Valuation 9: Contingent Choice

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Valuation 9Contingent Choice

• Contingent Choice Modelling and its variants
• Some econometrics
• Application to green product choice

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Previously, we looked at

• Revealed and stated preference methods
• Revealed preferences methods (hedonic pricing,
  travel costs) have the advantage of being based
  in actual behaviour, but can only capture use
  value
• Stated preference methods (contingent valuation)
  do not have this restriction, but are entirely
  hypothetical

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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
  who much are you willing to pay, the question
  is which situation would you prefer
• Choice modelling comprises choice experiments,
  contingent ranking, contingent rating and paired
  comparisons
• Similar to conjoint analysis, apart from the
  interpretation of the results

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Choice Experiments

• Which of the following two schemes do you favour?
• Native woodland 500 ha 700 ha
• Heather moorland 1200 ha 0 ha
• Lowland hay meadow 200 ha 300 ha
• Additional tax 25 15
• I would prefer A B Neither

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Contingent Ranking

• Rank the alternative policy options
• Woodland 500 ha 100 ha 700 ha
• Moorland 1200 ha 600 ha 0 ha
• Meadow 200 ha 0 ha 300 ha
• Tax 25 5 15
• Your ranking 1 2 3
• Note that this does not correspond to typical
  market behaviour!

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Contingent Rating

• How strongly would you prefer the following?
• Native woodland 500 ha
• Heather moorland 1200 ha
• Lowland hay meadow 200 ha
• Additional tax 25
• 1 2 3 4 5 6 7 8 9 10
• Very low preference Very
  high preference
• Again, not common market behaviour

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Paired Comparisons

• Which of these do you prefer?
• Woodland 500 ha 700 ha
• Moorland 1200 ha 0 ha
• Meadow 200 ha 300 ha
• Tax 25 15
• 1 2 3 4 5 6 7 8 9 10
• Strongly prefer A
  Strongly prefer B

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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

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CM v CV

• 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

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Implementation

• Characterise the decision problem
• Select attributes and levels
• Develop questionnaire
• Design experiment
• Collect data
• Estimate model
• Apply model

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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 (and psychology)
• It start by saying that one would choose option 0
  if its utility is higher than option 1

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Econometrics -2

• One would choose option 0 if its utility is
  higher than option 1 U0 gt U1
• Utility consist of a structural and an
  ideosyncratic component Ui Xi?vi
• The vector X describes the attributes that
  influence utility
• The vector ? has the attribute weights
• The scalar v is the random component of utility
• P(U0 gt U1) P(X0?- X1?gt v0 v1)

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Econometrics -3

• P(U0 gt U1) P(X0?- X1?gt v0 v1)
• Under appropriate assumptions, this becomes p
  X0? / X0? X1?
• The model predicts the probability that option 0
  is chosen
• Choose ? such that ?(y-p)2 (for example) is
  minimal
• Above, we do logit and least squares, but we
  could also use other assumption on the
  distribution of v and other distance metrics

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Econometrics -4

• Above, we use 0-1 decisions, and use attributes
  of the choice only
• Adding attributes of the decision maker is
  trivial
• There may be more than two choices
• If ordered, relatively straightforward
• 0.0ltplt0.5 -gt 0 0.5ltplt1.0 -gt 1
• 0.0ltplt0.3 -gt 0 0.3ltplt0.7 -gt 1 0.7ltplt1.0 -gt 2
• If not, complicated P(U0gt U1) and P(U0gt U2) have
  to be evaluated separately this gets messy when
  there are many choices

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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

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Attributes

• Price and special on price
• Number of rolls in pack (2, 4, 6, 8)
• Number of ply (1, 2, 3)
• Number of sheets
• Softness, as claimed
• Colour
• Scent
• Type of paper (standard, recycled, unbleached)
• Brand this is not really an attribute, but a
  bundle of attributes has to be included because
  of habit

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Choices

• With 8 attributes, the number of combinations is
  quite astounding
• 128 types were created, using something like
  Latin Hypercube sampling
• 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

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Results

• The model predicts the probability of buying a
  product, given its characteristics, and the
  characteristics of the buyer (green, like scent,
  cheap, decor, clean, age)
• Positive Special, no. rolls, no. plys, white,
  coloured, unbleached and recycled
• Negative Price, off-white, standard, unbleached,
  scented
• Interactive effect between stated and actual
  greenness
• Green brands have negative dummies

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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, attributes
  and price unspecified)
• For greens, its 1.69, 0.39 for others

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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)

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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 and the preference for standard
  paper

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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

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RP v SP1 v SP2

• Price 0.36 (0.53) v 0.40 (0.02) v 0.48
  (0.02)
• Special 0.46 (0.02) v 0.18 (0.02) v 0.13
  (0.02)
• Roll 0.15 (0.03) v 0.23 (0.01) v
  0.29 (0.01)
• White 0.24 (0.06) v 0.11 (0.04) v 0.04
  (0.04)
• Standard 0.17 (0.14) v 0.07 (0.05) v 0.06
  (0.05)
• Unbleach 1.09 (0.15) v 0.12 (0.09) v 0.25
  (0.09)
• UB rec 0.13 (0.12) v 0.23 ( 0.04) v 0.27
  (0.04)
• Stated preferences deviate from revealed ones,
  even for standard products like toilet paper, and
  even for such innocent things as its colour