How Much Choice is Too Much?:
Contributions to 401(k) Retirement Plans
Sheena S. Iyengar
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
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.
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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)
COEF t COEF t COEF t COEF t COEF t
Pr COEF t
197.44 -6.13 -216.88 -6.26
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
=+ + + ++
y is the desired contribution made by individual i in plan j. ij
y is the observed
contribution which is doubly censored at 0v
. There are three sets of
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
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