SOCIAL INFLUENCE
IN TRUSTORS’ NEIGHBORHOODS
Luigi Luini (University of Siena)
Annamaria Nese (University of Salerno)
Patrizia Sbriglia (University of Naples)
CERGE–EI
Prague, April 5, 2012
RESEARCH QUESTIONS
1) Can trusting (or untrusting) behavior be influenced by social interaction ?
2) Social interaction increases or decreases trust?
RELATED LITERATURE
PEER PRESSURE IN CONTEXTS WHERE SOCIAL PREFERENCES
PLAY A ROLE
•
•
•
•
Gachter, Nosenzo, Sefton (2010): Gift Exchange
Falk, Fishbacher, Gachter (2009): Public Goods
Mittone, Ploner (2011): Trust game, four trustees
Not only strategic interaction matters but also social interaction
under absence of payoff relevance of peer behavior
SEE ALSO: Falk, Ichino (2003): peer pressure and work efforts
RELATED LITERATURE
EXISTENCE AND EFFECTS OF PEER PRESSURE:
Trust Game:
Game Mittone, Ploner (2011)
one trustor/four trustees in one-shot Investment Game
the individual level of reciprocity tends to decrease;
Public Good game: Falk, Fishbaker, Gachter (2009), same individual in two different
neighborhoods
actions are affected by the choices of the two groups’ components
Workplace Effort: (Falk, Ichino, 2003)
positive effects on the individuals’ effort
Gift Exchange Game: Gachter, Nosenzo, Sefton (2010)
two employees sequentially choose their work efforts,
the second can observe the choice of the first
results mixed
TRUST GAME
Trustor
(sender)
Nash solution:
Sender = 0
No Trust (sender)
impossibility of Trustworthiness
(receiver)
Trustee
(receiver)
Trustor
(sender)
MOTIVATIONS OF TRUSTING BEHAVIOR
(ROBUST) RESULT FROM TRUST GAME EXPERIMENTS: THE TRUSTOR
SENDS PART OF ENDOWMENT TO THE RECEIVER EVEN IF TRUST
“DOES NOT PAY” (CAMERER, 2003)
MOTIVATIONS:
1) KINDNESS, ALTRUISM; (ASHRAF ET AL., 2006; COX, 2004, ETC.)
2) EXPECTED TRUSTWORTHINESS; (ASHRAF ET AL., 2006; SAPIENZA
ET-AL,. 2007)
3) BIOLOGICAL MOTIVATIONS (FEHR, 2009)
4) SOCIODEMGRAPHIC COMPONENTS
MOTIVATIONS OF TRUSTING BEHAVIOR
ACCOUNTING FOR ALTRUISM:
Dictator vs Trust: the additive difference in contribution due to “calculative trust”; the
dictators’ contribution due to “unconditional kindness”, Dufwenberg et al (2001), Cox
(2004) ; Between-subjects treatments; Ashraf et al., 2006 within-subjects design
ACCOUNTING FOR EXPECTED TRUSTWORTHINESS:
Beliefs’ elicitation (see Ashraf for references;); questionnaires on trusting individuals’
attitude (Sapienza, Toldra and Zingales, 2007)
ACCOUNTING FOR PSYCHOLOGICAL AND BIOLOGICAL MOTIVATIONS:
See Fehr, 2009
ACCOUNTING FOR CULTURE, GENDER, ETC.,
See Ashraf, 2006 for references
MOTIVATIONS OF TRUSTING BEHAVIOR
Trust attitude and risk attitude:
Eckel, Wilson (2004)
weak relationship
Strategic uncertainty (betrayal) different from State uncertainty (risk)
Do experimental subjects require an “additional premium” to balance the betrayal cost?
“Small” Bohnet,Zeckhauser (2004) “Significant” Houser, Schunk, Winter (2010)
Do risk attitudes predict trustor’s investment in the risky game and in the (corresponding)
trust game?
Houser, Schunk, Winter (2010) clear evidence that risk attitudes predict decisions
under State uncertainty (risk) but no connection between risk attitudes and the
decision to opt-out (invest zero)
Motives for trusts not connected in a simple way to risk attitudes
Potential “emotional” explanations of betrayal aversion
MOTIVATIONS OF TRUSTING BEHAVIOR
SUMMING UP :
The decision to send a positive amount of tokens to an anonymous recipient may be
motivated by:
(1) Trustor’s risk attitude
(2) Trustor’s social preference The sender has no expectation on result: the driving
element can be altruism, “warm glow”, etc.; the trustor has no expectation of a
monetary return
(3) Calculative Trust The sender has positive expectation on result: Expected
Reciprocity (and fairness)
THE EXPERIMENTAL DESIGN
THE TRUST GAME
The experimental design is based on a standard Investment Game in which two agents acted
sequentially.
