Transcript An experimental analysis of the Tiebout’s model in a

Ph.D. in Political Science - Comparative and European Politics
Academic year 2012-2013
Part 3 Applied Experiments
EXPERIMENTAL METHODS IN POLITICAL AND SOCIAL SCIENCES
Alessandro Innocenti
[email protected]
OUTLINE
Part 1 Laboratory Methods
To provide a basic introduction to experimental methodology both from a theoretical and
an empirical point of view.
Part 2 Experimental Design
To learn how to design an experiment and to understand that experiments in political
sciences share many features from cognitive and experimental economics.
Part 3 Applied Experiments
To understand the differences between different kinds of experimental designs by
discussing weaknesses and strengths of some experimental papers and the
specificities of their designs.
1
Part 3 Applied Experiments
Informational
cascades and overconfident behavior
Innocenti, A., A. Rufa and J. Semmoloni (2010) "Overconfident behavior in
informational cascades: An eye-tracking study", Journal of Neuroscience,
Psychology, and Economics, 3, 74-82.
Voting
by ballots and by feet
Innocenti A. and C. Rapallini (2011) "Voting by Ballots and Feet in the Laboratory",
Giornale degli Economisti e Annali di Economia, 70, 3-24.
Travel
mode choice and transportation policy
Innocenti, A., P. Lattarulo and M.G. Pazienza (2013) "Car Stickiness: Heuristics
and Biases in Travel Choice", Transport Policy, 25, 153-168.
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Eye tracker movements provide quantitative
evidence on subjects’ visual attention and on
the relation between attentional patterns and
external stimulus.
Individuals perceive clearly what they look at
only in the central area of their visual field and
to observe wider areas they execute frequent
and very fast eye-movements.
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Gaze direction alternates between eye fixations
(longer than 200 ms), and saccades, which are
fast transitions between two consecutive
fixations.
Visual information is acquired during the
fixations but the visual field looked at depend
on saccades, which are so fast as not to be fully
controlled.
First fixations are determined automatically and
unconsciously.
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For reading, it has been shown that, as text
becomes conceptually more difficult, fixation
duration increases and saccade length decreases
⇓
longer fixations imply more cognitive effort.
For scene screening, participants get the gist of a
scene very early in the process of looking, even
from a single brief exposure
⇓
first fixations gives the essence of the scene and
the remainder is used to fill in details.
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Attention as brain’s “allocation of limited
processing resources to some stimuli or tasks at
the expense of others” (Kowler, et al, 1995)
For this reason, the retina has evolved a fovea,
which is a dense concentration of rod and cone
cells collecting most of the information extracted
from the visual scene.
This process is called foveation, the brain directs
its attention to different objects in a visual field.
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Brain allocates its attentional resources toward a
subset of the necessary information first, before
reallocating them to another subset.
Mere exposure effect (Zajonc 1980) - subjects
tend to like stimuli we are exposed to even when
the presentation is entirely subliminal.
Advertising - Repeated exposure to the brand and
its products is thought to increase viewer’s
preference towards them.
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When subjects allocate attention to decide what
they prefer, they exhibit a gaze cascade effect, i.e.
they look progressively more toward the item that
they are about to choose. (Shimojo et al 2003)
This evidence is interpreted that as the brain is
about to settle on a choice, it biases its gaze
toward the item eventually to be chosen in order to
“lock in” that preference.
Gaze direction would participate directly in the
preference formation processes and could also be
interpreted as preference at a subconscious level.
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The rationality assumption implies that a player will
look up all costlessly available information that
might affect his beliefs and update consequently
these beliefs.
Behavioral evidence contradicts this assumption
(Costa Gomes-Crawford 2006, Johnson et al.
2002, Laibson et al 2006, Camerer et al. 2009,
Chen et al 2009)
Subjects collect and process information by means
of heuristic procedures and rules of thumb to limit
cognitive effort.
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Subjects collect only a limited portion of the
available information.
Gaze direction often exhibit biases in scrutinizing
information which depend on subjects’ cognitive
attitude and past experience
Players’ types defined on actual choices and gaze
direction are correlated.
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Can gaze bias predict the orienting behavior for
