Research
Financial Literacy Education
The Effects of Financial Education in the Workplace: Evidence from a Survey of Employers, Stanford University, 1996, Bayer, Bernheim, & Scholz
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ABSTRACT
We examine the effects of education on financial decision-making skills by identifying an interesting
source of variation in pertinent training. During the 1990s, an increasing number of individuals were exposed
to programs of financial education provided by their employers. If, as some have argued, low saving
frequently results from a failure to appreciate economic vulnerabilities, then education of this form could
prove to have a powerful effect on rates of behavior. The current paper undertakes an analysis of these
programs using a previously unexploited survey of employers. We find that both participation in and
contributions to voluntary savings plans are significantly higher when employers offer retirement seminars.
The effect is typically much stronger for non-highly compensated employees than for highly compensated
employees. The frequency of seminars emerges as a particularly important correlate of behavior. We are
unable to detect any effects of written materials, such as newsletters and summary plan descriptions,
regardless of frequency. We also present evidence on other determinants of plan activity.
Introduction
Since the early work of Becker (1967), economists studying the returns to education have traditionally
focused on the relation between education and wages. From the perspective of the associated literature,
education creates value by conferring skills that are of use to employers. Clearly, however, this is not the sole
economic objective of education. In addition to labor market skills, education may also confer decision
making skills. Apart from any affect on labor market performance, these decision making skills may improve
an individual's ability to weigh alternatives, exploit opportunities, and achieve personal objectives.
Some of the most complex decisions undertaken by ordinary individuals concern financial issues, such
as the determination of retirement income needs, or the allocation of resources among alternative investments.
Most individuals make these decisions on the basis of their own judgement, rather than with the help of
experts, in large part because the market for financial expertise is imperfect (see Bernheim 1994a, 1996b). It
is therefore conceivable that appropriate forms of education may improve the quality of personal financial
decision-making.
Existing evidence concerning the relation between education and financial choices is quite limited.
Correlations between an individual's general level of educational attainment and his or her rate of saving have
been documented by Bernheim and Scholz (1993) and Hubbard, Skinner, and Zeldes (1995). However, as in
the literature on returns to education in labor markets, these correlations may be attributable to other related
factors. For example, individuals with greater patience presumably tend to remain in school longer, and to
save at higher rates. As noted by those studying the relation between wage and schooling (see e.g. Card,
1995), causal inferences about the effects of education are potentially misleading unless they are derived from
sources of variation in education that are plausibly exogenous.
One particularly pertinent source of variation in education concerns the availability of financial
education in the workplace. According to one recent survey, as of 1994, 88 percent of large employers offered some form of financial education, and more than two-thirds had added these programs after 1990. 1 Typically, employers provide information and guidance on a range of topics related to retirement planning.
While nearly all such programs cover principles of asset allocation, sizable majorities treat retirement income
needs (73 percent) and retirement strategies (88 percent). 2 If, as argued by Bernheim (1994a, 1995a), low
saving frequently results from a failure to appreciate economic vulnerabilities, then education of this form
could prove to have a powerful effect on rates of saving.
It is doubtful that the availability of employer-based retirement education is entirely unrelated to
workers' underlying predispositions to save. However, there are a variety of reasons (discussed below) to
believe that employers adopt these programs as remedial measures in instances where employees are
disinclined to save. If this is the case, then cross-sectional estimates of the relation between saving and
education may provide lower bounds on the causal effects of education. In addition, since many of these
programs have been adopted quite recently, it may be possible to control for an unobserved predisposition to
save by contrasting the behavior of the same individuals before and after educational interventions.
In this paper, we study the behavioral effects of financial education in the workplace using survey data
collected from employers who sponsor pension plans. Our analysis is based in part on estimates of the crosssectional
relations between various forms of education and plan activity. Since the data contain repeated
observations on many firms, they also permit us to evaluate the direction of the probable bias in crosssectional
estimates by testing the hypothesis that educational is remedial (through an examination of the
circumstances under which programs are adopted or expanded). Moreover, the longitudinal data allow us to
control explicitly for unobserved (firm-level) fixed effects.
Despite the growing importance of employer-based retirement education, existing evidence on this topic is largely confined to qualitative surveys and case studies (see e.g. Employee Benefit Research Institute,
1994, 1995, A. Foster Higgins & Co., Inc., 1994, Borleis and Wedell, 1994, or Geisel, 1995). One exception
is Bernheim and Garrett (1996), who use a novel household survey to study the effects of these programs.
Their analysis is complementary to the current paper; we discuss the relations between these studies in greater
depth below.
The remainder of this paper is organized as follows. After describing our data (section 2), we provide
an analysis of the circumstances under which employers offer retirement education (section 3). While certain
kinds of education are more common at organizations that offer self-directed pension plans (such as 401(k)s
and 403(b)s), even employers that offer defined benefit plans (and nothing else) frequently provide some
form of financial education. For 401(k) plans in particular, the data indicate that low participation among
non-highly compensated employees is a strong predictor of the adoption and/or enhancement of educational
offerings. At least in the context of 401(k) plans, education therefore appears to be remedial, in the sense
that it is made available to those who are least inclined to save. In part, this may be a consequence of nondiscrimination
requirements, which limit contributions of highly compensated employees as a function of
contributions by non-highly compensated employees. Based on this finding, one would expect crosssectional
estimates of the relation between participation (contributions) and education to be biased against the
conclusion that education enhances participation and contributions to self-directed plans.
In section 4, we examine factors correlated with participation in and contributions to 401(k) plans. We
find that both measures of activity are significantly higher when employers offer retirement seminars. The
effect is much stronger for non-highly compensated employees than for highly compensated employees. The
frequency of seminars emerges as a particularly important correlate of behavior. We are unable to detect any
effects of written materials, such as newsletters and summary plan descriptions, regardless of frequency. We
obtain similar results based on longitudinal patterns, as well as for an assortment of estimation methods. In
light of the likely bias mentioned in the previous paragraph and discussed in more detail in section 3, these findings are strongly consistent with the efficacy of retirement seminars, and they do not rule out the
possibility that other forms of education are also effective.
In studying the relation between 401(k) activity and education, we control for a variety of plan features.
The effects of these features are, of course, of independent interest, and have been the subject of several prior
analyses (see Poterba, Venti, and Wise, 1994, Papke, Petersen, and Poterba, 1993, Papke, 1995, Andrews,
1992, Kusko, Poterba, and Wilcox, 1993, and Scott, 1994). Generally, we find that the existence of an
employee match is strongly related to 401(k) contributions, and especially to participation, in cross-sections.
However, this effect is not readily apparent in longitudinal data. There is relatively little indication that any
measure of 401(k) activity is significantly related to loan provisions. Investment options have no detectable
effect on participation, but contributions tend to be a bit higher when greater flexibility is offered.
The paper closes with a brief conclusion.
2. Data
The data for our analysis come from the 1993 and 1994 versions of the KPMG Peat Marwick
Retirement Benefits Survey. In 1993, KPMG Peat Marwick selected approximately 1100 employers at
random from a list of all the private and public employers in the United States with at least 200 employees. If
they were willing to participate again, these same employers were retained for the 1994 survey. Any
employers who declined to participate in 1994 were replaced with a randomly selected employer from the
same industry, region, and employer-size category.
In each year, these employers were questioned by telephone about the administration, features, and
employee utilization of their retirement plans. Some basic employer data, such as total employees, sales, and
industry, are available for all respondents. In addition, those employers who have a retirement plan (910 in
1993 and 861 in 1994) provide some general information about their plan, including the number of
employees covered by the plan, the types of plans offered, and the extent to which financial education and guidance is provided by the employer to help employees invest for retirement. Furthermore, for each type of
retirement plan that a firm offers, the survey contains detailed questions about its features, eligibility
requirements, and employee activity.
Those employers who offer 401(k) plans (596 in 1993 and 566 in 1994) report the features of their
plan, including the availability of an employer match, the matching rate provided, whether hardship
withdrawals and loans are permitted, and the number and type of investment options available to a participant
in the plan. The survey also allows us to determine which employee groups, such as union, salaried, or parttime
employees, are eligible to participate in the plan. In addition, participation and contribution rates are
provided for the employees eligible for the 401(k) plan. Thus, for a large sample of over 500 firms each year,
the survey provides a rich set of plan characteristics and utilization rates. The variables that we focus on in
this study fall into three categories: basic firm characteristics (where the firm is the unit of analysis for the
study); general plan characteristics, encompassing all retirement plans offered by the firm; and 401(k) plan
characteristics.
