Transcript Government Employees Superannuation Board (GESB)

Member Investment Choice and International Asset
Exposure:
A Preliminary Investigation of Home Bias
Paul Gerrans
Deb Gardner
Marilyn Clark-Murphy
Craig Speelman
Edith Cowan University
We gratefully acknowledge the support of the GESB,
UniSuper, STA and HESTA in the conduct of this research
The Context
• An environment of ever increasing
choice
• Many concerns expressed about
members ability to choose well
• Discussion on the role of education
and information in facilitating good
choices
Two Specific Issues
• Home bias
– More knowledgeable about home assets
(Kilka & Weber, 2000)
– More optimistic about the familiar
(Huberman, 2001)
– Manifestation of the recognition heuristic
(Goldstein & Gigerenzer, 2002)
• Naïve diversification (Benartzi & Thaler,
2002) (Hedesstrom et al 2004)
The Present Study :
Government Employees Superannuation Board (GESB)
• Do members exhibit home bias in choices?
• Would this vary over time?
• GESB
– Not-for profit fund > $5 billion assets
– W.A. public sector employees
– MIC data 4/2001 – 9/2004
1986
Pension Scheme
1995/1992
Gold State Super
Defined Benefit
West State Super
Defined Contribution
Member Investment Choice
April 2001
Asset Classes
Equity
Aust.
Int.
Options
Debt
Fixed Int.
Securities
Inflation
Bonds
2001
2004
2005
2001
2004
2005
Global
Bonds
2001
2004
Prop.
Cash
Listed
Prop.
Cash
2005
Growth
25%
40%
15%
8%
8%
4%
11%
10%
2%
Balanced
20%
30%
30%
15%
8%
4%
19%
10%
2%
Conservative
10%
15%
60%
30%
8%
4%
34%
5%
2%
Cash
My Plan
100%
100% 100%
100%
100%
100% 100%
Member accounts
• 199 559 (92%) default, 17 616 (8%) MIC
• Inactive accounts
– For members since choice introduced
• 30% have balance < $435
– Include members
• Made contributions 2004 financial year, or
• Have balance of > $500 and have been a member
since choice introduced
• Reduces accounts to 147 157 default
– No gender difference
Choice & No Choice Members
Default
Choice
Cash
Cons.
n=862
Bal.
n=368
Growth
MyPlan
Balance $
Mean
SD
Median
12597
25855
34115
18210
42706
76324
17490
30808
47353
17189
45863
63123
31145
22572
23748
17217
29678
Male/Female %
31/69
41/59
44/56
36/64
46/54
39/61
51/49
42
61
51
11
48
55
11
52
53
9
51
62
9
62
60
Mem.length Yrs
Mean
SD
Median
8
5
9
8
4
10
8
4
9
7
4
9
8
4
10
8
3
10
8
Total Cont’s. $
Mean
SD
Median
2529
5271
13274
35352
3781
7429
19792
3542
11723
30419
4820
4496
7819
3884
n=146739
Age Yrs
Mean
SD
Median
16197
6557
11
42
2247
2247
n=18547
10
60
12100
3918
n=743
n=12851
n=3723
38759
21038
9
60
4
10
5101
7498
4102
Home Bias? What is optimal?
• Markowitz optimisation
• French and Poterba (1991)
– estimated expected return differentials required to
justify observed holdings relative to market weighted
allocation, rather than optimum
• Gorman and Jorgensen (2002)
– “international diversification benefits are particularly
difficult to capture in practice”
• Herold and Maurer (2003)
– US investors bias can be explained by beliefs of
efficiency of US/Global portfolio & measure of regret
aversion
• Dimson, Marsh and Staunton (2002)
– Sharpe Ratio World/Aust = 1, 20th Century, 1.5 1950-2000
Bias? Industry Norm:
Allocations Multisector Super Funds
Aggressive
(n=20)
Growth
(n=202)
Balanced
(n=64)
Mean Median SD Mean Median SD Mean Median
%
%
%
%
%
%
%
%
SD
%
Aust Equity
38
35
6
37
39
5
33
30
8
Int. Equity
37
36
5
25
25
5
19
20
5
Aust. Fixed
Int. Sec.
8
11
2
16
16
2
24
28
7
Int. Fixed
Int. Sec.
6
9
3
5
5
3
6
7
3
Aust. Prop.
Int. Prop.
7
0
6
4
10
7
2
0
10
0
0
8
4
9
0
0
2
0
Source: Morningstar
Total Access
GESB: My Plan Asset Allocations
• Where non-ve weighting in Aust. or Int.
– 64% (62) equity male (female)
– International/Australian equity 50/50
• No more evidence of home bias than
industry norm
– though less exposure than GESB growth
option
Asset Class Allocations in My Plan
Int.
Equity
%
Aust.
Equity
%
Property
FIS
%
33.41
(28.42)
29.45
(23.27)
29.17
(29.78)
Sample,
n=4604
(SD)
<Growth
Male
(Female)
34.61*
(32.04)*
<Growth
* 90%
Cash
%
Inflation
Linked
Bonds %
18.60
(22.98)

