Comparative Financial Analysis of Darden Restaurants and Flanigan's Enterprises

OUTLINE
Term Project
Comparative Financial Statement Analysis of Darden
Restaurants and Flanigan’s Enterprises
Prepared by
Christopher Valdes
For Professor C.E. Reese
In partial fulfillment of the requirements for
ACC 770 – Managerial Accounting
Gus Machado School of Business / Graduate Studies
St. Thomas University
Miami Gardens, Florida.
Term Fl2 / Fall, 2019
December 12, 2019
Table of Contents
I. Introduction
a. Objective
b. Scope
c. Methodology/Organization

II. Business history and future
a. Industry
b. Darden Restaurants
c. Flanigan’s Enterprises
III. Financial analysis
a. Ratio Analysis Explanation
i. Liquidity Ratios
ii. Activity Ratios
iii. Solvency Ratios
iv. Profitability Ratios
b. Horizontal and Vertical Analysis
i. Overview
ii. Complementary Application
IV. Liquidity analysis
a. Industry
V. Activity analysis
a. Industry
VI. Solvency analysis
a. Industry
VII. Profitability analysis
a. Industry
VIII. Horizontal and Vertical Analysis
IX. Comparative analysis
a. Credit Worthiness Analysis
i. Short Term
ii. Long Term
b. Investment Attractiveness Analysis
c. Recommendations / Current Developments

X. Summary and Conclusions
XI. References / Bibliography
XII. Appendices
a. Horizontal Analysis Tables
b.Vertical Analysis Tables

Introduction
This paper conducts a comparative financial analysis on Darden
Restaurants and Flanigan’s Enterprises with the objective to
assess the financial health of the companies. Financial analysis
provides companies with objective answers and support for
making informed decisions. By reviewing past and current
financial statements and comparing them to the restaurant
industry, future predictions can be made to ensure that the
companies can be profitable. Financial analysis allows
companies to discover areas that must be improved to ensure
that creditors look favorable upon the companies and drive
profit potential.
Darden Restaurants ranked number 15 in Florida’s 125 top
publicly traded companies. The Darden family
of restaurants features some of the most recognizable and
successful brands in full-service dining: Olive Garden, Long
Horn Steakhouse, Cheddar's Scratch Kitchen, Yard House, The
Capital Grille, Seasons 52, Bahama Breeze® and Eddie V's.
Flanigan’s Enterprises ranked number 108 in Florida’s 125 top
publicly traded companies operates as a chain of full-service
restaurants and package liquor stores. The Company operates

through two segments: the restaurant segment and the package
liquor store segment. The operation of package stores consists
of retail liquor sales and related items.
Journal of Youth and Adolescence (2019) 48:864–875
https://doi.org/10.1007/s10964-019-01012-3
EMPIRICAL RESEARCH
When Discrimination Hurts: The Longitudinal Impact of
Increases in
Peer Discrimination on Anxiety and Depressive Symptoms in
Mexican-origin Youth
Gabriela Livas Stein 1 ● Laura Castro-Schilo2 ● Alyson M.
Cavanaugh3 ● Yesenia Mejia1 ● N. Keita Christophe1 ●
Richard Robins4
Received: 4 January 2019 / Accepted: 4 March 2019 / Published
online: 16 March 2019
© Springer Science+Business Media, LLC, part of Springer
Nature 2019
Abstract
Life course models of the impact of discrimination on health
and mental health outcomes posit that the pernicious effects of
discrimination may not be immediate, but instead may become
apparent at later stages in development. This study tests
whether peer discrimination changes at particular transition
points (i.e., transition to middle and high school) predict
subsequent internalizing symptoms in Mexican-origin youth. In
a sample of 674 Mexican-origin youth (50% female), this
study used a latent change score framework to model changes in

peer discrimination across time and to test whether changes
in peer discrimination at 7th and 9th grades predicted greater
depressive and anxiety symptoms in 12th grade controlling for
5th grade symptoms. Irrespective of longitudinal changes,
greater peer discrimination in 5th grade predicted greater
depressive and anxiety symptoms in 12th grade. Further,
significant increases in peer discrimination from 7th to 8th
grade
and in 9th to 10th grade uniquely predicted greater anxiety
symptoms in 12th grade. These findings suggest that
longitudinal
research on peer discrimination needs to take into account
unique periods of risk. Future research implications are
discussed.
Keywords Latinx ● Peer discrimination ● Internalizing
Introduction
Experiences of peer racial/ethnic discrimination in late
childhood and adolescence are associated with a host of
negative outcomes, including greater symptoms of
depression (Delgado et al. 2017) and internalizing
problems (Berkel et al. 2010). Longitudinal examinations
of the link between discrimination and internalizing
symptoms typically examine either covarying trajectories
over time (e.g., Bellmore et al. 2012) or how baseline
discrimination influences trajectories of internalizing
symptoms (e.g., Delgado et al. 2017). Although these
approaches provide important information on longitudinal
patterns, they fail to capture whether changes at specific
points in development (i.e., transition points) influence
subsequent functioning (i.e., at the end of high school).
Scholars have posited that experiences of discrimination
may influence outcomes differentially across the life

course, and that increases in discrimination at certain
points in development may serve as “sensitive periods”
predicting later functioning (Gee et al. 2012). This article
leverages a novel statistical technique (i.e., latent change
score (LCS) framework; Castro-Schilo et al. 2016) to
examine whether there are specific timepoints across early
to late adolescence where increases in peer discrimination
have a greater impact on internalizing symptomatology in
a sample of Mexican-origin youth.
* Gabriela Livas Stein
[email protected]
1 Department of Psychology, University of North Carolina at
Greensboro, Greensboro, NC, USA
2 SAS Institute Inc, RTP, Greensboro, NC, USA
3 Frank Porter Graham Child Development Institute, University
of
North Carolina at Chapel Hill, Chapel Hill, NC, USA
4 Department of Psychology, University of California at Davis,
Davis, CA, USA
Supplementary information The online version of this article
(https://
doi.org/10.1007/s10964-019-01012-3) contains supplementary
material, which is available to authorized users.
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01012-3&domain=pdf
01012-3&domain=pdf
01012-3&domain=pdf
http://orcid.org/0000-0002-7365-5169
http://orcid.org/0000-0002-7365-5169
http://orcid.org/0000-0002-7365-5169
http://orcid.org/0000-0002-7365-5169
http://orcid.org/0000-0002-7365-5169
mailto:[email protected]
https://doi.org/10.1007/s10964-019-01012-3
https://doi.org/10.1007/s10964-019-01012-3
Peer Discrimination and Internalizing Symptoms
Multiple socioecological models of development in youth
of color have focused on the processes through which
families successfully navigate the oppressive and dis-

criminatory landscape in the United States (i.e., Garcia Coll
et al. 1996). These models highlight the damaging effects of
discrimination on developmental outcomes in youth of
color and the critical need to understand how these
experiences influence youth across development. Broadly,
depressive symptoms serve as the most widely studied
outcome associated with discrimination in youth, with
fewer studies examining anxiety (Priest et al. 2013). Peer
discrimination may be particularly harmful for youth as it
serves as an interpersonal stressor that impacts develop-
mental processes central to adolescents (e.g., ethnic-racial
identity, peer acceptance, self-concept, and emerging
abstract reasoning; Hughes, Watford et al. 2016). Peer
discrimination encompasses direct biased mistreatment by
peers due to race/ethnicity and also indirect experiences,
such as hearing classmates make jokes about racial groups,
contributing to a climate where youth feel devalued in
schools (Douglass et al. 2016). There has been variability
across past studies on the aspects of peer discrimination
assessed, including direct biased treatment (i.e., Niwa et al.
2014) or more indirect experiences (i.e., Berkel et al. 2010).
Indeed, indirect and direct peer discrimination are asso-
ciated with greater depressive symptoms and anxiety
symptoms in Mexican-origin youth across time. Greater
peer discrimination in 5th grade was associated with more
internalizing symptoms two years later (Berkel et al. 2010).
Similarly, greater peer discrimination in 7th grade predicted
greater depressive symptoms in 9th grade that declined over
time across high school (Delgado et al. 2017). Yet, neither
of these studies tested how longitudinal changes in peer
discrimination influenced subsequent outcomes.
Longitudinal Studies of Peer Discrimination
The majority of research on the longitudinal trajectories of
peer discrimination across early and mid-adolescence in

