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Volume 13, Issue 2
17
Parental and Early Influences on Expectations of
Financial Planning for Retirement
Janet L. Koposko, M.S., Doctoral Candidate, Department of Psychology, Oklahoma State University
Douglas A. Hershey, Ph.D., Professor, Department of Psychology, Oklahoma State University
Author Note: The authors are indebted to Celinda Reese-Melancon and Maureen
Sullivan for critical comments on an earlier draft of the manuscript. Correspondence
should be addressed to the rst author at the Department of Psychology, Oklahoma State
University, Stillwater, Oklahoma 74078 or via email at koposko@okstate.edu.
This investigation was designed to test a theoretically-grounded model of the psychomo-
tivational dimensions that underlie retirement planning. In developing the hypothesized
model, special consideration was given to positive early inuences on development that
could potentially impact other dimensions known to predict successful planning practic-
es. Participants were 722 college students who reported the extent of childhood personal
nance lessons learned, their retirement goal clarity and knowledge of nancial planning,
and expectations of future planning and anticipated satisfaction with life in retirement.
As hypothesized, two measures of early nancial inuences were predictive of other
variables known to underlie the retirement planning decision-making process, and one’s
vision of satisfaction in retirement. Results and implications are discussed in terms of the
way in which motivational forces, particularly those that occur early in life, contribute to
perceptions of future planning efforts.
Journal of Personal Finance
©2014, IARFC. All rights of reproduction in any form reserved.
18
Introduction
The process of how individuals go about making nancial plans
for retirement is not a simple one or one that is easy to explain,
and evidence suggests that many Americans fail to adequately
plan and save for the post-employment period (VanDerhei &
Copeland, 2010; Wiener & Doescher, 2008). A survey by the
Employee Benet Research Institute (Helman, Copeland, Adams,
& VanDerhi, 2013) found that 57 percent of employees have less
than $25,000 saved for retirement, and only 21 to 28 percent felt
condent that they would be able to save enough to live com-
fortably after leaving the workforce. A similar lack of personal
retirement savings can be found throughout much of the western
world, particularly in countries where individual workers shoul-
der the responsibility for a portion of their own retirement income
(Hershey, Jacobs-Lawson, & Austin, 2013).
Saving opportunities may be restricted by factors such as a
limited income, not having access to an employer-sponsored
retirement plan, or having other major expenses (e.g., a child’s
college tuition) that limit discretionary resources. However,
even individuals who do not face these saving challenges are
sometimes nancially ill-prepared for old age. This could, in
part, be due to certain motivational forces that predispose some,
but not others, to plan and save for retirement (Hershey, 2004;
Lunt & Livingstone, 1991). A number of key motivational
dimensions that inuence saving have been identied in
previous investigations. However, few studies have focused on
positive nancial learning experiences that occur early in life,
and how those experiences contribute to a pattern of effective
saving in adulthood. From an applied perspective, if early
inuences are found to play a role in retirement saving practices
in adulthood, then it becomes important to focus attention on
this dimension. This is because unlike some motivational forces
that are relatively immutable (such as personality traits or
income limitations), early nancial learning experiences can be
carefully cultivated through modeling and intervention efforts.
The conceptual goal of the present investigation is to test a
psychomotivational model of nancial planning for retirement.
The hypothesized model (see Figure 1) includes variables
previously shown to motivate nancial planning activities
(e.g., nancial knowledge, retirement goal clarity, future time
perspective), in addition to variables that tap positive early
nancial learning experiences believed to contribute to a
pattern of planning success. To test the model, we examined the
experiences, attitudes, perceptions, and beliefs of an important
yet understudied segment of the population—undergraduate
college students. Although most published studies on this topic
focus attention on middle-aged and older working adults, we felt
that it was important to examine the future nancial planning and
saving intentions of college-age adults, inasmuch as intentions
have been shown to be one of the best predictors of future
behavior (Ajzen, 1991). An additional rationale for focusing on
younger adults is because a large majority of these individuals
stand on the threshold of entering the workforce, where they will
be required to make important programmatic retirement saving
decisions, and most will set in place a pattern of saving practices
that could extend decades into the future.
Figure 1. Hypothesized model of influences on expectations of financial planning for retirement and expected satisfaction with life in
retirement. All paths shown in the model are expected to have beta weights with positive valences.
Expected
Satisfaction
with Life in
Retirement
Expectations
of Financial
Planning for
Retirement
Parental
Influences
on Saving
Conscient-
iousness
Future Time
Perspective
Non-Family
Early
Influences
Retirement
Goal
Clarity
Financial
Knowledge
H1
H5
H9
H11
H10
H7
H6
H3
H2
H8
H4
Volume 13, Issue 2
19
Role of Motivational Forces
Financial Literacy. As a motivational construct, nancial litera-
cy involves nancial knowledge, behavior, and attitudes, and it is
used to refer to the range of awareness, knowledge, and skills that
help people to make good decisions when it comes to managing
money (OECD INFE, 2011). Many individuals who live in West-
ern societies tend to demonstrate low levels of nancial literacy
(Lusardi & Mitchell, 2011a; Lusardi & Mitchell, 2011b), and
it has been argued that literacy levels among youth and young
adults are insufcient to make reasonably informed nancial de-
cisions (Anderson, Zhan, & Scott, 2004; Mandell & Klein, 2007).
The situation described above can be rectied by educating
children and adolescents about personal nance so as to pro-
mote sound nancial saving habits over the course of one’s life
(OECD, 2005). In recent decades, a handful of private and gov-
ernment programs have been instituted that are designed to teach
children about personal nance (Anderson et al., 2004; Jump$tart
Coalition, 2012). Although the need for approaches to early nan-
cial education has been recognized (Anderson et al., 2004; Shobe
& Sturm, 2007), the implementation of worthwhile programs
often face barriers because they can be costly and time consum-
ing to administer. Furthermore, controversy exists as to the most
effective means of educating children and adolescents about -
nances, and how early intervention programs should be best eval-
uated (McCormick, 2009). Some researchers have suggested that
because parents have the primary inuence on their children’s
development, it is them who should be responsible for serving
as positive role models so as to help their children achieve a
reasonable degree of nancial literacy (Heckman & Grable,
2011), make sound economic decisions (Webley & Nyhus, 2006),
and develop healthy nancial behaviors and attitudes (Jorgensen,
2010; Lusardi, Mitchell, & Curto, 2010). In the present investi-
gation, self-rated nancial knowledge will be used as the indi-
cator of nancial literacy.1 Based on these considerations, it is
hypothesized that nancial knowledge will be not only positively
related to expectations of nancial planning for retirement (path
H5; Adams & Rau, 2011; Hershey, Jacobs-Lawson, McArdle, &
Hamagami, 2007; Van Rooij, Lusardi, & Alessie, 2011), but also
to expected satisfaction with life in retirement (path H2; Elder &
Rudolpha, 1999; Gutierrez & Hershey, 2014).
