1. Valuation 7: Contingent Choice Modelling
Contingent choice modelling and its variants
Steps and design stages for choice modelling
Some econometrics
Application to green product choice

2. Last two weeks The contingent valuation method
History and welfare measures
Study design
Validity, reliability and biases
Application to non-use values including the Exxon Valdez oil spill
Embedding and warm-glow
The EU environmental liability directive

3. Contingent Choice
(Contingent) choice modelling is similar to contingent valuation in that it is a stated preference technique based on surveys
The main difference is that instead to asking „how much are you willing to pay“, the question is „which situation would you prefer“
The approach is based around the idea that any good can be described in terms of its attributes, or characteristics, and the levels that these take
It originates in the market research and transport literature and has only recently been applied to areas such as the environment

4. Contingent Choice (2) Delivers answers to questions such as
Which attributes are significant determinants of the value of non-market goods?
How are attributes ranked?
What is the value of changing more than one attribute?
Choice modelling comprises choice experiments, contingent ranking, contingent rating and paired comparisons
Similar to conjoint analysis, apart from the interpretation of the results

5. Choice Experiments
The “good” to value is wildlife habitat on farms, defined as habitat areas and cost to the taxpayer.
Which of the following two schemes do you favour? Each would have a cost to your household. Alternatively you might neither scheme: taxes would not rise, but no areas would be protected.
Choice A Choice B
Native woodland 500 ha 700 ha
Heather moorland ha 0 ha
Lowland hay meadow 200 ha 300 ha
Additional tax $25 $15
I would prefer: Choice A… Choice B… Neither…

6. Contingent Ranking
Rank the alternative policy options below according to your preferences, assigning 1 to the most preferred.
Choice A Choice B Choice C
Native woodland 500 ha 100 ha 700 ha
Heather moorland 1200 ha 600 ha 0 ha
Hay meadow 200 ha 0 ha 300 ha
Additional tax $25 $5 $15
Your ranking: 1… 2… 3…
Note that this does not correspond to typical market behaviour!

7. Contingent Rating
On the scale below, please show how strongly you would prefer the following policy option?
Characteristics Option 1
Native woodland ha
Heather moorland ha
Lowland hay meadow 200 ha
Additional tax $25
Very low preference Very high preference
Again, not common market behaviour!

8. Paired Comparisons
Which of the two policy options described below would you be most in favour of? Indicate your preferences using the scale below
Choice A Choice B
Native woodland 500 ha 700 ha
Heather moorland ha 0 ha
Lowland hay meadow ha 300 ha
Addition tax $25 $15
Strongly prefer A Strongly prefer B

9. Choice Modelling
Provided that „do nothing“ is included, choice experiments and contingent ranking can be used to estimate WTP or WTAC
If „do nothing“ is not included, the set of options may be infeasible for the interviewee, resulting in nonsensical results
Contingent rating does not yield WTP, as there is only one alternative
Pairwise comparison is like a CVM referendum, but with shades of grey that are difficult to interpret

10. Implementation Characterisation of the decision problem
Select attributes and levels
Experimental design
Choice sets
Develop questionnaire
Collect data
Estimate model
Apply model

11. Decision problem
The initial step is the identification of the economic and environmental problem
What is the geographic and temporal scope of the change?
Impact on single or multiple site
Possible spill-overs between changes
Instantaneously implemented
What type of values are associated with the change?
Who will benefit
Will passive use values be affected
If use values are affected, what is the behaviour that captures this value

12. Attributes and levels Identifying the relevant attributes
Have to be part of people’s preferences for the environmental change
Attributes can be impacted by policy/project/management option choice
A monetary cost should be one of the attributes, to allow the estimation of WTP
Attribute levels should be realistic
They should span the range over which we expect respondents to have preferences
They should be achievable

13. Experimental design Complete factorial design
Allows estimation of the full effects of the attributes
Often produces an impracticably large number of combinations to be evaluated
An experiment with 4 attributes each at 3 levels would lead to 3x3x3x3=81 (La) alternatives
Reduce the number of scenario combinations
Identify subsets of the possible combinations of attributes and levels that will “best” identify the attribute preferences
Orthogonality is a desirable property
Include interaction effects?

