So many goods, so many anchorings

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So many goods, so many anchorings

• Szeged, 2006. April 14.
• Presentation by László Szepesi, PhD student at
  University of Pécs
• Based on a common work with György Komáromi

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Agenda

• Anchoring
• The experiment design
• Hypothesises
• Findings and discussion
• Methodological issues
• Going forward
• Questions

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Anchoring

• One of three first decision making heuristics
  identified
• People make estimates by starting from an
  initial value that is adjusted to yield the final
  answer (Tversky Kahneman, 1974)
• Examples
• Number of African countries in the UN
• Compare your driving skills (Kruger, 1999)
• Value goods (Ariely et al, 2003)

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Economic relevance

• Classical theory is based on the concept that
  economic agents are rational
• These agents are maximizing their utility
• This presupposes that they are able to value the
  different possibilities, i.e. that they can not
  only rank but also assign a value to the
  available choices
• But we know since Simon (1955) that humans are
  only quasi-rational
• Anchoring perturbs rational valuation process
• Hence importance of understanding how robust the
  effect is, what influences it

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Current issues with Anchoring

• Simmonson (2003) notes that the effect is not
  uniform. Introduces notion of compatibility
  between anchor and focal point of uncertainty
• Strack Mussweiler (1997) affirm that relevance
  of information contained in the anchor influences
  the strength of the effect
• Rubinstein (1999) reports that involving real
  money in the experiment design makes no difference

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The goal of our experiment

• Check whether
• anchoring works on different types of goods
• the anchoring effect would be different based on
  the quality of the goods themselves
• valuation is influenced by gender or commitment

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Experiment design

• Questionnaire filled by 129 students
• Asked about three goods bottle of wine, book
  coupon worth 1000 HUF and cappuccino voucher
• Two parts
• Would you buy the goods at XXX?
• What price would you be willing to pay?

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Anchor prices for the goods
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Formal Hypothesises

• Hypothesis 1 We expected the anchoring effect to
  be of different strength, with the wine showing
  the strongest anchor effect, the book coupon the
  weakest, and the cappuccino voucher an
  intermediate strength.
• Hypothesis 2 We expected the value put on the
  goods to be different between male and female
  respondents.
• Hypothesis 3 We expected the value put on the
  goods to be different between those respondents
  who agreed to buy the goods and those who were
  just playing.

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Average bids and relative standard deviations
Bids in HUF average AVG relative standard
deviation (RSDEV) standard deviation / average.
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Acceptance rate
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Findings for H1

• We found that anchor prices biased the average
  bids in our experiment
• The extent of the deviation, however, seems to be
  different for the three goods (different levels
  of relative standard deviation, RSD)
• It is suggested that the lower the probable level
  of knowledge of the market price, the higher the
  RSD
• RSD and acceptance rate differences can be
  explained by marketability (flexibility to use)
  of the goods
• Further control experiments needed

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Strength of anchoring

• Checked within the 8 groups the averages for Low
  and High conditions (expecting Low lt High
  everywhere)
• Books3 out of 8 where average High is not gt Low
• Cappuccino and Wineall cases show Low lt High
• Cappuccinolowest High is always gt highest Low
• Wine2 cases where lowest High lt highest Low

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Average bids of the 8 groups of subjects
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Frequency analysis

• Calculated the categorical relative frequencies
  of groups in order to assess the degree to which
  the pattern of Group A differs from the pattern
  of the Group B (e.g. Bids for Wine with condition
  High and with condition Low).
• Needed to filter out the distortion effect of
  asymmetric anchor prices
• Ranges 0Low/2, Low/2Low, Low (Low
  Medium)/2, (Low Medium)/2 Medium,Medium
  (High Medium)/2, High Medium/2 ?)

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Relative frequencies of bids in defined ranges

Book coupon
Wine
Cappuccino
Cappuccino II.
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Studies using K-S

• Analyzed the frequency data with Kolmogorov -
  Smirnov test in order to get the level at which
  the frequency patterns significantly differ.
• The K-S test, a type of "goodness of fit" tests
  is widely used in analysing frequency data,
  because it is distribution free, and suitable for
  small sample.

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Findings on H2 and H3

• Reject H2 since there are no statistically
  significant differences between male and female
  respondents valuations
• Reject H3 since there are no statistically
  significant differences between valuation made by
  respondents willing to buy and those not willing
  to buy

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Wine
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Cappuccino
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Book
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Methodological issues

• Non-symmetric anchor prices
• How to treat extreme answers noise or meaningful
  information?

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Going forward

• Control experiment in Veszprém with 47 students
• Investigate further the quality of proposed
  goods strong feminine good like eau de toilette
  vs. a strong masculine good?
• Extreme pricing, extreme anchors?

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Thank you for your attention!

• Questions and comments are most welcome