ETC_WTP_proceedings

8/7/2019 ETC_WTP_proceedings

1/23

MEASURING WILLINGNESS TO PAY FOR GREEN OPTIONS

Charisma Choudhury ab , Flavia Tsang a , Peter Burge a , Charlene Rohr a Rob Sheldon c aRAND Europe, bMassachusetts Institute of Technology, cAccent

1 INTRODUCTIONThe need for social change is being regarded as an essential pre-requisite for preventing climate change and ensuring environmental sustainability. Given thecurrent level of emissions and resource consumption, this requires a behaviouralshift towards sustainable and environmentally friendly options. Following theStern Review and the Intergovernmental Panel on Climate ChangesAssessment, it is generally believed that there is an increased awareness of environmental issues. But the critical question is does this awareness translateinto willingness to pay (WTP) for greener options?

This paper reviews research findings from seven recent studies in three differentsectors, all conducted in order to better understand customers WTP for serviceimprovements, including environmental improvements. Our analysis focuses onthree main issues: i) heterogeneity of the sample of population, (ii) packagingeffects and (iii) diminishing marginal returns of utility. The paper is organised asfollows. First we present the background of this study, a general overview of thecase studies and the methodology applied for measuring WTP. A summary of theresults is then presented. This is followed by a discussion of our key findings onthe three main issues. Finally, we discuss our conclusions and directions of future research.

2 BACKGROUNDOver the years, many econometric approaches have been deployed to quantifyenvironmental benefits and measure peoples associated willingness to pay: themost effective ones being direct (close-ended) contingent valuations (DCV),ranking exercises (RE), hypothetical referendum approaches (HRA) and statedpreference choice exercises (CE). The CE technique is based on the notion thata good or service can be described by attributes and levels which respondentsare willing to trade-off between one another and differs from other approaches interms of the nature of the choice task. In the CE approach, respondents makechoices among hypothetical choice scenarios where multiple attributes can vary;in DCV, they are directly asked to state a specific value for a particular aspect of improvement (e.g. how much are you WTP for reducing 5% emissions) ; in RE,they are asked to rank the attributes of interest according to their preference; inHRA, they are told how much they would have to pay if the measure passed andare then asked to cast a simple "yes" or "no" vote (e.g.

would you be willing to

contribute D pounds to cover the cost of avoiding environmental damage X?) .CE experiments offer some important advantages over the other methods,principally the ability to estimate values for attributes of a good, including itsenvironmental characteristics and the trade-offs among multiple attributes of


2/23

interest (see Hanley et al. 1998 for a critical comparison). However, as in other stated preference methods, the obtained WTP values are sensitive to details of the survey instrument used and are vulnerable to upward bias (Arrow et al.1993).

Review of literature on previous WTP studies related to environment relatedoptions revealed interesting findings, the key ones being as follows:

Environmental attributes in which self-interest is unimportant are unlikely tobe appropriately valued when mixed in a trade-off with attributes in whichthere is strong self-interest, unless noticeable gains in self-interestaccompany desirable levels of attributes defining environmental impacts(Daniels and Hensher 2000).

There is substantial heterogeneity in respondent preferences (Layton andBrown 2000, Morey and Rossman 2003, Arana and Leon 2005 ).

Respondents often derive moral satisfaction or a warm glow from the act of giving per se and overstate their WTP (Kahneman and J. Knetsch 1992,Arrow et al. 1993, Nunes 2003).

Voluntary or opt-in programs and non-voluntary programs result in differenceWTP for green options, the WTP being higher for voluntary programs(Borchers et al. 2007).

There are often significant differences in hypothetical and actual WTP(Duffield and Patterson 1991, Seip and Strand 1992, Arrow et al. 1993)though there are exceptions (Horowitz and McConell 2002, Carlsson andMartinsson 2004).

People are often willing to pay significantly more to correct problems causedby humans than by nature (the outrage effect) (Bulte et al. 2005).

Willingness to accept money for reductions in service levels (WTA) is usuallysubstantially higher than pay money for service improvements (WTP)(Horowitz and McConell 2002).

This paper is a review of a number of recent CE studies to address some of these issues. It draws on the findings of seven stated choice modelling studiescarried out by Accent and RAND Europe in various contexts, including one intransport, one in electricity distribution (which included data from thirteenelectricity distribution operators) and five in water services. Brief overviews of the case studies are presented next.

