ArticlePDF Available

How Much Choice Is Too Much? Contributions to 401(K) Retirement Plans


Abstract and Figures

The wide range of 401(k) plans offered to employees has raised the question of whether there is such as thing as too much choice. The 401(k) participation rates among clients of the Vanguard Group were studied to verify the assumption that more choice is more desirable and intrinsically motivating. It was found that 401(k) plans that offered more funds had lower probability of employee participation. © Pension Research Council, The Wharton School, University of Pennsylvania, 2004. All rights reserved.
Content may be subject to copyright.
How Much Choice is Too Much?:
Contributions to 401(k) Retirement Plans
Sheena S. Iyengar
Wei Jiang
Gur Huberman
PRC WP 2003-10
Pension Research Council Working Paper
Pension Research Council
The Wharton School, University of Pennsylvania
3641 Locust Walk, 304 CPC
Philadelphia, PA 19104-6218
Tel: 215.898.7620 Fax: 215.898.0310
Pension Research Council Working Papers are intended to make research findings available to other researchers in
preliminary form, to encourage discussion and suggestions for revision before final publication. Opinions are solely
those of the authors. This paper is to appear in Pension Design and Structure: New Lessons from Behavioral
Finance (forthcoming). Edited by Olivia S. Mitchell and Stephen P. Utkus. Oxford: Oxford University Press.
We acknowledge the contributions of Steve Utkus, who made available the data essential for conducting this analysis and
who provided us constructive feedback throughout the process. We would also like to thank Gary Mottola for the
considerable time and effort he dedicated to assisting us in refining and analyzing the data set.
©2003 Pension Research Council of the Wharton School of the University of Pennsylvania. All Rights Reserved.
How Much Choice is Too Much?: Contributions to 401(k) Retirement Plans
Sheena S. Iyengar, Wei Jiang, and Gur Huberman
Although extensive choice seems appealing, research shows that it may hinder motivation
to buy and decrease subsequent satisfaction with purchased goods. This paper examines whether
these findings generalize to employees who are making decisions about whether to invest in
401(k) retirement saving plans. Using data from nearly 800,000 employees, we tested the
hypothesis that employee 401(k) participation rates fall as the number of fund options increase.
Our results confirm that participation in 401(k) plans is higher in plans offering a handful of
funds, as compared to plans offering ten or more options.
How Much Choice is Too Much?: Contributions to 401(k) Retirement Plans
Gur Huberman, Sheena S. Iyengar, and Wei Jiang
It is commonly supposed that the more choices we have, the better off we are – that the
human ability to manage and the desire for choice are infinite. From classic economic theories
of free enterprise, to mundane marketing practices that offer aisles of potato chips and soft
drinks, the desire for infinite choice pervades our institutions, norms, and customs. Ice cream
parlors compete to offer the most flavors while major fast-food chains urge customers to “Have
it your way.” Furthermore, the challenges of choice are not merely confined to snack foods.
With today’s plethora of retirement savings plans, important life decisions have also become a
matter of choice, where employees become consumers, contemplating alternative career options
and multiple investment opportunities.
These days, most workers cannot expect to retire on Social Security alone; therefore
people increasingly are turning to company pension plans to help them save for retirement.
Firms offer 401(k) plans in order to attract new employees, encourage superior performances
from current employees, and increase employee retention. The 401(k) plan, named for section
401(k) of the Internal Revenue Code, permits employees of qualifying companies to set aside
tax-deferred funds with each paycheck. While the employer is responsible for establishing a
401(k) plans, employees must decide what percentage of their paycheck will be deducted for
their plans. Employees can legally contribute up to 25% of their annual earnings as long as the
amount does not exceed the legal cap (which was $12,000 in 2003). Over the past decade the
number of employer-provided retirement plans has skyrocketed from under 100,000 in 1990, to
over 400,000 by 2002 (Mottola and Utkus, 2003).
While the promise of a greater variety of plans seems beneficial, is there such a thing as
too much choice? Indeed, if we look beyond the number of plans available, and we examine the
options within the plans themselves, we find even more decisions waiting to be made. Most
401(k) plans offer employees a myriad of investment opportunities from mutual funds, insurance
companies, and/or banks. Indeed, some providers even allow employees to invest in individual
stocks, and on global capital exchanges allowing for maximum portfolio diversification. But,
does bigger necessarily mean better? When large companies woo potential employees with a
smorgasbord of options, do these options actually enhance employee welfare?
Inherent to consumerism is the assumption that choice is both desirable and powerful.
Psychological theory and research have similarly presumed that choice is invariably beneficial.
Repeatedly, across many domains of inquiry, psychologists have contended that the provision of
choice can increase the individual’s sense of personal control (Rotter, 1966; Taylor, 1989; Taylor
and Brown, 1988) and feelings of intrinsic motivation (deCharms, 1968; Deci, 1981; Deci and
Ryan, 1985). In turn, personal control and intrinsic motivation have been correlated with
numerous physical and psychological benefits, including greater task enjoyment, enhanced task
performance, and increased life satisfaction. Indeed, even seemingly trivial or wholly illusory
choices have been shown to have powerful motivating consequences (Langer and Rodin, 1976;
Dember et. al., 1992; Langer, 1975).