Personality Factors. Personality represents a second moti-
vational dimension that has been shown to be associated with
retirement planning and saving. Two personality traits in par-
ticular have received a fair amount of attention in the literature.
Conscientiousness refers to the extent to which one is mindful
of planning and responsive to making preparations, and it has
been shown to be related to aspirational motivations in retirement
(Robinson, Demetre, & Corney, 2010). This trait has also been
shown to be predictive of another personality trait, future time
perspective (Hershey & Mowen, 2000), which itself has been tied
to planning practices. As a trait, future time perspective character-
izes the extent to which individuals enjoy thinking about events
in the distant future. Persons who are more future oriented or who
feel more connected to possible future events tend to be more
effective at planning and saving for retirement than those who are
not (Knoll, Tamborini, & Whitman, 2012; Wiener & Doescher,
2008). Being future oriented has also been associated with the
desire to think about and discuss retirement plans with others
(Yang & Devaney, 2011), which, we believe, should help to rene
and clarify individuals’ long-range nancial goals. Based on these
ndings, it is predicted that conscientiousness will be positively
related to future time perspective (path H11; Hershey & Mowen,
2000; Webley & Nyhus, 2006). It is also predicted that future
time perspective will be positively linked to both retirement goal
clarity (path H9; Hershey et al., 2007; Yang & Devaney, 2011)
and to expected satisfaction with life in retirement (path H3;
Gutierrez & Hershey, 2014).
Goals. The clarity of individuals’ retirement goals represents a
third important dimension that has been linked to planning and
saving practices. Financial advisors would argue that it is benecial
to calculate one’s nancial needs well in advance of retirement, as
doing so not only allows one to set critical savings goals, but it also
allows one to establish a metric against which savings efforts may
be measured. Yet, many individuals fail to carry out a future needs
analysis that will facilitate setting a concrete savings goal, because
they do not consider the task worthwhile (Mayer, Zick, & Marsden,
2011). In one recent study by Petkoska and Earl (2009), nancial
goals were shown to be a signicant predictor of engaging in ac-
tivities designed to increase nancial knowledge and preparedness.
That same investigation demonstrated that being in possession of
clear and meaningful retirement goals played an important adaptive
role in other (non-nancial) domains, such as health and leisure. In
other work by Stawski, Hershey, and Jacobs-Lawson (2007), the
clarity of individuals’ retirement goals was found to be positively
related to nancial planning activities, which in turn, was linked to
regular savings contributions. Based on the evidence cited above, it
is anticipated that retirement goal clarity will be positively related
to nancial knowledge (path H7; Hershey et al., 2010; Petkoska &
Earl, 2009).
Expected Satisfaction with Life in Retirement. The fourth
motivational dimension that will be examined as a part of this
study involves expectations of satisfaction with life in retire-
ment. Financial security is one key component when it comes
to experiencing a high quality of life in old age, and insufcient
engagement in planning and saving activities over the course
of one’s career is likely to hinder post-employment satisfaction
(Couture, 2011; Elder & Rudolpha, 1999). Moreover, previous re-
search (Quick & Moen, 1998) has demonstrated that differences
in planning behaviors lead to different quality of life outcomes in
old age. In light of these linkages between planning and anticipat-
ed future quality of life, in the present study we use the Gutierrez
and Hershey (2014) Expected Satisfaction with Life in Retire-
ment Scale (SWLRS), which is based on the well-known Diener,
Emmons, Larson, and Grifn (1985) Satisfaction with Life Scale
(SWLS). It is hypothesized that nancial knowledge will be pos-
itively related to expectations of nancial planning for retirement
(path H5; Adams & Rau, 2011; Hershey, et al., 2007; Van Rooij
et al., 2011). Furthermore, it is anticipated that expectations of
nancial planning for retirement will be positively related to
expected satisfaction with life in retirement (path H1; Elder &
Rudolpha, 1999; Quick & Moen, 1998).
Journal of Personal Finance
©2014, IARFC. All rights of reproduction in any form reserved.
20
Role of Early Learning Experiences
In addition to the motivational forces identied in the previous
section, planning and saving practices may also be realistically
inuenced by positive early nancial learning experiences. Shobe
and Sturm (2007) have made a strong argument to suggest that a
lack of nancial literacy among children and adolescents is a se-
rious problem, and nancial learning opportunities should ideally
be introduced as early in life as possible. Studies have shown that
parental inuences play a considerable role in how individuals
go about forming their attitudes, beliefs, and behaviors, both in
the area of nance (Jorgensen, 2010) and in other life domains
(Webly & Nyhus, 2006). Early parental and social inuences
on retirement planning and saving have been found to have a
signicant effect on retirement goal clarity (Hershey, Henkens, &
Van Dalen, 2010) and nancial knowledge (Guiterrez & Hershey,
2014). Furthermore, having parents who planned for their own
retirement has been found to be predictive of one’s income (Dan,
2004), and income, in turn, has been shown to predict savings
contributions (Hira, Rock, & Loibl, 2009; Lunt & Livingstone,
1991).
Whereas positive parental and family learning experiences can
increase nancial planning involvement, more formal nancial
education also has the potential to make a signicant contribu-
tion (Bernheim, Garrett, & Maki, 2001). Some schools include
personal nance components as part of the curriculum (Fox,
Bartholomae, & Lee, 2005; Spielhofer, Kerr, & Gardiner, 2010),
and focused education in personal economics and related areas
have been shown to help increase overall levels of nancial
literacy (Van Rooij, et al., 2011). Therefore, in addition to the
role of parental inuences on planning and saving, exposure to
non-family early inuences, such as school-based educational
programs, should help to improve lifespan nancial planning. In
the present investigation, two different measures of early learning
(parental inuences and non-family inuences) will be employed
to assess the extent to which early nancial learning experiences
inuence expectations of not only future planning and saving, but
also expectations of satisfaction with life in retirement. Indeed,
one of the clear value added aspects of the present study involves
the inclusion of early learning indicators in the theoretical model
to be tested.