Player A was given an endowment of 6 experimental tokens at the beginning of each period and he
had to decide how much of this endowment he kept for himself and how much he transferred to
player B who received the amount the amount sent by A multiplied by a factor: α = 3.
Player B had therefore to decide how many tokens he would send back to Player A and the game
ended.
The experimental exchange rate was 1 token = 1 Euro.
45 PLAYERS A , 45 PLAYERS B, STRANGER DESIGN, 20 REPETITIONS
EXPERIMENTS IN SIENA, NAPLES AND SALERNO ; 1 HOUR AND HALF PER
SESSION; INDIVIDUAL PAYOFF: €19
THE “NEIGHBORHOODS”
Starting with the sixth period, each sender was positioned in a group of
three senders and he\she was able to observe the choices of the other
members of the group for the remaining fifteen periods of play.
THE PARTICIPANTS WERE PAID - AT THE END OF THE SESSION - FOR A
SINGLE ROUND RANDOMLY SELECTED BY THE COMPUTER
ACCOUNTING FOR THE TRUSTORS’ MOTIVATIONS:
The experiments comprised three parts – presented in random order - (see Ashraf, 2006):
•
•
•
Questionnaire;
Dictator games;
Lotteries (Holt and Laury, 2002)
ACCOUNTING FOR THE TRUSTORS’ MOTIVATIONS
THE QUESTIONNAIRE:
•
•
•
GENDER; FAMILY INCOME; PARENTAL EDUCATION; FACULTY REGISTRATION;
QUESTIONS RELATED TO THE INDIVIDUAL’S ATTITUDE TO TAKE RISKS (FEHR, 2009);
QUESTIONS RELATED TO THE INDIVIDUAL’S ATTITUDE TO TRUST OTHERS:
"Generally speaking, would you say that you can trust most people or that one can never be too
careful?“
THE DICTATOR GAMES:
TWO DICTATOR GAMES (A PLAYERS AS DICTATORS): ENDOWMENT: 2 EURO;
THE LOTTERIES:
CHOICES IN SIX LOTTERIES (ECKEL AND WILSON, 2004).
SOCIAL INFLUENCE:
SOME METHODOLOGICAL ISSUES
AS NOTED IN FALK AND ICHINO, 2003, EE CAN HELP IN CORRECTLY ASSESSING THE
EXISTENCE OF CONTAGION AND SOCIAL INFLUENCE.
POSSIBLE SOURCES OF BIAS:
1)
2)
3)
4)
SELF SELECTION (MANSKI, 1993);
TIME EFFECTS;
SPURIOUS CORRELATION (“HOMOPHILY”);
SIMULTANEITY PROBLEMS:GROUP BEHAVIOR AFFECTS AGENT’S BEHAVIOR
WHICH IN TURN AFFECTS THE GROUP (MOFFIT, 2001; KRAUTH 2002).
We control for unobserved correlates by regressing the behavior of each trustor on the behavior a
couple of trustors randomly drawn from the sample (not the couple actually observed): if we
observed significant correlation in agent’s actions then we should admit the existence of
spurious correlation in our data.
Furthermore, the availability of panel data permits us to mitigate problems of unobserved
(individual and time) correlated effects via the inclusion of both (time and individual) fixed
effect and random effects accounting for individual heterogeneity (Hartmann et al. 2008).
Finally, simultaneity problems are taken into account by estimating peer effects via instrumental
variables that affect agent’s decision but that can be a priori excluded from the decision of
others in the reference group (Sacerdote, 2001; Hartmann et al. 2008).
HYPOTHESES
FROM 6-20:
H1: β=0 NO SOCIAL INFLUENCE;
H2: SOCIAL INFLUENCE PRODUCES A (POSITIVE) NEGATIVE CHANGE IN
TRUSTING BEHAVIOR;
H3: (DESCRIPTIVE ANALYSIS) HETEROGENEITY INCREASES SOCIAL
INFLUENCE
THE RESULTS
AGGREGATE STATISTICS
trust affected by contagion effects
Individual heterogeneity (average number of tokens sent)
high variance 0.15 – 3.60 tokens sent
Group (neighborhoods) heterogeneity:
Some decreasing trust
Some increasing trust
Some not significantly affected
Overall: trust reduction across the periods
Individual heterogeneity : generosity, risk
(spearman rho correlation coefficients: all 45 subjects, periods 6-20)
amounts sent, risk attitude, generosity
risk “attitude”: two measures (questionnaire, as in Dohmen et al (2005), Fehr (2009) & lab as in
Holt, Laury, 2002) & coherence between the two measures
“generosity”: (in dictator g. as in Eckel, Grossman, 1998)
•
Most of the subjects: risk averse and ungenerous (whichever the index)
rra indicates relative individual risk aversion in the lottery game.