3 CASE STUDIES

Transport

In the transport case study, consumer choices relating to car ownership and useunder an emissions-based charging system have been studied. The transport


3/23

case study surveyed 1,100 car travellers to central London and investigated thelikely traveller response under various emissions-based charging schemes.Possible responses included (i) continuing to drive, using the existing vehicle, (ii)continuing to drive, using a less polluting vehicle available in the household, (iii)continuing to drive, purchasing a new vehicle that would be in a lower emissions

category, choosing to use public transport, or (iv) not travelling. With regard topurchasing new vehicles, respondents were asked to trade-off fuel efficiencyalongside car purchasing cost, speed, acceleration, car size and level of chargefor driving in to central London.

Electricity

The case study of the electricity sector was based on a large survey of 1,942respondents carried out on behalf of thirteen electricity distribution operators inthe UK. The aim of this study was to better understand consumers expectationsand quantify their WTP for improvements in electricity distribution services.Estimating customers WTP for environmental options was just one aspect of the

study. Environmental attributes, in this case replacing equipment with thoseusing less polluting fuels and undergrounding power lines for amenity reasons,were valued alongside other improvements, such as reduction in power cuts,reduction in short interruptions and timeliness of power restoration.

Water services

The case study of the water sector is based on five studies carried out on behalf different water services providers in the UK 1. The attributes and levels of improvement examined therefore vary slightly from study to study; however, theSP design, survey implementation, and modelling methodology were executed ina similar manner. The main objectives for these five water WTP studies were tobetter understand consumers priorities and to quantify their WTP for possibleimprovement in water and sewerage services. A number of environmentalattributes, including reduction in greenhouse gas emissions, reduction in river pollution, and increase in the use of renewables, are valued alongside a widerange of water and sewerage service attributes, including frequency of flooding(internally and externally) to hardness and colour of water. Precise descriptionsof the environmental attributes examined in these studies are listed in Table 1;descriptions of the water and sewerage services which were evaluated alongsideare shown in section 6 (Figures 8a to 8c).Table 1 summarises the environmental attributes examined in the water andelectricity sector case studies. We have examined different levels of improvement (and in some cases deterioration) for each of the attributes. For brevity, we have only presented the maximum improvement possible in the table.We have broadly categorized the environmental attributes into seven topics:reduction in greenhouse gas emissions, move to renewable energy sources,

1 The sample sizes of these five case studies are: 977 respondents for water company A, 991 for water company B, 600 for water company C, 1001 for water company D and 754 for water company E.


4/23

reduction of river pollution, improvement of low flow rivers, investment inresearching sustainability of aquifer supplies, investment in replacing habitats,and reducing visual intrusion.

Table 1: An overview of the environmental attributes examined in the utilitycase studies 2

Case Study Description

Reduction in greenhouse gas emissionsWater Company C WTP for 20% reduction in greenhouse gases produced

(by 2015)Water Company D WTP for 20% reduction in greenhouse gases from

operationsWater Company E WTP for 20% reduction in greenhouse gases from

operationsElectricity Distributors A to M WTP for replacing 10% of equipment and vehicles with

those using less polluting fuelsMove to renewable energyWater Company A WTP for moving from 0.6% of energy requirements from

renewables to 20% of energy requirements fromrenewables

Water Company B WTP for increasing renewable electricity generated fromequivalent of 40,000 to 100,000 homes

Reduction of river pollutionWater Company A WTP for moving from improving 17% to improving 37% of

rivers of rivers by reductions in discharges from plants andpipes

Water Company B WTP for change to river ecology due to pollution from 43%to 20% of length unable to sustain wildlife

Water Company D WTP for reduction in percentage of water returned torivers not capable of supporting a good environment for salmon, trout, plants and animals from 17% to 5%

Improvement of low flow riversWater Company B WTP for reducing low flow rivers from 16% to 5% of length

unable to sustain wildlifeInvestment in researching sustainability of aquifer suppliesWater Company C WTP for moving from investigating impact of water

extraction of aquifers from as required to a moreproactive investigation of all current and future

Investment in replacing habitatsWater Company C WTP for replacing and enhancing all habitats where an

area of land is removed by engineering works, comparedto level of minimum replacement

Reducing visual intrusionElectricity Distributors A to M Undergrounding of power lines for amenity reasons, from

1.5% per year to 5% per year

2 The attributes examined in the transport case study is not included in this overview as they arenot directly comparable with the water and electricity sector case studies.