Based on the considerations regarding early learning experiences
in the preceding paragraphs, it is hypothesized that non-family
early inuences will be positively related to nancial knowledge
(path H6; Bernheim et al., 2001; Van Rooij et al., 2011). It is also
hypothesized that parental inuences on saving will be positively
related not only to future time perspective (path H10; Hershey
& Mowen, 2000), but to nancial knowledge as well (path H8;
Bernheim et al., 2001; Walker, 2012). Furthermore, it is anticipat-
ed that parental inuences on saving will be positively related to
expected satisfaction with life in retirement (path H4; Gutierrez
& Hershey, 2014).
Theoretical Framework
Elements of the theoretical foundation for the current study draw
upon the life course perspective (also known as life course the-
ory) (Crosnoe & Elder, 2002; Elder, 1994; Elder, 1998a, 1998b;
Umberson, Crosnoe, & Reczek, 2010). The life course perspec-
tive is a broad, meta-theoretical view of adult development. One
aspect of the model maintains that individuals’ decisions are
inuenced by past life events as well as future expectations. Fol-
lowing from this observation, positive early nancial learning ex-
periences are likely to inuence the way individuals think about
retirement at present, and those present viewpoints are posited to
shape expectations of future planning and saving practices.
Core propositions found in image theory (Beach, 1998; Beach
& Mitchell, 1987) also serve to buttress the proposed theoretical
framework. Image theory researchers maintain that individuals
do not use a formal analytical process when making signicant
life decisions (Beach, 1998); but rather, they make decisions on
the basis of three things: (i) how well an action plan (in this case,
making savings contributions) is likely to achieve one’s goals, (ii)
whether the action plan is consistent with one’s morals, values,
and beliefs, and (iii) whether the types of tactics and strategies
associated with the action plan are reasonable and effective.
Furthermore, like the life course perspective, image theory holds
that lifespan planning and decision making is colored by person-
al experiences, previous consequential life decisions, and other
contextual and situational factors.
This study was designed to contribute to the extant literature in
four different ways. First, it will build upon existing investiga-
tions by testing a theoretical model that is designed to replicate
and extend the eld of forces that underlie retirement planning
practices. Second, as mentioned above, by studying college
students we will examine a large and important segment of the
population that has received scant attention in the literature on
retirement nances. Third, by taking individuals’ early nan-
cial inuences into account, we seek to take existing theoretical
models in a novel and protable direction. Finally, the present
study is unique in that it will test a theoretically-derived model
that is conceptualized from a lifespan perspective (Baltes, 1987;
Baltes, Staudinger, & Lindenberger, 1999). This is accomplished
by examining the way in which early nancial inuences shape
perceptions and beliefs, as well as the way in which perceptions
and beliefs lead to expectations of future nancial sufciency and
quality of life.
Method
Participants
All participants in the study (N = 722) were students attending
a large, mid-western state university. Each respondent earned
partial credit in a psychology course for their participation. The
mean age of the sample was 19.51 years (SD = 2.83), and 64.0
percent of the sample was female. The majority of the partici-
pants self-identied as being White (80.5 percent) and non-His-
panic (91.1 percent). At the time of testing, the majority of
respondents were unemployed (72.4 percent). Only 3.0 percent of
participants held jobs where they worked more than 32 hours per
week.
Measures
The present study utilized a number of different scales and
measures, some of which were existing scales that had been used
Volume 13, Issue 2
21
in previous investigations and others that were developed for the
purpose of this study. All but the last scale listed below used a
7-point Likert-type response format (1 = strongly disagree; 7 =
strongly agree). Each scale is described in detail below.
Future Time Perspective. This 5-item scale (M = 5.66; SD = 1.09)
measures the extent to which individuals are prone to think about
the future, specically in the context of retirement planning. The
measure used in this investigation is a modied version of the
Hershey et al. (2007) scale.2 A sample item is, “I enjoy thinking
about how I will live years from now in the future.” Psychomet-
ric evaluation of the measure revealed a single factor structure
and a coefcient alpha level of .89. The future time perspective
score for each participant is the mean of the ve items, with
higher scores indicating a greater tendency toward future-oriented
thinking.
Financial Knowledge. This 3-item scale (M = 3.62; SD = 1.56)
measures self-reported knowledge of nancial planning for retire-
ment (Hershey et al., 2010). A sample item is, “I know more than
most people about retirement planning.” Psychometric evaluation
of the measure revealed a single factor structure and a coefcient
alpha level of .92. The nancial knowledge score for each partic-
ipant is the mean of the three items, with higher scores indicating
higher levels of perceived nancial knowledge.
Retirement Goal Clarity. This 5-item scale (M = 3.73; SD = 1.52)
measures the extent to which individuals report thinking about
and setting specic goals for retirement (Stawski, Hershey, &
Jacobs-Lawson, 2007). A sample item is, “I have a clear vision
of how life will be in retirement.” Psychometric evaluation of the
measure revealed a single factor structure and a coefcient alpha
level of .91. The retirement goal clarity score for each participant
is the mean of the ve items, with higher scores indicating a
greater degree of retirement goal clarity.
Conscientiousness. This 3-item scale (M = 5.45; SD = 1.19)
measures the extent to which individuals are efcient and precise
when engaged on a task (Hershey & Mowen, 2000; Mow-
en, 2000). A sample item is, “I am organized.” Psychometric
evaluation of the measure revealed a single factor structure and
a coefcient alpha level of .87. The conscientiousness score for
each participant is the mean of the three items, with higher scores
indicating higher levels of task-related conscientiousness.
Expected Satisfaction with Life in Retirement Scale. This 4-item
scale (M = 5.04; SD = 1.16) assesses expectations of satisfac-
tion with retirement among individuals who are not yet retired
(Gutierrez & Hershey, 2014). A sample item is, “I expect that in
retirement my life will be close to ideal.” Psychometric eval-
uation of the measure revealed a single factor structure and a
coefcient alpha level of .89. The retirement satisfaction with
life score for each participant is the mean of the four items, with
higher scores indicating expectations of greater satisfaction with
life in retirement.
Expectations of Financial Planning for Retirement. This 3-item
scale (M = 5.23; SD = 1.09) is a new scale designed for the
present study to assess participants’ expectations of how easy or
difcult they anticipate nding the task of retirement planning.
A sample item is, “Success at nancial planning for retirement
will be something that will come easily to me.” Psychometric
evaluation of the measure revealed a single factor structure and a
coefcient alpha level of .84. The expectations of nancial plan-
ning for retirement score for each participant is the mean of the
three items, with higher scores indicating expectations of minimal
difculties in carrying out nancial planning tasks.
