for online publication deconstructing bias: individual groupiness … · 2017-08-14 · for online...
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1
FOR ONLINE PUBLICATION
Deconstructing Bias: Individual Groupiness and Income Allocation
Online Appendix
Rachel Kranton, Matthew Pease, Seth Sanders, and Scott Huettel
August 2017
This appendix contains the following:
1. Further details of the experiment, including screen shots, sample questions from the surveys that preceded the group treatments, and descriptions of the algorithms pairing subjects in the group treatments. 2. Further order effect study: predicted favoritism levels from separate estimations of nine-type latent class model for minimal-group-first subjects and for political-group-first subjects 3. Predicted by type difference in i’s and j’s payoffs in minimal group and political group. 4. Predicted by type payoffs for i and for j and predicted expected total payoffs per match. 5. Cross tabulation of subjects: groupiness designation by individual data versus type categorization 6. Non-group condition: parameter values for six-type latent class utility function estimation 7. Cross-tabulation of subjects non-group condition social preference sets and nine-types from group condition. 8. Regression of nine types categorizations on non-group social preference sets.
2
1. Further details of the experiment. Examples of questions used for the Minimal Group Treatment survey:
Question)4: Which%painting%do%you%prefer?
You$friendly$boatmen$and$mechanics!$You$roughs!
You$twain!$And$all$processions$moving$along$the$streets!
Question)8: Which%line%of%poetry%do%you%prefer?
3
Sample questions on subjects’ political affiliation for the Political Treatment survey:
Pairings in the Minimal Group Treatment: Taken from a bank of other participant’s responses, the Own Group Member was selected as the one that answered similarly on the highest number
DEMOCRAT
1.#Do#you#consider#yourself#a(n):
REPUBLICAN NONE#OF THE#ABOVE
INDEPENDENT
1 2 3 4
STRONG
1(a).#Are#you#a#strong#or#moderate#DEMOCRAT?
MODERATE
1 2
1(a).#Do#you#consider#yourself#closer#to#the::
DEMOCRATIC*PARTY
REPUBLICAN+PARTY
1 2
4
of questions as the subject while the Other Group Member answered most dissimilarly on survey questions. Specifically, an ordered list of subjects who have previously answered the survey is generated. Given a subject i, for the Own Group Member, the algorithm goes down this list, counting for each subject the number of similar answers to survey questions. If the second person on the list has a higher number of similar questions, then s/he replaces the first subject as the subject with the highest similarity rating. If a subject further down the list has a greater number of similar answers, s/he then replaces the current most similar subject. Ties are broken in favor of the ordered list. Then, from among the three categories of questions (poetry, painting, and image), whichever category with the highest number of similar responses is selected. Subject i is then given the following information: "Overall, the OWN GROUP MEMBER answered [the number of similarly answered questions, overall] survey questions with the same response as you" and "This participant preferred the same [chosen as most similar category, category name] as you on [number of similarly answered questions, in this category] out of 7 questions." A parallel procedure searched for the participant in the pool with the most dissimilar answers to select the Other Group Member and present the corresponding information. Pairings in the Political Group Treatment: Taken from a bank of other participant’s responses, the subjects were divided into two groups. Democrats and subjects answering they were "closer" to Democrats were assigned to the Democrat group. Similarly, Republicans and subjects "closer" to the Republican party were assigned to the Republican group. For Democrats and D-Independents, therefore, the Own Group was the Democrat group, and the Other Group was the Republican group. The subjects were given the following information: "Your OWN GROUP answered similarly on political survey questions," and "The OTHER GROUP answered differently on political survey questions." For the Own Group members selected to be the recipient (by an algorithm that identified a subject that answered similarly on at least one of the five political questions), subjects were presented with the statement "This participant identifies with the [Democrat/Republican] party and subjects were also told the question on which the subject and Own Group Member answered similarly. If the subject and Own Group Member answered several questions similarly, preference was given, in order, to - the abortion, gay marriage, Arizona immigration law, Bush tax cut, and government size questions. Parallel information was given for the Other Group member selected, except the algorithm searched for subjects in the Other Group who had answered dissimilarly on at least one political position question. Code available upon request.
!5!
Tab
le O
A1.
M
inim
al G
roup
Fir
st S
ubje
cts:
Pr
edic
ted
Favo
ritis
m L
evel
s Nin
e T
ype
Mod
el
M
inim
al G
roup
Firs
t Sub
ject
s
Pred
icte
d Fa
vorit
ism
Lev
els
Type
A
Type
B
Type
C
Type
D
Type
E
Type
F
Type
G
Type
H
Type
I
M
G
1.48
2 -1
.999
-0
.118
3.
015
-0.2
18
33.0
0***
1.
536
-0.9
52
-6.6
42
(1
.151
) (1
.444
) (1
.931
) (3
.124
) (4
.206
) (3
.516
) (2
.280
) (5
.790
) (6
.717
) PO
L 5.
457*
**
1.71
7 14
.33*
**
2.88
5 15
.88*
**
39.1
8***
4.
805
-0.2
41
6.89
1
(1
.360
) (1
.501
) (1
.964
) (2
.521
) (4
.330
) (3
.282
) (3
.074
) (6
.031
) (4
.438
) M
G m
inus
PO
L 3.