multiethnic samples has found declines in middle school
(Niwa et al. 2014; 27% Latinx), declines throughout high
school (e.g., Bellmore et al. 2012; 54% Latinx) or no
changes in high school (e.g., Greene et al. 2006; 45%
Latinx). Only one study has examined trajectories of peer
discrimination in a solely Latinx sample, finding that the
trajectories depended on neighborhood context (increases
for youth living in neighborhoods with fewer Latinx co-
ethnics) and nativity status (no changes for U.S. born youth
vs. declines for youth born outside of the U.S. (White et al.
2014; 100% Mexican-origin). Other studies in Latinx
samples examined trajectories using global measures of
discrimination (including peer discrimination) finding more
variability. One study documented increases from 9th to
10th grade (i.e., Benner and Graham 2011; 62% Mexican-
origin). Other studies found no changes across 10th to 12th
grades (Sirin et al. 2015; no information on country of
origin), or different classes of trajectories across 9th grade
to three years post high school (i.e., increasing, decreasing,
and two stable; Unger et al. 2014; no information on
country of origin)). Regardless of mean level trajectories,
there has been significant individual variability in trajec-
tories such that greater levels of discrimination across time
have been associated with worse depressive (Stein et al.
2016; 19% Latinx) and/or anxiety (Sirin et al. 2015)
symptoms in multiethnic samples. However, no past study
has examined how peer discrimination longitudinally relates
to depressive and/or anxiety symptoms in a solely Latinx
sample.
These disparate findings of peer discrimination trajec-
tories are likely in part due to differences in methodology
(i.e., age ranges, measurement), population (i.e., ethnic/
racial make-up) and context (i.e., diversity of school,
urbanity). Yet, longitudinal changes in peer discrimination

appear to depend on age range, with a recent study doc-
umenting that peer discrimination increases in middle
school and decreases in high school (e.g., Hughes et al.
2016; 24% Latinx). Understanding longitudinal changes in
discrimination may require modeling approaches that are
able to capture change with a higher level of granularity
(Benner 2017), including testing differences across specific
transitions.
Transition Points in Adolescence
School transition points have long been posited as critical
periods linked to increased risk for negative outcomes in
adolescence due to the convergence of changes across the
individual and environment (i.e., role demands, class sizes,
shifts in social networks, educational expectations, cogni-
tive development; Barber and Olson 2004). In particular,
the mismatch of the adolescent’s developmental needs for
interpersonal connections and support with school envir-
onments that are inherently less personal and rife with social
stress may serve to place youth at risk for internalizing
symptoms across time (Eccles et al. 1993). Additionally,
transitions to middle and high school are usually associated
with changes in student demographics where youth are
more likely to have greater exposure to other racial/ethnic
peers (Aud et al. 2010). In one study, the transition to high
school was associated with increases in Latinx students’
reports of discrimination, which translated to worse aca-
demic functioning (Benner and Graham 2011; 62% Mex-
ican-origin), and these increased reports were higher for
youth in schools with greater ethnic diversity. The changes
Journal of Youth and Adolescence (2019) 48:864–875 865

in the school context at transition points, together with shifts
in cognitive processes, likely set the stage for changes in the
experience of peer discrimination (Hughes et al. 2016b).
Increases in stressful peer experiences at critical transi-
tion points may translate to longitudinal risk in internalizing
symptomatology, as these experiences constitute inter-
personal rejections that build over time, interact with psy-
chobiological risk, and in turn, lead to greater
symptomology (Hankin 2015). A life course perspective on
the impact of racism highlights the importance of under-
standing how changes in settings may serve as risks for
increased exposure, and how this exposure may have psy-
chological impacts across time (Gee et al. 2012). Specifi-
cally, it is important to understand “sensitive periods”
where exposure to discrimination affects functioning at later
stages in development (i.e., at the end of adolescence). For
peer discrimination, changes in these experiences may be
uniquely damaging over time given the intersection of peer
salience and emerging identity processes (i.e., grappling
with oppression and unfair treatment; Hughes et al. 2016b).
Understanding the differential impact of transition points
on the development of internalizing symptoms necessitates an
individual differences approach that allows modeling of both
within person change at specific points in time and how those
changes predict subsequent adjustment (Rudolph et al. 2001).
The current article takes advantage of a latent change score
(LCS) framework that explicitly models changes across time
allowing for unique change-to-outcome prediction across time
(Castro-Schilo et al. 2016). In other words, an LCS can test
whether there are specific increases that are more problematic
or “risky” for particular psychological outcomes over time.
For the current article, this allows a test of how changes at
specific time points (increases or decreases in peer dis-
crimination) relative to other time points influence subsequent

anxiety and depressive symptoms later in development. This
article examined how changes in the interpersonal context at
key transition points influence subsequent symptomatology,
to decipher whether increases overall are more harmful or
there is unique harm from changes at the start of an educa-
tional experience. Increases in peer discrimination that are
timed at the transition points are hypothesized to be particu-
larly harmful, as these would be foundational for engagement
in school, potentially leading youth to perceive school as an
“inhibiting environment” (Garcia Coll et al. 1996).
Current Study
The transitions to middle and high school serve as key
developmental milestones that are associated with
increased psychosocial risk, including potential experi-
ences with peer discrimination associated with these
transitions. Building off past longitudinal work on peer
discrimination predicting internalizing symptoms long-
itudinally, this study tests the impact of changes in dis-
crimination at specific points in development in a Latinx
sample. The current article used an LCS framework to test
whether increases in peer discrimination at these educa-
tional transition points were associated with greater
internalizing symptoms in 12th grade.
It was hypothesized that Mexican-origin youth would
experience increases in peer discrimination at both the
middle school and high school transitions (i.e., 6th to 7th
and 8th to 9th). In order to test the uniqueness of the timing
effect, changes were examined for every grade, as has been
done in previous tests of transition points (e.g., Barber and
Olson 2004). Because past work has found greater increases
in discrimination in boys relative to girls (e.g., Benner and
Graham 2011), the analyses also tested whether biological

sex affected these increases. Moreover, it was hypothesized
that baseline peer discrimination would be related to more
anxiety and depressive symptoms overall, and that increases
at the transition to middle and high school would be asso-
ciated with greater depressive and anxiety symptoms at 12th
grade controlling for symptoms in 5th grade and socio-
economic status and nativity.
Method
Participants and Procedures
The current article used data from the California Families
Project (CFP), which was granted approval by the University
of California at Davis Institutional Review Board (Protocol #
217484-21). CFP is a longitudinal study of Mexican-origin
youth and their parents (N = 674) that started in 2006. Chil-
dren were drawn at random from rosters of students from the
Sacramento and Woodland, CA, school districts (83 different
elementary schools). Across the first four waves of data col-
lection, the Sacramento school district served a high percen-
tage of low-income students (64–71% of students were
eligible for free or reduced lunch) and a very diverse ethnic
demographic (32–36% Hispanic, 18–21% White, 18–21%
Asian, 18–21% African American, 5–9% other; DataQuest
2013). The Woodland school district also served a high per-
centage of low-income students (49–63% of students were
eligible for free or reduced lunch) and a diverse ethnic
demographic (57–63% Hispanic, 28–33% White, 5% Asian,
1% African American, 3–6% other; DataQuest 2013). The
focal child had to be in the 5th grade, of Mexican origin, and
living with his or her biological mother to participate in the
study. Approximately 72.6% of the eligible families agreed to
participate in the study. The children (50% female) were
assessed annually from 5th (Mage at Wave 1 = 10.86, SD =
0.50) through 12th grade (Mage at Wave 8 = 17.73, SD =

866 Journal of Youth and Adolescence (2019) 48:864–875
0.52). Data collection occurred from 2006 to 2015 for the
waves in the present study. Family-level retention rates
(relative to the original sample) were 85% at 6th grade, 86%
at 7th grade, 89% at 8th grade, 91% at 9th grade, 89% at 10th
grade, 90% at 11th grade, and 92% at 12th grade. To
investigate the potential impact of attrition, individuals who
did and did not participate in the 12th grade assessment on
study variables assessed in the 5th grade were compared. No
significant differences were found in the study variables or
gender, all p’s > 0.10. Participants were interviewed in their
homes in Spanish or English, depending on their preference.
Interviewers were bilingual and most were of Mexican heri-
tage. Across Waves 1 to 8, between 3.9% and 15.0% of the
focal children were interviewed in Spanish. Sixty-three per-
cent of mothers and 65% of fathers had less than a high
school education (median = 9th grade for both mothers and
fathers); median total household income was between
$30,000 and $35,000 at Wave 1 (overall range of income = <
$5000 to >$95,000). With regard to generational status,
83.6% of mothers and 89.4% of fathers were first generation
(born outside the United States), and 16.4% of mothers and
10.6% of fathers were born in the United States. Also, 28.5%
of children were first generation and 71.5% were born in the
United States. At Wave 1, 124 of the families were single-
parent households (mothers only), and 549 of the families
were two-parent households. Ninety-seven percent of youth
transitioned to middle school in 7th grade and the high school
transition occurred at 9th grade for all youth.
Measures

