THE ROLE OF TIME PREFERENCES AND EXPONENTIAL-GROWTH BIAS IN RETIREMENT SAVINGS Gopi Shah Goda, Stanford University & NBER Matthew R. Levy, London School of Economics Colleen Flaherty Manchester, Univ. of Minnesota Aaron Sojourner, Univ. of Minnesota & IZA Joshua Tasoff, Claremont McKenna Graduate School Financial support provided by TIAA-CREF Institute, Pension Research Council- Boettner Center, U.S. Social Security Administration via the NBER Retirement Research Consortium, and National Institutes of Health.
Transcript
THE ROLE OF TIME PREFERENCES AND EXPONENTIAL-GROWTH BIAS IN RETIREMENT SAVINGS
Gopi Shah Goda, Stanford University & NBER
Matthew R. Levy, London School of Economics
Colleen Flaherty Manchester, Univ. of Minnesota
Aaron Sojourner, Univ. of Minnesota & IZA
Joshua Tasoff, Claremont McKenna Graduate School
Financial support provided by TIAA-CREF Institute, Pension Research Council-Boettner Center, U.S. Social Security Administration via the NBER Retirement
Research Consortium, and National Institutes of Health.
OVERVIEW
90% of Americans display decision-making biases relevant to retirement saving Inconsistency favoring immediate gratification Inaccurate view the power of compound interest
Those with bias have far less retirement savings Tested against many competing explanations
Nudges to counteract biases affect choices, especially among the most biased.
CHALLENGES IN MAKING APPROPRIATE RETIREMENT PLANNING DECISIONS
Motivational barrier
Cognitive barrier
BARRIER 1: PRESENT BIAS (PB)
Time-inconsistent privileging of the present. Beyond time-consistent preference for sooner over
later. Can produce procrastination in enrolling or saving.
Example: tomorrow (Saturday), will you prefer:$100 on Saturday or $101 on Sunday?
Decision when asked today
Decision when asked tomorrow
Present
biased?
1 $101 on Sunday $101 on Sunday No
2 $101 on Sunday $100 on Saturday Yes
BARRIER 2: EXPONENTIAL-GROWTH BIAS (EGB), A FACET OF FINANCIAL LITERACY
Note: The figure shows the perceived asset value with a starting value of $1 at time zero growing at an annual interest rate of 10 percent for savers with varying levels of linearized exponential growth bias.
0 5 10 15 20 250
2
4
6
8
10
12
Years
Perc
eiv
ed
Asset
Valu
e
($)
Linear
Accurate
Below EG
Above EG
RESEARCH QUESTIONS
To what extent are these biases present among U.S. households? How much overlap is there?
Do these biases explain variation in retirement savings among U.S. households?
How can the effect of these biases on saving behavior be mitigated? Would that affect savings, especially among the most biased?
RESEARCH DESIGN Survey large, broad sample of U.S. households
(N=2,317) using the American Life Panel & the Understanding America Survey. Directly measure each individual’s:
Other factors that may influence retirement savings: long-run discount rate, income, age, IQ, broad financial literacy, education, race/ethnicity, family structure, state of residence, risk aversion…
NEW RESULT: 90% OF AMERICANS DISPLAY SOME BIAS
Neither bias
RESEARCH QUESTIONS
To what extent are these biases present among U.S. households? How much overlap is there?
Do these biases explain variation in retirement savings among U.S. households?
How can the effect of these biases on saving behavior be mitigated? Would that affect savings, especially among the most biased?
NEW RESULT: LESS BIASED SAVED MORE (MUCH MORE)
Estimated difference in retirement savings for a 1 standard deviation difference in each variable. From regression controlling also for 10-year age bin, household income category (17), age-income interactions, highest-level of education, gender, marital status, number of household members, number of children, race, ethnicity, state of residence, and risk aversion.
Time preferences
NEW RESULT: BIASES SHOW UP AS BIGGER FACTORS FOR OLDER AMERICANS
EG BiasPresent
Bias
Broad Financial Literacy IQ
Notes: N=2,317. Estimated difference in retirement savings for a 1 standard deviation difference in each variable using regression with quadratic age interactions. From regression controlling for 10-year age bin, household income category (17), age-income interactions, highest-level of education, gender, marital status, number of household members, number of children, race, ethnicity, state of residence, and risk aversion.
RESULT:AWARENESS OF BIAS MATTERS
First to measure (un)awareness of biases directly and relate to economic outcome. Awareness can lead individuals to get help. Unawareness can lead to mistakes.
Overconfident in EGB save less: believe you are more accurate with respect to EG than you are.
Naive about PB save less (weaker evidence): believe you will act patiently in future.
RESEARCH QUESTIONS
To what extent are these biases present among U.S. households? How much overlap is there?
Do these biases explain variation in retirement savings among U.S. households?
How can the effect of these biases on saving behavior be mitigated? Would that affect savings, especially among the most biased?
INTERVENTION TO COUNTERACT EG BIAS
Informed that employer just added a match for every dollar contributed (hypothetical)
Control: Show Annual Value of match
EGB Balance Treatment: Show projected Balance of match at retirement
EGB Income Treatment: Show projected Annual Income supported by match in retirement
Present-Future staircase: Would you rather receive $100 today or $[X] in 12 months?
Future-Future staircase: Would you rather receive $120 in 12 months or $[Y] in 24 months?
Prediction staircase: Suppose that 12 months from now, you are going to be given the choice between the following: receiving a payment on that day (that is, 12 months from today) or a payment 12 months later (that is, 24 months from today). Do you think you would rather choose to receive $110 on that day or $[Z] 12 months later?
MEASURING EXPONENTIAL-GROWTH BIAS: THIS IS 3RD OF 5 QUESTIONS
RESULT: BIASES MAY ACTUALLY HAVE STRONGER RELATIONSHIPS TO SAVINGS