Parental Inuences on Saving. This 4-item scale (M = 5.67; SD
= 1.24) is a new measure designed for the present study to assess
the effect one’s parents had on money management and saving. A
sample item is, “My parents had a strong inuence on my current
opinions about saving.” Psychometric evaluation of the measure
revealed a single factor structure and a coefcient alpha level of
.86. The parental inuences on saving score for each participant
is the mean of the four items, with higher scores indicating a
greater degree of positive parental inuences on saving.
Non-Family Early Learning Experiences. This 5-item scale
(M = 0.45; SD = 0.09) is a new measure designed for the present
study to asses nancial knowledge derived during childhood or
adolescence from sources beyond one’s family or parents. A sam-
ple item is, “In school I took a course on money management,
investing, or personal nance.” The response format for each of
the ve items was dichotomous (0 = no; 1 = yes); therefore, the
total score for each participant was the sum of the ve dichot-
omous items. The degree of internal consistency (KR-20) is
adequate at .67. Higher scores on this measure indicate more in
the way of nancial learning experiences in school or communi-
ty-based settings.
The last three (newly developed) scales listed above were created
by identifying dimensions relevant to the scale topic, writing
items that reect those dimensions, and then pilot testing those
items to determine whether they were suitable as part of the three
measures.
Procedure
Participants completed an online questionnaire that was designed
using the web-based software SurveyGizmo (Widgix, 2012).
Most questions contained in the instrument used 7-point Likert-
type scales; one measure (non-family inuences) used dichot-
omous (yes/no) scoring. Each of the scales and measures con-
tained in the questionnaire is described in Table 1; a complete
list of scales and their corresponding items can be found in the
Appendix. Following the completion of testing, all participants
were thanked for their participation and given contact informa-
tion for the investigators should they have any questions about
the study.
Analysis Plan. In terms of an analysis plan, a measurement mod-
el will rst be tested to ensure that all scale items load on their
respective constructs. Once the factor structure for the scales has
been conrmed, the path model shown in Figure 1 will be tested.
As part of that process, the statistical signicance of slope param-
eters in the model will be evaluated, and the overall goodness of
t of the broader theoretical framework will be assessed.
Journal of Personal Finance
©2014, IARFC. All rights of reproduction in any form reserved.
22
Results
The data were cleansed and examined for skew, kurtosis, outli-
ers, and any other possible issues that may lead to either distri-
butional distortions or violations of the assumptions of general
linear model analyses. Prior to testing the model shown in Figure
1, a measurement model was created to ensure that the factor
structure of the items were as hypothesized for each scale. One
independent variable, the non-family early inuences measure,
was not included in the measurement model because it utilized a
different type of response format. The measurement model was
evaluated using the Analysis of Moments Structures (AMOS)
software version 19 (Arbuckle, 2010). Model t indices for both
the measurement and path model were interpreted according to
criteria established by Hu and Bentler (1999), as well as Hooper,
Coughlan, & Mullen (2008).
The measurement model was found to be a good t to the data,
χ2 (303) = 1221.24, p < .01, TLI = .92; CFI = .93; RMSEA = .07.
No appreciable cross-loadings were observed and the model t
could not be improved by re-specifying paths to non-hypothe-
sized constructs. In sum, the computation of this measurement
model demonstrates empirical evidence that the items for the
various scales loaded on their respective factors, which served to
pave the way to compute the hypothesized path analysis model.
The path model shown in Figure 1 was then analyzed in order
to compute values for the eleven path parameters and establish
metrics reecting overall goodness-of-t. Exogenous variables
were allowed to correlate.3 As is often the case when using
structural equation modeling software, the initial run of the model
was found to have a less than adequate t, χ2 (14) = 433.17,
p < .01, TLI = .55, CFI = .78, RMSEA = .20. Modication indices
revealed that the t could be improved by deleting the path from
parental inuences on saving to expected satisfaction with life
in retirement (H4). Modication indices also suggested that t
could be improved by adding three new paths to the model: one
from conscientiousness to expectations of nancial planning for
retirement, a second from non-family early inuences to goal
clarity, and a third from future time perspective to expectations
of nancial planning for retirement. It was decided that all three
of these paths were theoretically plausible; therefore, each was
incorporated into the revised model.
Next, a revised path model was tested that contained all eight
original variables, but now thirteen paths. In this model, exog-
enous variables were again allowed to correlate. The resulting
specication was shown to be a good t to the data,
χ2 (12) = 68.74, p < .01, TLI = .93, CFI = .97, RMSEA = .08.
Moreover, all thirteen path parameters were shown to be statisti-
cally signicant at the .01 level. A graphic representation of the
revised model, which contains R2 values for each endogenous
variable and standardized beta weights for each path, is shown
in Figure 2. As seen in the gure, this model did an excellent
job in accounting for variance among the endogenous variables,
capturing between 22 to 59 percent of the total variance operating
for each construct.
Discussion
The overarching goal of the present investigation was to test
a theoretically driven, lifespan model of retirement planning.
It was expected that the hypothesized paths shown in Figure 1
would reveal a number of important relationships between key
retirement planning constructs, and those predicted relationships
would account for appreciable amounts of variance among the
Figure 2. Observed model of influences on expectations of financial planning for retirement and anticipated satisfaction with life in retirement.
All path parameters shown are standardized beta weights, and all were found to be statistically significant at the .01 level.
Expected
Satisfaction
with Life in
Retirement
Expectations
of Financial
Planning for
Retirement
Parental
Influences
on Saving
Conscient-
iousness
Future Time
Perspective
Non-Family
Early
Influences
Retirement
Goal
Clarity
Financial
Knowledge
R2 = .30
R
2
= .40 R
2
= .59
R2 = .22
R
2
= .30
.30
.28
.25
.35
.32
.67
.16
.38
.25
.14
.30
.30
.08
Volume 13, Issue 2
23
endogenous variables. The revised path model was found to
meet those expectations. Indeed, the ndings provide important
insights into the way college students think about the retirement
planning process.
Two broad take-away messages are worth noting at the
outset of the discussion. The rst is that the eld of forces that
inuence the anticipated retirement planning practices of young
(mostly non-working) college students is quite similar to the
motivational forces that shape the planning and saving behaviors
of older, working adults. This is seen by the fact that many of the
variables (and relationships between variables) identied as im-
portant in the present investigation have also been shown to play
a role in studies carried out with members of middle-aged and
older cohorts (Adams & Rau, 2011; Hira et al., 2009; Hershey et
al., 2007; Hershey et al., 2010; Petkoska & Earl, 2009; Webley &
Nyhus, 2006). The second broad nding is that early nancial in-
uences do indeed have an effect on individuals’ motives to save
for retirement, which is a topic that has received scant attention in
the extant literature on nancial and retirement planning (Doyle,
2007; Jorgenson, 2010; Lusardi et al., 2010). Both ndings
suggest important theoretical and applied implications, which are
discussed in the following paragraphs.