More recently, however, a few researchers have demonstrated potential limitations to this
assumption. Rather than presuming the benefits of choice to be ubiquitous, Iyengar and Lepper
(2000) examined the consequences of offering choosers an extensive range of alternatives, in
which the differences among options were relatively small. They hypothesized that choosers will
be intrinsically motivated by the actual provision of extensive choices, because such contexts
allow for maximal opportunity in the achievement of personal preference matching. Nonetheless,
the very act of making a choice from an excessive number of options might result in “choice
overload,” in turn lessening both the motivation to choose and the subsequent motivation to
commit to a choice.
Field and laboratory experiments were conducted in which the intrinsic motivations of
participants encountering limited as opposed to extensive choices were compared (Iyengar and
Lepper, 2000). In one compelling field demonstration, a tasting booth for exotic jams was
arranged at Draegers, a California gourmet grocery store. This grocery store is of particular
interest because its salient distinguishing feature is the extraordinary selection it offers,
especially when compared with large grocery chains. For instance, Draeger's offers roughly 250
different varieties of mustard, 75 different varieties of olive oil, and over 300 varieties of jam.
Shoppers are frequently offered sample tastes of this enormous array of available products;
consequently, Draeger’s provided a particularly conducive environment for a naturalistic
experiment, using tasting booths.
As customers passed the tasting booth, they encountered a display with either 6 or 24
different flavored jams. The number of passers-by who approached the tasting booth and the
number of purchases made in these two conditions served as dependent variables. The results
indicated that although extensive choice proved initially more enticing than limited choice,
limited choice was ultimately more motivating. Thus, 60 percent of the passers-by approached
the table in the extensive-choice condition as compared to only 40 percent in the limited-choice
condition. However, as depicted in Figure 1, 30 percent of the customers who encountered the
limited selection actually purchased a jam, while only 3 percent of those offered the extensive
selection made a purchase.
Figure 1 here
This study’s results challenge a fundamental assumption underlying classic psychological
theories of human motivation and economic theories of rational-choice; that is, that having more
choice is necessarily more desirable and intrinsically motivating. These findings from this study
show that an extensive array of options can at first seem highly appealing to consumers, yet it
also can reduce subsequent motivation to purchase the product. Even though consumers
presumably shop at this particular store in part because of the large number of selections
available, having “too much” choice seems nonetheless to have hampered their later motivation
to buy.
Subsequent laboratory experiments not only support the “choice overload” hypothesis,
but they also provide insight into the potential mediators of this hypothesis (Iyengar and Lepper,
2000). In one experiment, this time involving displays of Godiva chocolate, participants once
again encountered either a limited or an extensive array of option, and were asked to make a
choice. Unlike the jam study, however, before being given the opportunity to sample the
selection they had made, choosers’ expectations about their choices were assessed. Participants
provided predictions about how satisfied they would be with their stated preference— whether
they expected the choice they made to be merely “satisfactory,” or “among the best.” After
making their choices, participants were asked to provide ratings of their enjoyment, difficulty,
and frustration during the choice-making process. Later, after sampling their choices, they again
provided ratings of satisfaction and regret.
Study participants either sampled a chosen Godiva chocolate from a limited selection of
6, or an extensive selection of 30. At the time they made their choices, participants reported
enjoying the process more when choosing from the display of 30 chocolates as opposed to the
display of 6. Subsequently, however, participants choosing from the selection of 6 proved more
satisfied and more likely to purchase chocolates again, as compared to participants choosing
from a selection the 30. Collectively, these results suggest that choosers may experience
frustration with complex choice-making processes, and that dissatisfaction with their choices—
stemming from greater feelings of responsibility for the choices they make—may lead to a lower
willingness to commit to one choice.
It is not that people are saddened by the decisions they make in the face of abundant
options, but rather that they are rendered unsure, burdened by the responsibility of choosing
optimally. In theory, the burden of choosing experienced by choosers in these studies should
have been insignificant, since the task of choosing among chocolates or jams is less about
distinguishing between “right” and “wrong” choices and more about the identification of
personal preferences. Nevertheless the findings demonstrate that the offer of overly extensive
choices in relatively less consequential choice-making contexts can have significant
demotivating effects. Participants in both the jam and chocolates studies proved less likely to
buy these products when confronted with an overwhelming array of choices.
Perhaps the phenomenon of choice overload may be further exacerbated by contexts in
which (a) the costs associated with making the “wrong” choice, or even beliefs that there are
truly “wrong” choices, are much more prominent; and/or (b) substantial time and effort would be
required for choosers to make truly informed comparisons among alternatives. The more
choosers perceive their choice-making task to necessitate expert information, the more they may
be inclined not to choose. In such cases, in fact, they may even surrender the choice to someone
else— whom then presumably see as more expert (de Charms, 1968; Deci and Ryan, 1985;
Langer and Rodin, 1976; Lepper, 1983; Malone and Lepper, 1987; Schulz, 1976; Taylor, 1989;
Zuckerman et al., 1978). In Schwartz’s (1994) terms, one important paradox confronting the
modern world is that as the freedom of individuals expands, so too does people’s dependence on
institutions and on other people.