975*
* 3.
716*
14
.45*
**
-0.1
31
16.1
0***
6.
175
3.26
9 0.
711
13.5
3*
(1
.631
) (2
.083
) (2
.601
) (3
.919
) (6
.008
) (4
.810
) (3
.824
) (8
.353
) (8
.050
)
Frac
tion
of M
G F
irst S
ubje
cts
0.26
4***
0.
253*
**
0.18
3***
0.
0700
**
0.06
17**
0.
0602
**
0.04
81**
0.
0362
* 0.
0241
(0
.049
6)
(0.0
478)
(0
.043
6)
(0.0
288)
(0
.027
2)
(0.0
261)
(0
.023
5)
(0.0
205)
(0
.016
8)
Obs
erva
tions
8,
591
8,59
1 8,
591
8,59
1 8,
591
8,59
1 8,
591
8,59
1 8,
591
Stan
dard
err
ors i
n pa
rent
hese
s **
* p<
0.01
, **
p<0.
05, *
p<0
.1
!6!
Tab
le O
A2.
Po
litic
al G
roup
Fir
st S
ubje
cts:
Pr
edic
ted
Favo
ritis
m L
evel
s Nin
e T
ype
Mod
el
Polit
ical
Gro
up F
irst S
ubje
cts
Pr
edic
ted
Favo
ritis
m L
evel
s Ty
pe R
Ty
pe S
Ty
pe T
Ty
pe U
Ty
pe V
Ty
pe W
Ty
pe X
Ty
pe Y
Ty
pe Z
M
G
38.1
6***
-0
.065
7 10
.59*
**
1.85
2 3.
581
0.98
6 9.
484
N/A
(2
.267
) (2
.050
) (2
.431
) (2
.537
) (3
.185
) (1
.446
) (5
.992
)
PO
L 42
.71*
**
1.51
6 8.
456*
**
9.64
9***
20
.85*
**
5.69
2***
-0
.394
N
/A
(2.0
79)
(2.0
80)
(1.9
49)
(2.2
72)
(3.5
84)
(1.8
50)
(6.0
81)
MG
min
us P
OL
4.55
6 1.
581
-2.1
34
7.79
8**
17.2
7***
4.
707*
* -9
.879
N
/A
(3.0
75)
(2.9
28)
(3.1
06)
(3.3
92)
(4.7
95)
(2.3
48)
(8.5
25)
Frac
tion
of P
OL
Firs
t Sub
ject
s 0.
207*
**
0.19
0***
0.
172*
**
0.15
5***
0.
121*
**
0.08
62**
0.
0517
* 0.
0172
0
(0
.053
2)
(0.0
515)
(0
.049
9)
(0.0
476)
(0
.042
9)
(0.0
373)
(0
.029
1)
(0.0
171)
0
Obs
erva
tions
5,
996
5,99
6 5,
996
5,99
6 5,
996
5,99
6 5,
996
5,99
6 5,
996
Stan
dard
err
ors i
n pa
rent
hese
s **
* p<
0.01
, **
p<0.
05, *
p<0
.1
!7!
Tab
le O
A3.
Pr
edic
ted
Diff
eren
ces i
n D
ecis
ion
Mak
er’s
Pay
offs
by
Typ
e: Y
ou-O
wn
vs. Y
ou-O
ther
A
vera
ge
Mat
ch T
ype
Type
1
Type
2
Type
3
Type
4
Type
5
Type
6
Type
7
Type
8
Type
8
Subj
ect
M
G
-0.0
604
-0.2
45*
0.44
5 -4
.943
***
-0.0
899
-1.9
58
3.22
4 1.
941
1.54
3 -0
.330
(0
.706
) (0
.147
) (0
.490
) (1
.010
) (0
.499
) (1
.417
) (1
.968
) (1
.221
) (2
.656
) (0
.334
) PO
L -0
.767
0.
0926
-3
.883
***
-6.7
59**
* 0.
907*
**
-3.7
70**
* -2
.158
0.
918
0.11
8 -1
.933
***
(0
.731
) (0
.201
) (0
.504
) (0
.969
) (0
.336
) (1
.289
) (2
.120
) (1
.348
) (2
.477
) (0
.325
) M
G m
inus
PO
L 0.
706
-0.3
37
4.32
8***
1.
816
-0.9
97*
1.81
2 5.
383*
1.
022
1.42
5 1.
604*
**
(1
.016
) (0
.231
) (0
.701
) (1
.399
) (0
.605
) (1
.902
) (2
.893
) (1
.819
) (3
.632
) (0
.466
)
O
bser
vatio
ns
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
Stan
dard
err
ors i
n pa
rent
hese
s
***
p<0.
01, *
* p<
0.05
, * p
<0.1
!8!
Tab
le O
A4.