decision processes that are not driven by individual
preferences, but related to an uncertain event to be
guessed on partial-information clues?
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Cognitive reference theory: dual process theory of
reasoning and rationality (System 1 vs. System 2)
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Experimental setting: informational cascades model of sequential decision for rational herding
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Since the 1970s a lot of experimental and
theoretical work has been devoted to describe
attention orienting as a dual processing activity
(Schneider and Shiffrin 1977, Cohen 1993,
Birnboim 2003)
Selective attention is defined as "control of
information processing so that a sensory input is
perceived or remembered better in one situation
than another according to the desires of the
subject" (Schneider and Shriffin 1977, p. 4)
This selection process operates according two
different patterns: controlled search and automatic
detection
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Controlled search is a serial process that uses
short-term memory capacity, is flexible, modifiable
and sequential
Automatic detection works in parallel, is
independent of attention, difficult to modify and
suppress once learned
Each subject adopts two types of cognitive
processes, named System 1 and System 2
(Stanovich and West 1999, Kahneman and
Frederick 2002)
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System 1 collects all the properties of automaticity
and heuristic processing as discussed by the
literature on bounded rationality
System 1 is fast, automatic, effortless, largely
unconscious, associative and difficult to control or
modify
The perceptual system and the intuitive operations
of System 1 generate non voluntary impressions of
the attributes of objects and thought
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System 2 encompasses the processes of analytic
intelligence, which have traditionally been studied
by information processing theorists
System 2 is slower, serial, effortful, deliberately
controlled, relatively flexible and potentially rulegoverned
In contrast with System 1, System 2 originates
judgments that are always explicit and intentional,
whether or not they are overtly expressed
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Both System 1 and System 2 are an evolutionary
product. People heterogeneity as the result of
individually specific patterns of interaction between
the two systems
If eye movements and attention shifts are tightly
tied, gaze direction could represent a signal of how
automatic and immediate reactions (giving right or
wrong information) to visual stimuli are modified
or sustained by more conscious and rational
processes of information collecting
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Informational cascade - model to describe and
explain herding and imitative behavior focusing on
the rational motivation for herding (Banerjee 1992,
Bikhchandani et al. 1992)
Key assumptions
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Other individuals’ action but not information is
publicly observable
private information is bounded in quality
agents have the same quality of private information
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Consider two restaurants named "A" and "B" located
next to one another
According to experts and food guides A is only
slightly better than B (i.e. the prior probabilities
are 51 percent for restaurant A being the better
and 49 percent for restaurant B being better)
People arrive at the restaurants in sequence,
observe the choices made by people before them
and must decide where to eat
Apart from knowing the prior probabilities, each of
these people also got a private signal which says
either that A is better or that B is better (of course
the signal could be wrong)
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Suppose that 99 of the 100 people have received
private signals that B is better, but the one person
whose signal favors A gets to choose first
Clearly, the first chooser will go to A. The second
chooser will now know that the first chooser had a
signal that favored A, while his or her own signal
favors B
Since the private signals are assumed to be of equal
quality, they cancel out, and the rational choice is to
decide by the prior probabilities and go to A
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The second person thus chooses A regardless of
her signal
Her choice therefore provides no new information
to the next person in line: the third person's
situation is thus exactly the same as that of the
second person, and she should make the same
choice and so on
Everyone ends up at restaurant A even if, given the
aggregate information, it is practically certain that
B is better (99 people over 100 have private signal
that is the case)
This takes to develop a “wrong” information
cascade, i.e. that is triggered by a small amount of
original information followed by imitations
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A is chosen although almost all people receive