The Effect of Choice Overload on 401(k) Plan Contributions
Given that the choice overload phenomenon was observed in less consequential choice-
making contexts (i.e. when choosing jams and chocolates), to what extent might it also hold for
major life decision-making situations? To test its presence in more consequential decision-
making, we examined employee’ decisions about whether—and how much—to participate in the
401(k) retirement benefit plan offered to them by their employers. The ramifications of
employee investment decisions are potentially life-changing. Contributions to the 401(k) protect
employees’ income from being taxed, thus allowing employees to save more for their retirement.
Moreover, employers often match employee contributions to the 401(k). One might have
predicted participation rates to be at an all-time high, given the plethora of options available to
employees and the ease with which many employees can transfer funds using the internet. In
fact, from 1998 to 2001, the average 401(k) plan has boosted its available investment options by
21 percent (Mottola and Utkus, 2003).
A Hewitt Associates survey as cited in The Washington Post shows that participation in
401(k) plans dropped to 68.2 percent of workers at the end of 2002, from 71 percent a year
earlier (Washington Post, 2003). Additionally, the average 401(k) participant contributes less
than seven percent of pre-tax salary, even though financial advisors encourage a contribution of
ten percent or more of pre-tax salary (Financial Planning Association, 2002). Why are
participation rates so low, despite an ever- increasing array of plan offerings? Could it be that
the provision of more 401(k) plan options does not have a positive effect on employee
willingness to participate in a plan? Instead, does the consequentiality of the investment
decision, combined with employee intimidation by the complex details of the various plan
offerings, contribute to a pronounced choice overload effect, resulting in a greater likelihood of
investors choosing not to choose?
We test this hypothesis by examining 401(k) participation rates among clients of the
Vanguard Group, an investment management company. The firm provided records of
contributions to 401(k) plans at both the plan and individual levels for the year 2001. We
identified employees as participants in the 401(k) plans if they contributed any part of their
salary to the plan. We made no distinctions among participants based on the amount they
contributed as long as it was above $0. Those employees who chose not to contribute any part of
their salary to a 401(k) were designated non-participants. The sample included 926,104 records
for 899,631 employees of 647 plans in 69 industries. We excluded any employee hired after
January 1, 2001 (10 percent), who was less than 18 years old (0.02 percent), or whose annual
salary was less than $10,000 or above $1,000,000 (7.51 percent), leaving an analysis group of
793,794 people. The records identified 442,544 of these people as male and 264,471 as female,
and the mean age was 43. The mean and median salaries were $61,150 and $47,430 respectively.
Over 71 percent of the employees contributed positive amounts to tax-deferred accounts in 2001,
and 75 percent of the accounts had positive balances in tax-deferred accounts. The savings rate
was 5.2 percent, and 12.2 percent of 401(k) participants contributed the maximum amount in
2001(which was an annual limit of $10, 500).
We analyzed how individual and plan characteristics affect individual participation, and
in particular, whether more funds offered correlated negatively with participation rates. The
empirical regression examined the effect of the number of offered funds (which ranged from 2 to
59) on the employee likelihood of participating in the 401(k) plan.1 Our regressions controlled
for both employee and plan level characteristics.2 Employee-level data is particularly important
because it is generally inappropriate to estimate a relation on an aggregate level and then infer
that an analogous relation holds at the individual level. For example, our data shows that at plan
level, a $10,000 increase in average compensation, everything else equal, would increase average
contribution by $480, while at the individual level, the same coefficient is $907. In some cases,
even the sign of certain factors could be reversed (C.F., 2001).
The regressions, controlled for several employee attributes: annual compensation in
$10,000 (COMP); gender (FEMALE); age in years (AGE); the wealth rank (1 to 24) of the nine-
digit zip code neighborhood where the individual lives, WEALTH);3 and the length (in years) of
the individual’s tenure with the current employer. Plan-level attributes for which we controlled
were: average compensation in $10,000 (COMP_MEAN); average age (AGE_MEAN); average
tenure (TENURE_MEAN); average wealth rank (WEALTH_MEAN); number of employees in
natural logo (NEMPLOY); the rate of web registration among participants in the plan in
percentage points (WEB); a variable indicating whether the plan allowed individuals to take
loans out of their tax-deferred savings. Some 541 plans covering 88 percent of the employees
offered loans, and about 17 percent of those employees had a positive loan balance at the end of
2001, with a median loan balance of $4,373. Also controlled was the rate (in percentage points)
at which employers matched employee contributions (MATCH); and a variable indicating
whether the company’s own stock was offered. There were 125 plans covering 59 percent of the
employees in this population who were offered company-owned stock (COMPSTK). Most
importantly, the number of funds offered (NFUNDS) was a key regressor.
As shown in Table 1, if a plan offered more funds, this depressed probability of employee
401(k) participation. Other things equal, every ten funds added was associated with 1.5 percent
to 2 percent drop in participation rate. Figure 2 illustrates the decline of participation rates as a
function of number of funds offered, controlling for all other variables listed in Table 1 (by
setting them at their mean values). If there were only two funds offered, participation rates
peaked at 75 percent, but when there were 59 funds offered, participation rates dipped to a low of
approximately 60 percent. The majority of the plans included in this data set offered between 10
and 30 options, yet Figure 2 shows that plans offering (fewer than 10 plans) had significantly
higher employee participation rates. Although the number of plans that offered between 30 and
60 options was few, there is a distinctive trend, which suggests that the decline in participation
rates is exacerbated as offerings increased further.
