Neuroeconomics and Savings
David Laibson Harvard University, Department of Economics and National Bureau of Economic Research April 1, 2006 NIA Conference, Stanford University
Psychological Foundations A Thought Experiment
Would you like to have A) 15 minute massage now or B) 20 minute massage in an hour
Would you like to have C) 15 minute massage in a week or D) 20 minute massage in a week and an hour
Read and van Leeuwen (1998)
Choosing Today
Eating Next Week
Time
If you were deciding today, would you choose fruit or chocolate for next week?
Patient choices for the future:
Choosing Today Eating Next Week
Time
Today, subjects typically choose fruit for next week.
74% choose fruit
Impatient choices for today:
Choosing and Eating Simultaneously
Time
If you were deciding today, would you choose fruit or chocolate for today?
Time Inconsistent Preferences:
Choosing and Eating Simultaneously
Time
70% choose chocolate
Instant Gratification and Movie Demand
Read, Loewenstein & Kalyanaraman (1999)
Choose among 24 movie videos • Some are “low brow”: Four Weddings and a Funeral • Some are “high brow”: Schindler’s List • Picking for tonight: 66% of subjects choose low brow. • Picking for next Thursday: 37% choose low brow. • Picking for second Thursday: 29% choose low brow.
Tonight I want sugar-coated entertainment… next week I want things that are good for me.
Outline:
• Modeling impulsivity • Self-defeating behaviors • Neuroimaging evidence and neuroeconomics
Behavioral Model
• Quasi-hyperbolic discounting
– Phelps and Pollak (1968), Laibson (1997)
• Discounted utility function Ut = ut + ½ [ut+1 + ut+2 + ut+3 + ...] • Discounted utility from the perspective of time t+1. Ut+1 = ut+1 + ½ [ut+2 + ut+3 + ...] • Discount function reflects dynamic inconsistency: preferences held at date t do not agree with preferences held at date t+1.
Procrastination
Akerlof 1991
• Suppose you can exercise (effort cost 6) to gain delayed benefits (health value 8). • When will you exercise? • Exercise Today: • Exercise Tomorrow: -6 + ½ [8] = -2 0 + ½ [-6 + 8] = 1
• Happy to make plans today to exercise tomorrow. • But likely to fail to follow through.
Self-defeating behaviors
Patient activities many of us plan to do tomorrow: • Watch less TV. • Improve diet. • Quit smoking. • Floss. • Comply with prescriptions. • Exercise. • Cut back credit card spending. • Join retirement savings plan.
Della Vigna and Malmendier (2004)
• • • • Average cost of gym membership: $75 per month Average number of visits: 4 Average cost per vist: $19 Cost of “pay per visit”: $10
Laibson, Repetto, and Tobacman (2004)
Need impulsivity to explain lifecycle consumption facts: – Substantial illiquid retirement wealth: W/Y = 3.9. – But, extensive credit card borrowing: • 68% didn‟t pay their credit card in full last month • Average credit card interest rate is 14% • Credit card debt averages 13% of annual income Why do we see both saving and borrowing?! – Patient long-run view leads us to set up automatic savings institutions (home mortgage, DB and DC pensions) – Impatient short-run view leads us to postpone sacrifices to tomorrow, so we live hand to mouth, borrow on credit cards, and procrastinate
Survey Evidence on Procrastination
Choi, Laibson, Madrian, Metrick (2002)
• Survey –Mailed to 590 employees (random sample) –195 usable responses –Matched to administrative data on actual savings behavior • Consider a population of 100 employees –68 report saving too little –24 of 68 plan to raise 401(k) contribution in next 2 months –Only 3 of 24 actually do so in the next 4 months
Active decisions:
Choi, Laibson, Madrian, Metrick (2004)
Active decision mechanisms require employees to make an active choice about 401(k) participation. • Welcome to the company • You are required to submit this form within 30 days of hire, regardless of your 401(k) participation choice • If you don‟t want to participate, indicate that decision • If you want to participate, indicate your contribution rate and asset allocation • Being passive is not an option
Hire Date and 401(k) Participation
Participation Rate in 3rd Month of Tenure
80% 70% 60% 50% 40% 30% 20% 10% 0%
ar y
ne Ju
ry
ch
M ay
ril
br ua
Ja
Fe
M ar
nu
Month of Hire
Active decision
Ap
Standard enrollment
Ju
ly
401(k) participation increases under active decisions
401(k) participation by tenure: Company E
Fraction of employees ever participated
100% 80% 60% 40% 20% 0% 0 6 12 18 24 30 36 42 48 54 Tenure at company (months)
Active decision cohort Standard enrollment cohort
Active decisions
• Active decision raises 401(k) participation.
• Active decision raises savings rates by 50%.
• Active decision doesn‟t induce choice clustering. • Under active decision, employees choose participation level and savings rates that they otherwise would have taken three years to achieve.