private signal that B is better than A and there is no
clear prior evidence that A is better than B (51% vs.
49%)
If the second person had been someone who always
followed her own signal, the third person would
have known that the second person's signal had
favored B. The third person would then have chosen
B, and so everybody else
The second person's decision to ignore her own
information and imitate the first chooser inflicts a
negative externality on the rest of the population
lf she had used her own information, her decision
would have provided information to the rest of the
population, which would have encouraged them to
use their own information as well
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People have private information ("signals") and can
also observe public information
Public information is a history of all the actions (not
information) of predecessors
People are rational because they are assumed to
update their prior probabilities by using Bayes’ rule
to process the public and private information they
possess
An individual herds on the public belief when his
action is independent of his private signal
If all agents herd there is an informational cascade
that may be both “wrong” or “right”
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The theory of informational cascades assumes that
decision makers behave rationally in processing all
the available information
Experimental evidence points out how subjects
exhibit in the laboratory various cognitive biases in
deciding if entering or not a cascade:
One third of the subjects exhibit a tendency to rely
on the mere counting of signals (Anderson-Holt
1997)
Subjects’ overconfidence consistently explains the
deviations from Bayes’ rule (Huck-Oechssler 2000,
Nöth-Weber 2003, Spiwoks et al. 2008)
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Two events - Square and Circle - may occur with
equal probability.
For each session, 9 students were arranged in a prespecified order and asked to predict the state with a
monetary reward for a correct prediction
Each subject observes:
 an independent and private signal (Private Draw) which
has a 2/3 chance of indicating the correct event
 the predictions (Previous Choices) made by the
subjects choosing previously
?
2/3
2/3
1/3
1/3
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HP: rational subjects process information according to
Bayes’ rule and predict the event indicated as more
probable by the combination of private signals and
publicly known predictions
This implies that the choice of the first decision maker
reveals the private signal he has drawn
For example, if he chooses A, later decision makers
will infer that he has observed the signal a
[Pr(a|A)=2/3 > Pr(a|B)=1/3]
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If the second decision maker observes the same
private signal a he will predict accordingly.
If she receives the other signal b, he will assign a 50%
probability to the two events and both predictions will
be equally rational.
If the second decision maker chooses A, the third
decision maker will observe two previous choices of A.
If her private signal is b, it will be rational to ignore
this private information and to predict A as the
previous choosers (information cascade).
If (a,b) indicates the numbers of signals a and b received
or inferred, Bayes’ rule imposes:
[Pr(a,b|A) Pr(A)]
______________________________________________
Pr (A|a,b) =
[Pr(a,b|A) Pr(A) + Pr(a,b|B) Pr(B)]
In the example, the third decision maker observes two
signals a inferred and receives one signal b received
and the expression above gives:
(2/3)2(1/3)(1/2)
Pr (A|a,b) = ______________________________________________________= 2/3
(2/3)2(1/3)(1/2) + (1/3)2(2/3)(1/2)
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Being signals balanced [Pr(A|a) = Pr(B|b) = 2/3], the
difference between the number of signals a and b
inferred or observed determines the more probable
event.
In this simplified case, Bayes’ rule corresponds to a very
simple and intuitive counting heuristic, which is easily
computable by all subjects.
In the example above, the third decision maker has to
count two previous choices over his/her only one
private signal to determine her choice of A as rational
Session
Treatment
1
2
3
4
5
6
7
8
9
Total
(PD left - PC right)
(PD left - PC right)
(PD left - PC right)
(PC right - PD left)
(PC right - PD left)
(PC right - PD left)
(PD left - PC right)
(PD left - PC right)
(PD left - PC right)
Participants: 81
Participants (women + men)
9
9
9
9
9
9
9
9
9
81
(4 + 5)
(5 + 4)
(6 + 3)
(4 + 5)
(5 + 4)
(5 + 4)
(3 + 6)
(5 + 4)
(4 + 5)
(41+40)
Mean age: 22,4 Years
Private draw- PD (right)
First screen (5 seconds)
Previous choice-PC (left)
Initial screen (2 seconds)
First screen (5 seconds)
Second screen (5 seconds)
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First Fixations
Total number of fixations (Fixations = gazing at
region of interest –ROI- for at least 200 milliseconds)
Relative time spent fixating ROI (relative time = time
in a ROI divided by the total time spent on a task)
Sequence of last fixations