Table 1 and Figure 2 here
While other researchers have considered some of the issues covered here, our results are
particularly compelling because of the size and nature of the data used, namely actual employee
records (including non-participants’ records) from hundreds of 401(k) plans. Our findings have
important implications for sponsors designing investment menus for 401(k) plans, as well as for
policymakers considering private accounts within Social Security. Both sponsors and
policymakers may intuitively feel that limiting the number of options to a manageable few is
desirable based on considerations such as the demographics of participants/employees, their
investment knowledge or experience, and the complexity of investment decision-making
generally or from the options themselves. Our research provides a quantitative basis for this
Recently, there has also been a trend to offer "fund windows" or "brokerage accounts," in
which employees are offered hundreds or thousands of securities. A fund window is an
investment structure that significantly expands 401(k) plan investment choices by allowing
participants to choose from funds beyond their main investment options. Although record-
keeping for assets in the fund window is usually performed on the same system as the main
401(k) investments, the funds in the window are considered distinct from the main options.
(Hewitt Associates, 2001). With brokerage accounts, employees are permitted to trade virtually
any U.S. stock, bond, or mutual fund; the problem, of course, is if they are not informed, they
run the risk of investing rashly.
Plan providers who continue to present participants with a plethora of options including
brokerage accounts and fund windows might perhaps consider "tiering" the options. This could
include focusing communication activities on a core set of investment options, with more limited
information about the larger number of choices (or perhaps just a reference to where the
information can be found –e.g. a website). As an example, a plan could offer two tiers of
investments including ten main funds in Tier I, and 60 in the fund window in Tier II. Another
possibility, rather than offering a menu of 100 or 1000 options, is to present participants with a
menu of 10 options plus one -- with the last being "many more choices."
Pension fiduciary law requires the plan sponsor to investigate fund options, provide
manageable choices to employees, and offer educational programs through which employees can
verse themselves in their options. Yet often employees fail to avail themselves of the necessary
information. Industry evidence indicates that half of all these participants never contact their
money managers in any given year, and those who do tend to be affluent, higher-balance
participants. Perhaps in attempting to provide employees with a generous number of 401(k)
options, employers may actually intimidate rather than induce employees to invest in personal
retirement plans. One way to combat the dangers of choice overload in which employees
“choose not to choose,” is to implement for “libertarian paternalism,” a phrase recently coined to
describe institutional efforts to affect individuals’ behavior while respecting their freedom of
choice. Sunstein and Thaler (2003) who develop this notion, propose that people’s preferences
often are ill-informed, which leads to decisions, that are unduly influenced by default rules,
framing effects, and starting points (Sunstein and Thaler, 2003). An employer aware of such
issues could react by steering employee choices in a welfare-promoting direction, yet without
eliminating their freedom of choice. In the present case, the libertarian paternalist employer
would design the plan carefully so as not to offer too much choice to employees. In order to
ensure that employees engage in some form of retirement savings, the employer might declare a
“standard” or default 401(k) plan into which workers are automatically enrolled, if they do not
elect to opt out. While this is currently permitted by US pension regulation, but it may actually
be dictated by the tenets of libertarian paternalism.
de Charms, Richard. 1968. Personal Causation. New York: Academic Press.
Deci, Edward L. 1981. The Psychology of Self-determination. Lexington, MA: Heaths.
Deci, Edward. L. and R.M. Ryan. 1985. Intrinsic Motivation and Self-determination in Human
Behavior. New York: Plenum Press.
Dember, William N., Tracy L. Galinsky and Joel S. Warm. 1992. “The Role of Choice in
Vigilance Performance.” Bulletin of the Psychonomic Society 30: 201-204.
Financial Planning Association. 2002.
Hewitt Associates. 2001.
Iyengar, Sheena S. and Mark Lepper. 2000. “When Choice is Demotivating: Can One Desire
Too Much of a Good Thing?” Journal of Personality and Social Psychology 76: 995-
Langer, Ellen J. 1975. “The Illusion of Control.” Journal of Personality and Social Psychology
32: 311-328.
Langer, Ellen J. and Judy Rodin. 1976. “The Effects of Choice and Enhanced Personal
Responsibility for the Aged: A Field Experiment in an Institutional Setting.” Journal of
Personality and Social Psychology 34: 191-198.
Lepper, Mark R. 1983. “Social Control Processes and the Internalization of Social Values: An
Attributional Perspective.” In Social Cognition and Social Development, eds. E. T.
Higgins, D. N. Ruble, and W. W. Hartup. New York: Cambridge University Press: 294-
Malone, Tom W. and Mark R. Lepper. 1987. “Making Learning Fun: A Taxonomy of Intrinsic
Motivations for Learning.” In Aptitude, Learning and Instruction: Vol. 3. Cognitive and
Affective Process Analysis, eds. R. E. Snow and M. J. Farr. Hillsdale, NJ: Erlbaum: 223-
Mottola, Gary R. and Stephen P. Utkus. 2003. “Can There Be Too Much Choice In a Retirement
Savings Plan?” Vanguard Center for Retirement Research: The Vanguard Group Inc.