Peer discrimination
Three items assessed peer global experiences of discrimination
reported by youth at every wave of data collection (Johnston
and Delgado 2004), and this measure of peer discrimination
has been used in other samples of Mexican-origin youth
reviewed above (Delgado et al. 2017). Youth responded on a
4-point Likert-type scale (1 = not at all true to 4 = very true)
on items assessing direct and indirect discrimination from
peers (i.e., You have heard kids at school making jokes or
saying bad things about Mexicans/Mexican-Americans; Kids
at school think bad things about Mexicans/Mexican Amer-
icans; Kids at school dislike Mexicans/Mexican Americans).
Coefficient alpha across waves ranged from 0.74 to 0.81.
Anxiety and depressive symptoms
The National Institute of Mental Health (NIMH) Diagnostic
Interview Schedule for Children-IV (DISC-IV) is a com-
monly used measure that assesses 30 different psychiatric
diagnoses for children and adolescents (Shaffer et al. 2000).
This measure has been validated in both English and Spanish.
This study used the child reported Generalized Anxiety Dis-
order (GAD; 65 items/12 symptoms) diagnostic section from
the Anxiety Disorders module and the Major Depression
Disorder (MDD, 256 items/22 symptoms) portion of the
Mood Disorders section from the DISC-IV. Children reported
whether they had experienced a symptom within the past year
(0 = no, 1 = yes). Symptom counts variables were calculated
for both GAD and MDD per wave. Only child-reported
symptoms were collected in this data set.
Covariates
The analyses included education, income, and youth

nativity (born in Mexico or born in the US) as control
variables for the key outcomes of anxiety and depression.
Mothers’ and fathers’ educations were reported by mothers
in years of schooling (M = 9.26, SD = 3.31) and were
included as the average across mothers and fathers, or only
mothers when data for fathers were not available. Mothers
reported family income in the first wave of data collection
using a 20-point scale with $5,000 increments (M =
$30,000–$35,000, SD = $15,000–$20,000).
Data Analysis
A latent change score (LCS) framework was used to
explicitly model changes in reported global discrimination
from peers across waves of assessment (5th to 12th grades).
Higher-order LCS models (Ferrer et al. 2008) allowed for
modeling of time-specific, error-free changes that were used
as predictors of subsequent psychological outcomes (e.g.,
Castro-Schilo et al. 2016). This was particularly useful for
this investigation because change-to-outcome effects could
vary over time. Traditional linear latent growth curve
models summarize rates of change in one latent variable
(i.e., slope) across all waves of measurement, whereas LCS
models enable specification of rates of change from one
wave to the next. The multiple change factors provide more
granularity to the overall trajectory and can be used to
predict future outcomes.
To account for measurement error in the latent change
factors, a measurement model for discrimination was spe-
cified at each measurement occasion. Tests of factorial
invariance (Widaman and Reise 1997) were then conducted
as a preliminary step to establish that the same construct
was modeled over time.
The higher-order LCS model can be written as

X tð Þn ¼ τx þ λxf tð Þn þ exðtÞn;
Y tð Þn ¼ τy þ λyf tð Þn þ eyðtÞn; and
W tð Þn ¼ τw þ λwf tð Þn þ ewðtÞn; with
Δf tð Þn ¼ μΔðtÞ þ β � f t�1ð Þn þ zΔn;
ð1Þ
where X, Y, and W, are manifest variables for person n at
time t, τ, λ, and e are the intercepts, factor loadings, and
unique factor scores, respectively, for each observed
variable, Δf represents change in factor f at time t, μΔ is
the intercept of the change factors at time t, β is a coefficient
representing the effect of the factor at the previous state on
the change, and zΔn is the residual of latent change. Thus,
the score of the latent factor f for person n at any given time
t can be written as a function of its initial state plus all the
changes accumulated up to time t, as
f tð Þn ¼ f0n þ
Xt
i¼1
Δf ið Þn
!
ð2Þ
Figure 1 provides a path diagram for the higher-order
LCS model. This figure depicts three manifest variables
measured across eight occasions. For the repeated assess-

ments, new latent variables f(t) are specified to facilitate the
higher-order LCS parameterization. With these new latent
variables, Δf(t)n are specified, which represent latent changes
from one occasion to the next. Latent change factors at each
occasion are influenced by the status in a previous time
point and by the average trajectory. The degree to which the
previous status influences changes is captured by the β
coefficients. Analogous to latent growth curve models,
means of change factors (μΔf(t)) are also estimated (the mean
of the higher-order level is fixed at zero for identification).
The factor’s longitudinal trajectory is modeled through
latent, error-free changes. Outcomes of change factors and
covariates can be included as depicted by the gray boxes.
Model Fit and Model Comparisons
A chi-square, χ2, comparative fit index (CFI; Bentler 1990)
and root mean square error of approximation (RMSEA;
Steiger 1990) was used to assess model fit. The χ2 statistic is
sensitive to sample size (Bollen 1989), such that models
with larger sample sizes tend to result in a significant χ2
(interpreted as significant misfit) despite having appropriate
fit to the data; thus, CFI and RMSEA estimates were
assessed when considering model fit and conducting model
comparisons. CFI values of .95 or greater and RMSEA
values of .10 or lower are interpreted as adequate fit
(MacCallum et al. 1996). With regard to model compar-
isons, a change in CFI and RMSEA of .01 or greater sug-
gests a substantial change in model fit (Cheung and
Rensvold 2002).
Results
Descriptive Statistics and Factorial Invariance

Three items were available at each wave from 5th to 12th
grade, and means varied across items and time points (item
means = 1.189–1.639; SD = 0.440–0.856; sample sizes =
565–661). These values suggest that, overall, participants
reported low levels of peer discrimination across the dura-
tion of the study. Standard recommendations for assessing
longitudinal factorial invariance (Widaman and Reise 1997)
were followed. After specifying a configural invariance
model—that is, one in which the same set of items over
time are indicators of multiple time point peer discrimina-
tion latent variables—equality constraints were placed on
the factor loadings and there was support for weak factorial
invariance (Δχ2 = 33.15, Δdf = 14, p = 0.002, ΔCFI =
0.003, ΔRMSEA = 0.000). Next, a test for strong factorial
invariance was conducted by placing equality constraints on
intercepts over time and found these restrictions tenable
(Δχ2 = 30.42, Δdf = 14, p = 0.006, ΔCFI = 0.003,
ΔRMSEA = 0.000). Equality constraints on uniquenesses,
however, resulted in large deterioration of model fit, as
assessed by much larger changes in chi-square, CFI and
RMSEA (Δχ2 = 354.49, Δdf = 21, p < 0.001, ΔCFI =
0.058, ΔRMSEA = 0.018). Thus, strict factorial invariance
did not hold and the strong invariance model was retained.
Fig. 1 Path diagram of higher-order latent change score (LCS)
model
across eight waves of assessment. Manifest variables are
represented
by squares. Latent variables are represented by circles. The
triangle
represents a constant to estimate means and intercepts.
Although not
depicted in this figure, covariances among unique factors of
same
manifest variables across time are estimated. Factor loadings,

manifest
variable intercepts, unique variances, and change factor residual
var-
iances are represented as invariant over time. Covariates and
outcomes
are represented as a group in the gray boxes. The second row of
factors
is specified to facilitate estimation of the model
Strong factorial invariance suggests comparable con-
ceptualization of peer discrimination over time and enables
a meaningfully assessment of longitudinal changes in this
process (Widaman and Reise 1997).
Peer Discrimination Trajectories
A higher-order LCS model was fit to these data to capture
the year-to-year changes in peer discrimination. The LCS
framework captures error-free changes to get a more accu-
rate picture of the trajectories over time. The first specified
model was estimated such as that portrayed in black in Fig.
1 (i.e., focusing only on the longitudinal trajectories of
perceived peer global discrimination). This model provided
good fit to the data, χ2(250) = 518.32, CFI = 0.953,
RMSEA = 0.040. This model was compared to one in
which the auto-proportion parameters (the beta coefficients
in Fig. 1) were constrained to be equal over time, χ2(256) =
534.46, CFI = 0.951, RMSEA = 0.040, and these con-
straints did not affect the fit of the model substantially, Δχ2
(6) = 16.14, ΔCFI = 0.002, ΔRMSEA = 0.000. However,
comparing the model in Fig. 1 to one with equal means of