Two different theoretical frameworks were used in order to posi-
tion the present investigation within the existing literature. These
frameworks were the life course perspective (Elder, 1998a) and
image theory (Beach & Mitchell, 1987). The ndings from the
observed path model were consistent with both of these theories.
One key proposition of the life course perspective is that individ-
uals’ lives are embedded in social contexts (Elder, 1998a), and
an individual’s family structure is one such context. Therefore,
the fact that parental inuences on saving was predictive of
individuals’ future time perspective is consistent with life course
theory. What this suggests is that for many of the college students
involved in this study, forward-thinking attitudes were promoted
in the social context of the home environment. The life course
perspective also suggests that individuals have “linked lives,”
and that each individual is inuenced by signicant others in his
or her life sphere (Elder, 1998a). This premise was also support-
ed by the data, in that individuals who reported having positive
parental inuences ultimately developed higher levels of nancial
knowledge (H8). However, the prediction that parental inuenc-
es would be related to superior expectations of satisfaction with
life in retirement (H4) was not supported by the data. Perhaps
this non-signicant hypothesized nding is due to the number of
years that transpire between one’s early learning experiences and
how they envision their quality of life decades into the future.
Another key element of the life course perspective is human
agency, or the idea that individuals shape their lives by choosing
to engage (or choosing not to engage) in certain types of activities
(Elder, 1994). Choosing to take part in non-family related nan-
cial learning activities during one’s formative years is consistent
with the notion of human agency, and it appears that the nature
of these experiences helps to shape individuals’ future behaviors
when it comes to planning and saving. Both of these life course
theory elements—linked lives and human agency—provide the-
oretical support for the observed relationships between parental
inuences on future time perspective (H10), and non-family early
inuences on nancial knowledge (H6), respectively.
The second theoretical framework used as a foundation for the
present investigation was image theory (Beach, 1998; Beach,
1990; Beach & Mitchell, 1987). The “trajectory image” in image
theory refers to a decision-maker’s goal state, or in other words,
the state the individual desires to achieve in the future (cf., Austin
& Vancouver, 1996). In this investigation, the extent to which one
thinks about future goal states was represented by the measure
of future time perspective, and this measure was predictive of
not only retirement goal clarity (H9), but also expectations of
satisfaction with life in retirement (H3). Taken together, this pair
of ndings provides empirical support for the closely aligned
constructs of one’s orientation to time, the clarity of one’s goals,
and one’s vision of the future.
Beyond the trajectory image, Beach’s image theory posits that
individuals make decisions in the context of two other images:
the “strategic image” and the “value image” (Beach, 1990; Beach
& Mitchell, 1987). The strategic image represents the plans and
tactics individuals use to achieve their goals. In terms of the pres-
ent investigation, nancial knowledge could be thought to serve
as a proxy indicator for the strategic image. The third of the three
images, the value image, represents personal values, morals, and
ethics held by the decision maker. In the present investigation,
the early inuence variables—parental inuences on saving and
non-family early inuences—could be considered to reect one’s
personal nancial values, inasmuch as they shape personal beliefs
about the world that the individual carries forward into adulthood.
In the observed model of retirement planning, both non-family
early inuences and parental inuences on saving were predic-
tive of nancial knowledge (H6 and H8, respectively), which are
reective of the theoretical link between one’s value image and
strategic image. Financial knowledge, in turn, was predictive
of variables involving future expectations (i.e., expectations of
nancial planning for retirement [H5] and expected satisfaction
with life in retirement [H2]), which is reective of the theoretical
link between one’s strategic image and trajectory image. In short,
these observed empirical relationships are consistent with the
ow of inuences posited in Beach’s theoretical framework.
Implications also exist in terms of the way in which personality
traits inuence individuals’ retirement planning decisions. Two
personality variables—conscientiousness and future time per-
spective—were included in the hypothesized model. In previous
investigations, conscientiousness has been shown to be associated
with future time perspective and knowledge of nancial planning
(Hershey & Mowen, 2000; Webley & Nyhus, 2006). In the ob-
served model, the rst of these two ndings (H11) was replicated.
Furthermore, the observed model revealed that conscientiousness
was predictive of expectations of nancial planning for retire-
ment, which is a non-hypothesized empirical link not previously
demonstrated. Given the fact that one’s level of conscientiousness
tends to remain developmentally stable over the life course (Gal-
lagher, Fleeson, & Hoyle, 2010), low levels of this personality
trait could represent a true barrier to envisioning oneself as being
Journal of Personal Finance
©2014, IARFC. All rights of reproduction in any form reserved.
24
effective when it comes to planning and saving for the future.
Like conscientiousness, the measure of future time perspective
served to replicate and extend associations with other measures
in the model. In support of H9, future time perspective was
predictive of retirement goal clarity among these college student
respondents, which is a relationship that has previously been
established among a sample of older adults (Hershey et al., 2007).
Furthermore, in support of H3, future time perspective was pre-
dictive of expectations of nancial planning for retirement, which
is an effect that has not previously been demonstrated. Knowl-
edge of the linkages between personality traits and expectations
of future life satisfaction might benet intervention specialists,
who not only face the challenge of getting their clients to plan
and save, but also to envision a nancially secure and worry-free
old age.
One nal, broader theoretical implication has to do with the
use of multivariate models to capture complex decision making
processes. The goal of understanding complex thought has been
the subject of increased attention in recent years (Bakken, 2008;
Bargh, 2011; Klein, 2005; Qudrat-Ullah, 2008). In the present
investigation, eight variables were analyzed in relation to one
another, which resulted in a holistic picture of the forces that
drive an individual to save for retirement. The results from this
analytic effort serve to replicate and extend existing multivar-
iate models of retirement planning (e.g., Adams & Rau, 2011;
Gutierrez & Hershey, 2014; Hershey et al., 2007; Hershey et
al., 2010; Hershey & Mowen, 2000; Webley & Nyhus, 2006).
The complex and dynamic nature of the model tested brings into
sharp focus the important role of human agency (Elder, 1994),
which suggests that individuals make decisions within the context
of multiple forms of opportunities and constraints.
In terms of applied implications, the ndings from this study
should help retirement counselors and nancial professionals
develop more effective and efcient approaches to intervention.