Malvern, PA.
Rotter, Julian B. 1966. “Generalized Expectancies for Internal Versus External Locus of Control
of Reinforcement.” Psychological Monographs 80: 1-28.
Schulz, Richard. 1976. “Effects of Control and Predictability on the Physical and Psychological
Well-being of the Institutionalized Aged.” Journal of Personality and Social Psychology
33: 563-573.
Schwartz, Barry. 1994. The Costs of Living: How Market Freedom Erodes the Best Things in
Life. New York: W. W. Norton & Company.
Sunstein, Cass R. and Richard H. Thaler. Forthcoming. “Libertarian Paternalism Is Not An
Oxymoron.” University of Chicago Law Review.
Taylor, Shelley E. 1989. Positive Illusions: Creative Self-deception and the Healthy Mind. New
York: Basic Books.
Taylor, Shelley E. and Jonathon D. Brown. 1988. “Illusion and Well-being: A Social-
psychological Perspective on Mental Health.” Psychological Bulletin 103: 193-210.
Washington Post. 2003. “401(k)s: Remember Them?” June 22, F4.
Zuckerman, Miron, Joseph Porac, David Lathin, R. Smith and Edward L. Deci. 1978. “On the
Importance of Self-Determination for Intrinsically Motivated Behavior.” Personality and
Social Psychology Bulletin 4: 443-446.
Limited Choice
Extensive Choice
Figure 1. Comparison of Jam Sampling vs. Purchasing in Limited and Extensive Choice
White bars = Percentage of passers-by who approached the tasting booth
Striped bars = Percentage of “approachers” who subsequently purchased jam
Source: Iyengar and Lepper (2000)
# Funds Offered
Figure 2. The Relation between Participation and Number of Funds Offered
Notes: The graph plots the relation between the plan participation rate. Explanatory variables
except the number of funds offered are set at their respective mean values and the number of
funds offered using a two-stage parametric estimation method. The dotted lines represent the
95% confidence intervals.
Source: Authors’ analyses
Table 1. Determinants of Individual Participation in Defined Contribution Plans (2001)
DepVar: Plan Participation rate (%)
Linear Probability Probit
Regressions Within-Between Log-Linear Linear
(1) (2) (3) (4) (5) (6)
197.44 -6.13 -216.88 -6.26
206.39 -5.73
278.13 -6.22
114.88 ---
172.37 -41.23 --
A. Individual Characteristics
COMP 15.12 0.162 22.19 0.190 15.00 0.175 15.19 0.101 57.00 0.406 15.31 7.84 0.068 2.54
FEMALE 5.73 0.406 7.74 0.809 4.35 0.879 6.12 0.108 19.57 0.401 5.26 17.60 0.375 5.71
AGE 0.47 0.078 0.38 0.091 0.39 0.123 0.47 0.048 1.10 0.132 0.29 2.09 0.124 0.68
AGE^2 -0.01 0.002 0.00 0.000 0.00 0.000 -0.01 0.001 -0.01 0.001 0.00 -0.02 0.001 -0.01
WEALTH 5.96 0.049 -- -- 5.91 0.064 5.91 0.034 23.29 0.142 6.25 2.9 0.056 0.94
TENURE 1.28 0.080 1.32 0.101 1.17 0.132 1.22 0.045 4.63 0.067 1.24 5.10 0.063 1.65
TENURE^2 -0.03 0.002 -0.03 0.003 -0.03 0.005 -0.03 0.001 -0.11 0.002 -0.03 -0.12 0.002 -0.04
B. Plan Policy Variables
LOANS -3.69 3.765 -2.67 44.500 -- -- -1.02 3.778 -12.9 0.639 -3.46 -4.58 0.607 -1.49
MATCH 0.18 0.015 0.18 0.015 -- -- 0.18 0.017 0.68 0.007 0.18 0.59 0.006 0.19
COMPSTK 2.89 1.338 2.94 1.598 -- -- 3.11 1.139 6.46 0.423 1.74 7.45 0.406 2.42
NFUNDS -0.2 0.083 -0.17 0.058 -- -- -0.21 0.077 -0.61 0.037 -0.16 -0.57 0.034 -0.19
C. Plan-Level Controls
COMP_MEAN -1.09 3.759 -0.72 -1.014 3.75 4.808 3.20 5.000 -10.63 0.756 -2.86 2.35 0.123 0.76
WEALTH_MEAN 0.69 2.300 -- -- -0.90 2.903 -0.69 2.654 4.88 0.424 1.31 -3.98 0.219 -1.29
Table 1 Continued
AGE_MEAN 1.47 0.274 1.55 0.463 1.04 0.486 1.31 0.376 4.41 0.096 1.18 4.36 0.088 1.41
TENURE_MEAN -1.06 0.275 -1.20 0.423 -0.82 0.371 -1.08 0.282 -3.52 0.074 -0.95 -3.64 0.069 -1.18
WEB 0.07 0.063 0.14 0.059 0.17 0.063 0.14 0.059 0.29 0.022 0.08 0.71 0.019 0.23
NEMPLOYEES -2.88 0.331 -3.29 0.593 -3.37 0.832 -3.73 0.789 -9.23 0.119 -2.48 -10.82 0.110 -3.51
R-sqr 0.19 0.16 0.18 0.16 0.18 0.33 0.12 0.23
Note: The all-sample participation rate is 70.8%. All coefficients are multiplied by 100. Columns (1) to (4) are results from a
linear probability model. COMP and WEALTH are expressed in dollars. The standard errors are obtained by bootstraps (50
replications) that adjust for both heteroskedasticity (both within and across groups, and group-specific disturbances) and within
group correlation (due to the group-specific disturbance). Columns (5) and (6) report results from Probit estimation. Pseudo
R-squared and incremental probability of correct prediction are reported for goodness-of-fit. Marginal probabilities are
calculated by setting all non-dummy variables at their mean values, and all dummy variables at zero. In column (6), COMP is
expressed in $10,000, and WEALTH is expressed in IXI ranks from 1 to 24. The number of observations is 793,794.