5/23

4 METHODOLOGY

All case studies discussed in this paper have been undertaken using statedresponses from choice experiments. Each choice experiment consisted of multiple service alternatives comprised of a group of attributes presented at arange of levels and a corresponding cost value. In the transport case study, anextensive literature review was performed to identify the critical attributesassociated with choices in an emissions-based charging scenario. In the utilitycase studies, the attributes presented in the experiments were chosen based onfindings from a series of focus groups. The attributes and the associated levels tobe included thus varied slightly based on the context, local preferences and theorganisation involved.

For the utility case studies, there were far too many attributes to evaluate in detailin a single SP choice exercise, alongside cost. As a result, the attributes weredivided into a number of groups (two/three) which were evaluated in separatestated preference exercises. In all studies, the environment and sustainability

related attributes were presented in the same group to provide some coherenceto respondents as well as to allow us to capture any correlation that may exist inrespondents valuations of these attributes. Moreover, previous experience inconducting SP experiments indicated that respondents can sometimes overstatetheir WTP for environmental improvement, and we believe that this was likely tobe more pronounced if the environmental improvement measures were beingevaluated on their own. So other attributes were presented alongside theenvironmental attributes to help respondents make more realistic trade-offs.

The data from the simple (lower level) choice experiments allow us to estimatecustomers WTP for improvements in each of the service attributes. However,there is concern that the estimation of WTP from multiple experiments using asubset of the attributes can lead to an overstatement of the total WTP for all of the improvements; the packaging effect. Many theories exist to explain thiseffect including budgeting effects, non-linearities in cost, and halo effects (whererespondents assume that because one attribute is improving that there are other improvements in other dimensions, which can then lead to double-counting inaggregation) (e.g. Jones 1997 and Thorndike 1920). Either way, it is appropriatein studies where the total attribute list is split into a number of sub-groups to testwhether an aggregation effect can be observed. If such an effect is observedthen this must be controlled for in the final valuations. As a result an additionalexperiment was also designed to explore packaging effects, where all of theattributes were presented simultaneously. In this experiment it would have beentoo complicated for respondents to vary all of the attributes simultaneously, sothe task was simplified by presenting the attributes in blocks of two or threeattributes, and presenting the attributes within each of these blockssimultaneously at one of three levels (level 0 as now, level 1, and the top level),such that all of the attributes in the same block are either at the same level asnow or are at the highest level. This was explained to respondents in theintroduction to the experiment. An example of the packaging experiment isshown in Figure 1. Each respondent was presented with at least three


6/23

experiments, i.e. at least two lower level experiments and the packagingexperiment. In each case the designs were tested and refined through the use of a pilot survey.

Figure 1: Example choice screen of the packaging experiment from the

case study of water company BChoice 1

Customer contactSewer Flooding - InternalSewer Flooding - ExternalMetering

Leakage & BurstsInterruptions to supplyLow PressureHosepipe ban frequency

Discoloured Water Taste and SmellHardnessOdour & Flies

Change to river ecology due to pollutionLow flow rivers due to abstractionRenewable electricity generated

Supply Pipe Adoption

Cost(change to annual water bill before inflation)

Choice (tick preferred option)

16% of length40,000 homes

Repairs paid for by company,replacements by customer

Increase by 30

10% of customers12% of customers4,500 complaints

43% of length

Decrease by 30

1 in 100 calls150 out of 3.7 million

1,600 out of 3.7 million66% on meters

110 litres per day3,500 out of 3.7 million2,000 out of 3.7 million

1 in 100 years

5,000 complaints

20% of length5% of length

100,000 homesRepairs and replacements

paid for by company

1,000 complaints5% of customers8% of customers1,000 complaints

11,500 out of 3.7 million15,000 out of 3.7 million

1 in 10 years

1 in 100 calls150 out of 3.7 million

1,600 out of 3.7 million66% on meters

Alternative 1 Alternative 2

Which of the following options would you prefer?

160 litres per day

Respondents were also asked qualitative questions as part of the general surveyto qualify their understanding of the choice experiments. In all cases,respondents reported a good understanding of the choice tasks.

5 SUMMARY OF RESULTS

Contrary to Daniels and Hensher (2000) in the transport sector, we were able toestimate statistically significant WTP values, even when the environmentalattributes were mixed with other service attributes 3.

The only exception was the attribute fuel efficiency of the transport case study. Itis suggested that this attribute was considered less salient by respondents, whenconsidered against potentially more important attributes such as the cost of theemissions-related charge (which was directly related to the emissions category of the vehicle, and hence also fuel efficiency). It was not possible to estimate a

3 Throughout this paper, a statistically significant result means the estimator was accepted at95% confidence level.


7/23

statistically significant term for this attribute, despite respondents stating that theyfound fuel efficiency to be important in an attitudinal question asked in thesurvey. All other terms, however, were significantly identified. Moreover, weobserved that significant proportions of respondents stated that under anemissions-related charge they would change the vehicle that they would use for

driving in to London, and in many cases would purchase a more efficient vehicleto benefit from lower charges. Significant heterogeneity was observed amongdifferent social groups, which will be discussed in section 6.