With respect to the first category, we experimented with a number of basic firm characteristics
(including sales and dummy variables for industry and region), but generally found that they had very little
effect on our results. For most of the results presented in this paper, we have retained only one general firm
characteristic: the total number of employees. 3
The second group of variables includes general features of the firm's retirement programs. The most
important of these describe the extent to which the firm provides financial education to its employees.
Specifically, the survey asks each respondent how often the firm provides summary plan descriptions,
employee newsletters or other periodic publications, investment seminars for all employees, seminars for
employees over age 50, and seminars for employees within a year or two of retirement. Each respondent was
asked whether the firm used these devices often, sometimes, rarely, or never. To incorporate the qualitative nature of these responses into our analysis, we use these responses to create three dummy variables for each
educational device. The first indicates whether the device is used often, the second indicates whether it is
used sometimes or rarely, and the third indicates it is never used. We combine the responses "sometimes"
and "rarely" because the data have limited ability to identify educational parameters, and since the subjective
distinctions between these responses seem the most likely to differ across respondents. 4
Other pertinent characteristics of an employer
s overall retirement program covered by the survey
include information on the composition of retirement plans (e.g. 401(k)s, defined benefit, profit sharing, and
so forth), and the fraction of employees who are covered by a retirement plan. Unfortunately, the survey
collects coverage information on a firm-wide basis, rather than plan-by-plan.
The final category of variables includes characteristics of 401(k) plans. These include dummy variables
for whether loans are permitted and whether an employer match is provided. We also calculate a measure of
the number of different kinds of investment options (employer stock, guaranteed income contracts, equity
mutual funds, corporate bond funds, government funds, and other funds) available to plan participants. Other
survey questions allow us to determine if certain employee groups, such as union, part-time, or salaried
employees, are eligible for the plan. 5
For 401(k) plans, we construct participation and contribution rates for eligible employees. The survey
provides measures of 401(k) plan activity for three categories of employees: all, highly compensated (HC),
and non-highly compensated (NHC). All eligible employees are classified as either HC or NHC according to specific rules set forth in the applicable non-discrimination provisions. These rules were instituted to ensure
an equitable distribution of benefits from pension plans. In the context of 401(k)s, they operate by limiting
the amounts that highly compensated employees can contribute as a function of contributions by non-highly
compensated employees. An individual is classified as highly compensated if he or she meets any of a
number of specific criteria (e.g. earnings of roughly $100,000 or more, ownership of more than 5 percent of
the company, or earnings of roughly $65,000 or more if this amount is in the top quintile of the firm
s salary
distribution). In addition to participation rates, the survey also provides contribution rates as a percentage of
salary for plan participants. 6 Once again, these figures are provided separately for all employees, HC
employees, and NHC employees. Taking the product of participation rates and average contribution rates
conditional on participation, we obtain average contribution rates conditional on eligibility.
Summary statistics for 401(k) participation and contribution rates are provided in Table 1. Mean
participation rates are slightly less than 60 percent for NHC employees, roughly 80 percent for HC
employees, and just over 60 percent overall in both 1993 and 1994. The distribution of participation rates for
HC employees is highly skewed (with outliers on the lower tail), causing the median participation rates to be
about 10 percentage points higher than the mean rates. Participating employees generally contribute between
5 and 7 percent of their salaries, with HC employees contributing approximately one percentage point more
than NHC employees. In both years, contribution rates for eligible employees averaged just under three
percent for NHC employees, over five percent for HC employees, and between three and four percent overall.
3. The Availability of Retirement Education
As a first step in our analysis, we provide descriptive information concerning the availability of different
kinds of retirement education in the workplace. Overall, in 1993 nearly 74 percent of pension plan sponsors
provided summary plan descriptions, roughly 65 percent distributed newsletters, and just over 44 percent
offered retirement seminars to all employees. When firms are weighted by total employment, summary plan
descriptions and newsletters appear to be somewhat more common (roughly 80 percent in each case), but the
frequency of seminars is essentially unchanged (44 percent). The fraction of firms providing summary plan
description was somewhat lower in 1994 than in 1993, but the fractions providing newsletters and seminars
rose slightly.
Since our ultimate objective is to evaluate the relation between education and behavior, it is important to
develop an understanding of the sources of variation in educational offerings across firms. Plan sponsors are
presumably more likely to provide information when participants are required to make decisions. It is
therefore natural to speculate that the growth of educational offerings results in large part from the rising
popularity of self-directed plans such as 401(k)s and 403(b)s (see EBRI, 1995, or the extended discussion in
section 3 of Bernheim and Garrett, 1996). Yet the KPMG Peat Marwick survey data reveal that seminars,
newsletters, and summary plan descriptions are nearly as common among firms with defined benefit plans
(43.8 percent, 68.9 percent, and 73.1 percent, respectively for 1993) as among firm with 401(k)s (44.4
percent, 71.2 percent, and 80.1 percent, respectively for 1993).
The preceding finding raises the possibility that many employers provide retirement education to
address general concerns about employees' preparation for retirement, rather than to equip them with planspecific
decision-making skills. One need not construe this as necessarily altruistic. Education may help
employees to appreciate the values of their pension plans. By promoting adequate preparation for retirement,
an employer may also hope to avoid subsequent conflicts (e.g. over demands for more generous pension
benefits) with older, poorly prepared workers. Assistance with financial planning may also enhance employee
loyalty, improve labor relations, and boost morale.
Of course, comparisons based on raw frequencies, such as those described above, may be misleading.
For example, it is common for employers to offer both a defined benefit plan and a supplemental 401(k). It is
therefore possible that the frequency of educational offerings at organizations with defined benefit plans in
part reflects the presence of secondary 401(k) plans. Also, it is conceivable that educational offerings may
differ systematically by company characteristics that are related to the presence of defined benefit plan.
To investigate this possibility, we estimate probit models explaining the availability of seminars for all
employees, seminars for employees over 50 years of age, seminars for employees nearing retirement,
summary plan descriptions, and newsletters or periodicals. Results are contained in table 2. Explanatory
variables include variables measuring the types and variety of plans (where the omitted category is "only a
defined benefit plan"), employment, plan coverage, and year. The data are pooled across years, and the
standard errors are corrected to account for potential correlation across observations from the same
organization.
Focusing attention on organizations with a single plan, it is evident that seminars of all kinds are most
common among non-profit institutions with 403(b)s. Companies with 401(k)s are more likely to offer
seminars to all employees than companies with defined benefit or other kinds of plans, but less likely to offer
seminars specifically for older employees. Written materials of all kinds are most commonly used among
companies with 401(k)s, but there are no significant differences between the likelihoods that sponsors of
other kinds of plans provide such materials. Thus, while the rising popularity of self-directed plans may have
promoted the growth of certain educational offerings, the impetus for this growth appears to be much more
general. This is consistent with the findings of Bernheim and Garrett (1996).
Table 2 also indicates that educational offerings are significantly more common among organization
with multiple plans. Employment and coverage are positively correlated with seminar offerings, but not with
the availability of written materials. This may reflect the presence of economies of scale in the provision of
seminars. Generally, the frequencies of educational offerings did not change appreciably between 1993 and 1994.
When analyzing the relation between education and behavior, we must necessarily restrict attention to
organizations with plans that permit employees to make choices. We therefore focus our attention on
401(k)s. Since the determinants of education offerings relate to the selection process determining the
incidence of "treatment," it is important to reexamine the determinants of these offerings specifically in the
context of 401(k)s. If, for example, education tends to be offered in response to a demand for information by
employees who are naturally inclined to save at high rates, then positive cross-sectional correlations between
education and 401(k) activity could reflect selection, rather than the influence of employer-based education on
employee behavior. If, on the other hand, companies tend to provide education as a remedial measure to
employees who are otherwise disinclined to save, then the nature of selection could obscure an underlying
relation between education and behavior.
Analogously to table 2, table 3 provides estimates of probit models explaining the availability of various
educational offerings in the pooled 1993/94 sample. In this instance, however, we have confined attention to
companies with 401(k)s. We have also added several new explanatory variables, including the number of
categories of investment options (e.g. employer stock, guaranteed income contracts, bond funds, equity
mutual funds, and so forth) available to participants, and dummy variables indicating whether the plan covers
union employees, 7 whether it provides for an employer match, and whether loans are permitted.