latent change factors over time, χ2(256) = 625.31, CFI =
0.935, RMSEA = 0.046, suggested such constraints were
not tenable, Δχ2(6) = 106.99, ΔCFI = 0.016, ΔRMSEA =
0.006. In sum, the model comparisons suggested that peer
discrimination trajectories were best characterized by the
model portrayed in Fig. 1 but with equal auto-proportion
estimates.
Parameter estimates from the final model pointed to
significant changes, on average, from 5th to 6th grade, μΔf2
= −0.165, SE = 0.03, p < 0.001, followed by non-
significant average changes from 6th to 7th and 7th to 8th
grades, μΔf3 = −0.031, SE = 0.03, p = 0.219 and μΔf4 =
0.016, SE = 0.02, p = 0.483, respectively. Thereafter, all
changes were statistically significant, including those from
8th to 9th grade, μΔf5 = 0.090, SE = 0.02, from 9th to 10th,
μΔf6 = −0.069, SE = 0.02, 10th to 11th grade, μΔf7 = 0.091,
SE = 0.02, and 11th to 12th grade, μΔf8 = −0.144, SE =
0.02, all ps < 0.001. Importantly, there was significant
variability in peer discrimination at baseline (5th grade) σ2f 0
= 0.123, SE = 0.02, p < 0.001, and also in the residual
variance of latent changes, σ2Δ = 0.04, SE = 0.01, p < 0.001,
pointing to significant departures from the average trajec-
tory across all time points. Furthermore, the auto-proportion
coefficient was also significant, b = −0.15, SE = 0.02, p <
0.001. This effect suggests significant negative influences
between status on peer discrimination on a given grade and
subsequent changes in this construct. Because there are two
“forces” dictating individual trajectories of peer dis-
crimination—namely, the auto-regressive effect and the
mean changes—plotting the model-predicted latent trajec-
tories can be useful for interpreting results. These
trajectories, from grades 5 to 12 for a random sample of 100
individuals (to facilitate interpretation of the plot), are
shown in Fig. 2.

The average trajectory in Fig. 2 shows the average
decreases in peer discrimination in the first year of the
study, followed by two years of stability and a further
increase, decrease, increase, and a final decrease during the
last year. However, the individual trajectories in this plot
also illustrate the departures from the average trajectory for
a subset of individuals. For example, some individuals
increase in peer discrimination from 5th to 6th grade, which
is contrary to the average trajectory. Similar discrepancies
with the average trajectory are apparent across time for
some individuals, reflecting the significant variability in
change over time.
To investigate whether girls and boys differ in their
perceived peer global discrimination, an additional model
was fit in which a binary predictor (0 = male, 1 = female) of
the initial level and subsequent latent change factors of peer
discrimination were included. Results from this model
suggested null effects of gender on baseline (b = −0.08, SE
= 0.05, p = 0.147) and changes in trajectories over time (b
= 0.04, −0.05, 0.03, −0.06, 0.01, 0.06, −0.01, SE = 0.05,
0.06, 0.05, 0.04, 0.04, 0.04, 0.04, 0.04, p = 0.147, 0.452,
0.326, 0.555, 0.160, 0.776, 0.143, 0.800, for changes from
5th to 6th, 6th to 7th, 7th to 8th, 8th to 9th, 9th to 10th, 10th
to 11th, and 11th to 12th grade, respectively).
Outcomes of Peer Discrimination Changes
The last step in this investigation consisted of unveiling the
associations of youths’ patterns of change in peer dis-
crimination with future internalizing outcomes. These ana-
lyses tested whether levels of peer discrimination at 5th
grade and ensuing changes in this construct through 12th
grade were predictive of anxiety and depressive symptoms
at 12th grade. These analyses accounted for the effect of

Fig. 2 Implied model trajectories of peer discrimination from
5th to
12th grades for a randomly selected sample of 100 participants.
The
thick dotted line represents the average model implied
trajectory
parental education, family income, nativity, and anxiety and
depressive symptoms measured at 5th grade (see gray boxes
in Fig. 1). Fit indices for this model suggested good fit to
these data, χ2(403) = 700.49, CFI = 0.951, RMSEA =
0.033. Regression estimates for the model are listed in
Table 1. In line with the hypotheses, results suggest that
baseline levels of peer discrimination at 5th grade sig-
nificantly predicted anxiety, β = 0.26, b = 1.09, SE = 0.35,
p < 0.005, and depressive symptoms, β = 0.25, b = 2.35,
SE = 0.76, p < 0.005, 7 years later. Importantly, changes in
peer discrimination between grades 7 and 8 (1 year after the
transition to middle school) and grades 9 to 10 (1 year after
the transition to high school) predicted future anxiety
symptoms at 12th grade, β = 0.25 and 0.31, b = 1.70 and
2.07, SE = 0.70 and 0.73, p < 0.05 and <0.01, respectively.
Specifically, increases in peer discrimination during those
years, and not at other timepoints, were associated with
higher levels of anxiety symptomatology in 12th grade. In
contrast, none of the latent change factors were predictive of
future depressive symptoms.
It is important to note the analyses originally also
attempted to include teacher discrimination. However, the

distributions of the items were highly skewed and initial
models either did not converge or produced non-positive
definite matrices, thus leading to the focus on peer
discrimination.
Discussion
Due to the negative psychological impact of peer dis-
crimination across adolescence, research has attempted to
understand the trajectories of peer discrimination in middle
and high school aged youth and their relation to mental
health functioning, with multiple studies supporting this
longitudinal association (Benner et al. 2018). Public health
models attempting to understand health inequities have
argued for a life course perspective testing whether
experiences of discrimination at earlier points in develop-
ment may serve as sensitive periods predicting later func-
tioning (Acevedo-Garcia et al. 2013). Similarly, transitions
to middle and high school have been suggested to serve as
potential risks to adolescent functioning (Barber and Olson
2004). However, no past longitudinal study of peer dis-
crimination has taken this approach and examined how
increases at transition points (i.e., transition to middle and
high school) impact subsequent mental health functioning
(i.e., depressive and anxiety symptoms). To fill this gap in
the literature, this article examined changes in peer dis-
crimination across 5th to 12th grades in a Mexican-origin
sample. Using a novel statistical technique (LCS), the cur-
rent study was able to test whether increases in reports of
peer discrimination at particular points in development (i.e.,
transition to middle school or high school) uniquely pre-
dicted internalizing symptom at the end of high school.
Consistent with past work, peer discrimination in 5th grade
predicted greater symptoms of both depression and anxiety
in 12th grade, contributing to the literature on the negative
impact of these experiences across adolescence (Benner

et al. 2018). Further, there were significant differences in
the year-to-year changes in reports of peer discrimination,
supporting the need for research to consider how experi-
ences of discrimination may change across schooling peri-
ods and the need to take a life course perspective that tests
potential “sensitive periods” (Acevedo-Garcia et al. 2013).
Although there was no support for the hypothesis that
increases in peer discrimination immediately after the
transitions to middle and high school impact subsequent
functioning, increases in peer discrimination in the year
after the transition points in schooling were uniquely
Table 1 Regression estimates from higher-order latent change
score
model with internalizing outcomes
β b SE z p
Predictors of grade 12 anxiety
symptoms
Baseline grade 5 0.26 1.09 0.35 3.17 0.002
Changes grade 5–6 −0.17 −1.12 0.95 −1.19 0.236
Changes grade 6–7 0.14 0.94 0.73 1.29 0.197
Changes grade 7–8 0.25 1.70 0.70 2.42 0.015
Changes grade 8–9 0.00 0.02 0.69 0.03 0.973
Changes grade 9–10 0.31 2.07 0.73 2.84 0.005
Changes grade 10–11 −0.16 −1.09 0.72 −1.51 0.130
Changes grade 11–12 −0.07 −0.46 0.64 −0.73 0.466

Anxiety symptoms grade 5 −0.02 −0.01 0.04 −0.29 0.771
Depression symptoms grade 5 0.12 0.05 0.02 2.52 0.012
Income −0.02 −0.01 0.02 −0.39 0.694
Family education 0.09 0.04 0.02 1.89 0.059
Nativity −0.06 −0.20 0.14 −1.40 0.162
Predictors of grade 12
depression symptoms
Baseline grade 5 0.25 2.35 0.76 3.10 0.002
Changes grade 5–6 −0.01 −0.09 1.99 −0.04 0.966
Changes grade 6–7 0.13 1.96 1.62 1.21 0.225
Changes grade 7–8 −0.03 −0.41 1.53 −0.27 0.791
Changes grade 8–9 0.07 0.99 1.50 0.66 0.508
Changes grade 9–10 0.18 2.71 1.54 1.76 0.079
Changes grade 10–11 −0.13 −1.96 1.57 −1.25 0.212
Changes grade 11–12 −0.03 −0.49 1.42 −0.34 0.732
Anxiety symptoms grade 5 0.04 0.07 0.08 0.80 0.426
Depression symptoms grade 5 0.13 0.11 0.04 2.68 0.007
Income −0.03 −0.03 0.04 −0.74 0.462