Source: Authors’ Computations
1 Strictly speaking, we lack data on the total number of funds offered by each plan, so we
approximate it by counting the number of funds used by at least one participant in each plan. As
a result, the number of funds offered could be under estimated for plans with few employees
and/or with low participation ratios. Given that the average plan in our sample had 1,486
employees, the measurement error should be minimal. If a bias arises from this approximation, it
will bias against finding a demotivating effect of more choices.
2 Specifically the following empirical equation was estimated:
ij ij j j j ij
ij ij
vify v
=+ + + ++
uv uv
Here, *
y is the desired contribution made by individual i in plan j. ij
y is the observed
contribution which is doubly censored at 0v
and 10,500v
. There are three sets of
regressors. ij
is a set of individual characteristics variables; j
represents the plan-level
averages of individual characteristics; and j
is a set of plan policy variables. The disturbance
can be decomposed into a plan-specific error, j
, assumed uncorrelated across difference plans,
and an individual disturbance, ij
, which is independently distributed across individuals. Both j
and ij
could be heteroskedastic across different plans and/or individuals, but are assumed to be
independent of the regressors. From an economic analysis perspective, the meaningful
contribution is the "desired contribution," and not necessarily the observed one. For example, if
next year the 401(k) contribution cap is raised from $12,000 to $15,000, those who are currently
contributing $12,000 would likely contribute more because their desired contribution is greater
than the observed level. Personal and plan attributes both determine desired contribution, but the
latter is only partially observed.
3 A company called IXI collects retail and IRA asset data from most of the large financial
services companies, Vanguard being one of them. IXI then aggregates the data from all the
companies at the Zip+4 level. IXI divides the total of retail and IRA assets in each Zip+4 by the
number of households (based on US Census data) to determine the average assets for each
Zip+4. This enables IXI to assign a code (from 1 to 24) at the Zip+4 level which indicates about
how much money in investable assets people living in each a particular Zip+4 have. A Zip+4
has, on average, about 10 to 12 houses in it. So, the IXI system works under the premise that
peoples’ financial situation is similar to that of their immediate neighbors, which is a reasonable
premise. Further, using the wealth level of the neighborhood, instead using that of the individual
under consideration, eliminates spurious correlation between current contribution and
accumulated wealth. The term 'wealth' used here includes bank, brokerage, and mutual fund
investment assets.
... Choice overload occurs when individuals would be better off with fewer options as the overload overwhelms them and typically leads to them either not deciding or making a sub-optimal choice (Schwartz 2004). This phenomenon has been shown to reduce 401(k) plan participation and lead to a lack of retirement savings and investing (Iyengar et al. 2004). Target Date Funds (TDFs) were created to help overcome this indecisiveness and choice overload (Investment Company Institute 2014). 1 The Pension Protection Act of 2006 had implications for retirement plans. ...
Full-text available
Target Date Funds (TDFs) have become the default investment choice in retirement accounts for most households. Later-dated TDFs (e.g., further away from the present day) allocate a more significant percentage of each dollar invested into equities relative to fixed income. As the TDF moves closer to the designated retirement date, the TDF embarks on its’ glide path. We study the impact of the COVID-19 Pandemic and Federal Reserve intervention on the max drawdowns experienced by TDFs during 2020. Later-dated funds experienced more significant drawdowns relative to near-dated funds. Moving out one target date fund increased the drawdown by approximately 1.90%. Approximately 80% of TDFs experienced their max drawdown on 23 March 2020. The max drawdowns of the TDFs are then studied in the following three sub-periods: (1) before the first Federal Reserve Intervention (2 March 2020), (2) after the first intervention and before the second intervention (16 March 2020), and (3) the period after the second intervention. TDFs experienced the greatest drawdowns after the first intervention by the Federal Reserve (approximately 19%) relative to the other two periods (approximately 7%). Fees associated with the TDFs tend not to influence the drawdowns except for the near-dated funds, where the low-fee funds performed better. Finally, near-dated funds recovered from their max drawdowns around September 2020, whereas later-dated funds did not fully recover until December 2020.