As in table 2, seminars for older workers are more likely when companies offer plans other than
401(k)s, and the likelihood of seminar offerings generally tends to rise with employment. Notably, education
does not appear to be more common among plans that cover union employees. Since employees presumably
have greater leverage when they are unionized, this casts doubt on the hypothesis that education is provided
in response to employee demand. It is also notable that the correlation between seminars and employer matching provisions is negative (though not significant at conventional levels). This is consistent with the
view that education and matching are substitutable methods of encouraging participation in situations where
employees show insufficient interest in the plan. Not surprisingly, education of all forms is significantly more
likely when employers offer participants more investment options. There is also some indication that
seminars and loan provisions are positively correlated.
Thus far, we have not exploited the longitudinal features of our data. Doing so permits us to examine
the circumstances under which employers establish or expand educational offerings. Specifically, we regress
the change in seminar offerings between 1993 and 1994 on a variety of "initial" (1993) company and pension
plan characteristics. For the purpose of this analysis, we measure the change in seminar offerings as the
difference between the "intensity" of seminars (measured on a scale of 0 to 3) in 1993 and 1994 (see footnote
4).
Results appear in table 4. Separate results are presented for each of our five educational categories.
The most striking feature of this table is the pattern of negative coefficients for the initial participation rate of
NHC employees in the specifications explaining changes in seminar offerings. In the case of seminars for all
employees, the coefficient is highly significant; it is marginally significant (i.e. with slightly less than 95%
confidence) for the other two seminar variables. This implies that low participation among NHC employees
is strongly associated with subsequent increases in employer-sponsored seminars. This result does not,
however, carry over to written materials. No other variable consistently passes tests for statistical
significance at conventional levels. The coefficients of the initial HC participation rate are also negative for
the seminar variables, but their magnitudes and levels of significance are smaller. With low confidence, the
estimates indicate that educational improvements were more likely among firms with pensions plans that
covered larger fractions of employees. Improvements in age-specific seminars were also less common among
larger firms and among unionized firms. There is little if any relation between initial pension plan
characteristics and subsequent changes in educational offerings.
The pattern documented in table 4 supports the hypothesis that, in the context of 401(k)s, retirement
seminars are remedial. These offerings appear to be motivated by low participation among NHC employees.
This is consistent with the view that non-discrimination requirements provide a powerful impetus for the
provision of retirement education among 401(k) sponsors. However, it is doubtful that this is the only
motivation. If it were, then high initial HC participation would also correlate with subsequent increases in
education, which is not the case. The small negative effect of initial HC participation probably reflects the
offsetting effects of two separate considerations: first, that employers are inclined to offer education as a
remedial measure when 401(k) activity is low (regardless of HC or NHC status), and second, that employers
also use education to address binding non-discrimination constraints (which tend to arise when HC
participation is high). These findings are consistent with the indirect evidence on selection offered by
Bernheim and Garrett (1995).
4. Evidence on Participation in and Contributions to 401(k) Plans
In this section we use the KPMG Peat Marwick plan-level data to examine factors associated with
participation in and contributions to 401(k) plans. We use cross-sectional data on all the firms in our sample
and also examine changes for the same firm over 1993 and 1994. While we focus on the role employer-based
education plays in these decisions, we examine several other plan and firm characteristics that may be related
to participation and contributions.
A. Factors affecting participation in self-directed plans
The first step in our analysis of 401(k) activity is to examine cross-sectional OLS regressions of planlevel
participation rates. Since there are strong similarities between the data for 1993 and 1994, and since we
are not interested in investigating any specific hypotheses about the differences between these years, we pool
the two surveys. We include a year dummy to account for any systematic factors that might influence
participation or contributions differently through time. As in the previous section, pooling the data raises one important empirical issue: since many of the same firms were surveyed in both years, it is doubtful that the
error terms are independent across all observations. While OLS estimates are still consistent under these
conditions, the conventional method of computing standard errors is inapplicable. In our reported estimates,
we again correct our standard errors to reflect clustered sampling.
Since nondiscrimination rules are binding for many employers (Garrett, 1996), education programs may
be designed to encourage participation by NHC employees. Moreover, since HC and NHC households start
out with different levels of financial sophistication, we would expect financial education to affect their
behavior differently. For both reasons, we estimate separate regressions for these groups as well as for the
combined sample.
Results are contained in the first panel of table 5. The dependent variables for these regressions - the
plan participation rates - vary from 1 to 100 percent. The estimated effects of the key explanatory variables
are described below.
i. The role of seminars
For our base-case estimates, we use dummy variables to measure the intensity (frequency) of
educational offerings. In this way, we avoid imposing assumptions on the functional relation between
participation and an arbitrarily scaled measure of education (as discussed in section 2, we do, however, use
the same dummy variable to represent the responses "sometimes" and "rarely"). In subsection D, we also
present results based on a single scalar measure of educational intensity. We also focus exclusively on
seminars for all employees, rather than on seminars targeted at employees over 50 or employees near
retirement. In practice, the seminar variables are highly colinear, and it is difficult to identify their separate
effects with precision.
Reading across the first two rows of the first panel of Table 5, it is apparent that frequent seminars have
a consistently positive and significant effect on participation in self-directed plans. For non-highly
compensated employees, frequent seminars are associated with participation rates that are 11.5 percentage points higher than plans with no seminars. The corresponding figure for highly compensated employees is
6.4 percentage points. These are economically large estimates given mean participation rates - 60 to 80
percent - in the sample. The occasional seminar indicator variable is, however, insignificant in each
specification.
The results in table 5 may obscure the relation between education and participation among HC
employees. Although censoring at the plan level (at either 0 percent or 100 percent) is relatively rare for "all"
employees and for NHC employees, it is much more common for HC employees. Specifically, for 32 percent
of the sample, the HC participation rate is 100 percent. Obviously, increases in seminars and changes in
other plan characteristics cannot be associated with higher participation rates for companies that achieve 100
percent HC participation. We investigate the effects of censoring in section D, below, where we estimate
Tobit specifications.
These results are consistent with the hypothesis that seminars stimulate 401(k) participation generally,
and especially among NHC employees. This implies that retirement seminars may be an effective response to
non-discrimination rules. However, there is no indication in the pooled results that seminars matter unless
they are conducted frequently.
ii: Other forms of education and information dissemination
We include several additional education variables (newsletters and summary plan descriptions) to
examine whether all educational and informational efforts are equally effective. Summary plan descriptions
typically amount to disclosure of plan characteristics, and contain very little (if any) recognizable education.
While it is perhaps conceivable that employees would be unwilling to trust (and therefore to participate in)
their pension plans without disclosure, we would nevertheless be surprised if the use of these materials had a
measurable effects on plan activity. In contrast, newsletters often serve the same function as seminars, but
provide information through printed, rather that audio-visual media. According to a survey by the Employee
Benefit Research Institute, 92 percent of 401(k) participants say that they read these materials, and 33 percent say that they contribute more to their plans as a result. One might therefore expect newsletters to
have an effect on behavior similar to that of seminars. Alternatively, individuals may exaggerate their
responses to newsletters in response to survey questions, particularly if they perceive this to be the
"appropriate response."
Notably, in the regressions of table 5, aside from seminars, no other medium of providing information
and education to employees - either through newsletters or summary plan descriptions - has any significant
association with participation rates. This is consistent with the hypothesis that these media have no effect on
participation. In principle, selection bias could mask a behavioral response. However, in contrast to
seminars, there is little indication in the results of section 3 that the provision of written materials is
motivated by low participation.
iii. Plan characteristics
There is mixed evidence in the literature on the effect of matching rates on participation in self-directed
plans, despite the fact that matching is very common. According to a 1990 Hewitt and Associates survey, 79
percent of 944 major U.S. corporations matched employee contributions. Papke (1995) finds a strong,
positive relationship between match rates and participation in cross-sectional regressions using data from
Form 5500. 8 The effect disappears in her preferred, fixed effects specification. Andrews (1992) uses data
from the Current Population Survey and finds a positive relationship between the presence of a match and
participation rates. Kusko, Poterba, and Wilcox (1994) examine data from a single firm over several years,
where the match rate varied from 0 to 139 percent of employee contributions (up to six percent of salary).