Pr
edic
ted
Payo
ffs f
or R
ecip
ient
(j),
Dec
isio
n M
aker
(i),
and
Exp
ecte
d T
otal
Pay
offs
per
Mat
ch:
Min
imal
Gro
up
M
atch
and
Pay
offs
Ty
pe 1
Ty
pe 2
Ty
pe 3
Ty
pe 4
Ty
pe 5
Ty
pe 7
Ty
pe 8
Ty
pe 8
Ty
pe 9
j '
s pay
offs
MG
You
-Ow
n 10
8.2*
**
86.2
0***
95
.36*
**
97.3
9***
83
.24*
**
101.
1***
80
.67*
**
58.3
7***
75
.22*
**
(0
.892
) (0
.726
) (1
.044
) (1
.602
) (1
.500
) (1
.818
) (2
.950
) (1
.384
) (4
.418
) j '
s pay
offs
MG
You
-Oth
er
109.
6***
84
.11*
**
94.8
0***
60
.74*
**
76.2
2***
99
.10*
**
76.1
5***
56
.68*
**
81.8
6***
(0
.786
) (0
.610
) (1
.118
) (1
.055
) (1
.550
) (1
.871
) (3
.020
) (1
.424
) (5
.059
) i '
s pay
offs
MG
You
-Ow
n 12
5.8*
**
138.
8***
13
5.8*
**
128.
0***
13
7.1*
**
125.
9***
13
0.6*
**
134.
1***
13
3.5*
**
(0
.494
) (0
.109
) (0
.296
) (0
.814
) (0
.336
) (0
.920
) (1
.271
) (0
.790
) (1
.673
) i '
s pay
offs
MG
You
-Oth
er
125.
9***
13
9.0*
**
135.
4***
13
2.3*
**
137.
1***
12
7.8*
**
127.
4***
13
2.2*
**
132.
1***
(0
.471
) (0
.085
5)
(0.3
43)
(0.5
53)
(0.3
39)
(1.0
29)
(1.4
38)
(0.9
12)
(1.9
42)
Expe
cted
Tot
al P
ayof
fs fo
r i M
G
117.
4***
11
2.0*
**
115.
4***
10
4.6*
**
108.
4***
11
3.5*
**
103.
7***
95
.33*
**
105.
7***
(0
.290
) (0
.215
) (0
.337
) (0
.536
) (0
.569
) (0
.653
) (1
.135
) (0
.753
) (1
.831
) Ex
pect
ed T
otal
Pay
offs
MG
12
5.9*
**
138.
9***
13
5.6*
**
130.
1***
13
7.1*
**
126.
8***
12
9.0*
**
133.
1***
13
2.8*
**
(0
.341
) (0
.073
2)
(0.2
32)
(0.4
92)
(0.2
51)
(0.6
90)
(0.9
60)
(0.6
03)
(1.2
82)
Obs
erva
tions
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
Stan
dard
err
ors i
n pa
rent
hese
s
**
* p<
0.01
, **
p<0.
05, *
p<0
.1
!9!
Tab
le O
A5.
Pr
edic
ted
Payo
ffs f
or R
ecip
ient
(j),
Dec
isio
n M
aker
(i),
and
Exp
ecte
d T
otal
Pay
offs
per
Mat
ch:
Polit
ical
Gro
up
M
atch
and
Pay
offs
Ty
pe 1
Ty
pe 2
Ty
pe 3
Ty
pe 4
Ty
pe 5
Ty
pe 6
Ty
pe 9
Ty
pe 8
Ty
pe 9
j '
s pay
offs
PO
L Y
ou-O
wn
108.
8***
86
.71*
**
98.6
2***
10
1.2*
**
77.9
9***
96
.95*
**
79.3
8***
65
.70*
**
113.
1***
(0
.832
) (0
.781
) (1
.063
) (1
.491
) (1
.172
) (1
.939
) (3
.028
) (2
.248
) (2
.433
) j '
s pay
offs
PO
L Y
ou-O
ther
10
7.1*
**
81.5
8***
86
.05*
**
59.5
1***
70
.90*
**
78.1
7***
79
.77*
**
58.1
5***
10
6.2*
**
(0
.923
) (0
.805
) (1
.078
) (0
.962
) (1
.231
) (2
.012
) (3
.056
) (1
.548
) (3
.712
) i '
s pay
offs
PO
L Y
ou-O
wn
125.
9***
13
8.7*
**
134.
0***
12
6.6*
**
138.
6***
12
8.7*
**
125.
0***
13
3.9*
**
121.
3***
(0
.485
) (0
.126
) (0
.417
) (0
.787
) (0
.181
) (0
.957
) (1
.482
) (0
.953
) (1
.510
) i '
s pay
offs
PO
L Y
ou-O
ther
12
6.6*
**
138.
7***
13
7.5*
**
132.
6***
13
7.7*
**
132.
2***
12
7.1*
**
132.
9***
12
1.0*
**
(0
.516
) (0
.117
) (0
.220
) (0
.525
) (0
.252
) (0
.813
) (1
.455
) (0
.904
) (1
.873
) Ex
pect
ed T
otal
Pay
offs
for i
in
POL
126.
3***
13
8.7*
**
135.
7***
12
9.6*
**
138.
2***
13
0.4*
**
126.
0***
13
3.4*
**
121.
