page 85 and 86: PART 391
Page 87 and 88: measures of value. An appendix to t
Page 89 and 90: features (such as parks, beaches or
Page 91 and 92: included in cost-benefit analysis o
Page 93 and 94: A Discussion of Past Efforts to Dev
Page 95 and 96: Satellite AccountsIn addition to th
Page 97 and 98: which many people argue are associa
Page 99 and 100: approach to competing uses of water
Page 101 and 102: Figure 6.2 Trade-Off AnalysisEnviro
Page 103 and 104: However, the farmers need not bear
Page 105 and 106: Appendix 1: Theory and Application
Page 107 and 108: iwhere C is the income adjustment n
Page 109 and 110: complete. If there are more than on
Page 111 and 112: Horowitz, Joel. L. and Jordan. J. L
Page 113 and 114: CHAPTER 7:by Dennis M. KING and Lis
Page 115 and 116: Box 7.1 Definition of terms related
Page 117 and 118: Box 7.2 Categories of Ecosystem Ser
Page 119 and 120: Box 7.4 Dollar-based ecosystem valu
Page 121 and 122: Non-monetary indicators of ecosyste
Page 123 and 124: Figure 7.1 Effects of Wetland Locat
Page 125 and 126: description, and that the usefulnes
Page 127 and 128: 2) Service capacity sub-indexIndica
Page 129 and 130: wetlands, for example, results in F
Page 131 and 132: (1) Functional CapacityIndexFigure
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constituents of runoff can be predi
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Service(on or off site)Recreational
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Table 7.3 Service Risk Sub-index De
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Measuring Service Preference Weight
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Table 7.4 Illustration of Paired Co
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PART 4151
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Ecological foundations for biodiver
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Phenotic diversity is a measure bas
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Operationalisation of the biotic-ri
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ten attributes that could score a m
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The choice of the scale relates to
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Nature measurement methodIn 1995, t
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Table 8.4 Value orientations and en
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Table 8.5 Identification of monetar
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Table 8.6 Valuation studiesSingle s
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in waterway systems for nine impact
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to other contexts, conditions, loca
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ReferencesAkcakaya, H.R. (1994).
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de Groot, R.S. (1994). “Environme
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Mace, G. M. & S. N. Stuart. (1994).
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Turner, R.K., Perrings, C. and Folk
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John A. DixonJohn A. Dixon is Lead
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Robert O’NeillDr. O’Neill recei
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Steven StewartSteven Stewart is Ass
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OECD PUBLICATIONS, 2, rue André-Pa
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