They found little variation in participation rates across years, which lead them to conclude that their results
suggest "a relatively small elasticity of participation with respect to the match rate, and cast substantial doubt
on the view that employer matching is a key factor in explaining the rapid expansion of 401(k) plans." However, the 401(k) sponsored by the firm examined by Kusko, Poterba, and Wilcox was part of a profitsharing
plan, and hence had unusually volatile match rates. It is not clear that one can generalize from
participation responses in profit-sharing plans to more common plan types, where match rates change much
less frequently. In principal, we expect matching rates to exert a positive effect on participation since they
provide a pure substitution effect at the extensive margin.
In all the cross-sectional regressions we have examined, there is a positive and significant correlation
between the existence of a match and participation. 9 The regression results in table 5 imply that plans with
matches have participation rates that are 14.6 to 16.9 percentage points higher than plans without matches.
Loan provisions allow families to borrow against contributions made to the self-directed plan.
Conventional reasoning suggests that eligible workers will be more likely to participate in plans with loan
provisions since they will have access to funds in the event they need to borrow. An alternative view holds
that loan provisions will be negatively correlated with participation because they exacerbate "self-control"
problems with saving (see e.g. Sheffrin and Thaler, 1988). We find that the correlation between the existence
of loan provisions and participation are positive but insignificant in the regressions for all employees, and
negative but insignificant in the separate regressions for HC or NHC employees.
Having a broad range of investment options presumably increases the attractiveness of participation.
The number of options in these plans is not particularly large, with a mean of 2.8 in 1993 and a mean of 3.7
in 1994. A single investment option can be narrow (say stock in the employee's company, or a guaranteed
life insurance contracts), or broad, like the Fidelity family of mutual funds. Although we expect investment
options to be positively correlated with participation, this effect is not significant in any specification.
Conceivably, this finding may be attributable to the coarseness of our measure for the number of options
(e.g., the vast family of Fidelity equity mutual funds would be considered one option).
iv. Firm characteristics
An obvious concern with cross-sectional estimates of the kind considered here is that the variables of
interest may be correlated with unobserved firm-specific characteristic. In that case, the correlations that we
attribute to seminars may in fact reflect other factors. In addition to the plan characteristics already
mentioned, we therefore include a set of firm-specific variables to try to account for other pertinent factors.
The existence of other pension plans should matter for two distinct reasons. First, other pension plans
may be positively correlated with participation in a self-directed plan. There is extensive evidence that the
existence of a 401(k) is positively correlated with employees' tastes for saving (Engen, Gale, and Scholz,
1995; and Bernheim 1996a). It is likely that the same is true for other pensions. Thus, the presence of
pensions may be positively correlated with participation in self-directed plans. Second, other pension plans
may reduce the likelihood of participation in a self-directed plan because the pension may provide households
with sufficient retirement saving.
As would be expected if pensions and self-directed plans are initiated in response to employees' wishes,
participation rates are higher in self-directed plans when the sponsoring firms offers at least one other
pension plan. The effect for all employees is significant at conventional levels.
There may be systematic differences in self-directed plan offerings depending on the size of the firm,
and on the number of employees covered by the plan. These differences might, for example, arise from
economies of scale in plan administration, or from correlations between size and other variables, such as plan
age, unobserved dimensions of plan generosity, or the nature of peer group effects. We include the number
of employees in the firm to capture variations in participation that may be associated with firm size, and the
fraction of employees covered to capture variations in participation that may be related to plan size. We find
that firm size is negatively associated with participation, but that participation rises significantly with the
fraction of employees covered.
The unionization indicator variable is consistently insignificant across specifications.
v. Summary
In pooled cross-sectional regressions, there are a number of factors that are significantly associated with
participation, including match rates and certain characteristics of the company. The effect of frequent
seminars is economically large, positive, statistically significant. No other educational variable significantly
affects participation. In light of the selection issue documented in section 3, there is reason to believe that
these estimates understate the behavioral impact of retirement seminars, but may accurately reflect the impact
of written materials.
B. Factors related to contributions in self-directed plans
As indicated in table 1, the survey collects information on average contribution rates for plan
participants. Multiplying the average contribution rate times the participation rate gives the average
contribution rate across all eligibles. We use this as our dependent variable to examine contributions.
Because the data are aggregated across plans, there is no obvious way to use information on the fraction of
nonparticipants and the conditional mean among participants separately without making strong ad hoc
assumptions on the data. Since the conditional mean among participants is of limited intrinsic interest, we
therefore use the transformed contribution variable.
Obviously, our contributions variable may inherit some of the properties of our participation variable.
Even so, there is no compelling reason to expect, a priori, that contributions will vary with education in the
same way as participation. To see why, consider the following example. Suppose a firm's employees differ
in their taste for saving. Those with a high taste will participate in self-directed plans when available and,
due to the tax subsidy (and possibly employer match), devote a relatively high fraction of salary to these
plans. Employees with low tastes for saving will choose not to contribute. Now suppose frequent seminars
induce employees with low tastes for saving to contribute. If they contribute at low levels, the mean
contribution, conditional on participation, may actually fall, unless education also encourages high savers to
save even more. It is conceivable, however, that education might actually reduce saving among those who would otherwise put away "too much" relative to standard rules of thumb. Thus, even the unconditional
mean of the contribution rate might fall with education.
As is clear from the second panel of Table 5, the frequent seminar variable is positively and significantly
associated with contributions for the regressions involving all employees and non-highly compensated
employees. The effect is quite large. Mean (unconditional) contribution rates are around 3.4 percent of
salary, so the estimates imply that contributions are nearly 20 percent larger in firms offering frequent
seminars. This result is consistent with the hypothesis that retirement education - and frequent seminars in
particular - positively affect the size of contributions to self-directed plans.
In the specification for all employees, both match rates and loan provisions are positively and
significantly associated with contribution rates. Larger firms have lower contribution rates (the effect is
significant for highly-compensated employees). The larger the fraction of employees covered by a selfdirected
plan, the higher are contribution rates (the effect is significant for non-highly compensated
employees and the all employees specification).
C. Longitudinal evidence on participation and contributions
The specifications displayed in table 5 use pooled data from 1993 and 1994. To control for spurious
factors that might generate an apparent cross-sectional relationship between seminars and participation or
contributions, we included a number of plan- and firm-specific variables. Nevertheless, a skeptical reader
might question these results on the grounds that seminars are correlated with other firm-specific
characteristics, such as the degree of interest management takes in their employees, and that these other
characteristics are responsible for the observed correlation with behavior (perhaps through plan generosity,
which is only imperfectly accounted for in our specification).
As discussed earlier, we have observations in both years for nearly 300 firms. Thus, it is possible to
repeat our analysis, differencing the data for our short (2-year) panel. While differencing removes timeinvariant
plan-specific characteristics, it also exacerbates any measurement error problems that might be present, making it more difficult to estimate correlations that arise from behavioral relationships.
The first panel of table 6 examines participation, repeating the same specification as shown in table 5,
but using the first-differenced data. Although the statistical significance of the results is not quite as striking,
this is probably to be expected because the sample size is considerably smaller and because of the problems
arising from differencing short panels. Nevertheless, we find that instituting seminars on a frequent basis is
associated with a 7.7 percentage point increase in participation rates, and the effect is significant at the 11
percent level for the all-employee sample. For non-highly compensated employees, the effect is 12.1
percentage points, and it is significant at the 7 percent level. It is worth noting that the estimated effects of
occasional seminars appear stronger in the differenced estimates. Indeed, the effects of frequent and
occasional seminars now appear to be roughly proportional.
We view this as further support for the hypothesis that retirement education - and frequent seminars in
particular - influence the saving behavior of employees. Naturally, we cannot resolve the question of
causality with only two years of data; it is, for example, conceivable that employees might agitate for
seminars once they start participating (though it is doubtful that their employer would respond over such a
short time frame).
Our results on match rates follow the pattern observed in the literature. Although we find that match
rates appear to have a strong, positive correlation with participation and contributions in cross-sectional data,
the effect disappears when one follows the same firms over time. Because actual changes in match rates are
infrequent, it is possible that "observed" changes are dominated by measurement errors, in which case the
panel estimates of the matching effect may be highly misleading. Satisfactory resolution of the role played by
matching on participation in self-directed plans requires better data. In general, very few other variables are
significant in the participation rate specifications (and none are significant in the highly-compensated group). 10
The second panel of Table 6 examines contributions, repeating the same specification as shown in Table
5, but using the first-differenced data. The frequent seminar variable is again significant for the non-highly
compensated group, and it is marginally significant in the specification for all employees. The only other
significant coefficients (at conventional levels) are the occasional seminar variable (for HC employees) and
the unionization variable (for all employees and HC employees).
