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PROCRASTINATION, PRESENT-BIASED
PREFERENCES AND FINANCIAL BEHAVIORS
Jeffrey R. Brown
University of Illinois and NBER
Alessandro Previtero
Ivey Business School, Western University
Present-Bias and Procrastination
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
Economists model procrastination as the result of present-biased
preferences



Near term costs + distant consequences  delay
Theory: Akerlof (Ely Lecture, 1991); Laibson (1997); O’Donoghue & Rabin
(1999a, 1999b, 2001); Fudenberg & Levine (2006, 2012)
If true, then this this has implications for retirement planning
behaviors, policy and plan design
 Direct empirical evidence on relevance of present-biased
preferences and procrastination is very limited
Highly Relevant to Retirement
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



DC system provides more autonomy, and also more room for
mistakes (Benartzi and Thaler, 2007)
We still do not fully understand why there is such a large dispersion
of wealth at retirement (Poterba, Venti, Wise, 2013)
Intuitively, procrastination is a likely culprit, especially because it is
more likely “the further away an event is temporally” (Steel, 2007)
Procrastination has been suggested as a reason default options
may exert such a power influence on behavior (Beshears et al 2009)
 If we can establish that present-biased preferences and
procrastination negatively affect retirement security, we can
better guide policy and plan design to improve outcomes
Measuring Procrastination
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
We empirically define “procrastinators” as people who wait
until the last day of open enrollment period to make their
health care plan election
The advantages of our measure of procrastination:


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
Actual and consequential behavior (Levitt and List, 2008)
Distinct decision from outcomes being studied (Kuchler, 2014)
Can be implemented in multiple data sets
Four measures
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
Procr_max: ever procrastinate in any year of data
Procr_mean: fraction of elections made in which procrastinated
Procr_first: whether procrastinated the first time a choice was made
Procr_ last: whether procrastinated the last time a choice was made
Five Hypotheses to Test if Procrastination is
Driven by Present-Biased Preferences
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Present-biased preferences will jointly predict that:
1.
2.
3.
4.
5.
Procrastinators are less likely to participate in supplemental
savings plans
Procrastinators who do save will take longer to sign up
Procrastinators will contribute less (conditional on
participating at all)
Procrastinators will be more likely to stick with the default
portfolio investment
Procrastinators will be less likely to annuitize
Three Data Sets
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1.
2,678 new employees joining U of I system during c.y. 2010

2.
Over 100,000 participants in 27 401(k) plans



Days to join 401(k)
Contribution rates
Share of portfolio invested in QDIA (lifecycle, target date, balanced)
Over 27,000 employees ages 55+ who retire from DB plan
3.