In the electricity case study it was found that customers stated that they werewilling to pay quite substantial amounts for their electricity distribution operatorsto replace equipment and vehicles with those using less polluting fuels. In fact, a10% reduction in carbon emissions was valued most highly of all of the serviceattributes tested in the survey. The large number of respondents (1942respondents) of this study has also provided a very rich dataset for theexploration of heterogeneity among respondents, which we will discuss in section

6.The findings were supported by the water case studies as well where it wasfound that customers stated that they were willing to pay for renewable energysources, reduction of green house and other gases and prevention of pollution inparticular.

The ranges and means of WTP values are plotted in Figure 2 to 5. The top of theranges were the valuations of the highest earners, whereas the bottoms of theranges were the valuations of the lowest earners. The means were the averageWTP across the sample of the population. Because we are examining acrossseven independent studies, many of the attributes and levels are too differentamong the studies to be directly compared. The only attribute which is commonacross three case studies (water company C, D, E) is reducing 20% of greenhouse gases from operations. The value of this attribute across the threewater studies falls in a reasonably small range (between 1.28 and 3.99).

As seen in the other tables, there are a number of attributes which had a larger range of WTP values, e.g. replacing 10% of equipment and vehicles with thoseusing less polluting fuels (from electricity sector case study), and undergroundingof power lines for amenity reasons (also from the electricity sector case study).The wider ranges of these values can be explained by the greater heterogeneityin the preference of the respondents (which is discussed in more detail in section6).


8/23


9/23

Figure 4: Willingness to pay for reducing river pollution

2.35

13.43

3.51

1.48

0.00

1.382.00

4.63

1.62

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

Moving from an improvement of 17% in river quality to an

improvement of 37% by reducingdischarges from plants and pipes

(water company A)

Reducing river pollution fromhaving 43% of length unable to

sustain wildlife to 20%(water company B)

Reducing the amount of water returned to rivers which is notcapable of supporting a goodenvironment for salmon, trout,

plants and animals from 17% to 5%(water company D)

willingness to pay

Max WTP

Min WTP

Mean WTP

Legend

Figure 5: Willingness to pay for various environmental improvement

9.32

2.54 2.88

11.89

1.77 1.52 1.722.272.79 1.88 2.13

4.36

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

Reducing low flow riversfrom 16% to 5% of

length unable to sustainwildlife

(water company B)

Moving frominvestigating impact of

water extraction of aquifers from as

required to a moreproactive investigation

of all current and future(water company C)

Replace and enhanceall habitats where an

area of land is removedby engineering works,compared to level of

minimum replacement(water company C)

Undergrounding of power lines for amenityreasons, from 1.5% per

year to 5% per year (thirteen electricity

distribution operators)

Willingness to pay

Max WTP

Min WTP

Mean WTP

Legend


10/23

5 DISCUSSION

Our analysis focuses on three critical issues: i) heterogeneity of the samples of population, (ii) packaging effects and (iii) diminishing marginal returns of utility.

Heterogeneity

The different preferences and WTP of different social groups (e.g. income,gender, age, and education level) has been a key issue for choice modelling(Horowitz and McConell 2002, Sonnier et al. 2007) and environmental costbenefit analysis (Swallow et al. 1994, Hanley et al. 1998, Morey et al. 2003).

In the transport case study, significant heterogeneity in WTP and behaviouralresponse to emission based congestion charge has been observed. This wasreflected in the models where statistically different constants were estimated torepresent the inherent preference of different social groups to choose to drive (or purchase and drive) a vehicle within a given emissions class in to London or select an alternative for their journeys. Model estimation results showed that: all

else being equal, people of three socio-economic groups stated that they aremore willing to switch to public transport than others: (i) those without children,(ii) those with only one car (compared with those with 2+ cars), and (iii) thoseliving in Greater London. In terms of preference for new vehicles of the leastpolluting category, it was found that households with income more than 30K per year and those belonging to the age group 25-34 were more likely than the restof the population to state that they would consider choosing these greener options.

