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PROCRASTINATION, PRESENT-BIASED PREFERENCES AND FINANCIAL BEHAVIORS Jeffrey R. Brown University of Illinois and NBER Alessandro Previtero Ivey Business.

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Presentation on theme: "PROCRASTINATION, PRESENT-BIASED PREFERENCES AND FINANCIAL BEHAVIORS Jeffrey R. Brown University of Illinois and NBER Alessandro Previtero Ivey Business."— Presentation transcript:

1 PROCRASTINATION, PRESENT-BIASED PREFERENCES AND FINANCIAL BEHAVIORS Jeffrey R. Brown University of Illinois and NBER Alessandro Previtero Ivey Business School, Western University 1

2 Present-Bias and Procrastination  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 2

3 Highly Relevant to Retirement  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 3

4 Measuring Procrastination  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:  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  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 4

5 Five Hypotheses to Test if Procrastination is Driven by Present-Biased Preferences Present-biased preferences will jointly predict that: 1. Procrastinators are less likely to participate in supplemental savings plans 2. Procrastinators who do save will take longer to sign up 3. Procrastinators will contribute less (conditional on participating at all) 4. Procrastinators will be more likely to stick with the default portfolio investment 5. Procrastinators will be less likely to annuitize 5

6 Three Data Sets 1. 2,678 new employees joining U of I system during c.y  Binary decision of whether to contribute to 403(b) or Over 100,000 participants in (k) plans  Days to join 401(k)  Contribution rates  Share of portfolio invested in QDIA (lifecycle, target date, balanced) 3. Over 27,000 employees ages 55+ who retire from DB plan  Annuity vs. lump-sum  In all three cases, we have information on exact date that health care plan was selected 6

7 Procrastinators 2.4% Points Less Likely to Sign Up for Supplemental Plan Plan Participation Procrastinator ** ** (0.0113)(0.0112) Female *** (0.0101) Age *** ( ) Faculty (0.0137) FinLit (0.0286) Constant *** ** ( )(0.0208) Table 2 Note that although some covariates are significant, they have no effect on procrastination coefficient 7

8 Procrastinators Take Days Longer to Join 401(k) OLSDays to Join Proc_Max 71.65*** (13.66) Proc_Mean 64.96*** (20.51) Proc_Last 52.39*** (16.60) Proc_First 44.06*** (13.37) Other controls?Yes N108,850 Regressions are right censored at 5 years after hire Regressions also control for female (+), hiring age (-), plan and year controls Table 3 Panel A 8

9 Procrastinators Contribute % of Pay Less (When Not Defaulted) Firms with no default optionFirms with default option Proc_Max * (0.050)(0.150) Proc_Mean **0.085 (0.083)(0.164) Proc_Last **0.140 (0.067)(0.157) Proc_First (0.057)(0.113) Other Controls? Yes N 88,118 21,167 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 9

10 Procrastinators Invest 3-5% More in QDIAs (Lifecycle, Target Date or Balanced) Pre-PPA ( ) Share in QDIA Fund Post-PPA (2008) Share in QDIA Fund Proc_Max ** (0.005)(0.012) Proc_Mean ** (0.011)(0.019) Proc_Last ** (0.005)(0.019) Proc_First ** (0.009)(0.015) Other Controls? Yes N 58,388 23,073 Regressions also control for female (+), hiring age (-), plan and year controls Table 5A 10

11 Pre-PPA ( ) Pr(Put 100% in QDIA) Post-PPA (2008) Pr(Put 100% in QDIA) Proc_Max (0.005)(0.018) Proc_Mean ** (0.012)(0.016) Proc_Last * (0.007)(0.018) Proc_First ** (0.009)(0.014) Other Controls? Yes N 59, Regressions also control for female (+), hiring age (0), plan and year controls Table 5B Procrastinators 3-4% Pts More Likely to Have 100% Allocation to QDIA Post-PPA 11

12 Procrastinators 4-5% Pts Less Likely to Annuitize DB Pr(Ann.) Proc_Max ** (0.016) Proc_Mean * (0.026) Proc_Last (0.019) Proc_First ** (0.020) Other Controls?Yes N18,294 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 12

13 Evidence of Present-Biased Preferences  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  When lump-sum made more salient (cash balance plans), the negative effect on annuitization is even stronger 13

14 And in a Separate Study … 14  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!

15 Summary of Findings  Procrastinators:  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 15

16 Policy Relevance 16  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


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