Family education 0.02 0.02 0.05 0.31 0.754
Nativity −0.11 −0.85 0.32 −2.66 0.008
predictive of greater anxiety symptoms in 12th grade, while
this was not the case for depressive symptoms.
Peer Discrimination Trajectories
The average trajectory of peer discrimination from 5th to
12th grade suggested stability at the initiation of middle
school and an increase at the transition to high school.
Overall, this pattern of findings is opposite to what has been
documented in recent work examining both schooling per-
iods, suggesting increases in peer discrimination in middle
school and decreases in high school (Hughes, Del Toro
et al. 2016). The different set of findings across both studies
could be due to statistical modeling approaches, as the
Hughes et al., study did not examine each transition point
independently, but instead modeled discontinuous trajec-
tories across both time frames. Additionally, the measures
of peer discrimination were different with the current
measure assessing an overall sense of discrimination rela-
tive to the frequency of peer discrimination in the Hughes
study. However, it may also be that the discrepant findings
resulted from important differences in the samples’ demo-
graphics (i.e., multi-ethnic vs. Mexican-origin), location
(New York City vs. central valley CA), and schooling
contexts (the timing of the transition) that potentially
influence the experiences of peer discrimination (Hughes
et al. 2016). The Hughes et al., study purposefully selected
middle schools based on diversity indices which was not the

case for the CFP sample as youth were recruited from two
large school districts. Thus, there may have been significant
differences in the ethnic/racial composition changes asso-
ciated with the middle school transition across both sam-
ples, which has been shown to be important for the
transition of youth of color (Benner 2011). Finally, work
done in California has generally documented increases in
peer discrimination, particularly in the high school period
(i.e., the current results, Benner and Graham 2011), but
work done in New York has failed to find mean level
increases (i.e., Hughes et al. 2016a; Sirin et al. 2015; Niwa
et al. 2014). Indeed, ethnic concentration in neighborhoods
has been shown to influence peer discrimination trajectories
(White et al. 2014) suggesting that it will be critical for
future work on peer discrimination at school transitions to
further consider how context plays a role in the experiences
of peer discrimination.
The results align with other studies of Latinx adolescents
that find increases in reported discrimination during high
school (Benner and Graham 2011), and suggest the transi-
tion to high school may bring specific risk through increases
in discrimination for Latinx youth. However, this risk was
not specific to either boys or girls in the current sample,
whereas Benner and Graham demonstrated a difference for
boys. This may be due to the measures of discrimination, as
Benner and Graham did not focus just on peer discrimina-
tion and included items that may be more salient for boys
(i.e., people were suspicious of you; disciplined unfairly and
given detention), as there are demonstrated gendered dis-
cipline disparities for Latinx youth (Wallace, Goodkind,
Wallace and Bachman 2008). Further, the analyses con-
trolled for nativity in our analyses, but future work should
consider what other factors (i.e., language use, SES) influ-
ence peer discrimination.

Peer Discrimination and Symptomatology
Not surprisingly, and in line with a growing body of
research, baseline peer discrimination predicted worse
symptoms in 12th grade, controlling for 5th grade symp-
toms. As theorized in models of non-White youth child
development (i.e., Garcia Coll et al. 1996), negative peer
discriminatory experiences can have far-reaching con-
sequences in development. This is one of the few studies
that has longitudinally established this relation across such a
large range of adolescence (5th to 12th grades) for both
symptoms of anxiety and depression and in a solely Latinx
sample (see Delgado et al. 2017 for another paper testing
depressive symptoms).
Future work should unpack the individual and contextual
risk and resilience mechanisms that lead to this longitudinal
association. For example, a negative perception of school
climate may be an important mediator that is associated
with changes in the racial/ethnic compositions of school
environments and peer discrimination (Benner and Graham
2011) and merits further research attention. Concomitant
changes in discrimination and perceptions of school climate
may negatively impact psychosocial and academic func-
tioning for Latinx youth. Similarly, school attachment and
ethnic-racial identity exploration in middle adolescence
served to protect Mexican-origin youth from internalizing
symptoms in late adolescence (White et al. 2018), and these
processes may be important sources of resilience. Further,
recent work suggests that the relation between internalizing
symptoms and discrimination across adolescence is bidir-
ectional (Hou et al. 2015), and more work should endeavor
to examine how these processes relate across time, espe-
cially for depressive symptoms for which there was no
evidence of timing effects.

The analyses, however, did find timing effects for
symptoms of anxiety and suggests that increases in
experiences of peer discrimination at specific points may be
critical to understanding the longitudinal interplay of these
symptoms and discrimination, albeit not occurring at the
year immediately after the transition. Nevertheless, this
finding falls in line with life course theories of the impact of
racism and suggests that timing effects are important to test
(Gee et al. 2012). Increases in peer discrimination in the
years after both the middle and high school transitions were
associated with greater anxiety symptoms in 12th grade
suggesting that it is important to consider how experiences
of discrimination at these two different schooling intervals
function to set up developmental pathways across the
remainder of adolescence. Although the transition points
did not function as the point of risk, the findings do suggest
that both middle and high school may serve as a “sensitive
period” where changes have longitudinal ramifications for
anxiety symptoms. Overall, adolescence has been posited to
serve as a “sensitive period” to social rejection due to
functional and structural changes in brain development
(Blakemore and Mills 2014). Yet, there has not been a
significant amount of work examining “sensitive periods”
involved in experiences of discrimination. Transition
changes may be particularly demanding for youth with risk
for anxiety, as these youth may feel more wary of navi-
gating the changing social landscape of their new environ-
ment. For example, teasing about ethnicity and race led to
greater daily anxiety for youth with already high anxiety
and also feelings of social anxiety that were evident for days

after the incident (Douglass et al. 2016; 43% Latinx).
The findings of the current study suggest, however, that
the risk of the transition was not immediate but that changes
in the year following the transition were most detrimental.
Perhaps this may be due to the fact that youth had to have
some significant peer experiences within the new school
context for them to characterize their peers as holding these
beliefs. Consistent with this notion that it is not the
immediate transition that is most detrimental, in a study by
Benner and Graham (2009), the transition to high school
resulted in increases in school belonging that started dis-
sipating in the year following the transition. This suggests
that interactions with peers and teachers were necessary to
inform their experience of school belonging, which may
operate similarly for experiences of peer discrimination.
As youth begin to assimilate these experiences, this may
lead to increases in the race-based rejection sensitivity
(Mendoza-Denton et al. 2002), withdrawal from peer net-
works due to avoidance, and disengagement from the
school environment culminating in greater symptomatology
over time (Erath et al. 2007). Models of health disparities
have also highlighted that rumination and anticipation of
future discrimination exert a toxic effect on health (i.e.,
racial vigilance; race rejection sensitivity, Hicken, Kravitz-
Wirtz, Durkee, and Jackson 2018). Recent experimental
work by Huyhn et al. (2017) with Latinx emerging adults
suggests that exposure to indirect discrimination resulted in
greater cortisol output in a stress task and poorer recovery,
suggesting that altered stress responsivity may be involved
in the continued risk for anxiety symptoms overtime. Thus,
these changes may be particularly problematic for changes
in anxiety symptoms and not as relevant for depressive
symptoms, which have more immediate impact. Indeed,

using the same measure in different samples of Latinx
youth, Berkel and colleagues (2010) demonstrated increases
in depressive symptoms in the following time point (2 years
later), and Delgado et al. 2017 showed that discrimination
in 7th grade impacted increases in depressive symptoms in
9th grade that then had downward trajectories. Future work
should continue to examine how peer discrimination serves
as risk differentially for depressive and anxiety symptoms,
especially given that there is much less work examining
anxiety symptoms specifically (Priest et al. 2013), and
whether there are other potentially “sensitive period” for
other outcomes. Further, future work should also start to
identify moderators and mediators of these associations to
help lead to preventive efforts.
Limitations and Implications
The current study contributes to the literature on the life
course and peer discrimination through the unique exam-
ination of changes across adolescence and their relation to
internalizing symptomatology, but there are significant
limitations to this current study. First, the data set does not
have a measure of changes in the racial/ethnic composition
of the schools to test whether these changes were related to
changes in reports of peer discrimination. Second, the cur-
rent measure of peer discrimination was global in nature and
did not capture nuanced experiences of peer discrimination
that would potentially be different across gender and
nationality. These potential nuanced experiences would be
important to consider from an intersectional perspective. In
the same vein, this measure did not capture the source of
peer discrimination (i.e., other Latinx peers vs. non-Latinx
white peers, see Stein et al. 2018) which may also have
implications for mental health functioning. Finally, the
measure included overall perceptions of peer discrimination
(indirect and direct) instead of frequency of personal