In the electricity case study, we observed that people in the highest incomegroup (household income over 60,000) and the lower middle class (SEG C1,e.g. supervisory or clerical and junior managerial, administrative or professional)were more ecologically conscious compared to the other groups. The highestearners in SEG C1 stated that they were willing to pay 34 more per year ontheir electricity bills for their electricity distribution operators to replace 10% of polluting equipment and vehicles (see Figure 6).


11/23

Figure 6: Heterogeneity in the valuation of carbon reduction (from theelectricity sector case study)

SEG C1

Not SEG C1

cost sensitivity0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

over

60K

34.0

19.2

50K to

60K

8.1

5.5

40K to

50K

7.8

5.3

30K to

40K

5.7

3.9

20K to

30K

5.5

3.7

10K to

20K

4.4

3.0

under

10K

3.8

2.6

unknown

4.7

3.2

absolute value of coefficient

SEG C1not SEG C1

Willingness to pay:

Note: (1) the WTP are adjusted for package effects by a factor of 0.52(2) the weighted average WTP for those with income over 60K is 22.9, as reported inFigure 2 of section 5.

It may be noted that we observed significantly different cost sensitivity for

differing income categories, whereby respondents from higher incomehouseholds are less sensitive to cost changes for service improvements. Thismeans that higher income respondents will have higher willingness to pay(because cost sensitivity is in the denominator of the calculation of willingness topay). Additionally, we observed that respondents from higher incomehouseholds placed a higher value on undergrounding power lines for amenityreasons, over and above the income effect. The trends of both of thesecomponents of willingness to pay are shown in Figure 7. Compounded by thedifference in cost sensitivity of different income groups and the range of valuesfor undergrounding we observe quite large variation in the resulting WTP (from1.6 to 11.9).


12/23

Figure 7: Heterogeneity of the valuation of undergrounding 5% of power lines per annum for amenity reasons (from the electricity sector casestudy)

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

over 60K

11.9

50K to60K

8.2

40K to50K

7.9

30K to40K

5.8

20K to30K

4.6

10K to20K

3.7

under 10K

2.3

unknown

1.6

absolute value of coefficient

household income:

WTP :

undergrounding coefficient

cost sensitivity

Note: (1) the WTP are adjusted for package effects by a factor of 0.52(2) the lower bound reported in Figure 5 of section 5 was 2.3 because the group withunknown income was excluded

Income was identified as a determinant of WTP in the water case studies as well.However, it does not necessarily reflect that the rich are greener. The differencesin WTP by income group in the water studies were primarily because of thedifferences in their cost sensitivity, not because of the differences in their preference for the green attributes. Across the case studies, we observed thatthe highest income group (with annual income over 100K) is 1.36 times to 3.10times less cost-sensitive than the lowest income group (those with annualincome under 10K (Table 4). This evidence suggests that the rich are generallywilling to pay more not only for green options, but for all sorts of options.


13/23

Table 2: Differences in cost sensitivity

Case study

lowestincomegroup

Highestincomegroup

ratio of their cost parameters

Water company A under 10K over 20K 1.59Water company B under 10K over 60K 2.81Water company C under 10K over 40K 1.67Water company D under 9.5K over 100K 2.54Water company E under 9.5K over 9.5K 1.36Electricity distribution operators A to M under 10K over 60K 3.10Transport under 10K over 10K 2.22

The observation that the rich are not necessarily greener is exemplified by theemissions-based charging case study, in which the higher income group wasmore willing to pay for the charge and continue to drive the most CO2 emittingvehicles (with CO2 emissions above 225g/km) into central London.

Market segmentation tests based on age, gender and occupation did not supportstatistically different coefficients related to green options among differentsegments in the samples examined within the case studies .

Overstatement

The issue of overstatement of WTP for green options has been investigated byprevious researchers (Nunes and Schokkaert 2003, Kahneman and Knetsch1992, Carlsson and Martinsson 2001, Jones P. 1993). This can either originatefrom the experimental design (valuating each green attribute on its own) or from

the warm-glow effect (moral satisfaction for choosing the ethically good option).As discussed previously in Section 4, the problem of overstating WTP as a resultof evaluating attributes individually can be controlled through the inclusion of package experiments. Figures 8a to 8c summarise our findings from the packageexperiments across a number of studies. In these figures, the packageadjustment factor is the ratio between the sum of the values of the individualattributes in the lower level experiments and the value of the sub-group obtainedfrom the package experiment. A small factor means a large adjustment, and thusa more overstated valuation.