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Binary decision of whether to contribute to 403(b) or 457
Annuity vs. lump-sum
In all three cases, we have information on exact date that
health care plan was selected
Procrastinators 2.4% Points Less Likely
to Sign Up for Supplemental Plan
Table 2
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Procrastinator
Plan Participation
Plan Participation
-0.0240**
-0.0239**
(0.0113)
(0.0112)
Female
-0.0308***
(0.0101)
Age
0.00404***
(0.000501)
Faculty
-0.0116
(0.0137)
FinLit
0.00768
(0.0286)
Constant
0.0820***
-0.0535**
(0.00602)
(0.0208)
Note that although
some covariates are
significant, they have
no effect on
procrastination
coefficient
Table 3 Panel A
Procrastinators Take 44-72 Days Longer to Join 401(k)
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OLS
Days to Join
Proc_Max
Days to Join
Days to Join
Days to Join
71.65***
(13.66)
Proc_Mean
64.96***
(20.51)
Proc_Last
52.39***
(16.60)
Proc_First
44.06***
Other controls?
Yes
Yes
Yes
(13.37)
Yes
N
108,850
108,850
108,850
108,850
Regressions are right censored at 5 years after hire
Regressions also control for female (+), hiring age (-), plan and year controls
Procrastinators Contribute 0.1-0.2% of Pay
Less (When Not Defaulted)
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Firms with no default option
Proc_Max
-0.095*
-0.051
(0.050)
(0.150)
Proc_Mean
-0.189**
0.085
(0.083)
(0.164)
Proc_Last
-0.169**
0.140
(0.067)
(0.157)
Proc_First
Other
Controls?
N
Firms with default option
-0.094
0.007
Yes
Yes
Yes
(0.113)
Yes
21,167
21,167
21,167
21,167
Yes
Yes
Yes
(0.057)
Yes
88,118
88,118
88,118
88,118
Further refinements to methodology for identifying defaults underway – “hot off the press”
results suggests that procrastinators who are auto-enrolled at firm with low default saving
rate may also have lower contribution rate than non-procrastinators
Table 4B
Procrastinators Invest 3-5% More in QDIAs
(Lifecycle, Target Date or Balanced)
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Pre-PPA (2002-2006)
Share in QDIA Fund
Proc_Max
-0.001
0.031**
(0.005)
(0.012)
Proc_Mean
0.008
0.046**
(0.011)
(0.019)
Proc_Last
0.003
0.045**
(0.005)
(0.019)
Proc_First
Other
Controls?
N
Post-PPA (2008)
Share in QDIA Fund
0.009
0.038**
(0.009)
(0.015)
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
58,388
58,388
58,388
58,388
23,073
23,073
23,073
23,073
Regressions also control for female (+), hiring age (-), plan and year controls
Table 5A
Procrastinators 3-4% Pts More Likely to Have
100% Allocation to QDIA Post-PPA
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Pre-PPA (2002-2006)
Pr(Put 100% in QDIA)
Proc_Max
0.001
-0.000
(0.005)
(0.018)
Proc_Mean
0.015
0.038**
(0.012)
(0.016)
Proc_Last
0.008
0.034*
(0.007)
(0.018)
Proc_First
Other
Controls?
N
Post-PPA (2008)
Pr(Put 100% in QDIA)
0.012
0.033**
(0.009)
(0.014)
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
59,520
59,520
59,520
59,520
23050
23050
23050
23050
Regressions also control for female (+), hiring age (0), plan and year controls
Table 5B
Procrastinators 4-5% Pts Less Likely to Annuitize DB
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Pr(Ann.)
Proc_Max
Pr(Ann.)
Pr(Ann.)
Pr(Ann.)
-0.042**
(0.016)
Proc_Mean
-0.052*
(0.026)
Proc_Last
-0.013
(0.019)
Proc_First
Other Controls?
N
-0.052**
Yes
Yes
Yes
(0.020)
Yes
18,294
18,294
18,294
18,294
Regressions also control for female (+), hiring age (-), Value of DB (+), tenure (-), 6 month
Interest rate (0), past 12m S&P (-), plan and year controls
Table 6
Evidence of Present-Biased Preferences
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

Optimal delayers (those who have multiple interactions,
including final one on last day) behave opposite of
procrastinators (i.e., save more, less likely to choose
default, etc.)
Only present-biased preferences can explain:
Low saving rate
 Lower probability of annuitizing
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When lump-sum made more salient (cash balance
plans), the negative effect on annuitization is even
stronger
And in a Separate Study …
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
RRC-Funded project by Brown, Farrell &
Weisbenner surveys Illinois SURS participants
 Those
who wait until “final reminder” to return our
survey are substantially more likely to be defaulted
into lifetime DB plan
 Current project is experimenting to see if reminders
closer to default date reduce the probability of
defaults – stay tuned!
Summary of Findings
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Procrastinators:
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Are less likely to participate in supplemental savings plans
Take longer to sign up when they do participate
Contribute less
Are more likely to stick with the default investment option after passage
of PPA 2006
Are more likely to allocate 100% of their portfolio to the default
investment option after passage of PPA 2006
Are less likely to annuitize their DB at retirement
And even less likely to annuitize their cash balance plan
Only present-biased preferences can jointly explain all of
these results
Policy Relevance
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
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Sheds light on a potentially important pathway
through which default options exert influence
Provides guidance as to type of interventions that
may be needed to increase active choice
 Making
choices more salient today; forced deadlines
 Much more research is needed here!

Current policy discussion around retirement income
need to account for present-biased preferences