2***
(0
.354
) (0
.084
3)
(0.2
39)
(0.4
73)
(0.1
55)
(0.6
30)
(1.0
40)
(0.6
57)
(1.2
03)
Expe
cted
Tot
al P
ayof
fs P
OL
117.
1***
11
1.4*
**
114.
0***
10
5.0*
**
106.
3***
10
9.0*
**
102.
8***
97
.67*
**
115.
4***
(0
.300
) (0
.256
) (0
.340
) (0
.505
) (0
.480
) (0
.725
) (1
.151
) (0
.896
) (1
.401
)
Obs
erva
tions
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
Stan
dard
err
ors i
n pa
rent
hese
s
***
p<0.
01, *
* p<
0.05
, * p
<0.1
!10!
T
able
s OA
6.
Cro
ss-T
ype
Diff
eren
ces i
n Pr
edic
ted
Favo
ritis
m L
evel
s and
Pre
dict
ed P
ayof
fs:
Typ
e 1
vs. T
ypes
2-9
and
vs.
Ave
rage
Sub
ject
C
ross
Typ
e D
iffer
ence
Ty
pe 1
v.
2 Ty
pe 1
v.
3 Ty
pe 1
v.
4 Ty
pe 1
v.
5 Ty
pe 1
v.
6 Ty
pe 1
v.
7 Ty
pe 1
v.
8 Ty
pe 1
v.
9 Ty
pe 1
v.
Ave
rage
D
iffer
ence
in F
avor
itism
leve
ls M
G
-3.5
11**
-1
.970
-3
8.07
***
-8.4
35**
* -3
.431
-5
.928
-3
.098
5.
227
-6.5
85**
*
(1
.527
) (1
.932
) (2
.258
) (2
.389
) (2
.900
) (4
.386
) (2
.315
) (6
.822
) (1
.428
) D
iffer
ence
in F
avor
itism
leve
ls P
OL
-3.4
37**
-1
0.88
***
-40.
02**
* -5
.389
***
-17.
09**
* 2.
091
-5.8
54*
-5.1
99
-9.5
96**
*
(1
.688
) (1
.950
) (2
.166
) (2
.040
) (3
.066
) (4
.478
) (2
.999
) (4
.609
) (1
.463
) D
iffer
ence
in E
xpec
ted
Tota
l Pay
offs
MG
5.
353*
**
2.04
4***
12
.80*
**
8.96
5***
3.
918*
**
13.6
9***
22
.07*
**
11.7
3***
5.
718*
**
(0
.361
) (0
.444
) (0
.609
) (0
.639
) (0
.713
) (1
.171
) (0
.807
) (1
.854
) (0
.349
) D
iffer
ence
in E
xpec
ted
Tota
l Pay
offs
PO
L 5.
687*
**
3.08
0***
12
.13*
**
10.8
1***
8.
125*
**
14.3
1***
19
.45*
**
1.71
7 6.
199*
**
(0
.395
) (0
.454
) (0
.587
) (0
.566
) (0
.777
) (1
.189
) (0
.945
) (1
.433
) (0
.357
) D
iffer
ence
in i'
s Exp
ecte
d Pa
yoff
s MG
-1
3.05
***
-9.7
42**
* -4
.239
***
-11.
25**
* -0
.962
-3
.117
***
-7.2
52**
* -6
.909
***
-6.6
60**
*
(0
.349
) (0
.412
) (0
.599
) (0
.423
) (0
.770
) (1
.019
) (0
.693
) (1
.326
) (0
.377
) D
iffer
ence
in i'
s Exp
ecte
d Pa
yoff
s PO
L -1
2.43
***
-9.4
60**
* -3
.336
***
-11.
89**
* -4
.149
***
0.24
5 -7
.123
***
5.11
0***
-6
.418
***
(0
.364
) (0
.427
) (0
.590
) (0
.386
) (0
.722
) (1
.098
) (0
.746
) (1
.254
) (0
.387
) D
iffer
ence
in D
iffer
ence
of M
G, P
OL
Favo
ritis
m L
evel
s -0
.073
5 8.
909*
**
1.94
8 -3
.045
13
.65*
**
-8.0
18
2.75
6 10
.43
3.01
0
(2
.238
) (2
.720
) (3
.139
) (3
.160
) (4
.257
) (6
.265
) (3
.797
) (8
.237
) (2
.061
)
Obs
erva
tions
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
Stan
dard
err
ors i
n pa
rent
hese
s
***
p<0.
01, *
* p<
0.05
, * p
<0.1
!11!
Tab
les O
A7.
C
ross
-Typ
e D
iffer
ence
s in
Pred
icte
d Fa
vori
tism
Lev
els a
nd P
redi
cted
Pay
offs
: T
ype
2 vs
. Typ
es 3
-9 a
nd v
s. A
vera
ge S
ubje
ct
Cro
ss T
ype
Diff
eren
ce
Type
2 v
. 3
Type
2 v
. 4
Type
2 v
. 5
Type
2 v
. 6
Type
2 v
. 7
Type
2 v
. 8
Type
2 v
. 9
Type
2 v
. A
vera
ge
D
iffer
ence
in F
avor
itism
leve
ls M
G
1.54
1 -3
4.56
***
-4.9
24**
0.