BAYESIAN - the equal probability of the two states
implies that the optimal Bayesian decision rule is to
predict the state which obtains the greatest number
of observed (Private draw) and inferred signal
(Previous choices).
If subjects choose differently from what implied by
Bayesian update:
 OVERCONFIDENT - if subject’s choice is equal to his
Private draw
 IRRATIONAL - if subject’s choice is not equal to his
Private draw
Order of choice
Bayesian
Overconfident
Irrational
1st
2nd
3rd
4th
5th
6th
7th
8th
9th
Total
Total (first chooser excluded)
6
9
5
6
7
6
6
6
6
57
51
0
0
2
2
1
2
3
3
3
16
16
3
0
2
1
1
1
0
0
0
8
5
TABLE 5. TOTAL ALLOCATION OF ATTENTION (PERCENTAGE OF TOTAL TIME)
PRIVATE
FORMER
NO FIXATION
TOTAL
DRAW (PD) CHOICES (FC)
FORMER CHOICES/
N. OF FORMER
CHOICES
BAYESIAN
OVERCONFIDENT
IRRATIONAL
TOTAL
26.9
10.4
47.1
25.6
63.0
86.4
39.9
65.3
10.1
3.2
13.0
9.1
100
100
100
100
22.4
19.5
22.6
21.8
TABLE 6. TOTAL ALLOCATION OF ATTENTION BY SCREEN SIDE (PERCENTAGE OF TOTAL TIME)
PRIVATE DRAW
FORMER CHOICES / N. OF FORMER
BAYESIAN
OVERCONFIDENT
IRRATIONAL
TOTAL
LEFT SIDE
19.5
9.2
52.0
RIGHT SIDE
29.5
10.9
12.7
TOTAL
26.9
10.4
47.1
25.6
LEFT SIDE
25.5
16.8
21.4
CHOICES
RIGHT SIDE
21.2
20.7
27.5
TOTAL
22.4
19.5
22.6
21.8
 Only irrational subjects were significantly more inclined to look at
private draw (47.1%) than at former choices (22.6%).
Private Draw
Previous Choices
Latency of
first fixations
N. of
first fixations
%
N. of
first fixations
%
Average
duration
Bayesian
0.306 sec
27 (13L+14R)
52.9
24 (13L+11R)
47.1
0.838 sec
Overconfident
0.412 sec
13 (6L+7R)
81.2
3 (1L+2R)
18.8
0.523 sec
Irrational
0.191 sec
3 (2L+1R)
60.0
2 (0L+2R)
40.0
0.835 sec
Total
0.321 sec
43 (21L+22R)
46.8
25 (14L+15R)
53.2
0.775 sec
•Overconfident subjects allocated their initial attention to private draw in 81% of the cases, and
exhibited a longer average reaction time (0.412 sec.) and a shorter average duration of first fixation
(0.523)
TABLE 4. FIRST FIXATION BY SCREEN SIDES (FIRST CHOOSERS EXCLUDED)
PRIVATE DRAW (PD)
LEFT
N.
TOT.
BAYESIAN
8
14
OVERCONFIDENT
5
IRRATIONAL
TOTAL
FORMER CHOICES (FC)
RIGHT
%
N. TOT.
LEFT
%
N. TOT.
57.1 20
30 66.6 16
9
55.6
9
15 60.0
1
1
100
2
3 66.6
14
24
58.3 31
RIGHT
%
N.
TOT.
%
38 42.1
6
16
37.5
2
6 33.3
1
3
33.3
2
4 50.0
0
3
0
48 64.6 21
48 43.7
8
24
33.3
 No statistically significant difference between left and right orientation of the screen
was detected and the pattern of first fixations across subjects’ types
0.7
Probabiliy of looking at the chosen signal
0.6
0.5
0.4
0.3
0.2
0.1
0
Time until decision (sec.)
No gaze cascade effect: observers gaze was not
increasingly directed towards the chosen signal
0,78
0,76
0,72
0,7
0,68
0,66
0,64
0,62
2,
00
1,
85
1,
70
1,
55
1,
40
1,
25
1,
10
0,
95
0,
80
0,
65
0,
50
0,
35
0,
20
0,
05
Bayesiani
0,74
0,2
0,18
0,16
0,14
0,12
0,1
0,08
0,06
0,04
0,02
0
Overconfident
Fig.2 Likelihood that subjects look at the chosen signal as a
function of time until decision (by subjects' types)
Bayes
Overconf
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Overconfident subjects allocate the first fixation
(initial attention) toward private draw and take more
time than others to decide if the private signal is on
the right or the left of the screen.
Bayesian subjects allocate their initial attention to
both kinds of information without exhibiting any
particular bias
No evidence of the gaze cascade effect
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In terms of the Dual Process theory, our findings
support the hypothesis that automatic detection, as
inferred from gaze direction, depends on cognitive
biases.
The heuristic and automatic functioning of System 1
orients attention so as to confirm rather than to