... Another effect of decision-making cost minimization is the negative effect on consumption of too many choices that has been analyzed under the label of "the paradox of choice" (Schwartz, 2004). It has been observed that too many choices increase decision costs, demotivating potential adopters; this phenomenon has been observed in many markets such as financial products (Iyengar et al., 2004) and food (Iyengar and Lepper, 2000). As a consequence, firms try to reduce the number of versions of the same products (Osnos, 1997;Goldstein et al., 2007). ...
Full-text available
Why is it that both complex and simple solutions that have proved to be effective have low rates of adoption? The literature on innovation (i.e., a specific category of solutions) management has provided some clues, identifying barriers of several types: organizational, technological, economic, human behavior and the nature of the innovation. We suggest that one reason is the misalignment between the degrees of complexity i.e., the degree of knowledge embedded, of the problem and its solution. A solution perceived to be too simple for a complex problem falls into the category of what might be called “Columbus' egg”. At the basis of this effect there is the tendency to minimize expected frustration as the difference between the effort made in looking for a solution and the obtained reward. When the solution is too complex for a simple problem, this is the case of the “Engineer's effect”. This effect has its cognitive underpinnings in the tendency to minimize decision-making costs. We discuss and illustrate these phenomena and propose some guidelines for technology developers and product innovation managers, as well as for forecasting solutions adoption.
We consider a model of product differentiation where consumers are uncertain about the qualities and prices of firms' products. They can inspect all products at zero cost. A share of consumers is expectation-based loss averse. For these consumers, buying products of varying quality and price creates disutility from gain-loss sensations. Even at modest degrees of loss aversion they may refrain from inspecting all products and choose an individual default that is strictly dominated in terms of surplus. Firms' strategic behavior exacerbates the scope for this effect. The model generates “scale-dependent psychological switching costs” that increase in the value of the transaction. They imply that making switching easier or costless for consumers would not motivate more switching.
This paper studies how an optimal menu chosen by a social planner depends on whether agents receive imperfect signals about their true tastes (imperfect self-knowledge) or the properties of available alternatives (imperfect information). Under imperfect self-knowledge, it is not optimal to offer fewer alternatives than the number of different tastes present in the population, unless noise is infinite (agents have no clue about their true preferences). As noise increases, the social planner offers menu items that are closer together (more similar). However, under imperfect information, as noise increases, it could be optimal to construct a menu with more distinct alternatives, restrict the number of options, or, for some finite noise, offer a single item.
This essay uses concepts from Adam Smith’s The Theory of Moral Sentiments to develop ideas about choice and welfare. I use those ideas to offer several challenges to common approaches to behavioral welfare economics and new paternalist policy making. Drawing on Smith’s dialectical concept of practical reason, which he develops in expositing ideas about self-awareness and self-judgment, I first argue that inconsistency need not be viewed as pathological. Inconsistent choices might indicate legitimate context-dependencies as individuals reflect over disjointed perspectives and act accordingly. Understanding inconsistency as reasonable raises epistemic difficulties for identifying errant choices and designing corrective policies. Second, I draw on Smith’s theory of the impartial spectator to discuss dynamic aspects of welfare. Welfare is not simply a matter of preference satisfaction but involves a sense of progress and improvement towards better preferences. Smith’s account suggests that economists interested in welfare should focus on institutional arrangements that facilitate self-development.
en The European regulatory landscape for digital markets is undergoing a transformative change. There is an observed shift toward the protection of public values and fundamental rights, as the market mechanism and market values that traditionally led regulatory processes in digital markets seem to have fallen short. In the context of the user-centric digital economy, a clear commitment to safeguarding citizens' interests is ever-more salient. This article provides a comprehensive account of hypernudging—dynamically personalized user steering, which represents the next generation user influencing techniques online, with the potential to lead to multifaceted individual and collective harms. However, problematizing the phenomenon for digital policy purposes is not a straightforward task. Due to the complexity and opaqueness of its underlying mechanisms and effects, policymakers are operating under conditions of uncertainty, necessitating a shared understanding of what impact hypernudging has on users as well as crafting a shared vision of values that ought to be embedded and safeguarded in digital choice architectures. To highlight the developing European approach in relation to hypernudging, the assessment of the recent legislative initiatives—the Artificial Intelligence Act, the Digital Markets Act, and the Digital Services Act—showcases underlying learning opportunities for addressing emergent challenges. 摘要 zh 欧洲数字市场的监管环境正经历转型变革。鉴于传统上主导数字市场监管过程的市场机制和市场价值似乎已无法满足期望,因此出现了可见的转变,用于保护公共价值观与基本权利。在以用户为中心的数字经济背景下,保护公民利益的明确承诺变得更加突出。本文全面叙述了超助推(hypernudging)——动态个性化的用户引导,代表了下一代用户在线影响技术,并有可能导致多方面的个体和集体危害。不过,出于数字政策目的将此现象问题化,并不是一项简单的任务。由于其潜在机制和影响的复杂性和不透明性,政策制定者在不确定的条件下作决策,这需要就超助推对用户的影响达成共识,并制定一个共享的价值观愿景,后者应在数字选择架构中被嵌入和保护。为了强调正在开发的欧洲方法(与超助推相关),评估近期立法倡议——《人工智能法案》、《数字市场法案》与《数字服务法案》——一事展示了用于应对紧急挑战的潜在学习机会。 Resumen es El panorama regulatorio europeo para los mercados digitales está experimentando un cambio transformador. Se observa un cambio hacia la protección de los valores públicos y los derechos fundamentales, ya que el mecanismo de mercado y los valores de mercado que tradicionalmente lideraron los procesos regulatorios en los mercados digitales parecen haberse quedado cortos. En el contexto de la economía digital centrada en el usuario, un claro compromiso con la salvaguarda de los intereses de los ciudadanos es cada vez más destacado. Este artículo proporciona una descripción completa del hypernudging: la dirección del usuario dinámicamente personalizada, que representa las técnicas de influencia del usuario de próxima generación en línea, con el potencial de conducir a daños individuales y colectivos multifacéticos. Sin embargo, problematizar el fenómeno con fines de política digital no es una tarea sencilla. Debido a la complejidad y la opacidad de sus mecanismos y efectos subyacentes, los formuladores de políticas operan en condiciones de incertidumbre, lo que requiere una comprensión compartida del impacto que tiene el hypernudging en los usuarios, así como la elaboración de una visión compartida de los valores que deben integrarse y salvaguardarse en digital. arquitecturas de elección. Para resaltar el enfoque europeo en desarrollo en relación con el hypernudging, la evaluación de las iniciativas legislativas recientes (la Ley de Inteligencia Artificial, la Ley de Mercados Digitales y la Ley de Servicios Digitales) muestra oportunidades de aprendizaje subyacentes para abordar los desafíos emergentes.