0794
-2
.417
0.
413
8.73
8 -3
.074
**
(1
.849
) (2
.143
) (2
.309
) (2
.787
) (4
.327
) (2
.203
) (6
.784
) (1
.238
) D
iffer
ence
in F
avor
itism
leve
ls P
OL
-7.4
42**
* -3
6.58
***
-1.9
52
-13.
65**
* 5.
528
-2.4
17
-1.7
62
-6.1
58**
*
(1
.962
) (2
.110
) (2
.019
) (3
.004
) (4
.452
) (2
.959
) (4
.583
) (1
.379
) D
iffer
ence
in E
xpec
ted
Tota
l Pay
offs
MG
-3
.309
***
7.45
2***
3.
612*
**
-1.4
35**
8.
339*
**
16.7
1***
6.
378*
**
0.36
5
(0
.397
) (0
.577
) (0
.612
) (0
.688
) (1
.155
) (0
.783
) (1
.844
) (0
.290
) D
iffer
ence
in E
xpec
ted
Tota
l Pay
offs
PO
L -2
.607
***
6.43
8***
5.
125*
**
2.43
7***
8.
625*
**
13.7
7***
-3
.970
***
0.51
1
(0
.424
) (0
.566
) (0
.531
) (0
.769
) (1
.179
) (0
.932
) (1
.424
) (0
.322
) D
iffer
ence
in i'
s Exp
ecte
d Pa
yoff
s MG
3.
307*
**
8.81
0***
1.
798*
**
12.0
9***
9.
932*
**
5.79
6***
6.
140*
**
6.38
9***
(0
.235
) (0
.498
) (0
.259
) (0
.694
) (0
.963
) (0
.608
) (1
.284
) (0
.177
) D
iffer
ence
in i'
s Exp
ecte
d Pa
yoff
s PO
L 2.
974*
**
9.09
8***
0.
548*
**
8.28
5***
12
.68*
**
5.31
0***
17
.54*
**
6.01
6***
(0
.247
) (0
.480
) (0
.182
) (0
.635
) (1
.043
) (0
.662
) (1
.206
) (0
.178
) D
iffer
ence
in D
iffer
ence
of M
G, P
OL
Favo
ritis
m
Leve
ls
8.98
3***
2.
021
-2.9
72
13.7
3***
-7
.945
2.
830
10.5
0 3.
084*
(2
.523
) (2
.967
) (3
.056
) (4
.070
) (6
.181
) (3
.656
) (8
.173
) (1
.788
)
O
bser
vatio
ns
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
Stan
dard
err
ors i
n pa
rent
hese
s
**
* p<
0.01
, **
p<0.
05, *
p<0
.1
!12!
Tab
les O
A8.
C
ross
-Typ
e D
iffer
ence
s in
Pred
icte
d Fa
vori
tism
Lev
els a
nd P
redi
cted
Pay
offs
: T
ype
3 vs
. Typ
es 4
-9 a
nd v
s. A
vera
ge S
ubje
ct
Cro
ss T
ype
Diff
eren
ce
Type
3 v
. 4
Type
3 v
. 5
Type
3 v
. 6
Type
3 v
. 7
Type
3 v
. 8
Type
3 v
. 9
Type
3 v
. A
vera
ge
Diff
eren
ce in
Fav
oriti
sm le
vels
MG
-3
6.10
***
-6.4
65**
-1
.462
-3
.958
-1
.129
7.
197
-4.6
16**
*
(2
.448
) (2
.586
) (3
.034
) (4
.486
) (2
.501
) (6
.887
) (1
.713
) D
iffer
ence
in F
avor
itism
leve
ls P
OL
-29.
14**
* 5.
489*
* -6
.207
**
12.9
7***
5.
024
5.67
9 1.
283
(2
.325
) (2
.214
) (3
.163
) (4
.557
) (3
.115
) (4
.685
) (1
.690
) D
iffer
ence
in E
xpec
ted
Tota
l Pay
offs
MG
10
.76*
**
6.92
1***
1.
874*
* 11
.65*
**
20.0
2***
9.
687*
**
3.67
4***
(0
.633
) (0
.655
) (0
.735
) (1
.184
) (0
.824
) (1
.862
) (0
.389
) D
iffer
ence
in E
xpec
ted
Tota
l Pay
offs
PO
L 9.
046*
**
7.73
2***
5.
045*
**
11.2
3***
16
.37*
**
-1.3
63
3.11
9***
(0
.609
) (0
.580
) (0
.800
) (1
.200
) (0
.958
) (1
.442
) (0
.392
) D
iffer
ence
in i'
s Exp
ecte
d Pa
yoff
s MG
5.
503*
**
-1.5
08**
* 8.
780*
**
6.62
5***
2.
490*
**
2.83
3**
3.08
2***
(0
.544
) (0
.348
) (0
.727
) (0
.987
) (0
.646
) (1
.302
) (0
.282
) D
iffer
ence
in i'
s Exp
ecte
d Pa
yoff
s PO
L 6.
124*
**
-2.4
26**
* 5.
311*
**
9.70
5***
2.
337*
**
14.5
7***
3.