experiences of discrimination from peers. Thus, changes
found in this study related to overall perceptions of peer
discrimination and bias are not changes in frequency of
personal discrimination, which would also be important to
test using LCS. Yet, this measure of discrimination has been
used to test developmental trajectories of discrimination in
other Latinx samples between 5th and 7th grades (Berkel
et al. 2010), 7th grade to post high school (Delgado et al.
2017), and 5th to 10th grades (White et al. 2014).
Conclusion
Peer discrimination negatively impacts Latinx youth across
development in multiple ways, including increasing risk for
internalizing symptoms (Berkel et al. 2010). Using a life
course perspective, the current study tested whether
increases in peer discrimination associated with the transi-
tions to middle and high school impacted anxiety and
depressive symptoms at the end of high school. This study
significantly contributes to the literature on longitudinal
trajectories of peer discrimination across adolescence by
leveraging a novel statistical technique that allowed for the
explicit modeling of changes across time and unique
change-to-outcome prediction. The study offers new
insights into the understanding of the negative ramifications
of peer discrimination by suggesting that increases between
7th and 10th grades predict worse anxiety symptoms across
time, pointing to a potentially “sensitive period” that war-
rants further investigation. However, contrary to our pre-
diction, increases in peer discrimination in the year after the
transition were particularly harmful for later anxiety

symptoms but not depressive symptoms. This suggests two
things: (1) additional work on the impact of schooling
transition examining peer interactions should further
examine when the risk is most pronounced (i.e, immediately
or after some time) and (2) it is important to continue to
examine the unique developmental pathways through which
discrimination impacts depressive and anxiety symptoms as
the current finding suggests that there may be cumulative
effects of peer discrimination on anxiety symptoms. Addi-
tionally, these findings highlight the importance of schools
addressing issues of peer discrimination and adopting zero-
tolerance policies about discrimination. Given that one of
the three items focused on peers making jokes or saying bad
things about Mexicans/Mexican Americans, this suggests
that experiences that may be viewed as less harmful or do
not involve physical threats still take a significant toll on the
mental health of Mexican-origin youth and warrant inter-
vention. Youth in general need help from adults to navigate
social contexts and create peer ecologies that are supportive,
and, given the findings related to peer discrimination in this
article, it is clear that adults in schools need to foster sup-
portive school cultures where all youth can thrive. In par-
ticular, it may be essential for schools to support youth in
the year after the transition to new school contexts to assess
their experiences of discrimination and pay special attention
to interventions at these points.
Authors’ Contributions All authors contributed significantly
intellec-
tually to the current manuscript. G.L.S. conceived the current
study
from an existing data set, helped plan the statistical analyses,
and
drafted the majority of the manuscript. L.C. conducted the
statistical
analyses, wrote the Data Analysis and Results sections, and

made the
Table and Figures. A.C., Y.M. and K.C. contributed to the
literature
review, interpretation of data, and manuscript preparation. R.R.
con-
ceived and designed the original study, secured funding,
coordinated
data collection, and helped draft the manuscript. All authors
read and
approved the final manuscript.
Funding This research was supported by a grant from the
National
Institute on Drug Abuse (DA017902) to Richard W. Robins and
Rand
D. Conger. We thank the participating families, staff, and
research
assistants who took part in this study. The content is solely the
responsibility of the authors and does not represent the official
views
of the National Institutes of Health.
Data Sharing and Declaration The datasets generated and/or
analyzed
during the current study are not publicly available.
Compliance with Ethical Standards
Conflict of Interest The authors declare that they have no
conflict of
interest.
Ethical Approval The California Families Project (CFP) was
granted
ethical approval by the Institutional Review Board (Protocol #
217484-27) of the University of California, Davis. All authors

have
complied with the American Psychology Association’s ethical
stan-
dards in the treatment of our sample.
Informed Consent Per IRB requirements, all study participants
pro-
vide informed consent to be in the study.
Publisher’s note: Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional
affiliations.
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TrajectoriesOutcomes of Peer Discrimination
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Discrimination and SymptomatologyLimitations and
ImplicationsConclusionCompliance with Ethical
StandardsACKNOWLEDGMENTSReferencesA9A10A11A12A1
3A14
Term Project
Financial Statement Analysis of Autonation and Lithia Motors
Inc.

Prepared by
Monica Galindo
For
Professor C.E. Reese
in partial fulfillment of the requirement for
ACC 770 – Managerial Accounting
School of Business/Graduate Studies
Miami Garden, Fla.
Term A2/Spring, 2017
May 11, 2017
Table of Contents
Introduction 1
Business history and future 2
Financial analysis 6
Liquidity analysis 12
Activity analysis 14
Solvency analysis 15
Profitability analysis 16
Comparative analysis 18
Summary and Conclusions 21
Appendices 22
References 29

3
Term Project
Financial Statement Analysis of Autonation and Lithia Motors
Inc. 2014 - 2016
Prepared by
Carlos Flores
For
Professor C.E. Reese
in partial fulfillment of the requirement for
FIN 751 – Managerial Accounting
School of Business/Graduate Studies
Miami Garden, Fla.
Term A2/Spring, 2017
May 11, 2017
Table of Contents
Introduction 2
Business history and future 3
Financial analysis 7
Liquidity analysis 14
Activity analysis 15
Solvency analysis 16

Profitability analysis 18
Comparative analysis 19
Summary and Conclusions 22
Appendices 24
References 31
Introduction
a. Objective
This paper conducts a comparative financial analysis on
AutoNation and Lithia Motors with the objective to assess the
financial health of the companies. Financial analyses provide
objective answers and gives companies support for making
informed decisions. By reviewing past and current financial
statements and comparing them to the automobile industry,
future predictions can be made to ensure that the companies can
be profitable. Financial analyses thus allows companies to
discover areas that must be improve to ensure that creditors
look favorable upon the companies and drive profit potential
(Asongu, 2015).
b. Scope
This financial analysis is conducted to understand key business
ratios to understand AutoNation and Lithia Motors stability and
compare business's financial performance to competitors and the
industry as a whole. In the end, creditworthiness is assessed for
both companies to determine if credit should be extended as
well as the recommendations for both companies after all of the
data has been analyzed and interpreted.
c. Methodology
The information from balance sheet, income statement and other
financial statements will be used to calculate the relevant ratios
to complete these analyses. The relevant ratios that will be used
are the liquidity, activity, solvency and profitability ratios. The
financial statements will then be used to conduct vertical and

horizontal analyses to indicate any changes in the companies’
accounts and evaluate which accounts uses much of the
companies' money. The various computations and websites
references will be employed to analyze the data and make sound
interpretations, recommendations and conclusions.
Business History and Future
a.Industry
The automobile industry is made up of several companies in
USA as well as in the global arena. Currently the US sector
market cap stands $61 billion with annual sales at 7.7 million
cars. The motor vehicles and parts are offered mostly through
franchises network. Although there exists variations in many
companies operations under the automobile industry, most of
the companies like Lithia and AutoNation deal in both new and
used cars. It is estimated that new cars make up to 60% of the
market whereas used cars fills the remaining 40%.The vehicles
being offered come from the leading global brands such as GM,
Toyota, BMW, Honda, Volkswagen, Porsche as well as Mazda.
The franchise form of business has enabled many automobile
oriented firms like Lithia and AutoNation to benefit from
opportunistic capital allocation strategy, including acquisitions
and share repurchases, and which have began to reduce the cost
structure and inventory levels to the current industry quality
levels.
b. Auto Nation
AutoNation is are renowned motor company and is currently the
largest automotive dealer in the US as well as the leading
provider of new and second-hand vehicles. The company has
organized its business through franchise as it is estimated that
the firm owns more than 310 franchises in USA. The current
President and CEO is Mike Jackson, who was the former CEO
of Mercedes-Benz in North American region (Calta & Kleiner,
2001).
The started back in 1996, when entrepreneur H. Wayne