Full-text available
Many everyday life decisions require allocating finite resources, such as attention or time, to examine multiple available options, like choosing an online food supplier. In these cases, our search resources can be spread across many options (breadth) or focused on a few of them (depth). Whilst theoretical work has described how finite resources should be allocated to maximise utility in these problems, evidence about how humans balance breadth and depth is lacking. We introduce a novel experimental paradigm where humans make a many-alternative decision under finite resources. In an imaginary scenario, participants allocate a finite budget to sample amongst multiple apricot suppliers in order to estimate the quality of their fruits, and ultimately choose the best one. We found that at low budget capacity participants sample as many suppliers as possible, and thus prefer breadth, whereas at high capacities participants sample just a few chosen alternatives in depth, and intentionally ignore the rest. The number of alternatives sampled increases with capacity following a power law with an exponent close to 0.75. In richer environments, where good outcomes are more likely, humans further favour depth. Participants deviate from optimality and tend to allocate capacity amongst the selected alternatives more homogeneously than it would be optimal, but the impact on the outcome is small. Overall, our results undercover a rich phenomenology of close-to-optimal behaviour and biases in complex choices.
We study the impact of changing choice set size on the quality of choices in health insurance markets. Using novel data on enrollment and medical claims for school district employees in the state of Oregon, we document that the average employee could save $600 by switching to a lower cost plan. Structural modeling reveals large “choice inconsistencies” such as non-equalization of the dollar spent on premiums and out of pocket, and a novel form of “approximate inertia” where enrollees are excessively likely to switch to other plans that are close to the current plan on the plan design spreadsheet. Variation in the number of plan choices across districts and over time shows that enrollees make lower-cost choices when the choice set is smaller. We show that a curated restriction of choice set size improves choices more than the best available information intervention, partly because approximate inertia lowers gains from new information. We explicitly test and reject the assumption that this is because individuals choose worse from larger choice sets, or “choice overload”. Rather, we show that this feature arises from the fact that larger choice sets feature worse choices on average that are not offset by individual re-optimization.
We introduce a risk‐reduction‐based procedure to identify a subset of funds with a resulting opportunity set that is at least as good as the original menu when short‐sales are imposed. Relying on Wald tests for mean‐variance spanning, we show that the better results for the subset can be explained by a higher concentration of covariance entries between its assets, ultimately leading to smaller Frobenius norms of the associated matrices. With data on U.S. defined contribution plans, where participants have limited financial literacy, tend to be overwhelmed and prefer to make decisions among fewer choices, we obtain a 75% average reduction. This article is protected by copyright. All rights reserved.
Full-text available
Yoked pairs of subjects solved puzzles such that one member of each pair was given choice about what puzzles to work on and how much time to allot to each, while the yoked subject was assigned the same puzzles and time allotments as those chosen by the first subject. It was predicted and found that subjects who chose the activities and time allotments -in other words, who had additional self-determination--would be more intrinsically motivated than subjects doing the same activity without choice.
I: Background.- 1. An Introduction.- 2. Conceptualizations of Intrinsic Motivation and Self-Determination.- II: Self-Determination Theory.- 3. Cognitive Evaluation Theory: Perceived Causality and Perceived Competence.- 4. Cognitive Evaluation Theory: Interpersonal Communication and Intrapersonal Regulation.- 5. Toward an Organismic Integration Theory: Motivation and Development.- 6. Causality Orientations Theory: Personality Influences on Motivation.- III: Alternative Approaches.- 7. Operant and Attributional Theories.- 8. Information-Processing Theories.- IV: Applications and Implications.- 9. Education.- 10. Psychotherapy.- 11. Work.- 12. Sports.- References.- Author Index.