042*
**
(0
.530
) (0
.285
) (0
.673
) (1
.067
) (0
.699
) (1
.226
) (0
.286
) D
iffer
ence
in D
iffer
ence
of M
G, P
OL
Favo
ritis
m
Leve
ls
-6.9
61**
-1
1.95
***
4.74
6 -1
6.93
***
-6.1
53
1.51
7 -5
.899
**
(3
.346
) (3
.382
) (4
.356
) (6
.372
) (3
.970
) (8
.318
) (2
.364
)
Obs
erva
tions
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
Stan
dard
err
ors i
n pa
rent
hese
s
***
p<0.
01, *
* p<
0.05
, * p
<0.1
!13!
Tab
les O
A9.
C
ross
-Typ
e D
iffer
ence
s in
Pred
icte
d Fa
vori
tism
Lev
els a
nd P
redi
cted
Pay
offs
: T
ype
4 vs
. Typ
es 5
-9 a
nd v
s. A
vera
ge S
ubje
ct
C
ross
Typ
e D
iffer
ence
Ty
pe 4
v.
5 Ty
pe 4
v.
6 Ty
pe 4
v.
7 Ty
pe 4
v.
8 Ty
pe 4
v.
9 Ty
pe 4
v.
Ave
rage
Diff
eren
ce in
Fav
oriti
sm le
vels
MG
29
.63*
**
34.6
4***
32
.14*
**
34.9
7***
43
.30*
**
31.4
8***
(2
.823
) (3
.245
) (4
.636
) (2
.760
) (6
.985
) (2
.073
)
Diff
eren
ce in
Fav
oriti
sm le
vels
PO
L 34
.63*
**
22.9
3***
42
.11*
**
34.1
6***
34
.82*
**
30.4
2***
(2
.401
) (3
.296
) (4
.653
) (3
.255
) (4
.779
) (1
.935
)
Diff
eren
ce in
Exp
ecte
d To
tal P
ayof
fs M
G
-3.8
39**
* -8
.886
***
0.88
7 9.
262*
**
-1.0
74
-7.0
87**
*
(0
.781
) (0
.844
) (1
.255
) (0
.924
) (1
.908
) (0
.570
)
Diff
eren
ce in
Exp
ecte
d To
tal P
ayof
fs P
OL
-1.3
13*
-4.0
01**
* 2.
187*
7.
327*
**
-10.
41**
* -5
.927
***
(0.6
96)
(0.8
83)
(1.2
57)
(1.0
28)
(1.4
89)
(0.5
41)
D
iffer
ence
in i'
s Exp
ecte
d Pa
yoff
s MG
-7
.012
***
3.27
7***
1.
122
-3.0
14**
* -2
.670
* -2
.421
***
(0.5
52)
(0.8
48)
(1.0
79)
(0.7
79)
(1.3
73)
(0.5
18)
D
iffer
ence
in i'
s Exp
ecte
d Pa
yoff
s PO
L -8
.550
***
-0.8
13
3.58
1***
-3
.788
***
8.44
6***
-3
.082
***
(0.4
98)
(0.7
88)
(1.1
42)
(0.8
09)
(1.2
92)
(0.4
98)
D
iffer
ence
in D
iffer
ence
of M
G, P
OL
Favo
ritis
m
Leve
ls
-4.9
93
11.7
1**
-9.9
66
0.80
8 8.
479
1.06
3
(3
.713
) (4
.628
) (6
.562
) (4
.267
) (8
.464
) (2
.836
)
Obs
erva
tions
14
,587
14
,587
14
,587
14
,587
14
,587
14
,587
Stan
dard
err
ors i
n pa
rent
hese
s
***
p<0.
01, *
* p<
0.05
, * p
<0.1
!14!
Tab
les O
A10
. C
ross
-Typ
e D
iffer
ence
s in
Pred
icte
d Fa
vori
tism
Lev
els a
nd P
redi
cted
Pay
offs
: T
ype
5 vs
. Typ
es 6
-9 a
nd v
s. A
vera
ge S
ubje
ct
Cro
ss T
ype
Diff
eren
ce
Type
5 v
. 6
Type
5 v
. 7
Type
5 v
. 8
Type
5 v
. 9
Type
5 v
. A
vera
ge
Diff
eren
ce in
Fav
oriti
sm le
vels
MG
5.
003
2.50
7 5.
336*
13
.66*
1.
849
(3
.339
) (4
.702
) (2
.869
) (7
.029
) (2
.216
) D
iffer
ence
in F
avor
itism
leve
ls P
OL
-11.
70**
* 7.
480
-0.4
65
0.19
0 -4
.206
**
(3
.215
) (4
.597
) (3
.173
) (4
.724
) (1
.793
) D
iffer
ence
in E
xpec
ted
Tota
l Pay
offs
MG
-5
.047
***
4.72
6***
13
.10*
**
2.76
6 -3
.247
***
(0
.866
) (1
.270
) (0
.944
) (1
.918
) (0
.601
) D
iffer
ence
in E
xpec
ted
Tota
l Pay
offs
PO
L -2
.688
***
3.50
1***
8.