Rra=1 indicates high risk aversion; rra =0 indicates
risk
neutralitygener=1 when individuals are classified as
in dictator game.
generous
RESULTS
EXPECTED TRUSTHORTHINESS CORRELATED TO AMOUNT SENT IN
THE FIRST FIVE PERIODS;
UNCORRELATED TO GENEROSITY AND RISK;
EV IS NOT RELEVANT FOR SOCIAL INFLUENCE
Evidence of the existence of
peer effects
FIG. 1: Number of tokens sent in the fifth period
by each trustor as function of neighbors’ choices
in the previous period.
BEFORE OBSERVING PEERS
FIG. 2: Average number of tokens sent by each
trustor as function of neighbors’ choices in the
previous period (6th – 20th periods).
AFTER OBSERVING PEERS
Contagion effects
5.25
• Positive (increasing trust)
4.20
SENT
3.15
2.10
1.05
.00
0
5
10
15
20
25
PERIOD
2.20
TR34
TR35
TR36
1.76
: NEIGHBORHOOD 12
SENT
1.32
.88
.44
.00
0
5
10
15
20
PERIOD
TR1
TR2
TR3
: NEIGHBOURHOOD 1
25
Negative (decreasing trust)
How Groups (Neighborhoods)
Change Behavior after period 5?
• In absence of imitation we should observe
similar trends in trust before and after period 5
2.00
1.60
SENT
1.20
.80
.40
.00
0
5
10
TR7
15
PERIOD
TR8
20
25
TR9
NEIGHBOURHOOD 3
• Only three groups do not significantly change
H3: (DESCRIPTIVE ANALYSIS) HETEROGENEITY INCREASES SOCIAL
INFLUENCE
Two types of subjects:
1) Influenced by peers
2) Not influenced by peers
Specific types of agents (generous or selfish) imitate more often the same type,
when positioned in the same group
furthermore:
-
Untrusting subjects less affected by their peers compared to generous and
trusting
Untrusting subjects imitate less even when positioned in groups
of agents with similar characteristics
(Glaeser et al, 1996, Falk et al, 2009)
Estimation Results (H1, H2)
i) Coefficient on neighbors’ action: 0.208 statistically significant at 1% level
(null hypothesis on peer effect rejected)
ii) Tobit on others’ actions: 0.322 statistically significant at 1% level
(null hypothesis on peer effect rejected)
iii) Other unobservables (time effect) no statistically significant correlation
Causal interpretation of correlation among subjects’ choices
- Inclusion of random effects to control for individual heterogeneity
- Separate estimation for each time interval (6-10, 11-15, 16-20)
Estimation Results (H1, H2)
-
Decisions to trust significantly and positively correlated not only with individual
generosity but also with risk attitudes
- Females more trust than males
coherence with Eckel-Grossman (1998)
-
“Neighbors’ actions”: Large and statistically significant
“Neighbors’ type”: Small and insignificant
•
However, when the variable “neighbors’ action” is dropped from the model specification in
columns (3), (7) and (11), the estimated coefficients for “neighbors’ type” are statistically
significant at least at 1% level. Now, the last coefficients can be interpreted as causal since the
relative variable is not subject to reflection problem
•
When considering the marginal effects, the variable “neighbors’ type” raises the dependent
variable by 0.22 in column (3), by 0.39 in column (7) and by 0.29 in column (11); at the same time,
the estimated marginal effects for the variable “own type” are, respectively, 0.87, 0.66 and 0.77.
•
Implication: Peer effect at least 20% percent large as the own effect
(not far from the results of Sacerdote, 2001)
Social Influence
Fundamental question:
Individuals follow the prevailing behavior in the group (social influence hypothesis)?
“Neighbors’ profile” and “Own profile” new variables
The higher the similarity between each trustor and his neighbors
The greater the peer effect
The coefficient on the main term (the variable “neighbors’ profile”) becomes small and
insignificant
Whereas
The coefficient on the interactive term is large and significant until the 15th round
In the last rounds, however, the coefficient on the main term increases (it becomes 1.613) and
becomes statistically significant at 5% level.
Overall:
In the previous rounds of the game, individuals follow others’ behavior if the latter is
consistent with their internal preferences
In the last rounds, coherently with the social influence hypothesis, individuals follow the
prevailing behavior in the group
CONCLUSIONS
1) TRUST IS AFFECTED BY CONTAGION EFFECTS;
2 ) THE EFFECT OF SOCIAL INFLUENCE ON TRUST IS NEGATIVE;
3) HETEROGENEITY:
A) SI VARIES ACCORDING TO THE TYPE;
B) B) INDIVIDUALS TEND TO FOLLOW SIMILAR BEHAVIORS
HYPOTHESES