D. Robustness
The results presented in the previous sections depict a strong correlation between frequent seminars and
401(k) activity, especially among NHC employees. In order to verify the robustness of these results we
examine the sensitivity of our results to a different method for measuring the intensity of education. We also
employ several alternate estimation techniques: median, robust, and Tobit regression.
In the previous section, there were certain cases (most notably differenced specifications for
participation) where the effects of frequent seminars were only marginally significant. This may occur, at
least in part, because we are asking the data to identify too many parameters. In these same cases, the point
estimates for the effects of occasional seminars are roughly half of the corresponding point estimates for the
effects of frequent seminars (see table 6). It is therefore natural to consider an alternate specification based
on a scalar measure of educational intensity that allows us to summarize the effects of education through a
single parameter. Instead of constructing dummy variables based on the frequency of educational offerings,
we simply measure frequency on a scale of zero to three, depending on whether education is offered never,
rarely, sometimes, or often. This specification forces the effects of an increase in the frequency of education
to be the same when moving from each qualitative response to the next. That is, it assumes that an increase from never to rarely has the same effect on participation and contribution rates as an increase from rarely to
sometimes or sometimes to often. While restrictive, it is more parsimonious than our original procedure, and
is generally not rejected by the data.
We estimate median and robust regression models to reduce the potential influence of outlying
observations. 11 The standard errors reported for the median and robust regressions (as well as for the Tobit
estimates) using the pooled data are not adjusted for the fact that the same firm may appear in the pooled
sample twice. As the standard errors were similar with and without this correction in the OLS specifications
shown in Table 5, we do not view this as a major shortcoming.
We use Tobit regressions to account for right and left censoring of participation rates at 0 and 100
percent. While censoring occurs in the data for all three employee categories, it is particularly prevalent for
HC employees. In the pooled data, the participation rate equals 100 percent for all employees in 29 of 1027 observations and for NHC employees in 27 observations out of 805. For HC employees this number jumps
to 267 of 824 observations, or approximately 30 percent of the sample. Left-censored observation (i.e., those
for which the participation rate is 0 percent) are not nearly as prevalent. There are no such observations for
all employees and NHC employees, and only 12 cases for HC employees. We estimate Tobit models only for
participation rates using pooled cross-sectional data. While censoring is also present in the differenced
versions of these models, as well as in models for contribution rates (both because of the censoring of
participation and because of limits on contributions), the Tobit model is inappropriate in these contexts.
We report the coefficients of the seminar variables for these alternate specifications in Table 7 and
Table 8. We omit the coefficients of other explanatory variables to conserve space. Each of these
specifications employs the same additional covariates as the earlier OLS regressions; results for these other covariates are similar to those reported in previous subsections and are available on request.
i. An alternative measure of seminar intensity
For every specification contained in tables 5, 6, 7, and 8, we present results based on an analogous
specification in which we use a single scalar measure of educational intensity, as described at the outset of
this section. The resulting coefficients for seminars are presented in tables 7 and 8 under columns labeled
"intensity."
Generally speaking, for specifications involving pooled (as opposed to differenced) data, the magnitudes
and statistical precision of educational effects are similar to the results obtained using separate dummies for
frequent and occasional seminars. However, the use of the seminar intensity variable sharpens the estimates
considerably for the differenced data. For example, in the first column of table 6 (which concerns
participation rates), the coefficient on frequent seminars for NHC employees is only significant at the 7
percent level. However, its magnitude is also roughly twice that of the occasional seminar variable, which
suggests that use of the intensity variable may be appropriate. Indeed, as indicated in the first column of
table 7, the estimated coefficient for the intensity variable in an analogous specification is statistically
significant at the 1 percent level. A similar observation applies to differenced estimates of participation rates
for all employees. In general, with differenced data, the effects of seminars on participation (table 7) and
contributions (table 8) are found to be significant at a higher level of confidence when a single measure of
educational intensity is used.
ii. Median and robust regression: robustness of participation results
We present median and robust regression results for participation in the middle sections of Table 7. In
many respects, these results are qualitatively similar to the OLS estimates. In the pooled data, the coefficient
on frequent seminars for NHC employees drops from 11.5 in the OLS specification to 9.9 in the median and
11.2 in the robust regression. However, both of these coefficients remain significant at the 1 percent level. The coefficients of occasional seminars for NHC employees rise relative to OLS, but still fail to achieve
statistical significance at conventional levels. There is no indication that seminars - even frequent ones - have a significant impact on the participation rates of HC employees. It is therefore possible that the effects
of frequent seminars on HC employees measured in OLS regressions (as well as in the Tobit regressions
reported later) reflect the influence of outliers. For HC employees, the unexpected negative coefficient (from
OLS) on occasional seminars is reduced to a number much closer to zero in both the median and robust
regressions. Finally, the effect of frequent seminars on participation rates for all employees is a bit weaker in
median regression and robust regressions than for OLS; however, the effect of occasional seminars, though
still smaller than the effect of frequent seminars, now achieves conventional levels of statistical significance.
For the differenced data, both the median and robust regressions reduce the size of the coefficients for
frequent seminars, but also increase the precision with which they are measured. The coefficient on frequent
seminars for NHC employees drops from 12.1 in the OLS specification to 7.4 in the median and 8.6 in the
robust regression. However, while the OLS coefficient was only significant at the 7 percent level, the median
regression coefficient is significant at the 2 percent level and the robust regression at the 5 percent level.
Notably, while the effect of occasional seminars on NHC participation was not significant in OLS estimates
with differenced data, it is significant (and substantial) in both median and robust regression estimates.
Median and robust regressions also yield more precise coefficients for HC employees. For the median
regression in particular, the effect is statistically significant, even though its magnitude is small. We suspect
that this result is attributable to the nature of the distribution of the differenced HC participation rates. Many
of the participation rates for HC employees are at or near 100 percent for both 1993 and 1994; consequently,
more than 30 percent of the firms in the sample experience no change in the measured participation rate of
HC employees between 1993 and 1994. Since the median change is zero, and since there are so many zeros,
it is not surprising that our explanatory variables are found to have very little effect on the median, or that this
finding is precise. The effect of frequent seminars on participation rates disappears in the median and robust
regression estimates of the differenced specification for all employees; however, the impact of occasional
seminars emerges as significant. Finally, as noted earlier the use of the intensity variable also enhances the statistical significance of the educational effect on NHC participation rates in both the median and robust
regression estimates that make use of differenced data.
iii. Median and robust regression: robustness of the contribution results
The median and robust regression results for contribution rates appear in Table 8. The top panel
contains results for regressions with pooled data. The results for the robust regressions are qualitatively
similar to the earlier OLS estimation, with a slight drop in the coefficients on frequent seminars. For
example, in the specification for NHC employees, this coefficient drops from 0.81 to 0.69. The statistical
significance of the estimates is comparable to that of the OLS coefficients, with the coefficient on frequent
seminars for NHC employees remaining significant at the 1 percent significance level. The effect of
occasional seminars is also statistically significant in the specification for all employees. In contrast, the
median regression results for contribution rates are weaker than the OLS and robust regression results. While
the signs of the coefficients are the same, magnitudes are generally lower, and no single seminar dummy
achieves statistical significance at conventional levels. However, the seminar intensity variables approaches
statistical significance at the 95 percent confidence level in the specifications for NHC and all employees.
The bottom panel of table 8 presents median and robust regression results for contribution rates using
differenced data. The effect of frequent seminars on NHC contribution rates is still reasonably strong, and
similar to that obtained using OLS. None of the other seminar dummies depicted in this lower panel achieves
statistical significance. The estimated effect of frequent seminars on the HC contribution rate is actually
negative and fairly large in magnitude, but not very precise. However, as with the previous specifications,
when the seminar intensity variable is used, median and robust regression estimates of the seminar effect for
NHC employees are similar in magnitude to the OLS results and statistically significant at the usual levels of
confidence.
iv. Tobit regression results
Tobit results for rates of participation appear in the last section of Table 7. The coefficients for both frequent and occasional seminars increase in size (relative to OLS) for all three employee groups. The most
dramatic change occurs in the coefficient for frequent seminars for HC employees, which increases from 6.4
to 10.5. This result is not surprising given the fact that more than 30 percent of the HC observations are
right-censored. Although precision is somewhat lower for the Tobit estimates than for OLS, the coefficient
of frequent seminars for NHC employees remains significant at the 1 percent level, and the coefficient for HC
employees remains significant at the 5 percent level. These results suggest that censoring causes a downward
bias in the OLS coefficients, and that HC and NHC employees respond to education more similarly than the
OLS results appear to indicate. Again, using the seminar intensity variable results in more precisely
estimated effects.