640*
**
-9.0
95**
* -4
.614
***
(0
.869
) (1
.247
) (1
.016
) (1
.481
) (0
.518
) D
iffer
ence
in i'
s Exp
ecte
d Pa
yoff
s MG
10
.29*
**
8.13
3***
3.
998*
**
4.34
1***
4.
591*
**
(0
.735
) (0
.992
) (0
.653
) (1
.306
) (0
.298
) D
iffer
ence
in i'
s Exp
ecte
d Pa
yoff
s PO
L 7.
737*
**
12.1
3***
4.
763*
**
17.0
0***
5.
468*
**
(0
.649
) (1
.051
) (0
.675
) (1
.213
) (0
.220
) D
iffer
ence
in D
iffer
ence
of M
G, P
OL
Favo
ritis
m L
evel
s 16
.70*
**
-4.9
73
5.80
1 13
.47
6.05
6**
(4
.642
) (6
.571
) (4
.283
) (8
.472
) (2
.859
)
Obs
erva
tions
14
,587
14
,587
14
,587
14
,587
14
,587
Stan
dard
err
ors i
n pa
rent
hese
s
***
p<0.
01, *
* p<
0.05
, * p
<0.1
!15!
Tab
les O
A11
. C
ross
-Typ
e D
iffer
ence
s in
Pred
icte
d Fa
vori
tism
Lev
els a
nd P
redi
cted
Pay
offs
: T
ype
6, 7
, 8, 9
vs.
Typ
es 7
-9 a
nd v
s. A
vera
ge S
ubje
ct
Cro
ss T
ype
Diff
eren
ce
Type
6 v
. 7
Type
6 v
. 8
Type
6 v
. 9
Type
6 v
. A
vera
ge
Type
7 v
. 8
Type
7 v
. 9
Type
7 v
. A
vera
ge
Type
8 v
. 9
Type
8 v
. A
vera
ge
Type
9 v
. A
vera
ge
D
iffer
ence
in F
avor
itism
leve
ls M
G
-2.4
96
0.33
3 8.
658
-3.1
54
2.82
9 11
.15
-0.6
58
8.32
5 -3
.487
-1
1.81
*
(4
.969
) (3
.286
) (7
.209
) (2
.734
) (4
.664
) (7
.933
) (4
.294
) (7
.004
) (2
.136
) (6
.763
) D
iffer
ence
in F
avor
itism
leve
ls P
OL
19.1
8***
11
.23*
**
11.8
9**
7.49
0***
-7
.945
-7
.290
-1
1.69
***
0.65
5 -3
.741
-4
.396
(5
.121
) (3
.894
) (5
.236
) (2
.884
) (5
.095
) (6
.181
) (4
.371
) (5
.210
) (2
.836
) (4
.505
) D
iffer
ence
in E
xpec
ted
Tota
l Pay
offs
MG
9.
773*
**
18.1
5***
7.
812*
**
1.80
0***
8.
375*
**
-1.9
61
-7.9
74**
* -1
0.34
***
-16.
35**
* -6
.013
***
(1
.308
) (0
.996
) (1
.944
) (0
.681
) (1
.361
) (2
.154
) (1
.151
) (1
.980
) (0
.777
) (1
.842
) D
iffer
ence
in E
xpec
ted
Tota
l Pay
offs
PO
L 6.
188*
**
11.3
3***
-6
.407
***
-1.9
26**
5.
140*
**
-12.
60**
* -8
.114
***
-17.
74**
* -1
3.25
***
4.48
2***
(1
.360
) (1
.152
) (1
.577
) (0
.750
) (1
.458
) (1
.813
) (1
.167
) (1
.663
) (0
.917
) (1
.414
) D
iffer
ence
in i'
s Exp
ecte
d Pa
yoff
s MG
-2
.155
* -6
.290
***
-5.9
47**
* -5
.697
***
-4.1
35**
* -3
.792
**
-3.5
42**
* 0.
343
0.59
3 0.
249
(1
.183
) (0
.917
) (1
.456
) (0
.709
) (1
.134
) (1
.601
) (0
.973
) (1
.417
) (0
.624
) (1
.292
) D
iffer
ence
in i'
s Exp
ecte
d Pa
yoff
s PO
L 4.
394*
**
-2.9
74**
* 9.
259*
**
-2.2
69**
* -7
.369
***
4.86
5***
-6
.663
***
12.2
3***
0.
705
-11.
53**
*
(1
.217
) (0
.910
) (1
.358
) (0
.649
) (1
.229
) (1
.590
) (1
.051
) (1
.370
) (0
.675
) (1
.213
) D
iffer
ence
in D
iffer
ence
of M
G, P
OL
Favo
ritis
m L
evel
s -2
1.67
***
-10.
90**
-3
.228
-1
0.64
***
10.7
7 18
.44*
11
.03*
7.
670
0.25
4 -7
.416
(7
.129
) (5
.097
) (8
.911
) (3
.976
) (6
.900
) (1
0.05
) (6
.119
) (8
.729
) (3
.550
) (8
.126
)
O
bser
vatio
ns
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
14,5
87
Stan
dard
err
ors i
n pa
rent
hese
s
**
* p<
0.01
, **
p<0.
05, *
p<0
.1
!16!