eventually correct these biases.
The controlled search attributable to System 2 does
not significantly differ across subject types.
“Highly accessible impressions produced by System
1 control judgments and preferences, unless
modified or overridden by the deliberate operations
of System 2.” (Kahneman and Frederick 2002, p. 53)
Gaze participates actively in the process of choice
under uncertainty
first fixation effect ⇒ orienting choice
gaze cascade effect ⇒ reinforcing choice
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Heuristic processes of System 1 select the aspect of
the task on which gaze direction is immediately
focused
Analytic processes of System 2 derive inferences
from the heuristically-formed representation
through subsequent visual inspection
This dual account of visual attention orienting may
explain the emergence of cognitive biases whenever
relevant information is neglected at the heuristic
stage.
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Aim- is to provide experimental evidence on the Tiebout
efficiency-enhancing property in a decentralized system of
public goods provision
Object - a test of the Tiebout model in order to assess if
decentralization and local sorting produces efficiency gains
Key finding – we show that the model fails because residents
are different, not only in their preferences on local public
goods, but also because voting and moving are not equally
shared.
48
Tiebout’s (1956) model shows that if a sufficient number
of local communities exists to accommodate different
types of preferences, individuals could move to that
community whose local governments best satisfies his
set of preferences (pattern of expenditures and taxes).
Quoting Oates (1969) “Tiebout’s world is one in which
the consumer “shops” among different communities
offering varying packages of local public services and
selects as a residence the community which offers the
tax-expenditure program best suited to his tastes”.
This is the so called voting by feet
if households are free to move, people effectively sort
themselves into groups that are homogeneous with
respect to their demands for local services.
Since 1956, there is a wealth of literature surrounding
the Tiebout hypothesis, both from an empirical and a
theoretical point of view.
Rodhe and Strumpf (American Economic Review, 2003)
argue that long–run trends in geographical segregation
are inconsistent with choice model where residential
choices depends solely on local public goods
More precisely they demonstrate that the secular decline
in the mobility costs is not matched with an increase in
the heterogeneity in local public policies
Some example of mobility costs historical data
-
CAR: in 1903 to drive a car cost 143,8 cents/mile
in 1998 dollars, while in 1998 54,9 cents;
TRAIN: a passenger mile cost 37,4 cents in 1895
and 13,4 cents in 1995;
AIR: a passenger mile cost 108 cents in 1929 vs.
13,7 cents in 1995;
3 minute of transcontinental call in January 1915
cost 20,70$ in current dollars, which was almost
314$ in 1998 dollars.
Data on a sample of US municipalities (18701990), all Boston-area municipalities (1870-1990)
and all US counties (1850-1990) show that
municipal per capita taxes, school district per
capita taxes, total spending, protection spending
etc. incomes and racial composition are now less
differentiate across local communities than in the
past.
They explain this result as follows
1. growing federal role in providing public
services
2. zoning policies are more and more popular
after the war, avoiding the poor-chasingthe-rich phenomenon
3. growing local government competition (to
have the same category of residents: the
richer !)