Automatic enrollment
first studied by Madrian and Shea (2001)
• Welcome to the company • If you don‟t do anything
–You are automatically enrolled in the 401(k) –You save 2% of your pay –Your contributions go into a money market fund • Call this phone number to opt out of enrollment or change your investment allocations
Choi, Laibson, Madrian, Metrick (2004)
401(k) participation by tenure at firm: Company B
100%
Fraction of employees ever participated
80% 60% 40% 20% 0% 0 6 12 18 24 30 36 42 48 Tenure at company (months)
Hired before automatic enrollment Hired after automatic enrollment ended Hired during automatic enrollment
Employees enrolled under automatic enrollment cluster at the default contribution rate.
Distribution of contribution rates: Company B
80%
Fraction of participants
70% 60% 50% 40% 30% 20% 10% 0% 1%
3 6 1 20
67
Default contribution rate under automatic enrollment
37 31 26 17 9 7 14 18 14 9 6 4 10
2%
3-5%
6%
7-10%
11-16%
Contribution rate
Hired before automatic enrollment Hired after automatic enrollment ended Hired during automatic enrollment (2% default)
Participants stay at the automatic enrollment defaults for a long time.
Fraction of participants hired during automatic enrollment at both default contribution rate and asset allocation
Fraction of participants
100% 80% 60% 40% 20% 0% 0 6 12 18 24 30 36 42 48 Tenure at company (months)
Company B Company C Company D
Unsuccessful “solutions” to savings problems
• Paying employees to save:
– matches don‟t work well
• Educating employees:
– financial education (alone) doesn‟t work
$100 Bills on the Table
Choi, Laibson, Madrian (2004)
• Employer match is an instantaneous, riskless return on investment • Particularly appealing if you are over 59½ years old – Have the most experience, so should be savvy – Retirement is close, so should be thinking about saving – Can withdraw money from 401(k) without penalty • We study seven companies and find that on average, half of employees over 59½ years old are not fully exploiting their employer match – Average loss is 1.6% of salary per year
Financial education:
Choi, Laibson, Madrian, Metrick (2004)
• Seminars presented by professional financial advisors • Curriculum: Setting savings goals, asset allocation, managing credit and debt, insurance against financial risks • Seminars offered throughout 2000 • Linked data on individual employees‟ seminar attendance to administrative data on actual savings behavior before and after seminar
Treatment effect is positive but small
Seminar attendees % planning to make change Those not in 401(k) plan Enroll in 401(k) Plan 100% 14% 7% % actually made change Non-attendees % actually made change
Those already in 401(k) plan
Increase contribution rate Change fund selection Change asset allocation 28% 47% 36% 8% 15% 10% 5% 10% 6%
• Financial education effects are small • Seminar attendees have good intentions to change their 401(k) savings behavior, but most do not follow through • Financial education alone will not dramatically improve the quality of 401(k) savings outcomes • We have also studied the effect of the Enron/Worldcom/Global Crossing scandals on employer stock holdings –No net sales of employer stock in reaction to these news stories
What is the underlying mechanism?
• • • • Why are our preferences inconsistent? Is it adaptive? How should it be modeled? Does it arise from a single time preference mechanism (e.g., Herrnstein‟s reward per unit time)? • Or is it the resulting of multiple systems interacting (Shefrin and Thaler 1981, Bernheim and Rangel 2004, O‟Donoghue and Loewenstein 2004, Fudenberg and Levine 2004)?
Shiv and Fedorikhin (1999)
"Heart and Mind in Conflict: Interplay of Affect and Cognition in Consumer Decision Making," Journal of Consumer Research, Vol. 26 (December 1999), 278-282.
• Cognitive/deliberative mental processing resources manipulated by having people keep a 2-digit or 7-digit number in mind as they walk from one room to another • On the way, subjects face choice between piece of cake or fruit-salad
Processing burden Low (remember only 2 digits) High (remember 7 digits) % choosing cake 37% 59%
Limbic system vs. Fronto-Parietal System
Frontal cortex Parietal cortex
Limbic system
McClure, Laibson, Loewenstein, and Cohen (2004)
• Do agents think differently about immediate rewards and delayed rewards? • Does immediacy have a special emotional drive/reward component? • Does emotional (limbic) brain value delayed rewards differently than the analytic (fronto-parietal cortex) brain? • Specifically, does the limbic system discount the future at a greater rate than the fronto-parietal cortex?
Subject choices (delay d vs. delay d‟):
Time delay Reward d>0 R d‟ R‟
Hypothesis: fronto-parietal cortex.
Time delay Reward d=0 R d‟ R‟
Hypothesis: fronto-parietal cortex and limbic.
Methods
Subjects given a series of choices between ($R at d) and ($R' at d') where R