Huizenga ventured in a waste management company that
subsequently changed its name to Ft. Lauderdale and then to
FL.-based Republic Industries, Inc. It would then go ahead to
acquire about 300 new vehicle franchises, making it to be the
first nationwide auto dealer in the U.S. as well as the first to go
public. It was until April 1999, when Republic changed its name
to the current "AutoNation, Inc., the company we are currently
evaluating.
AutoNation currently operates over 300 franchises across the
USA, and has about 87,500 employees. It specializes in selling
35 different manufacturer brands across 15 states. The company
is currently ranked at #136 in the 2016 Fortune 500.It has
personalized its operations with a large internet presence,
offering its entire inventory for online searching. Due to this
efficiency the company current stock price is at $40.26 reported
a revenue increment of 4.2% to $5.44 billion and net income of
$ 112 million which represents a slight drop of 2.7%.
c. Lithia Motors
Lithia Motors was founded by Walt DeBoer in 1946 as a
Chrysler-Plymouth-Dodge dealership mainly based in Ashland,
Oregon. Currently, Lithia is among America’s largest
automotive dealers featuring most domestic and import
franchises. The Lithia stores serve rural and urban populations
across the Western and Midwest United States.
It is the 7th largest automotive retailer in the US and was
ranked #14 as Fortune’s Most Admired Companies in 2013.It
then broke into Fortune 500 list at #482 in 2015 making it one
of the only three Oregon-based companies in the Fortune
500.https://en.wikipedia.org/wiki/Lithia_Motors - cite_note-
sale_final-5 This came following a year that saw the acquisition
of the DCH Auto Group, which was one of largest dealer groups
in the country with 27 dealership outlets, before being acquired
by Lithia Motors.
Lithia specializes in new cars from Toyota, General Motors,
Toyota, BMW, Honda, Volkswagen, Porsche and Mazda, among
others. New cars make up 58% of auto sales, with second hand

cars making up 42%. The firm gets extra revenues from auto
repair at the dealerships, financing, and insurance sales.
Financial Analysis
The financial analysis will cover the key aspects of ratio
analysis and insights then the computation of horizontal and
vertical analysis tables. The liquidity ratios often evaluate
business's ability to pay off or service its short-term debt. The
two ratios used to evaluate the liquidity ratios business are the
current ratio and quick ratio. This will be followed by the
activity ratios to assess how Lithia Motors and AutoNation
often convert different assets, liabilities, and capital accounts
into cash.
Additionally, the solvency ratio which covers TIE and debt ratio
will show us how AutoNation and Lithia Motors can meet their
long term debt or their ability to sustain operations into
unforeseen future. We will then evaluate the profitability ratios
which aims at maximizing shareholder value as well as the
investment potential ratios. In the end the horizontal and
vertical statement analyses are presented to enable us to see the
variations in various economic items as well as the amount of
money a company spends in the key items of the financial
statements.
The following sections thus discusses the financial analysis in
more details.
IV. Liquidity Ratios and Analysis
Liquidity Ratios
2014
2015
2016
Industry
AutoNation

Lithia
Industry
AutoNation
Lithia
Industry
AutoNation
Lithia
Current Ratio
1.13
1.02
1.24
1.08
1.03
1.12
1.05
0.91
1.18
Quick ratio
0.22
0.22
0.22
0.23
0.23
0.23
0.21
0.19
0.22
As aforementioned, the liquidity ratio covers current and quick
ratio. The current ratio measures the ability to pay current
liabilities with reference to current assets whereas the quick
ratio evaluates the ability to pay all current liability if they
come due immediately; the relevant assets to use are the
business's cash, short-term investments, and net current
receivables. In our case we are evaluating the liquidity ratio
with reference to AutoNation and Lithia Motors as well as a

brief insight on the industry.
a.Industry
The above table highlights the liquidity ratio for automobile
industry. The current ratio, 1.13 and quick ratio is 0.22.Almost
average to the most industries in the USA. The current ratio
reflects that the two firms has a very low liability base and the
ratio could only reduce if the companies enters into short debt
obligations. Thus the two firms are very liquid and stable in the
automobile sector as reflected by the strong base of current
assets compared to current liabilities.
However, the quick ratio is too low. This implies that it is not
easy to convert the account receivables into cash quickly and it
reflects the ideal conditions of operations since motor vehicles
are less liquid assets (long term assets). However, the industry
quick ratio remained consistent in the subsequent years being
reported at 0.23 in 2015 and a slight drop which brings it to
0.21 in fiscal year 2015.The current ratio on the other hand has
shown a declining trend reported at 1.08 and 1.05 respectively
in 2015 and 2016 respectively may be due increased cash
expenditure.
b. AutoNation
AutoNation’s current ratio shows a good trend of liquidity. The
ratio stood at 1.02 in 2014, 1.03 in 2015 and a slight drop at
1.05 in 2016. On the same note its quick ratio were far much
lower implying a lesser degree of cash conversion and limited
short term investments. The quick ratio increased slightly to
0.23 in 2014 from 0.22 the previous year, but it then closes in
2015 by a drop to 0.19.The current ratio shows a lower value of
current liabilities and the firm need to enhance its marketable
securities as well as the receivables to improve the quick ratio.
c. Lithia Motors
Lithia motors quick ratio exhibits the same trend as AutoNation.
They are at par with its quick ratio reflected at 0.22 in 2014;

0.23 in 2015 and closing at 0.22 in 2016.Lithia Motors however
shows little stability compared to AutoNation in the quick ratio
trend. The firm also needs to leverage on its receivables and
short term investments to enhance the too low quick ratios.
When it comes to current ratio Lithia Motors performed
extremely well above both the AutoNation and the industry
average. Its ratio stood at 1.24 in 2013; 1.12 in 2015 and ending
at 1.18 in 2016.This indicates that the firm has enhanced its
working capital position and is in a better position to service its
debts compared to its peers in the industry such as AutoNation.
V. Activity Ratios and Analysis
Activity Ratios
2014
2015
2016
Industry
AutoNation
Lithia
Industry
AutoNation
Lithia
Industry
AutoNation
Lithia
Inventory Turnover
4.96
5.65
4.27
4.98
5.63
4.33
5.17
5.41

4.92
Day's Sales In Receivables
6.26
3.8
8.71
9.01
2.25
15.77
8.14
2.26
14.01
Activity ratios will show us how Lithia Motors and AutoNation
can convert different assets, liabilities, and capital accounts into
cash and how soon that can be the conversions are done. The
common ratios in this category are the inventory turnover and
days' sales in receivables. The inventory turnover the number of
times an enterprise sales its average inventory levels in a given
fiscal year whereas the days' sales in receivables reflects how
many days it takes to earn the receivables.
a. Industry
It is clear that inventory turnover (4.96 in 2013;4.98 in 2014
and 5.17 in 2015) in Automobile Sector in USA is average to
most of the other industries. This is because as much as the
companies order vehicles it is less frequent to the industries
dealing with fast-moving goods. The receivable days (6.26 in
2013; 9.01 in 2014 and 8.14 in 2015) is also relatively high in
comparison. This is because the firm deal in high valued items
(motor vehicles) which it is comparatively rare for the
customers to pay everything on spot. Further most firms use
installment payments or sales on account when selling the
vehicles. The firms in the sector can thus put incentives to
ensure the receivable days are reduced to enhance cash flows.
b. AutoNation

AutoNation inventory turnover ratio seems to be slightly above
the industry average standing at 5.65 in 2014; 5.63 in 2015 and
finally dropping to 5.41 in 2016. However, the firm’s sales
remained in account receivable less long at averagely 2 days
than the industry norm, which is averages at 5 days. AutoNation
is thus much more efficient in receiving cash from its customers
earlier and enhance its liquidity position compared to its
competitor Lithia Motors.
c. Lithia Motors
Lithia Motors is slightly below the industry level of inventory
turnover with the latest ratio in 2016 standing at 4.92 compared
to industry’s 5.17. The low turnover implies less sales and
explains why the firm is not properly servicing its short-term
debts. The much worrying trend on Lithia Motors is its
receivable days which is far much longer than the industry
level. Funnily the trend is upward as the ratio stood at 8.71 in
2014,increased to 15.77 in 2015 and remained further up at
14.01 in 2016.The longer a company gets paid by its customers,
the less likely it will be able to pay it short-term debt (becomes
less liquid).
VI. Solvency Ratios and Analysis
The solvency ratio will show us how AutoNation and Lithia
Motors can meet their long term debt or their ability to sustain
operations into unforeseen future. The key ratios to measure
solvency are the times interest earned and the debt ratio. The
debt ratio indicate what percentage assets are financed with
debt. If the percentage is less than 50%, then the business is
sustained by its equity, whereas a percentage of greater than
50% means implies the business is using debt cover its assets.
Solvency Ratios
2014
2015
2016