In our paper we test a fourth cause of the
phenomenon observed.
We show that the Tiebout model may fail not
only because residents have heterogeneous
preferences on local public goods, but also
because voting and moving are not equally
shared.
•
•
•
•
•
•
•
2 treatments x 3 sessions
10 rounds for each session
In each session 15 subjects (undergraduate
students) are randomly allocated in 5 communities
Each community is allowed to provide only one
public good
The four suits of cards (clubs, diamonds, hearts,
spades) represent different types of public goods
Playing cards randomly assigned to each subject
for the whole experiment
The number over the cards determines subject’s
preferences over public goods
The individual welfare given by public good provision is
the difference between individual benefit and individual
cost.
The individual benefit given by public good provision is
the minimum between the community provision level and
the sum of cards of that public good (suit) possessed.
B  minprovisionlevelof typei, sum of cards of typei
The individual cost is equal to the community production
cost, that is the quantity produced (Hp. constant and
unitary costs) divided by the number of community
members (Hp. community total cost is shared equally
among the members of the community).
Democracy treatment
Dictator treatment
In each of the 10 rounds
each community decides
by majority vote the type
and the amount of the
public good to produce
In each community there is
a subject (the dictator) who
decides before each of the
10 rounds the type and the
amount of the public good
to produce
All subjects can move or
The other community
members can only move or
not move and are informed
of the type and the amount
of goods produced by all
the communities before
deciding
not move and are informed
of the good produced by all
the communities in the
previous period
Session 2
Session 1
60.00
60.00
50.00
50.00
40.00
40.00
30.00
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Session 2
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
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Total welfare is higher in the democracy treatment
i.e. voting by feet increases efficiency if voting by
ballot is equally shared
Average cost per capita is higher in the dictator
treatment
In the democracy treatment cost per capita tends
to increase in the first part of the session, but
decreases after the 5th-6th rounds
Quantity produced does not statistically
differentiate across treatments
OLS -Welfare difference between 10th-1th round
VARIABLES
Nr of moving in 10 rounds
Nr. of Rounds in wich a person with an
opposite SC is meet
Nr. of Rounds in wich at least two people
with an opposite SC are meet
Moving/non moving decisions taken rightly
Community in which the individual move is
chosen rightly
Constant
Observations
R-squared
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Session 1
Democracy
Dictator
deltaW
deltaW
Session 2
Democracy
Dictator
deltaW
deltaW
Session 3
Democracy
Dictator
deltaW
deltaW
1.019***
(0.098)
0.295**
(0.142)
0.278***
(0.103)
0.380***
(0.088)
0.325***
(0.070)
-0.480***
(0.090)
-0.439***
(0.063)
-0.168
(0.120)
-3.320***
(0.593)
2.440***
(0.275)
-0.813***
(0.242)
0.447***
(0.084)
-0.576***
(0.045)
-0.091
(0.119)
-0.096
(0.113)
-0.419*
(0.229)
-0.729***
(0.099)
0.511***
(0.127)
1.106***
(0.147)
-1.003***
(0.289)
4.795***
(0.275)
-0.481***
(0.148)
-0.544***
(0.172)
0.076
(0.364)
-0.291***
(0.102)
-4.460***
(0.765)
1.625***
(0.241)
-3.230***
(1.223)
-5.218***
(0.317)
4.991***
(0.806)
0.577***
(0.158)
-1.552
(1.023)
0.783***
(0.115)
2.729**
(1.254)
0.060
(0.165)
0.615
(1.960)
150
0.764
100
0.685
150
0.787
100
0.667
150
0.762
100
0.444