In the present investigation, early learning experiences were
found to play a prominent role in shaping attitudes toward and
knowledge of retirement planning. This would suggest that the
scaffolding of youth nancial education programs could help
individuals acquire a solid level of nancial literacy by their early
twenties (Cowen, Blair, & Taylor, 2011). Indeed, we believe that
early nancial learning experiences can translate into positive
attitudes toward money management, saving, and nancial inde-
pendence if they are introduced to children and adolescents at the
right time and in a meaningful manner. Whereas certain psycho-
motivational dimensions that shape planning practices (such as
elemental personality traits) tend not to be malleable (Gallagher
et al., 2010), it is encouraging to note that early nancial learning
experiences (which can take the form of parental modeling or
formal interventions) may be a particularly effective means of
nurturing individuals into becoming both interested in planning
and competent when it comes to saving.
The results of this study offer a number of valuable insights into
the psychological mechanisms that underlie retirement planning.
However, certain limitations should be acknowledged. These
limitations include the fact that the scales used relied upon
self-report, which may be subject to certain reporting biases;
the investigation relied on the use of correlational data, which
limits the ability to draw causal conclusions (Cliff, 1983); and
the observed ndings cannot be generalized to non-college age
populations. To address the rst limitation, in future investiga-
tions researchers might consider using objective measures (where
applicable) in conjunction with self-reports. With regard to the
second limitation, in future studies a true experimental design
could be employed, in which one group of children is assigned to
complete a nancial literacy program (while the contrast group
does not). A different experimental design might involve having
one group of parents receive money management training, while
training is withheld from a second (matched) group of parents, to
observe the effects of the intervention on their children. And the
third limitation cited above could be addressed by designing a
study in which the model shown in Figure 2 is tested on popula-
tions other than college-aged students.
The results of this study make both theoretical and applied contri-
butions to the existing literature on the psychology of retirement
planning. From a broad theoretical perspective, the ndings
suggest that we should take seriously the impact early learning
experiences have on an individual’s development. It appears
the long-terms effects of positive nancial lessons learned in
the home, the school system, or the community, not only extend
one’s view of the future, but they also help to clarify retirement
goals and enhance levels of nancial literacy. From an applied
perspective, our ndings provide educators, retirement counsel-
ors, and nancial professionals excellent reasons and motives to
promote forward-thinking youth intervention programs designed
to foster appropriate levels of nancial competence.
Volume 13, Issue 2
25
References
Adams, G. A., & Rau, B. L. (2011). Putting off tomorrow to do what you
want today: Planning for retirement. American Psychologist, 66, 180-
192. doi: 10.1037/a0022131
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior &
Human Decision Processes, 50, 179. doi:10.1016/0749-5978(91)90020-T
Anderson, S. G., Zhan, M., & Scott, J. (2004). Targeting nancial manage-
ment training at low-income audiences. Journal of Consumer Affairs, 38,
167–177. doi: 10.1111/j.1745-6606.2004.tb00470.x
Arbuckle, J. L. (2010). IBM SPSS Amos 19 user’s guide. Chicago, IL: Amos
Development Corporation.
Austin, J. T., & Vancouver, J. B. (1996). Goal constructs in psychology:
Structure, process, and content. Psychological Bulletin, 120, 338-375.
doi: 10.1037/0033-2909.120.3.338
Bakken, B. E. (2008). On improving dynamic decision-making: Implications
from multiple-process cognitive theory. Systems Research and Behavior-
al Science, 25, 493-501. doi: 10.1002/sres.906
Baltes, P. B. (1987). Theoretical propositions of life-span developmental psy-
chology: On the dynamics between growth and decline. Developmental
Psychology, 2.1, 611-626. doi:10.1037/0012-1649.23.5.611
Baltes, P. B., Staudinger, U. M., & Lindenberger, U. (1999). Lifespan
psychology: Theory and application to intellectual functioning. Annual
Review of Psychology, 50, 471-507. doc10.1146/annurev.psych.50.1.471
Bargh, J. (2011). Unconscious thought theory and its discontents: A
critique of the critiques. Social Cognition, 29, 629-647. doi: 10.1521/
soco.2011.29.6.629
Beach, L. R. (1990). Image theory: Decision making in personal and organi-
zational contexts. Chichester, UK: Wiley.
Beach, L. R., & Mitchell, T. R. (1987). Image theory: Principles, goals,
and plans in decision making. Acta Psychologica, 66, 201-220. doi:
10.1016/0001-6918(87)90034-5
Beach, L. R. (Ed.). (1998). Image theory: Theoretical and empirical founda-
tions. Mahwah, NJ: Lawrence Erlbaum Associates.
Bernheim, B. D., Garrett, D. M., & Maki, D. M. (2001). Education and
saving: The long-term effects of high school nancial curriculum man-
dates. Journal of Public Economics, 80, 435-465. doi: 10.1016/S0047-
2727(00)00120-1
Cliff, N. (1983). Some cautions concerning the application of causal model-
ing methods. Multivariate Behavioral Research, 18, 115-126.
Couture, L. (2011). Planning for retirement. Activities, Adaptation, and
Aging, 35, 267-273. doi: 10.1080/01924788.2011.602927
Cowen, J., Blair, W., & Taylor, S. (2011). The use of scaffolding in the nan-
cial planning classroom: An Australian case study. Australian Accounting
and Business Finance Journal, 5, 3-16. Retrieved from: http://ro.uow.
edu.au/aabfj/vol5/iss3/2
Crosnoe, R., & Elder, G. H. Jr. (2002). Successful adaptation in the later
years: A life course approach to aging. Social Psychology Quarterly, 65,
309-328.
Dan, A. A. (2004). What are people doing to prepare for retirement?
Structural, personal, work, and family predictors of planning. Doctor-
al dissertation, Case Western Reserve University. DAI-A 65/01, 251.
Retrieved from: http:etd.ohiolink.edu/view.cgi/Dan%20 Amy%20Anne.
pdf?case1079241195
Diener, E., Emmons, R. A., Larsen, R. J., & Grifn, S. (1985). The satisfac-
tion with life scale. Journal of Personality Assessment, 49, 71-75. doi:
10.1207/s15327752jpa4901_13
Doyle, N. (2007). Children’s pensions: How to develop an accessible and un-
derstandable personal savings habit that produces an adequate retirement
income. Pensions, 12, 213-216. doi: 10.1057/palgrave.pm.5950057
Elder, G. H., Jr. (1998a). The life course and human development. In R. M.