8.31
(14.28)
1.89
(7.15)
5.00
(14.35)
18.43
(18.79)

8.32
(8.28)
2.05
(1.73)
4.44*
(5.67)*
%
Asset Allocation by Decision Order
* 90%
** 95%
Decision
Order
First
M,n=1759
(F,n=1689)
Second
M,n=391
(F,n=311)
Third
M,n=134
(F,n=79)
Fourth
M,n=56
(F,n=25)
Int.
Equity
%
40.10**
(35.84) **
Aust.
Equity
%
Property
FIS
Cash
%
Inf.
Linked
Bonds%
%
29.48
(30.74)
16.16
(16.97)
7.03
(7.38)
1.21
(1.04)
3.16**
(4.63) **

20.93*
(17.27) *
25.36
(26.69)
27.74
(26.62)
11.09
(11.88)
2.98
(3.68)
7.32
(8.56)
28.62
(26.39)
19.61
(22.82)
12.69
(10.16)
5.78
(6.89)
9.27
(7.33)
38.07
(27.24)
22.50
(25.80)
10.71
(14.88)
3.13
(2.40)
3.66**
(11.52) **

21.87
(21.46)
19.96**
(13.40) **

Influences on Asset Allocations
• Trailing 1, 6, 12 month returns of old
and new options using GESB published
monthly returns
Choice Historical Performance
Mean
(%)
SD
(%)
t-stat of
differences
All Investment options
12 month
(n=5103)
6 month
(n=6223)
1 month
(n=7623)
2001 Report
(n=13475)
Old
New
Old
New
Old
New
Old
New
3.7293
5.9190
2.3240
3.1930
0.1108
0.2093
2.6800
1.2400
8.6713
9.1219
4.7177
5.0709
1.6077
1.8179
0.4145
1.3587
23.5532
19.5169
7.5319
-119.2810
Choice Historical Performance
Mean
(%)
SD
(%)
t-stat of
differences
My Plan option
12 month
(n=1888)
6 month
(n=2184)
1 month
(n=2485)
2001 Report
(n=2424)
Old
New
Old
New
Old
New
Old
New
3.4179
7.2284
2.3102
3.9471
0.1294
0.3730
2.6564
0.0033
9.3117
9.4771
5.0475
5.4504
1.7522
2.0337
0.7799
2.0198
8.0024
6.7437
2.1734
-61.4683
What is the story?
• Two clearly different decisions
• 1. First decision when MIC introduced
– “Activate your super” “Take control”
– Do so by choosing different allocations
– Historical performance not a driver
– No home bias, higher international asset
allocation
What is the story?
• 2. Subsequent decisions
– Different information set, performance
(more salient?)
– Reduce exposure to poor performers and
increase exposure to property, Australian
equity
– Recognition bias rather than Home Bias
per se
Limitations & Future Work
• One fund – extend to two industry funds
• Time period – extend earlier period
• Pooled time series preserve time
structure & multivariate influences
• Thanks to support of GESB, UniSuper,
STA, HESTA