pay US$ 10 for wood B with no conservation <strong>of</strong> wood A. If the two woods are perfect substitutes, aprogramme jointly conserving woods A and B will also be valued at US$ 10. If conserving a singlewood costs US$ 8, then conserving either wood A or wood B in isolation is worthwhile, but jointlyconserving woods A and B is not. In cases where substitution is less severe, it may simply happen thatthe sum <strong>of</strong> benefits for each wood in isolation is larger than the joint benefit for the two woodstogether. If the two woods are perfect substitutes, the fact <strong>of</strong> one <strong>of</strong> them being conserved implies thatthere is no benefit at all from conserving the other. However, in general, if there is less-than-perfectsubstitution, we only know that the benefit <strong>of</strong> conserving one wood will depend on whether the otherwood is to be conserved.The same example could be extended to many other settings: we could ask whether people’sWTP for conserving the lynx depends on whether the tiger will also be conserved? or whether WTPfor conserving all threatened felines altogether is smaller than the sum <strong>of</strong> WTP for each speciesconsidered in isolation (i.e. if all others were to remain threatened)?Note that substitution effects between two services <strong>of</strong> biological resources has two sources[Santos (1998)]. First, both services may satisfy the same basic need; thus, they are substitutes inutility (as in the example <strong>of</strong> the two woods). Second, even if they are not substitutes in utility (as maybe the case with felines), at least they compete for the same budget. The WTP for one service isreduced after having paid for another service because income is now lower.There are two conclusions from the examples <strong>of</strong> substitution effects:1 the value for one service <strong>of</strong> biological resources is reduced if the level <strong>of</strong> a substituteservice is increased (the opposite occurs for services that are complements for eachother);2. the benefit <strong>of</strong> a policy providing two services that are substitutes for each other is smallerthan the sum <strong>of</strong> the benefits <strong>of</strong> providing each service in isolation.The first conclusion implies that, to value a change in one service level, the other servicesshould be held constant at levels that are known by the evaluator—they are a relevant part <strong>of</strong> thevaluation context. The second is related to a frequent bias when aggregating benefits across services:the independent valuation and summation (IVS) bias.The second conclusion also means that, for economics as well as for biology, the whole isdifferent from the sum <strong>of</strong> the parts. Therefore, assessing the welfare effects <strong>of</strong> multidimensionalchanges in biological resources is a task in which the complexity <strong>of</strong> value relationships compounds thecomplexity <strong>of</strong> the living world.Substitution effects in the valuation <strong>of</strong> multiple-service changes II: empirical evidence fromcontingent-valuation studiesWhat about the empirical evidence on the magnitude <strong>of</strong> substitution effects and the relatedaggregation (IVS) bias?Evidence discussed here comes from a contingent valuation (CV) study <strong>of</strong> the wildlife andlandscape-conservation benefits <strong>of</strong> the Pennine Dales Environmentally Sensitive Area (ESA) schemein the UK. This example was selected from a set <strong>of</strong> CV studies <strong>of</strong> substitution effects using similarmethods and achieving similar conclusions, which have been (or are still being) conducted in the UKand Portugal [see Santos (1997) and Santos (1998)].82
A discrete choice approach to questioning was adopted in this CV application. In a fieldsurvey <strong>of</strong> 422 visitors to the Pennine Dales ESA, respondents were asked to choose between (1) thecontinuance <strong>of</strong> a specified ESA scheme at a given tax-rise cost, and (2) giving up the scheme with notax increase.The valued ESA schemes represented different policy mixes across respondents.Hypothetical policy mixes were built by combining three basic programmes:· P1 - the conservation <strong>of</strong> existing stone walls and field barns;· P2 - the conservation <strong>of</strong> flower-rich hay meadows;· P3 - the conservation <strong>of</strong> remaining small broad-leaved woods.The first programme was perceived by most respondents as a purely aesthetic orcultural-landscape attribute. The second, as both an aesthetic attribute and an habitat for importantspecies <strong>of</strong> wild flowers and ground-nesting birds and the third programme was mostly perceived as animportant ecosystem and scarce wildlife habitat, and, secondarily, as an aesthetic landscape attribute.The three programmes were expected to be complements in utility, at least in aesthetic terms.In fact, as some <strong>of</strong> the most characteristic visual attributes <strong>of</strong> a cherished countryside area theseindividual attributes were expected to magnify the visual impact <strong>of</strong> each other. Hence, the aestheticimpact <strong>of</strong> the whole experience would be larger than the sum <strong>of</strong> the partial impacts <strong>of</strong> the attributes inisolation. Yet, meadows and woods, perceived as habitats for wildlife, could satisfy similar needs <strong>of</strong>visitors and could, thus, behave as substitutes in utility.Survey results were analysed using a model allowing for negative or positive substitutioneffects <strong>of</strong> any magnitude; this enabled researchers:1. to observe the sign <strong>of</strong> substitution effects (a negative sign means programmes aresubstitutes, that is they reduce the value <strong>of</strong> each other; a positive sign means programmesare complements, that is they increase the value <strong>of</strong> each other);2. to test for statistical significance <strong>of</strong> these signs; and3. to measure their magnitude, and hence that <strong>of</strong> the associated IVS bias.The estimated model is presented in Table 5.1. From this, we observe that the threeestimated parameters for substitution effects (that is: all programme-interactions P1*P2; P1*P3, andP2*P3) are negative, implying that all <strong>of</strong> the three programmes are substitutes in valuation. Thus, inspite <strong>of</strong> some expected complementarity in utility, only substitution in valuation was found. This caneasily be explained by the existence <strong>of</strong> a common budget for which WTP for all programmes compete,which, as shown above, is one <strong>of</strong> the two sources for substitution in valuation.Let us now look at the statistical significance and compared sizes <strong>of</strong> the several estimatedsubstitution effects. Note that only the parameter estimate for P2*P3 is significantly negative with a1% probability <strong>of</strong> error; while that for P1*P3 is also so with a 5% probability <strong>of</strong> error; and that forP1*P2 is not significantly different from zero even if we accept a 10% probability <strong>of</strong> error for the test.Thus, as expected:83
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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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- Page 39 and 40: McAllister, D., (1991). Estimating
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- Page 43 and 44: practice, the overlap between these
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- Page 53 and 54: endangered Indian rhino and other t
- Page 55 and 56: ReferencesBann, C., and M. Clemens
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- Page 59 and 60: many European countries, CBA has a
- Page 61 and 62: (1) Cost and time constraintsThe co
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- 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
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2) Service capacity sub-indexIndica
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wetlands, for example, results in F
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(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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