VII Lecture
Shaping effect
Wrap up of the previous lecture
• Coherent arbitrariness of preferences is consistent
with downward sloping demand curves.
• Anchoring effect determines a highly arbitrary
foundational choice that restricts the range of
future choices.
• Metrical problem: do past choices influence
utility or do they bias the subjective estimation of
utility?
Introduction
• If the recursive causal relation between preferences and
choices affects utility rather than biasing its subjective
estimation then we would observe the emergence of market
specific patterns of behavior even without anchoring effect.
• Need of a direct test of shaping effect intended as an
affiliation of individuals’ evaluations to previous market
prices even if such affiliation is excluded by design.
• Evidence of shaping effect is crucial to distinguish between
discovered preferences hypothesis and preferences
construction hypothesis.
Experiment on shaping effect in
median price selling auctions
• Test of the predictive implications of DPH and PCH in
repeated median price selling auctions (Tufano 2009).
• Median price selling auction: participants submit a
form with a range of questions on bids expressing their
willingness to accept money for an auctioned good. The
bids are the lowest prices at which they are willing
trade.
• The median bid is the market price and the subjects
with bids lower than the market-price trade and get paid
accordingly.
Budget constraint
• Subjects receive a participation fee.
• In median price auction, participants express WTA
valuations through a form with prices ranging from a
minimum (slightly positive) to a maximum amount equal to
the participation fee. The progression is geometric-like.
• The budget constraint is the participation fee (endowment)
and it is equal for everyone.
• Subjects respective earnings are calculated at the end of the
auction session.
Example of the form
Predictive implications of DPH and PCH
for median price selling auctions
• Assumptions: 1) no correlation of individual values, 2) no
possibility of buying and selling back auctioned good.
• DPH-based prediction. The variance of the mean bids
within a single auction varies in accordance to the error
pattern (if symmetric or asymmetric), but the relation of the
mean bids between several auctions remains unchanged:
equality of mean bids across markets.
• PCH-based prediction. The mean bids variance reduces
within a single auction: bids converge towards the market
price. The mean bids variance might increase between
different auctions (Tufano 2009).
Experiment implementation.
Preliminary steps
• Subjects take part to six market periods of a median
price selling auction in which an unpleasant mixture of
vinegar and Lucozade is auctioned.
• Subjects get a participation fee of 3.00 $.
• Each subject tastes 30ml of the liquid before the
auction starts. This allows for reflective learning (Plott
1996).
• Subjects are randomly assigned to two markets.
Experiment implementation.
Controlling for anchoring effect
• After testing 30 ml the liquid each subject in the two groups is asked the
following question: would you be willing to drink again for a payment of
x?
• The value of x is the specific anchor manipulation and it can be Low (£
0.05), Medium (£ 0.25) and High (£ 1.25).
• We have two treatments. In T1, the participant majority in a market (i.e., (n
+ 1)/2) was exposed to the low anchor whereas the minority (i.e., (n - 1)/2)
to the medium anchor; in T2, the majority was exposed to the high anchor
whereas the minority to the medium anchor.
• The price feedbacks in the two treatments had to be different if market bids
exhibit anchoring effects by being biased toward the given anchor.
Experiment implementation.
The auction starts
• Subjects are asked to submit a form with a range of
questions on bids expressing their WTA money to drink 60
ml of the liquid.
• The prices range from a minimum of 0.01$ to a maximum
of 3.00$ (budget constraint). The progression is geometric
like with a maximum step of 0.20$.
• The experimenter orders the lowest WTA valuations and
selects the median price for each market.
• The subjects whose bids are lower than the market price
drink the liquid and get paid accordingly.
Implications
• Median price auctions are a strongly competitive markets
that need to clear.
• If subjects bid their true values, then market clearing price
obtains.
• This does not mean that all the subjects have to truthfully
bid: above median bidders have an incentive to lower their
asks, while below median bidders do not.
• Issue addressed: is the median market price the same across
auctions?
Methodological justification of the
interactive structure and auctioned good
INTERACTIVE STRUCTURE
AUCTIONED GOOD
• It
is
simple,
incentive
compatible and guarantees
interactive learning (Binmore
1999).