Figures 8a to 8c show the package adjustment factor associated with the sub-group containing green attributes is never the smallest across all the subgroupswithin each case study. This suggests that although respondents tend tooverstate their valuation in general, they do not tend to overstate their valuationof the green attributes any more than other attributes. There is an exception withwater company D, but in this case the climate change attribute is in the samegroup as three other non-environment-related attributes. Furthermore, in thecase study of water company B, the adjustment factor associated with the green


14/23

attribute was larger than 1, meaning that the respondents understated their valuation in the lower level experiment.

In all of the studies described here, we have assigned the service attributes inthe first few experiments and the environmental attributes in the final experiment.

One may question whether the sequence of appearance has any effects on theadjustment required for the packages. As respondents may have become morefamiliar with SP exercises in later experiments, they may able to process theinformation presented more effectively in choosing their preferred options (Hessand Rose 2008). It is possible that less adjustment would be required for the later experiments for this reason. However, if this is true, we would observe asystematic decrease in the magnitude of adjustments in the later experiment ineach case study. The data in Figures 8a to 8c do not show a systematic patternwhich larger package adjustments are associated with later experiments. Theeffect of sequencing is thus not evident in our case studies.

It is important to note that carrying out a package experiments only means thatrespondents were encouraged to reconsider all the service improvements as awhole package and were given a second chance to reconsider their total WTP.Thus, applying package adjustment is useful for controlling any overstatementdue to budgeting effects, diminishing returns in utility, and halo effects. However,the WTP even after adjustment are still only a stated preference, so is stillsusceptible to the potential problem that peoples actual behaviour when facedwith a similar choice in a real-world situation may be different to that stated in asurvey.


15/23

Figure 8a: Summary of package adjustment (Water Company A and B)

0.00 0.20 0.40 0.60 0.80 1.00 1.20

Drinking water qualityWater pressure

Interruptions to supplyLeakage

Odour

External flooding of waste water Internal flooding of waste water

River water quality*Beach water quality*

Climate change*

Customer contactSewer flooding - internalSewer flooding - external

Metering

Leakage and burstsInterruptions to supply

Low pressureHosepipe ban frequency

Discoloured water Taste and smell

HardnessOdour and Flies

Change to river ecology due to pollution*Low flow rivers due to abstraction*Renewable electricity generated*

Supply pipe adoption

package adjustment factor Water Company A ...

Water Company B...

Experiment 1

Experiment 2

Experiment 3

Experiment 4

Experiment 1

Experiment 2

Experiment 3

Experiment 4

no ad j us t ment


16/23

Figure 8b: Summary of package adjustment (Water Company C and D)

0.00 0.20 0.40 0.60 0.80 1.00 1.20

Hosepipe bans/ non-essential use bans

Low pressure

Hardness of water Discoloured water

Opening hours

LeakageUnplanned interruptions

Greenhouse gasemissions*

Sustainability reductions*Replalce habitat*

Discoloured water Taste and odour of drinking

water Low pressureLoss of supply

Internal sewer floodingExternal swer flooding

Leakage

Climate change*

Reducing sewage litter Bathing water qualityRiver water quality*

package adjustment factor

Experiment 1

Experiment 2

Experiment 3

Experiment 4

Experiment 3

Experiment 2

Experiment 1

Water Company C...

Water Company D...

no ad j us t ment


17/23

Figure 8c: Summary of packaging adjustment (Water Company E andElectricity Distribution Operators A to M)

0.00 0.20 0.40 0.60 0.80 1.00 1.20

Discoloured water Taste and odour of drinking water

Low pressureLoss of supply

Hosepipe bansMetering

LeakageClimate change*

Frequency of power cuts over 3 minutesAverage duration of power cuts over 3 minutes

Number of short power interruptionsProvision of information

Restoration of supplyCompensation for restoration of supplyCompensation for multiple interruptions

Advanced notice for planned interruptiosn

Undergrounding of power lines for amenityreasons*

Network resilience to major stormsNetwork resilence to f looding

Reduction in carbon emission*

package adjustment factor

Experiment 1

Experiment 2

Experiment 3

Electricity distribution operators A to M...

Water Company E...

Experiment 4

Experiment 1

Experiment 2

Experiment 3

no ad j us t ment


18/23

Diminishing trend

Another issue explored in this paper is analysing whether the SP exercises onlycapture the attitude to prefer sustainable options or whether we observe trendsshowing linear/diminishing/increasing increase in WTP proportional to the levelsof improvement.

In the case studies analysed in this research, in general customers/users alwaysindicated preference for more environmentally friendly and sustainable serviceoptions. However in terms of diminishing trend, we had mixed findings.