5. Conclusions
In this paper, we have examined the effects of employer-based retirement education on 401(k) activity
using firm-level data. Our results indicate that retirement seminars are generally associated with significantly
higher rates of participation and contributions, at least when the frequency of these offerings is high. The
effect appears to be particularly strong for non-highly compensated employees. Our findings reflect both
cross-sectional and longitudinal patterns in the data, and they are robust with respect to a variety of
estimation techniques.
The current paper is complementary to Bernheim and Garrett (1996) who use household survey data to
investigate the effects of education on total saving, both inside and outside of pension plans. However, since
their data are cross-sectional, they are forced to make indirect inferences concerning the probable direction of
biases that might result from the inevitable failure to control for unobserved individual effects. With
household survey data, it is also difficult to distinguish between the effects of education on behavior, and the
effects of education on the way that individuals report behavior. In contrast, the employer survey data used
here allow us to examine both cross-sectional and longitudinal patterns; moreover, there is relatively little risk that the education of employees would affect the way that employers report rates of participation and
contributions. The tradeoff, of course, is that employer survey data provide no information on assets held
outside of pension plans, and therefore do not permit us to investigate whether increased participation and
contributions reflect new saving, rather than asset reshuffling.
Taken together, the current paper and that of Bernheim and Garrett (1996) suggest that financial
education in the workplace can exert a strong influence on personal financial decisions. More generally, these
studies raise the possibility that the enhancement of decision-making skills (as opposed to labor market
skills) may constitute a significant economic return to education.
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| Table 1: Mean and Median 401(k) Participation and Contribution Rates |
| |
|
Observations |
Median |
Mean |
Employment-Weighted Mean |
| 1993: |
| Participation Rates |
NHC |
415 |
60.9 |
59.44 |
59.66 |
| |
HC |
422 |
92.5 |
82.59 |
82.34 |
| |
All |
530 |
70.0 |
63.08 |
64.32 |
| Conditional Contribution Rates |
NHC |
395 |
5.0 |
4.96 |
4.72 |
| |
HC |
398 |
6.0 |
6.75 |
6.09 |
| |
All |
457 |
5.0 |
5.15 |
5.14 |
| Unconditional Contribution Rates |
NHC |
349 |
2.8 |
3.06 |
2.91 |
| |
HC |
352 |
5.7 |
5.79 |
5.16 |
| |
All |
437 |
3.4 |
3.39 |
3.46 |
| 1994: |
| Participation Rates |
NHC |
392 |
60.0 |
57.68 |
55.18 |
| |
HC |
404 |
92.0 |
78.56 |
82.69 |
| |
All |
500 |
70.0 |
61.23 |
60.77 |
| Conditional Contribution Rates |
NHC |
357 |
5.0 |
4.86 |
4.84 |
| |
HC |
359 |
6.0 |
6.66 |
6.05 |
| |
All |
412 |
5.0 |
5.34 |
5.32 |
| Unconditional Contribution Rates |
NHC |
311 |
2.6 |
2.94 |
2.79 |
| |
HC |
317 |
5.4 |
5.44 |
5.07 |
| |
All |
393 |
3.3 |
3.41 |
3.55 |
| Source: Derived from KPMG Peat Marwick's Retirement Benefits in the 1990s: 1993 and 1994 Survey Data. |
| Table 2: The Effect of Retirement Plan Type on Education - All Companies |
| |
Dependent Variable |
| |
Seminars for All Employees |
Seminars for Employees Over 50 |
Seminars for Employees Near Retirement |
Summary Plan Descriptions |
Newsletters or Periodicals |
| Only 401(k) Plan |
0.251 |
-0.221 |
-0.343 |
0.727 |
0.464 |
| (.129) |
(.141) |
(.143) |
(.134) |
(.129) |
| Only 403(b) Plan |
0.759 |
0.503 |
0.325 |
0.185 |
0.104 |
| (.204) |
(.205) |
(.207) |
(.202) |
(.200) |
| Only Another Plan |
0.107 |
-0.177 |
-0.092 |
0.059 |
-0.210 |
| (.151) |
(.165) |
(.162) |
(.148) |
(.148) |
| Two or More Plans |
0.326 |
0.34 |
0.274 |
0.554 |
0.484 |
| (.113) |
(.119) |
(.119) |
(.112) |
(.111) |
| Total Employement* |
0.255 |
0.352 |
0.322 |
-0.174 |
0.204 |
| (.181) |
(.141) |
(.141) |
(.169) |
(.147) |
| Fraction of Employees Covered by Plans |
0.0032 |
0.0047 |
0.0041 |
-0.0033 |
0.0001 |
| (.0012) |
(.0012) |
(.0012) |
(.0013) |
(.0012) |
| 1994 Dummy |
0.093 |
-0.050 |
0.003 |
-0.134 |
0.077 |
| (.060) |
(.063) |
(.064) |
(.065) |
(.063) |
| Intercept |
-0.647 |
-0.999 |
-0.951 |
-0.431 |
0.016 |
| (.142) |
(.151) |
(.151) |
(.145) |
(.141) |
| N |
1778 |
1773 |
1773 |
1771 |
1778 |
| *Coefficients for Total Employment are multiplied by 105.
Excluded Variable is Only Defined Benefits Plan.
Standard errors are in parentheses.
Source: Derived from KPMG Peat Marwick's Retirement Benefits in the 1990s: 1993 and 1994 Survey Data. |
| Table 3: The Effect of Retirement Plan Type on Education - Companies with 401(k) Plans |
| |
Dependent Variable |
| |
Seminars for All Employees |
Seminars for Employees Over 50 |
Seminars for Employees Near Retirement |
Summary Plan Descriptions |
Newsletters or Periodicals |
| Defined Benefits |
0.065 |
0.627 |
0.652 |
-0.090 |
0.072 |
| (.106) |
(.115) |
(.118) |
(.116) |
(.111) |
| Other Retirement Plan No DB Plan |
-0.009 |
0.258 |
0.343 |
-0.020 |
0.082 |
| (.109) |
(.120) |
(.121) |
(.118) |
(.113) |
| Total Employment* |
0.491 |
0.754 |
0.702 |
-0.389 |
0.397 |
| (.264) |
(.292) |
(.285) |
(.267) |
(.332) |
| Fraction of Employees Covered by Plans |
0.0019 |
0.0034 |
-0.0029 |
-0.0049 |
-0.0017 |
| (.0016) |
(.0017) |
(.0017) |
(.0017) |
(.0016) |
| Union Eligibility |
-0.038 |
0.016 |
0.034 |
0.056 |
0.140 |
| (.093) |
(.095) |
(.096) |
(.095) |
(.096) |
| Employer Match |
-0.165 |
-0.042 |
-0.123 |
0.203 |
0.054 |
| (.111) |
(.111) |
(.110) |
(.119) |
(.111) |
| Number of Options |
0.166 |
0.179 |
0.186 |
0.132 |
0.179 |
| (.036) |
(.039) |
(.040) |
(.041) |
(.038) |
| Loans Permitted |
0.213 |
0.147 |
0.120 |
0.013 |
-0.034 |
| (.090) |
(.095) |
(.093) |
(.095) |
(.091) |
| 1994 Dummy |
-0.015 |
-0.216 |
-0.203 |
-0.229 |
-0.026 |
| (.072) |
(.080) |
(.080) |
(.084) |
(.081) |
| Intercept |
-0.773 |
-1.729 |
-1.724 |
0.737 |
0.044 |
| (.173) |
(.188) |
(.190) |
(.188) |
(.176) |
| N |
1170 |
1169 |
1170 |
1162 |
1169 |
| *Coefficients for Total Employment are multiplied by 105; coefficients for 1994 Dummy are
multiplied by 104.
Excluded Variable is Only 401(k) Plan.
Standard errors are in parentheses.