Positive correlation between the number of moving individuals and
the increase of individual welfare in all the sessions of the
democracy treatment, and in two out of three session in the dictator
treatment
In the democratic treatment, the welfare increase is negatively
related with the number of rounds in which each individual met a
person with a SRCC* of the opposite sign, while in the dictator
treatment this variable is not significantly correlated with welfare.
*we evaluate heterogeneity in preferences within communities by
calculating Spearman's Rank Correlation Coefficients between each
one experimental subject and all the others
In the democratic treatment the welfare increase is
positively related with the right decision of moving/non
moving

In the dictator treatment the sign of the correlation
between welfare increase and the decision of
moving/non moving depends on the chosen community


Voting by feet enhances welfare, by reducing
heterogeneity among members of a community, only if
all that people has the right to vote.
Probit Moving-Non Moving
VARIABLES
Individual loss in the previous round(dummy)
Decision taken in the first five rounds(dummy)
Presence of at least one person w ith a SC w ith
the opposite sign
Presence of at least tw o people w ith a SC w ith
the opposite sign
Session 1
Democracy
Dictator
move
move
2.160***
(0.550)
0.889***
(0.313)
1.137***
(0.308)
-0.540
(0.418)
0.425
(0.388)
1.063***
(0.352)
0.744**
(0.336)
0.033
(0.398)
-0.596
(0.651)
0.010
(0.483)
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
0.529*
(0.276)
2.004***
(0.422)
1.398***
(0.388)
1.642***
(0.378)
-0.229
(0.310)
1.278***
(0.487)
Different individual vote on the quantity of good
produced(dummy)
Observations
1.174***
(0.268)
Session 3
Democracy Dictator
move
move
1.972***
(0.374)
0.564**
(0.263)
Different individual vote on the type of good
produced(dummy)
Constant
Session 2
Democracy Dictator
move
move
-1.700***
(0.265)
-1.184***
(0.251)
0.623**
(0.243)
-1.277***
(0.205)
150
100
150
-0.698***
(0.197)
-2.277***
(0.368)
-0.639***
(0.219)
100
150
100
1.
2.
3.
Individual loss in previous rounds is always
significantly correlated with the decision to move
in both treatments
Moving decisions are taken more often in the first
five rounds
In the democracy treatment the decision to move
is mainly influenced by community heterogeneity
or by the discrepancy between vote and public
good produced
Total welfare is always higher in democracy, i.e.
voting by feet increases efficiency if voting by
ballot is equally shared among residents
Under democracy the increase of individual welfare
is positively related to the number of moving
decisions
The better performance of the democratic process
over the dictatorship depends on the decreaseof
the average public good costs per capita
In democracy, the welfare increase is negatively
related with the heterogeneity of people in each
community, while in the dictator design this
variable is not significant
In the dictator design the increase in welfare is
positively related with a right decision on
moving/non moving only if the community is
correctly chosen, while in the democracy design
there is a positive coefficient if the moving/non
moving decision is rightly taken.
Aim: to extend previous experimental evidence on
travel mode choice by providing subject not only
with information acquired through personal
experience, but also with actual travel times of the
alternative non chosen travel modes
Key Findings:
 subjects exhibit a marked preference for cars
 are inclined to confirm their first choices
 update imperfectly expectations on travel times