• It avoids field price censoring,
affiliated beliefs of field prices,
affiliated beliefs about the
commodity quality (Harrison
et al. 2004).
• Revealing true preferences is a
weakly dominant strategy.
• The price is a reliable basis to
infer the median subject’s
preferences.
• It avoids correlation of values
across subjects.
• It allows
choices.
for
independent
Method of analysis
• Statistical test based on the analysis of bids’ variances
within and between markets.
• Two-way ANOVA model.
• Null hypothesis: mean bids variance across markets is
convergent (corresponding to DPH predictive implications).
• Alternative hypothesis: the mean bid variance across
markets is divergent (corresponding to PCH predictive
implications).
Control for anchoring effect
• Use of data in period 1 to test anchoring effect in the short run such
to exclude anchoring erosion due market forces.
• If anchoring effect matters, then subjects’ bids should vary with the
anchor.
• Hypothesis: given the different treatments (T1 and T2) and the
corresponding different price feedbacks, we should observe a market
price biased toward the low (high) anchor in T1 (T2). Therefore,
price feedbacks had to be lower in T1 than in T2.
• The means of bids in Period 1 across treatments and anchors are not
different from each other.
Illustration
Data analysis in period 1
• Both DPH and PCH predict equality of market means
in period 1 as result of correct randomization.
• Correct randomization: the assignment to a given
market of individuals with certain preferences or tastes
can be equally probable. Therefore, on average, there
should be the same distribution of tastes and,
consequently, of bids across markets.
• No statistically relevant difference among means of
bids in Period 1 (F(31, 168) = 1.114; p = 0.324).
Data analysis in period 6
• DPH predicts no statistically significant
differences of the mean bids variance between
markets, while PCH predicts a statistically
significant differences of the mean bids variance
across market.
• It is observed a statistically significant difference
across market mean bids in period 6. (F(31, 168)
= 7.093; p = 0.000).
• Empirical support for PCH.
Cross periods results
• Variation in opposite direction of the sum of squares
between and within markets.
• Between markets variation: increase from 26.260 in Period
1 to 78.338 in Period 6.
• Within market variation: decrease from 127.751 in Period 1
to 59.851 Period 6.
• The total variation explained by the variation between
markets passes from an R 2 = 0.171 in Period 1 to an R 2 =
0.567 in Period 6.
Illustration
Note
•
In Fig. 1, the market means of bids with data from Periods 1 to 6 are plotted; that is, each
point of the set scattered in Fig. 1 represents the mean of bids for a given market in Period 1,
in Period 2, and so on through Period 6. Of course, if two means are identical, only one
marker is displayed; alternatively, if two means differ only a little, two markers with some
overlap are shown. Hence, Fig. 1 clearly reports an increase of the variance of market means
across periods. This is a qualitative indication of market specific patterns and, consequently,
of shaping.
Implication for anomalies erosion in
repeated markets
• The erosion of anomalies provides empirical evidence that is
convergent with theoretical predictions.
• However this evidence is not univocal and we have showed a
divergent empirical evidence in repeated markets.
• The erosion of anomalies might be a support for some theoretical
predictions (i.e. reduction of the mean bids variance within a
market) but not necessarily a support of discovered preferences
hypothesis (i.e. reduction of the mean bids variance between
markets).
• It follows that PCH might account for this conflicting evidence.
Implications for metrical problem
• The experiment provides a distinction between
anchoring (bias) and shaping effect.
• The repetition of market interactions shapes
our preferences (hedonic utility).
• This possibility can be explained by PCH.
Is this the end of the story?
• We can claim that there are substantial shaping
effects in determining the emergence of prices.
• This means that our preferences
constructed in market interactions.
can
be
• This does not imply that we are completely
devoid of any inborn preferences structure, which
is explanatory relevant for economic behavioral
regularities.
Conclusions
• Problem of distinguishing between shaping utility and biasing its
subjective estimation.
• The experimental test of shaping effect provides evidence of a
reduction of the mean bids variance within markets and an increase
of the mean bids variance between markets.
• This evidence can be explained as a shaping effect phenomenon.
• Shaping utility is a concrete possibility of repeated markets
interactions.
• Empirical evidence of shaping effect are supportive of PCH.