Source: Derived from KPMG Peat Marwick's Retirement Benefits in the 1990s: 1993 and 1994 Survey Data. |
| Table 4: Predictors of Changes in Education |
| |
Dependent Variable |
| |
Seminars for All Employees |
Seminars for Employees Over 50 |
Seminars for Employees Near Retirement |
Summary Plan Descriptions |
Newsletters or Periodicals |
| NHC Participation 1993 |
-0.0084 |
-0.0058 |
-0.0059 |
-0.0013 |
0.0020 |
| (.0038) |
(.0031) |
(.0032) |
(.0047) |
(.0046) |
| HC Participation 1993 |
-0.0018 |
-0.0045 |
-0.0001 |
-0.0043 |
-0.0057 |
| (.0035) |
(.0028) |
(.0029) |
(.0044) |
(.0046) |
| Fraction of Employees Covered by Plan |
0.0044 |
0.0031 |
0.0012 |
0.0041 |
0.0004 |
| (.0030) |
(.0024) |
(.0025) |
(.0038) |
(.0037) |
| Total Employment* 1993 |
0.091 |
-0.959 |
-0.448 |
-0.338 |
0.165 |
| (0.504) |
(0.406) |
(0.420) |
(0.621) |
(.609) |
| Union Eligibility 1993 |
-0.083 |
-0.282 |
-0.196 |
-0.501 |
-0.057 |
| (.182) |
(.148) |
(.152) |
(.224) |
(.220) |
| Employer Match 1993 |
0.207 |
-0.058 |
-0.030 |
0.251 |
0.412 |
| (.227) |
(.182) |
(.189) |
(.280) |
(.274) |
| Defined Benefits Plan - 1993 |
-0.339 |
-0.082 |
-0.069 |
-0.183 |
-0.285 |
| (.197) |
(.159) |
(.164) |
(.243) |
(.238) |
| Other Pension Plan No DB Plan - 1993 |
-0.094 |
-0.184 |
-0.069 |
0.107 |
-0.180 |
| (.208) |
(.167) |
(.173) |
(.256) |
(.251) |
| Loans Permitted |
0.059 |
-0.144 |
-0.005 |
-0.015 |
-0.045 |
| (.169) |
(.136) |
(.141) |
(.209) |
(.204) |
| Investment Options |
0.058 |
0.071 |
0.027 |
0.003 |
0.079 |
| (.070) |
(.057) |
(.059) |
(.087) |
(.085) |
| Intercept |
0.168 |
0.579 |
0.201 |
-0.049 |
-0.013 |
| (.416) |
(.344) |
(.346) |
(.519) |
(.502) |
| N |
244 |
243 |
244 |
243 |
244 |
| *Coefficients for Total Employment are multiplied by 105.
All dependent variables are first differenced.
Standard errors are in parentheses.
Source: Derived from KPMG Peat Marwick's Retirement Benefits in the 1990s: 1993 and 1994 Survey Data. |
| Table 5: OLS Results for Participation and Contribution Rates |
| |
Dependent Variable |
| |
Participation Rates |
Contribution Rates |
| Seminars Often |
11.52 |
6.37 |
8.17 |
0.809 |
0.342 |
0.677 |
| (3.00) |
(2.94) |
(2.46) |
(.291) |
(.417) |
(.240) |
| Seminars Sometimes or Rarely |
1.74 |
-2.98 |
1.43 |
0.252 |
0.077 |
0.232 |
| (2.07) |
(2.37) |
(1.75) |
(.171) |
(.261) |
(.142) |
| Newsletters Often |
-0.58 |
1.09 |
-2.30 |
0.183 |
0.149 |
-0.120 |
| (2.72) |
(3.00) |
(2.23) |
(.211) |
(.380) |
(.186) |
| Newsletters Sometimes or Rarely |
-0.91 |
0.01 |
-0.83 |
-0.088 |
-0.353 |
-0.248 |
| (2.63) |
(2.81) |
(2.12) |
(.210) |
(.350) |
(.183) |
| Plan Descriptions Often |
0.35 |
-1.66 |
2.17 |
-0.084 |
0.024 |
-0.137 |
| (2.79) |
(3.16) |
(2.24) |
(.196) |
(.366) |
(.182) |
| Plan Descriptions Sometimes or Rarely |
2.16 |
-1.00 |
1.98 |
0.282 |
-0.274 |
0.007 |
| (2.83) |
(3.07) |
(2.32) |
(.220) |
(.347) |
(.197) |
| Employer Match |
14.59 |
16.94 |
17.27 |
0.389 |
0.732 |
0.566 |
| (2.55) |
(3.17) |
(2.04) |
(.238) |
(.413) |
(.205) |
| Loans Permitted |
-1.42 |
-2.34 |
1.78 |
0.076 |
0.003 |
0.313 |
| (2.09) |
(2.20) |
(1.74) |
(.159) |
(.258) |
(.149) |
| Investment Options |
-0.158 |
-0.237 |
0.712 |
0.105 |
0.156 |
0.099 |
| (.819) |
(.873) |
(.720) |
(.066) |
(.107) |
(.062) |
| Other Pension Plan |
4.41 |
3.39 |
5.02 |
-0.203 |
-0.306 |
-0.035 |
| (2.36) |
(2.53) |
(2.06) |
(.198) |
(.293) |
(.171) |
| Total Employment* |
-1.78 |
-0.29 |
-1.07 |
-0.91 |
-1.71 |
-0.45 |
| (0.64) |
(0.66) |
(0.53) |
(0.56) |
(0.59) |
(0.46) |
| Fraction of Employees Covered by Plan |
0.188 |
0.049 |
0.236 |
0.0141 |
0.0020 |
0.0153 |
| (.039) |
(.042) |
(.034) |
(.0032) |
(.0047) |
(.0029) |
| Union Eligibility |
1.49 |
1.56 |
3.56 |
-0.045 |
0.320 |
0.171 |
| (2.09) |
(2.19) |
(1.72) |
(.166) |
(.273) |
(.149) |
| 1994 Dummy |
-2.30 |
-4.41 |
-3.24 |
-0.184 |
-0.410 |
-0.102 |
| (1.82) |
(2.10) |
(1.48) |
(.145) |
(.239) |
(.124) |
| Intercept |
30.90 |
65.87 |
23.16 |
1.313 |
4.870 |
1.386 |
| (4.47) |
(5.09) |
(3.64) |
(.341) |
(.705) |
(.344) |
| N |
805 |
824 |
1027 |
658 |
667 |
827 |
| *Coefficients for Total Employment are multiplied by 104 in the participation specifications, and 105 in the
contribution specifications.
Huber standard errors are in parentheses.
Source: Derived from KPMG Peat Marwick's Retirement Benefits in the 1990s: 1993 and 1994 Survey Data. |
| Table 6: OLS Results for Changes in Participation and Contribution Rates |
| |
Dependent Variable |
| |
Participation Rates |
Contribution Rates |
| Seminars Often |
12.14 |
6.60 |
7.65 |
1.106 |
-0.141 |
0.408 |
| (6.58) |
(8.49) |
(4.72) |
(.513) |
(.772) |
(.348) |
| Seminars Sometimes or Rarely |
6.87 |
1.59 |
4.75 |
0.533 |
1.044 |
0.214 |
| (4.53) |
(5.97) |
(3.19) |
(.344) |
(.540) |
(.235) |
| Newsletters Often |
-7.02 |
-5.80 |
-2.87 |
-0.119 |
-0.912 |
-0.360 |
| (5.35) |
(7.01) |
(3.93) |
(.410) |
(.624) |
(.292) |
| Newsletters Sometimes or Rarely |
-1.41 |
-3.33 |
-1.49 |
-0.078 |
-0.557 |
-0.081 |
| (4.85) |
(6.30) |
(3.65) |
(.384) |
(.572) |
(.279) |
| Plan Descriptions Often |
6.32 |
6.62 |
3.18 |
0.240 |
0.021 |
-0.224 |
| (5.30) |
(6.69) |
(3.76) |
(.411) |
(.597) |
(.272) |
| Plan Descriptions Sometimes or Rarely |
11.34 |
11.60 |
6.29 |
0.711 |
0.695 |
0.217 |
| (5.49) |
(6.97) |
(3.80) |
(.424) |
(.624) |
(.278) |
| Employer Match |
-1.56 |
0.77 |
-0.22 |
-0.072 |
0.270 |
-0.016 |
| (5.66) |
(7.61) |
(4.36) |
(.457) |
(.695) |
(.325) |
| Loans Permitted |
1.31 |
1.30 |
2.54 |
-0.683 |
-0.715 |
-0.603 |
| (7.63) |
(10.52) |
(5.93) |
(.617) |
(1.02) |
(.433) |
| Investment Options |
2.44 |
2.76 |
0.18 |
0.300 |
0.102 |
0.132 |
| (1.89) |
(2.50) |
(1.43) |
(.153) |
(.226) |
(.107) |
| Other Pension Plan |
9.44 |
5.02 |
3.51 |
-0.002 |
0.408 |
0.037 |
| (5.25) |
(6.97) |
(4.11) |
(.419) |
(.629) |
(.295) |
| Total Employment* |
0.43 |
2.25 |
1.54 |
0.083 |
-0.011 |
0.030 |
| (3.51) |
(4.60) |
(2.34) |
(.261) |
(.389) |
(.168) |
| Fraction of Employees Covered by Plan |
0.135 |
0.098 |
0.078 |
0.0045 |
0.0131 |
-0.0041 |
| (.089) |
(.115) |
(.067) |
(.0070) |
(.0108) |
(.0049) |
| Union Eligibility |
-1.95 |
6.10 |
9.00 |
0.055 |
1.465 |
0.786 |
| (4.92) |
(6.28) |
(3.82) |
(.402) |
(.586) |
(.272) |
| Intercept |
-7.81 |
-8.55 |
-4.38 |
-0.360 |
-0.557 |
-0.213 |
| (2.88) |
(3.89) |
(2.10) |
(.239) |
(.359) |
(.165) |
| N |
188 |
196 |
291 |
148 |
147 |
213 |
| *Coefficients for Total Employment are multiplied by 104.