14. Fractional Factorial Design
Attribute levels for a hypothetical wetland management scheme
Fractional Factorial Design
Possible design suitable for four attributes each at three levels

15. Choice sets
The more familiar the subject the higher the number of choice tasks a respondent can be asked to perform
The fewer the number of attributes and levels, the higher the number of choice tasks that can be allotted
If there are too many attributes and/or levels
Reduce their number if possible
Group the attributes into subsets
If the design needs to be divided in separate blocks more interviews are needed

16. CM v CV Generalisation of the binary discrete choice CV study
Choice modelling allows for more nuanced distinctions – but this also implies that more situations need to be assessed, that the questionnaire gets longer, and the interviewee may tire
In choice modelling, money is less central (less protest votes), and preferences more
In choice modelling, the econometrics is considerably more complicated

17. Econometrics
Ordinary least squares assumes that variables are continuous
In choice modelling, the observations are discrete, often 0-1
How to interpret such data?
Techniques are known as random utility, discrete choice, logit ...
Random utility is the most common name in economics
It start by saying that one would choose option 0 if its utility is higher than option 1

18. Econometrics (2)
One would choose option 0 if its utility is higher than option 1: U0 > U1
Utility consist of a determinisitc and a stochastic component U = Xb+v
The vector X describes the attributes that influence utility
The b reflects the impact of changes in X
The v is the random component of utility
Prob(U0 > U1) = Prob(X0b0+ v0 > X1b1 +v1) = Prob(X0b0- X1b1> v1 –v0)
The model predicts the probability that option 0 is chosen
Above, we do logit, but we could also use other assumption on the distribution of v and other distance metrics

19. Example: Green product choice
Product: Toilet paper; advantages: widely used; many varieties, some green, some not; close to reality
Canberra, 1 supermarket, year unknown
Three focus groups as a preparation; to find out important attributes, and to test questionnaire
1100 questionnaires, 2 week period, 40% response rate
Questionnaire made clear that this was not for profit

20. Attributes Price Special on price Number of rolls in pack (2, 4, 6, 8)
Number of ply and number of sheets as an indicator for strength and overall quality
Colour/pattern on paper
Type of paper (standard, unbleached but not recycled, both recycled and unbleached)
Brand; this is not really an attribute, but a bundle of attributes; has to be included because of habit

21. Choices
With 6 attributes, the number of combinations is quite astounding
An orthogonal fractional factorial design with 128 choice sets were created
Each interviewee was asked to choose between 8 types, so that the sample was split in 16 subsamples
Recall that only 440 surveys were returned
Sampling strategy was stratified for time of day only, based on expert guesses

22. Results
The model predicts the probability of buying a product, given its characteristics, and the characteristics of the buyer (green, dislike scent, cheap, decor, clean, age)
Positive: Special, no. rolls, no. plys, white, coloured, unbleached and recycled
Negative: Price, off-white, standard, unbleached and not recycled, scented
Interactive effect between stated and actual greenness increases the unobserved utility

23. Prices The model contains both price and environmental attributes
That implies that one can compute the increase in price that would correspond to a greener product
The average respondent is willing to pay $0.66 extra to pay for recycled and unbleached toilet paper (this is for the average pack, other factors held constant)
For greens, its $1.69, $0.39 for others

24. Yea-saying
Yea-saying is one of the biases in stated preference methods; it means that the interviewee gives the answer that she thinks the interviewer wants to hear
Harmony is preferred over conflict, and if harmony can be had by a little lie ...
Consumer shopping survey (Green products)
By completing this survey, you will assist our understanding of what people do when they go shopping (and how they go about choosing among products that claim to have different implications for the environment)

25. Prices (2)
First: The average respondent is willing to pay $0.66 (0.33) extra to pay for recycled and unbleached toilet paper; For greens, its $1.69, $0.39 for others
Second: The average respondent is willing to pay $0.61 extra to pay for recycled and unbleached toilet paper; for greens, its $1.57, $0.33 for others
These differences are not-significant, but that may be because of the data
The preference for green paper increased, as did the number of self-proclaimed greens; but so did price-sensitivity

26. Revealed preferences
Another nice thing about toilet paper is that it is actually sold in all the varieties tested in the survey
How do the results compare to actual sales data?
Only aggregate sales are available, so one has to redo the stated preference model for the average consumer
A formal test of differences between the models is tricky, because the buyers face different choices than do the interviewees, but the differences seem to be significant

27. Revealed vs stated preferences
Stated preferences deviate from revealed ones, even for standard products like toilet paper, and even for such innocent things as its colour
It appears that the choice model has generated significantly different taste parameters to those implicit in actual behaviour