For some of the variables in some of the case studies, we observed clear diminishing trend. For example, in water company A, customers clearly preferredalternatives with lower environmental impact represented by the percentage of energy used from renewable sources. However, comparison of models withlinear and non-linear WTP revealed that a linear approximation provided asignificant loss of model fit, as would be expected from Figure 9. In fact, the

piecewise-linear model shows that respondents placed a positive and significantvalue on moving from 0.6% from renewables to 10% from renewables, but thendid not place a statistically significant value on moving from 10% to 20% of energy coming from renewables. This would seem to suggest that customerswant water company A to do something, but are relatively indifferent to howmuch they do.

Figure 9: Diminishing sensitivity to shift to renewable energyWater Company A

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0 5 10 15 20 25

% from renewable sources

Utility

Some other variables that exhibited diminishing trends included improving theriver water quality (water company A), and reduction of carbon and greenhousegases (water company D, water company E and the thirteen electricitydistributors).


19/23

However, in one case (water company C) a linear function was sufficient toexplain the sensitivity to green house gas reduction (i.e. the hypothesis that WTPfor greenhouse gas reduction is non-linear was rejected); that is, no diminishingtrend was observed (Figure 10). Another such examples include improvingbeach water quality (water company A),

Figure 10: Linear sensitivity to greenhouse gas reduction

However, it should be noted that extent of linear or non-linear effects may alsodepend on the range explored and it may be the case that the range was notwide enough in case of the two exceptions where linear increases in WTP havebeen observed.

6 CONCLUSIONS

In this paper, we have presented a review of WTP for green options using SPchoice exercises conducted in contexts involving transport and utility services. Intransport, drivers choices relating to car ownership and use under an emissions-based charging system have been studied. Significant heterogeneity inbehavioural responses has been identified with substantial stated willingness toshift from currently revealed behaviour, particularly in terms of purchasing newlower-emitting vehicles. In utility sectors, the research has been conductedamong domestic customers of five water service providers and thirteen energysuppliers. The attributes and improvement levels evaluated in the exercises vary,depending on the context of the study. Examples of evaluated variables includereduction of carbon emissions and other greenhouse gases, sustainability of water extraction procedure, improvements in disposed waste water quality,replacement of habitats affected by service operations, use of renewable energysources and provision of advice on energy efficiency. The richness of the dataallowed us to explore the some of the methodological issues associated withusing SP choice exercises for quantifying environmental benefits. Main findingsinclude the following:

Contrary to Daniels and Henshers findings about the challenge of self-interest proximity (2000), we were able to estimate statistically significant

Greenhouse gas

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 5 10 15 20 25

Percentage of reduction

Utility

Water com an C

Percentage of GHG reduction


20/23

WTP values in our utility sector case studies, even when the environmentalattributes were mixed with other service attributes. However, we were notable to estimate statistically significant WTP values for fuel efficiency in our transport sector case study but as discussed in section 4, this may be due tothe design issues.

Income is a major determinant of WTP; however, the differences in WTP byincome group were primarily because of the differences in their costsensitivity, not because of significant differences in their preferences. Wefound no significant heterogeneity in WTP across people of different age,gender, and occupation.

Respondents tend to overstate their valuations of the attributes when askedabout these in isolation, but we did not observe higher overstatements for green attributes compared to those of other utility service attributes.

For most of the green options evaluated in our case studies, respondentsclearly prefer companies to pursue greener options but diminishing trends inWTP were observed in most case studies.

The findings from the case studies provided useful practical insights in measuringWTP for sustainable options in transport as well as other sectors. This is of particular importance given the limited availability of corresponding revealedpreference data for policy analyses. The results thus draw important implicationsfor research, marketing, and policy decisions.

ACKNOWLEDGEMENT

This material is based upon work supported by Accent and RAND Europesclients in various public sectors. Any opinions, findings and conclusions or recommendations expressed in this publication are those of the authors and donot necessarily reflect the views of these public sector clients.


21/23

BIBLIOGRAPHY

Araa J. and Leon C. (2005) Flexible mixture distribution modeling of dichotomous choice contingent valuation with heterogeneity, Journal of Environmental Economics and Management, v 50-1, pp. 170-188.

Arrow K., Solow R., Portney P., Learner, E. Radner R. and Schuman H. (1993)Report of the NOAA panel on contingent valuation, Federal Register 58:lO (Jan.15, 1993), pp. 4601-4614.

Bulte E., Gerking S., List J. and de Zeeuw A. (2005) The effect of varying thecauses of environmental problems on stated WTP values: evidence from a fieldstudy, Journal of Environmental Economics and Management, v 49, pp. 330-342.