Lerner (Ed.), Handbook of Child Psychology: Vol. 1. Theoretical models
of human development, 5th ed., (pp. 939-991). New York: Wiley.
Elder, G. H., Jr. (1998b). The life course as developmental theory. Child
Development, 69, 1-12. doi: 10.1111/j.1467-8624.1998.tb06128.x
Elder, G. H., Jr. (1994). Time, human agency, and social change: Perspec-
tives on the life course. Social Psychology Quarterly, 57, 4-15. doi:
10.2307/2786971
Elder & Rudolpha (1999). Does retirement planning affect the level of retire-
ment satisfaction? Financial Services Review, 8, 117-127.
Fox, Bartholomae, & Lee (2005). Building the case for nancial educa-
tion. Journal of Consumer Affairs, 39, 195-213. doi: 10.1111/j.1745-
6606.2005.00009.x
Gallagher, P., Fleeson, W., & Hoyle, R. H. (2010). A self-regulato-
ry mechanism for personality trait stability: Contra-trait effort.
Social Psychological and Personality Science, 2, 335-342. doi:
10.1177/1948550610390701
Goldsmith, E., & Goldsmith, R. E. (1997). Gender differences in perceived
and real knowledge of nancial investments. Psychological Reports, 80,
236-238. doi: 10.2466/PR0.80.1.236-238
Goldsmith, R. E., Goldsmith, E. B., & Heaney, J. G. (1997). Sex differenc-
es in nancial knowledge: A replication and extension. Psychological
Reports, 81, 1169-1170. doi: 10.2466/pr0.1997.81.3f.1169
Gutierrez, H. C. & Hershey, D. A. (2014). Age differences in expected
satisfaction with life in retirement. International Journal of Aging and
Human Development, 78-116. doi: http://dx.doi.org/10.2190/AG.78.2.a
Heckman, S. J., & Grable, J. E. (2011). Testing the role of parental debt
attitudes, student income, dependency status, and nancial knowledge
have in shaping nancial self-efcacy among college students. College
Student Journal, 45, 51-64.
Helman, R., Adams, N., Copeland, C., & VanDerhei, J. (2013). The 2013
Retirement Condence Survey: Perceived Savings Needs Outpace Reality
for Many (Issue Brief No. 384). Washington, D. C.: EBRI. Retrieved
from http://www.ebri.org/publications/ib/index.cfm ?fa=ibDisp&con-
tent_id=5175
Hershey, D. A. (2004). Psychological inuences on the retirement investor.
CSA Journal, 22, 31-39.
Hershey, D. A., Henkens, K., & Van Dalen, H. P. (2010). Aging and nancial
planning for retirement: Interdisciplinary inuences viewed through a
cross-cultural lens. International Journal of Aging and Human Develop-
ment, 70, 1-38. doi: 10.2190/AG.70.1.a
Hershey, D. A., Jacobs-Lawson, J.M., & Austin, J. T. (2013). Effective nan-
cial planning for retirement. In M. Wang (Ed.), The Oxford handbook of
retirement (pp. 402-430). New York: Oxford University Press.
Hershey, D. A., Jacobs-Lawson, J. M., McArdle, J. J., & Hamagami, F.
(2007). Psychological foundations of nancial planning for retirement.
Journal of Adult Development, 14, 26-36. doi: 10.1007/s10804-007-
9028-1
Hershey, D. A. & Mowen, J. C. (2000). Psychological determinants of nan-
cial preparedness for retirement. The Gerontologist, 40, 687-697. doi:
10.1093/geront/40.6.687
Hira, T. K., Rock, W. L., & Loibl, C. (2009). Determinants of retirement
planning behaviour and differences by age. International Journal of Con-
sumer Studies, 33, 293-301. doi: 10.1111/j.1470-6431.2009.00742.x
Journal of Personal Finance
©2014, IARFC. All rights of reproduction in any form reserved.
26
Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation model-
ing: Guidelines for determining model t. Journal of Business Research
Methods, 6, 53-60.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for t indexes in covariance
structure analysis: Conventional criteria versus new alternatives. Struc-
tural Equation Modeling, 6, 1-55. doi: 10.1080/10705519909540118
Jorgensen, B. L. (2010). Financial literacy of young adults: The impor-
tance of parental socialization. Family Relations, 59, 465-478. doi:
10.1111/j.1741-3729.2010.00616.x
Jump$tart Coalition (2012). Jump$tart Coalition for Personal Financial
Literacy. Retrieved from http://jumpstart.org/about-us.html
Klein, J. (2005). The contributions of a decision support system to complex
educational decisions. Educational Research and Evaluation, 11, 221-
234. doi: 10.1080/13803610500101140
Knoll, M. A. Z., Tamborini, C. R., & Whitman, K. (2012). I do…want
to save: Marriage and retirement savings in young households.
Journal of Marriage and Family, 74, 86-100. doi: 10.1111/j.1741-
3737.2011.00877.x
Lunt, P. K., & Livingstone, S. M. (1991). Psychological, social, and eco-
nomic determinants of saving: Comparing recurrent and total savings.
Journal of Economic Psychology, 12, 621-641. doi: 10.1016/0167-
4870(91)90003-C
Lusardi, A., & Mitchell, O. S. (2011a). Financial literacy around the world:
An overview. Journal of Pension Economics and Finance, 10, 497-508.
doi: 10.1017/S1474747211000448
Lusardi, A. & Mitchell, O.S. (2011b). Financial literacy and retirement plan-
ning in the United States. Journal of Pension Economics and Finance,
10, 509-525. doi: 10.1017/S147474721100045x
Lusardi, A., Mitchell, O. S., & Curto, V. (2010). Financial literacy among
the young. The Journal of Consumer Affairs, 44, 358-380. doi:
10.1111/j.1745-6606.2010.01173.x
Mandell, L., & Klein, L. S. (2007). Motivation and nancial literacy. Finan-
cial Services Review, 16, 105-116.
Mayer, R. N., Zick, C. D., & Marsden, M. (2011). Does calculating retire-
ment needs boost retirement savings? The Journal of Consumer Affairs,
45, 175-200. doi: 10.1111/j.1745-6606.2011.01199.x
McCormick, M. H. (2009). The effectiveness of youth nancial education: A
review of the literature. Journal of Financial Counseling and Planning,
20, 70-79.
Mowen, J. C. (2000). The 3M Model of Personality: Theory and Empirical
Applications to Consumer Behavior. Boston: Kluwer Academic Press.
OECD INFE (2011). Measuring nancial literacy: Questionnaire and
guidance notes for conducting an internationally comparable survey of
nancial literacy. Paris: OECD.