Tab
le O
A12
. C
ross
Tab
ulat
ion
of In
divi
dual
Dat
a G
roup
ines
s Des
igna
tion
and
Typ
e A
ssig
nmen
t
Gro
upin
ess f
rom
N
ot G
roup
y
C
ond
Gro
upy
Gro
upy
Sum
by
Indi
vidu
al
In
divi
dual
Dat
a Ty
pe 1
Ty
pe 7
Ty
pe 9
Ty
pe 2
Ty
pe 3
Ty
pe 6
T
ype
4 Ty
pe 5
Ty
pe 8
G
roup
ines
s
Not
Gro
upy
29
6 2
20
18
8 1
10
2 96
Con
d G
roup
y 0
0 0
2 6
1 12
5
1 27
Gro
upy
1 1
0 2
4 6
2 1
1 18
Tota
l in
Each
Typ
e 30
7
2 24
28
15
15
16
4
141
!17!
Tab
le O
A13
. S
ix T
ype
Lat
ent C
lass
Est
imat
ion
Non
-Gro
up C
ontr
ol
U
tility
Pa
ram
eter
s ty
pe1
type
2 ty
pe3
type
4 ty
pe5
type
6
Bet
a 0.
150*
**
0.06
55**
* 0.
0865
***
0.01
79**
* 0.
0043
5 0.
0441
***
(0
.015
8)
(0.0
0773
) (0
.014
7)
(0.0
0520
) (0
.003
19)
(0.0
0728
)
Rho
0.
0050
0**
0.02
31**
* -
0.05
08**
* 0.
0258
***
0.00
931*
**
0.00
281
(0
.001
98)
(0.0
0410
) (0
.008
48)
(0.0
0422
) (0
.001
97)
(0.0
0246
)
M
ixin
g Pr
opor
tions
0.
246*
**
0.20
6***
0.
0600
* 0.
152*
**
0.18
9***
0.
147*
(0
.043
3)
(0.0
545)
(0
.031
3)
(0.0
582)
(0
.057
9)
(0.0
791)
O
bser
vatio
ns
3,63
6 3,
636
3,63
6 3,
636
3,63
6 3,
636
Stan
dard
err
ors i
n pa
rent
hese
s
***
p<0.
01, *
* p<
0.05
, * p
<0.1
!18!
T
able
OA
14.
Cro
ss T
abul
atio
n N
on-G
roup
Con
ditio
n So
cial
Pre
fere
nce
Cla
ss v
s. G
roup
ines
s
NG
Par
amet
ers
N
on G
roup
y
Con
d G
roup
y
Gro
upy
To
tal N
G C
lass
Ty
pe 1
Ty
pe 7
Ty
pe 9
Ty
pe 2
Ty
pe 3
Ty
pe 6
T
ype
4 Ty
pe 5
Ty
pe 8
0
< B
eta/
Rho
≤ 1
25
5
2 0
1 11
2
1 0
47
Bet
a/R
ho >
1
5 2
0 24
27
4
11
14
0 87
R
ho <
0
0 0
0 0
0 0
2 1
4 7
To
tal E
ach
Type
30
7
2 24
28
15
15
16
4
141
!19!
Tab
le O
A15
. R
egre
ssio
ns: N
ine
Typ
e Po
ster
ior
Prob
abili
ties o
n N
on-G
roup
Pos
teri
or P
roba
bilit
ies o
f Soc
ial P
refe
renc
es
NG
Soc
ial
Pref
eren
ces
Type
1
Type
2
Type
3
Type
4
Type
5
Type
6
Type
7
Type
8
Ty
pe 9
B
eta/
Rho
> 1
0.
0481
0.
287*
**
0.30
6***
0.
123*
**
0.17
8***
0.
0333
0.
0261
-5
.35e
-05
-0.0
0160
(0
.037
2)
(0.0
374)
(0
.039
8)
(0.0
323)
(0
.033
9)
(0.0
306)
(0
.023
7)
(0.0
121)
(0
.012
8)
0<B
eta/
Rho
≤1
0.55
4***
-0
.019
7 0.
0253
0.
0386
0.
0077
0 0.
238*
**
0.11
2***
3.
73e-
06
0.04
44**
(0
.050
4)
(0.0
507)
(0
.053
9)
(0.0
438)
(0
.046
0)
(0.0
415)
(0
.032
1)
(0.0
165)
(0
.017
4)
Rho
< 0
-5
.90e
-05
-0.0
0035
1 -0
.000
374
0.28
6***
0.
143
-4.0
7e-0
5 -3
.19e
-05
0.57
2***
1.
94e-
06
(0
.128
) (0
.128
) (0
.137
) (0
.111
) (0
.116
) (0
.105
) (0
.081
2)
(0.0
417)
(0
.044
0)
Obs
erva
tions
14
1 14
1 14
1 14
1 14
1 14
1 14
1 14
1 14
1 R
-squ
ared
0.
468
0.29
5 0.
298
0.13
7 0.
172
0.19
8 0.
089
0.57
1
Stan
dard
err
ors i
n pa
rent
hese
s
***
p<0.
01, *
* p<
0.05
, * p
<0.1