Borchersa A., Dukea J. and Parsons G. (2007) Does willingness to pay for greenenergy differ by source?, Energy Policy, v 35, pp. 33273334.

Burge P., Munro C., Read P. and Heywood C. (2007) Investigating the likelybehavioural responses to alternative congestion charge schemes in London,Proceedings of the European Transport Conference, Noordwijkerhout.

Carlsson F. and Martinsson P. (2001) Do Hypothetical and Actual MarginalWillingness to Pay Differ in Choice Experiments? Application to the Valuation of the Environment, Journal of Environmental Economics and Management, v 41,pp. 1006-1138.

Dayton B, and Brown G. (2000), Heterogenous preferences regarding globalclimate change, The Review of Economics and Statistics, v 82(4), pp. 616-624

Daniels R and Hensher D (2000) Valuation of environmental impacts of transportation projects: The challenge of self-interest proximity, Journal of Transport Economics and Policy, v 34-2, pp 189-214.

Duffield J., and Patterson D. (1991), Field Testing Existence Values: An InstreamFlow Trust Fund for Montana Rivers, Paper presented at the annual meeting of the American Economic Association; New Orleans, January 1991.

Green D., Jacowitz K., McFadden D. and Kahneman D. (1998), Referendumcontingent valuation, anchoring, and willingness to pay for public goods,Resources and Energy Economics, v20-2, pp. 85-116.

Hanley N., Wright R. and Adamowicz (1998), Using Choice Experiments to Valuethe Environment: Design Issues, Current Experience and Future Prospects,Environmental and Resource Economics, Volume 11, Issue 3, pp. 413428.


22/23

Hess S. and Rose J (2008), Intrarespondent Taste Heterogeneity inInstantaneous Panel Surveys, Transportation Research Board Annual Meeting,Washington DC.

Horowitz J. and McConnell K. (2002), Journal of Environmental Economics and

Management, v 44, pp. 426-447.IPCC (2007) IPCC Fourth Assessment Report: Climate Change 2007.Intergovernmental Panel on Climate Change. Available athttp://www.ipcc.ch/ipccreports/assessments-reports.htm . Accessed on 08September 2008.

Jones P. (1997) Addressing the Packaging Problem in Stated PreferenceStudies, European Transport Forum, September 1997.

Kahneman D. and Knetsch, J. (1992) Valuing public goods: the purchase of

moral satisfaction, Journal of Environmental Economics and Management, v22,pp. 5770.

Kahenman D., Ritov I. and Schkade D. (1999) Economic Preferences or AttitudeExpressions? An Analysis of Dollar Responses to Public Issues, Journal of Riskand Uncertainty, v 19, pp. 203-235.

Morey E. and Rossmann K. (2003) Using Stated-Preference Questions toInvestigate Variations in Willingness to Pay for Preserving Marble Monuments:Classic heterogeneity, random parameter and mixture models, Journal of Cultural Economics, v 27-4, pp. 215-229.

Nunes P. A. and Schokkaert E. (2003) Identifying the warm glow effect incontingent valuation, Journal of Environmental Economics and Managementv 45-2, pp. 231-245.

Seip K. and Strand J. (1992) Willingness to Pay for Environmental Goods inNorway: A Contingent Valuation Study with Real Payment, Paper prepared for the SAF Center for Applied Research, Department of Economics, University of Oslo, pp. 26.

Stern, N. (2006) The Economics of Climate Change: The Stern Review,Cambridge: Cambridge University Press.

Swallow S., Weaver T., Opaluch J. and Michelman T. (1994) HeterogeneousPreferences and Aggregation in Environmental Policy Analysis: A Landfill SitingCase, American journal of agricultural economics, v 76-3, pp. 431-443.
http://www.ipcc.ch/ipccreports/assessments-reports.htmhttp://www.ipcc.ch/ipccreports/assessments-reports.htmhttp://www.ipcc.ch/ipccreports/assessments-reports.htm


23/23

Sonnier G., Ainslie A., Otter T. (2007) Heterogeneity distributions of willingness-to-pay in choice models, Quantitative Marketing and Economics, v 5-3, pp. 313-331.

Thorndike, E. L. (1920) A constant error on psychological rating, Journal of

Applied Psychology, IV, pp. 25-29.

Date post:	08-Apr-2018
Category:	Documents
Upload:	marcio-nunes
View:	214 times
Download:	0 times

ETC_WTP_proceedings

Documents