OECD (2005). Recommendation on principles and good practices for
nancial education and awareness. Retrieved from http://www.oecd.org/
dataoecd/7/17/35108560.pdf
Petkoska & Earl (2009). Understanding the inuence of demographic and
psychological variables on retirement planning. Psychology and Aging,
24, 245-251. doi: 10.1037/a0014096
Qudrat-Ullah, H. (2008). Future directions on complex decision making
using modeling and simulation decision support. In H. Quadrat-Ullah, J.
M. Spector, & P. I. Davidsen (Eds), Complex Decision Making: Theory
and Practice (pp. 323-337). Cambridge, MA: Springer.
Quick H. E. & Moen, P. (1998). Gender, employment, and retirement
quality: A life course approach to the differential experiences of men
and women. Journal of Occupational Health Psychology, 3, 44-64. doi:
10.1037/1076-8998.3.1.44
Robinson, O. C., Demetre, J. D. & Corney, R. (2010). Personality and retire-
ment: Exploring the links between the Big Five personality traits, reasons
for retirement and the experience of being retired. Personality and Indi-
vidual Differences, 48, 792-797. doi: 10.1016/j.paid.2010.01.014
Shobe, M. A., & Sturm, S. L. (2007). Youth individual development
accounts: Retirement planning initiatives. Children & Schools, 29, 172-
181.
Spielhofer, T., Kerr, D., & Gardiner, C. (2010). Personal nance education:
Effective practice guide for schools. Slough, UK: National Foundation
for Educational Research.
Stawski, R. S., Hershey, D. A., & Jacobs-Lawson, J. M. (2007). Goal clarity
and nancial planning activities as determinants of retirement savings
contributions. International Journal of Aging and Human Development,
64, 13-32. doi: 10.2190/13GK-5H72-H324-16P2
Umberson, D. Crosnoe, R., & Reczek, C. (2010). Social relationships and
health behavior across the life course. Annual Review of Sociology, 36,
139-157. doi:10.1146/annurev-soc-070308-120011
VanDerhei, J., & Copeland, C. (2010). The EBRI retirement readiness rating:
Retirement income preparation and future prospects. (Issue Brief No.
344). Washington, D. C.: EBRI. Retrieved from http://ebri.org/publica-
tions/ib/index.cfm? fa=ib Disp&content_id=4593
Van Rooij, M. C. J., Lusardi, A., & Alessie, R. J. M. (2011). Financial
literacy and retirement planning in the Netherlands. Journal of Economic
Psychology, 32, 593-608. doi:10.1016/j.joep.2011.02.004
Walker, R. B. (2012). Sustainable personal retirement. McGraw-Hill
Research Foundation: Retrieved from: www.mcgraw-hillresearchfounda-
tion.org
Webley, P., & Nyhus, E. K. (2006). Parents’ inuence on children’s future
orientation and saving. Journal of Economic Psychology, 27, 140-164.
doi: 10.1016/j.joep.2005.06.016
Widgix (2012). SurveyGizmo [Computer Software] (2012). Boulder, CO:
Widgix, LLC.
Wiener, J., & Doescher, T. (2008). A framework for promoting retire-
ment savings. The Journal of Consumer Affairs, 42, 137-164. doi:
10.1111/j.1745-6606.2008.00102.x
Yang & Devaney (2011). Intrinsic rewards of work, future time perspective,
the economy in the future, and retirement planning. Journal of Consumer
Affairs, 45, 419-444. doi:10.1111/j.1745-6606.2011.01211.x
Endnotes
1Use of a self-report measure of nancial knowledge was decided upon
because it is more efcient to administer than an objective measure of
knowledge, and both objective and self-reported nancial knowledge have
previously been shown to be positively correlated (Goldsmith & Goldsmith,
1997; Goldsmith, Goldsmith, & Heaney, 1997).
2The original Hershey et al. (2007) future time perspective scale contained
six items, four of which were reverse coded. In an effort to improve the
level of internal consistency, the four reverse coded items were replaced
with the following three new items: “I look forward to life in the distant
future,” “It is important to take a long-term perspective on life,” and “My
close friends would describe me as future oriented.”
3The three correlations among exogenous measured variables (i.e., parental
inuences, conscientiousness, and non-family inuences) were all quite
small, and for that reason are not shown in Figure 1.
Volume 13, Issue 2
27
Appendix:
List of Scales Used in the Study
Expected Satisfaction with Life in Retirement Scale
1. I expect that in retirement my life will be close to ideal.
2. Once I enter retirement, the conditions of my life will be excellent.
3. After I retire, I will be satised with life.
4. After I retire, I will have gotten the important things I wanted in life.
Expected Financial Planning for Retirement Scale
1. I expect to meet my nancial goals in terms of planning and saving for
the future.
2. I think I will do a good job of planning and saving for retirement.
3. Success at nancial planning for retirement will be something that will
come easily to me.
Self-rated Financial Knowledge Scale
1. I know a great deal about nancial planning for retirement.
2. I have informed myself about nancial preparation for retirement.
3. I know more than most people about retirement planning.
Goal Clarity Scale
1. I have set clear goals for gaining information about retirement.
2. I have thought a great deal about my quality of life in retirement.
3. I set specic goals for how much will need to be saved for retirement.
4. I have a clear vision of how life will be in retirement.
5. I have discussed retirement plans with a spouse, friend, or signicant
other.
Future Time Perspective Scale
1. I enjoy thinking about how I will live years from now in the future.
2. I like to reect on what the future will hold.
3. I look forward to life in the distant future.
4. It is important to take a long-term perspective on life.
5. My close friends would describe me as future oriented.
Conscientiousness Scale
1. I am organized.
2. I am orderly.
3. I am efcient.
Non-Family Early Inuences Measure
1. In school I took a course on money management, investing, or personal
nance.
2. In the past, I have seen a guest speaker, educator, or other person talk
about nancial planning.
3. At some point during school, I studied the general structure of how
social security and pension plans work.
4. When I learned about career planning and career exploration in school,
I learned about typical retirement saving options that are offered to
employees by their employer.
5. I had to do an assignment or class project in the past that involved mak-
ing either a real or mock budget. This involved describing the types of
things I would spend money on and how I could save money to get the
things I need.
Parental Inuences on Saving Scale
1. Growing up, my parents helped me to imagine situations when I might
need extra money to fall back on.
2. My parents made sure that I understood the value of money and that
money is a limited resource.
3. Saving money for the future was an important lesson I learned as a child.
4. My parents suggested to me concrete ways to save money on my own.
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