All variables, both dependent and independent, are first differenced.
Standard errors are in parentheses.
Source: Derived from KPMG Peat Marwick's Retirement Benefits in the 1990s: 1993 and 1994 Survey Data. |
| Table 7: Robustness of Participation Results |
| |
OLS |
Median Regression |
Robust Regression |
Tobit Estimation |
| |
Intensity |
Often |
S/R |
Intensity |
Often |
S/R |
Intensity |
Often |
S/R |
Intensity |
| Pooled: |
| NHC |
2.69 |
9.85 |
2.89 |
2.65 |
11.15 |
3.05 |
2.99 |
12.95 |
1.90 |
2.97 |
| (0.91) |
(3.16) |
(1.92) |
(0.97) |
(3.33) |
(2.00) |
(0.91) |
(3.40) |
(2.02) |
(0.92) |
| HC |
0.32 |
1.74 |
-0.29 |
0.41 |
1.63 |
0.26 |
0.36 |
10.54 |
-2.55 |
1.06 |
| (0.99) |
(2.87) |
(1.76) |
(0.67) |
(1.31) |
(0.79) |
(0.35) |
(5.37) |
(3.15) |
(1.45) |
| All |
1.99 |
5.37 |
3.58 |
1.62 |
6.65 |
3.66 |
2.11 |
9.13 |
1.44 |
2.18 |
| (0.75) |
(2.86) |
(1.75) |
(0.93) |
(2.50) |
(1.53) |
(0.69) |
(2.80) |
(1.70) |
(0.77) |
| Panel: |
| NHC |
5.32 |
7.42 |
4.41 |
3.12 |
8.64 |
7.06 |
3.45 |
|
|
|
| (1.94) |
(3.20) |
(2.19) |
(0.54) |
(4.30) |
(2.96) |
(1.33) |
|
|
|
| HC |
2.91 |
0.87 |
0.22 |
0.170 |
2.03 |
-0.18 |
0.59 |
|
|
|
| (2.54) |
(0.19) |
(0.13) |
(0.06) |
(1.88) |
(1.30) |
(0.55) |
|
|
|
| All |
3.47 |
0.72 |
2.43 |
0.59 |
-0.91 |
3.60 |
0.42 |
|
|
|
| (1.40) |
(1.90) |
(1.31) |
(0.39) |
(2.12) |
(1.43) |
(.63) |
|
|
|
| Each entry is the coefficient on Seminars for that specification of the model
The abbreviation S/R indicates the Sometimes-Rarely Seminar variable.
Standard errors are in parentheses.
Source: Derived from KPMG Peat Marwick's Retirement Benefits in the 1990s: 1993 and 1994 Survey Data. |
| Table 8: Robustness of Contribution Results |
| |
OLS |
Median Regression |
Robust Regression |
| |
Intensity |
Often |
S/R |
Intensity |
Often |
S/R |
Intensity |
| Pooled: |
| NHC |
0.211 |
0.475 |
0.186 |
0.155 |
0.690 |
0.192 |
0.169 |
| (.080) |
(.363) |
(.219) |
(.084) |
(.254) |
(.153) |
(.070) |
| HC |
0.115 |
0.119 |
0.118 |
0.068 |
0.316 |
0.225 |
0.121 |
| (.119) |
(.405) |
(.247) |
(.075) |
(.389) |
(.231) |
(.106) |
| All |
0.198 |
0.484 |
0.249 |
0.124 |
0.487 |
0.261 |
0.163 |
| (.066) |
(.319) |
(.192) |
(.063) |
(.224) |
(.135) |
(.061) |
| Panel |
| NHC |
0.407 |
0.929 |
0.206 |
0.201 |
0.824 |
0.242 |
0.263 |
| (.153) |
(.506) |
(.338) |
(.084) |
(.426) |
(.285) |
(.123) |
| HC |
0.219 |
-0.837 |
0.011 |
-0.084 |
-0.518 |
0.663 |
-0.090 |
| (.242) |
(.490) |
(.338) |
(.110) |
(.684) |
(.478) |
(.202) |
| All |
0.194 |
0.248 |
0.038 |
0.105 |
0.265 |
0.113 |
0.113 |
| (.104) |
(.268) |
(.181) |
(.105) |
(.303) |
(.204) |
(.091) |
| Each entry is the coefficient on Seminars for that specification of the model
The abbreviation S/R indicates the Sometimes-Rarely Seminar variable.
Standard errors are in parentheses
Source: Derived from KPMG Peat Marwick's Retirement Benefits in the 1990s: 1993 and 1994 Survey Data |
1 "Employees getting more: Investment education, planning help on the increase," Pensions 1 & Investments, January 23,
1995, p. 74.
2 See Employee Benefit Research Institute (1995, p. 15).
3 Since the data were provided to us without firm identifiers, we were limited to information c 3 ollected by the survey.
4 The results in this paper do not change qualitatively 4 when we use other groupings of the responses to these questions.
In order to verify the robustness of our results and to reduce still further the number of parameters, we also occasionally
define a single variable measuring the intensity of the educational offering. The variable is set equal to 3 if the device is used
often, 2 if it is sometimes used, 1 if it is rarely used, and 0 if it is never used.
5 The survey also provides information about other potentially useful plan features, such as hardship withdrawals and the
actual matching rate provided by the firm. Unfortunately the usefulness of these variables is diminished by data limitations
and we therefore do not include them in our specifications. For example, in each year of the survey over 94 percent of
employers allow hardship withdrawals, so there is not enough variation in the data to examine their effect on plan activity.
Also, fewer than 40 percent of the employers who offer an employer match report the actual matching rate. Therefore,
incorporating the actual rate into our specifications would severely limit the sample size available for estimation.
6 While the survey asks for the average contribution as a percentage of compensation, 6 it is not completely clear from the
wording whether it means the average over contributors, or the average over eligibles. The designers of the survey suggest
the former is the natural interpretation. Given the data, this interpretation appears to be correct. We calculated the average
contribution for companies that reported participation rates from 0 to 25 percent, 25 to 50 percent, 50 to 75 percent, and
75 to 100 percent. There was no evidence of systematic variation in contributions over these categories. If companies were
reporting the average over eligibles, then the average would (as a purely mechanical matter) have to rise steeply across these
categories.
7 Unfortunately, this variable is not available for defined benefit p 7 lans, and therefore could not be included in the
regressions of table 2.
8 Form 5500 is filed annually with the IRS by all sponsors of pension plans with more than 8 100 participants. The data
include plan eligibility, participation, employment, administrative cost, distributions, and contributions.
9 Recall from section 2, that data on the level of match is missing for a large 9 number of observations so we use only an
indicator variable for whether the firm offers a match.
10 In table 6, the occasional provision of summary plan des 10 criptions appears to have a positive and significant effect on
participation. However, this result is apparently driven by outliers; it vanishes when more robust estimation techniques are
applied (as in the next section).
11 Median regression accomplishes this by minimizing the sum of the absolute values of the residuals 11 rather than the sum
of squared residuals. Robust regression first eliminates gross outliers and then performs Huber iterations followed by
biweight iterations in order to weight observations more evenly in the loss function.
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