Experimental literature on travel mode choice relies
on studies on route choice
Common object: coordination games, i.e. the
payoff each traveler can achieve is conditional on
her/his ability to diverge from or to converge with
other travelers’ choices
Selten et al. (2007), Ziegelmeyer et al. (2008),
Razzolini-Dutta (2009) provide laboratory
evidence that choices between route A and route B
generate Nash equilibria

Evidence from the field that these learning
processes are affected by cognitive biases (Kareev et
al. 1997, Verplanken–Aarts 1999)


To provide travelers with more accurate
information on actual travel times does not
necessarily increase their propensity to minimize
travel costs (Avineri-Prashker 2006)
Information is better processed when travelers lack
long-term experience on travel time distribution
(Ben Elia–Erev-Shiftan 2008)




Cars are generally perceived as travel means giving
people the sensation of freedom and independence
The costs associated to car use are undervalued
because they not paid contextually with car use
Pollution or social costs due to car accidents are often
neglected and not easily computable
These factors explain the presence of a general
propensity to use private cars and of a psychological
resistance to reduce it (Van Vugt et al. 1995, Tertoolen et al.
1998, Bamberg et al. 2003)

62 undergraduate students (31 women and 31
men) from the University of Firenze

Computerized experiment

Between subject

Each session lasted approximately an hour

Average earnings 18.4 euro
1) Choice between car or metro
Metro travel costs are fixed, while car costs are
uncertain and determined by the joint effect of
casual events and traffic congestion
2) Choice between car or bus
Car and bus are both uncertain and determined by
the combination of casual events and traffic
congestion.
Travelers’ utility only depends on travel times,
which are converted in monetary costs. After each
choice, subjects are informed of actual times of
both available modes, but not of the probability
distributions determining casual events
Table 2 Experimental parameters made known to subjects
Treatment
Car Expected
Time Travel
(in minutes)
Car Fixed
Cost
Metro / Bus
Expected Time
Travel
Metro / Bus
Fixed Cost
Metro vs. Car
25
1.5
30
1.0
Bus 1.0 vs. Car
27
1.5
32
1.0
Bus 0.8 vs. Car
27
1.5
32
0.8



Metro Car treatment- the expected total costs of
car and metro were equivalent if the share of car
users was not greater than 55%;
Bus 1.0 Car treatment - the expected total costs of
car and bus were equivalent if the share of car
users was not greater than 55%;
Bus 0.8 Car treatment- the expected total cost of
the bus was 20% lower than car expected total
costs if the share of car users was not greater than
55%.
Table 8 Proportion of car choices by treatment (each five periods)
Period
1
5
10
15
20
25
30
35
40
45
50
Total
Metro
0.70
0.67
0.60
0.57
0.57
0.77
0.67
0.70
0.60
0.67
0.73
0.68
Bus 1.0
0.60
0.67
0.47
0.67
0.53
0.53
0.73
0.60
0.53
0.60
0.53
0.58
Bus 0.8
0.59
0.35
0.35
0.47
0.53
0.41
0.71
0.71
0.53
0.53
0.53
0.50



The first choice effect decreases the propensity to
change travel mode
Only 28.6% of the subjects in the metro treatment
and 39% of the subjects in the bus treatments
change more than 20 times over 50 periods.
On average, subjects change mode 17.7 times in
the metro treatment and 18.0 times in the bus
treatments
Travel mode choice is significantly affected by
heuristics and biases that lead to robust deviations
from rational behaviour
Travelers choose modes using behavioural rules that
do not necessarily involve the minimization of total
travel costs.
Subjects show a marked preference for cars, are
inclined to confirm their first choice and exhibit a low
propensity to change travel mode.
86
In repeated travel mode choice, available information
is not properly processed, cognitive efforts are
generally low and rational calculation play a limited
role
The habit of using cars should be assumed to be
relatively resistant, to the effect of economic
incentives
Little progress can be expected by asking travelers to
voluntarily reduce the use of a car or even by
subsidizing public transport costs
87


One of the basic tenets of laboratory methodology
is that the use of non-professional subjects and
monetary incentives allows making subjects’ innate
characteristics largely irrelevant
In our experiment, it is as if subjects take into the
lab the preferences applied to real choices and
stick to them with high probability

This inclination to prefer cars tends to override the
incentives effect

Labels give subjects clues to become less and not
more rational



In our experiment, subjects’ behavior depends
more on prior learning outside the laboratory than
on expected gains in the laboratory
Labels have the power to increase external validity
with a minimal sacrifice of the internal validity
To test learning and cognitive models, it is
necessary to remind and to evoke contexts which
may activate emotions, association, similarities in
the laboratory
Tram
http://www.youtube.com/watch?v=H1XrL_U38-c


Metro
http://www.youtube.com/watch?v=dYmsmWqCV0A
Car
http://www.youtube.com/watch?NR=1&v=Sk-WlKTtExA

Progetto ALBO
http://www.progettoalbo.it/images/video/trailer.mp4

LAVREB Laboratory of Virtual reality and Economic Behavior
http://www.lavreb.unisi.it/