Industry
AutoNation
Lithia
Industry
AutoNation
Lithia
Industry
AutoNation
Lithia
Debt
0.42
0.48
0.36
0.46
0.51
0.40
0.44
0.53
0.35
TIE
7.14
5.27
9.00
7.72
5.87
9.56
6.79
5.84
7.73
a. Industry
The automobile industry's average debt in all the three years lie
below 50% implying that most firms in the sector are able to
fund the business more with equity compared to debt. The

industry's times-interest-earned (TIE) ratio stood at 7.14 in
2013; 7.72 in 2015 and 7.73 in 2016 and indication that the
firms in the industry are much efficient in managing their debt
repayment .The degree of consistency is also stable a reflection
of a well performing industry.
b. AutoNation
The AutoNation’s debt ratio is at a risky point. Its debt ratio
started at 0.48 or 48 % slightly below the 50% but rose rapidly
to 51% and then to 53% implying that the debt obligations are
increasing. AutoNation thus appears to be more dependent on
debt compared to equity. Further, the ratios are above the
industry level and implies that the company will have to pay
more interest due to more debt financing which can lead to a
decline in net income. TIE often indicates how many times a
company can cover its interest charges on a pretax earnings
basis. AutoNation has performed dismally in this case due to its
TIE lying below the industry average implying it did not
adequately cover the interest expenses.
c. Lithia Motors
Lithia Motors have shown outstanding performance on TIE .The
firm reported an increasing performance of interest earned
compared to the interest obligations. The ratio stood at 7.14 in
2014; 9.00 in 2015 and then closes at 9.56 in 2016 way above
the industry average. Further the firm’s debt ratio is also
appealing lying below 50% in all cases showing that it heavily
relies on equity for its financing and this is efficient it the
company enhancing its retained earnings due to low interest
obligations.
VII. Profitability Ratios and Analysis
The profitability ratios are used to evaluate a company’s ability
to generate earnings in a given fiscal year. Many ratios are
employed to determine a firm’s profitability. The ratio we will
discuss here include Return on Assets (ROA), Return on Equity
(ROE ),Return on Sales as well as the Earnings Per Share
(EPS) .The rate of return on net sales indicates the measure the

net income earned per dollar of sales.
The ROA on the other hand indicates how effectively a
company is using its assets to generate earnings before
contractual obligations must be paid. Next is the rate of return
on common stockholders' equity which evaluates how much
income is earned with the money invested by common
shareholders and finally the earnings per share of common
stock gives the amount of net income for one share of the
business's common stock.
Profitability Ratios
2014
2015
2016
Industry
AutoNation
Lithia
Industry
AutoNation
Lithia
Industry
AutoNation
Lithia
Return (Net Sales)
2.40%
2.14%
2.65%
2.38%
2.19%
2.57%
2.23%
2.12%
2.33%

Return Rate (Total Assets)
5.78%
4.96%
6.59%
5.58%
5.13%
6.02%
5.46%
4.93%
5.99%
Return Rate (Stock Eq.)
21.01%
19.99%
22.02%
21.62%
20.26%
22.97%
22.20%
20.02%
24.38%
EPS
3.55
3.04
4.05
4.39
3.52
5.26
5.40
3.89
6.91
a.Industry
The automobile industry profitability ratios are as reflected
above. Return on Equity seems to have been enhanced across
the automobile industry averaging about 20%, with return on
assets following but the return on sales is so dismal and needs

to be enhanced. The EPS is on an increasing trend showing good
returns to shareholders.
b. AutoNation
AutoNation appear to be less profitable according to all of the
ratios. Its rate of return of net sales (2.12% in 2014; 2.19% in
2015 and 2.12% in 2016) and total sales are indicators of the
business which has not enhanced its return on sales in contrast
to the automobile industry figures. The rate return on total
assets also stood at 4.93% in 2015 compared to 5.46%
automobile industry norms. The return on equity however stands
less at par with the industry average and its peer Lithia Motors
reported at 20.02% in 2015 to industry’s 22.02%.Nevertheless,
the company has shown good performance by of its progressive
EPS increasing from 3.04 in 2013 to 3.89 in 2016.
c.Lithia Motors
Lithia Motors appears to be more profitable than AutoNation
with its all its profitability ratios above the industry level. The
company’s return on sales closed at 2.33% in 2016 compared to
automobile industry average of 2.23% .The return of equity is
also impressive shooting from 22.02% in 2013 to 24.38% in
2016.The same trend of above the industry average is exhibited
by its EPS and return on total assets.
VIII. Horizontal and Vertical Analysis
Overview
The horizontal and the vertical evaluation provides a good
insight on business performance. Horizontal analysis is used to
compare historical financial information over a period of time.
The purpose for doing so is to observe whether there was a
significant increase or decrease in that time of financial

performance. It is crucial to conduct horizontal analysis of all
of the financial statements at the same time so that AutoNation
and Lithia motors can see the complete impact its operational
results over the 3-year period (Pellinen, Teittinen, & Järvenpää,
2016).
The vertical analysis similarly highlights the relationship
between accounts on the same financial statement by expressing
all amounts as a percentage of one account that is chosen on the
statement. Generally, the account selected is the revenue, or
sales, on the income statement. Vertical analysis can be created
to compare two businesses, of same or different sizes, to show
how much percent each business use on a given account. We
will employ vertical analysis to identify the proportions
between 2013 and 2015 as highlighted.
Complementary Application
Complementary application refers to the use of horizontal and
vertical analysis to interpret the inconsistencies in the ratio
analysis. Inevitably, there will be some inconsistencies when
multiple ratios are used to calculate a business's profitability or
liquidity. Thus, other analytical approaches must accompany the
financial ratios. This holistic approach will give a business a
more complete gauge of its financial status.
HORIZONTAL ANALYSIS
The horizontal and vertical analysis has reflected many trends,
differences, and similarities between AutoNation and Lithia
Motors. At the inception, the horizontal analysis of balance
sheet will be evaluated. Further, the two companies also
experienced significant growth in their assets. AutoNation’s
assets increased by 13.79% whereas Lithia Motors ones also

grew by 16.30%.Thegrowth was also experienced in
stockholders' equity. There only limited variations between the
two in Automobile Industry. AutoNation’s cash and cash
equivalents is on the decline whereas Lithia Motors cash is
growing at a higher rate. In 2016 for instance, Lithia Cash and
equivalents rose by 50.54% whereas AutoNation’s cash declined
by 1.72%.AutoNation also has a long term which is being
reduced whereas Lithia Motors has no long term debt
obligations (Rugraff, 2012).
On the statement of income, both firms recorded increase in
annual total revenue. However, Lithia Motors revenue is
growing at a very high rate and percentage compared to
AutoNation. In 2016, Lithia Motors recorded a 45.9% increase
compared to AutoNation’s 9.17% increase. The same trend is
exhibited in net earnings whereby Lithia Motors expanded its
earnings by 31.92 %in 2016 compared to AutoNation’s only
5.71%.
HORIZONTAL ANALYSIS
Balance Sheet items (%)
AutoNation
Lithia Motors
CURRENT ASSETS:
2015-2016
2015-2014
2015-2016
2015-2014
Cash and cash equivalents
-1.72%
8.96%
50.54%
26.21%
Receivables, net

11.05%
10.38%
21.87%
50.71%
Inventory
24.59%
2.54%
12.54%
16.21%
Other current assets
-43.43%
7.42%
4.43%
73.22%
Total Current Assets
17.81%
4.42%
3.91%
42.10%
PROPERTY AND EQUIPMENT, NET
10.13%
8.35%
56.52%
76.51%
GOODWILL, NET
6.07%
4.37%
17.71%
45.48%
OTHER INTANGIBLE ASSETS, NET
24.02%
5.85%
OTHER ASSETS
11.65%

21.65%
-12.47%
23.48%
Total Assets
13.79%
6.14%
16.30%
49.37%
CURRENT LIABILITIES:
Vehicle floorplan payable
20.34%
2.25%
17.14%
10.12%
Accounts payable
13.30%
0.65%
6.94%
302.71%
Commercial paper
Current maturities of long-term debt
-46.40%
-16.94%
Other current liabilities
6.89%
15.22%

3.75%
133.40%
Total Current Liabilities
33.16%
3.47%
12.02%
67.00%
LONG-TERM DEBT, NET OF CURRENT MATURITIES
-16.63%
16.22%
0.03%
38.49%
DEFERRED INCOME TAXES
-43.00%
18.37%
9.25%
64.07%
OTHER LIABILITIES
1.62%
17.21%
11.48%
65.11%
SHAREHOLDERS' EQUITY:
Preferred stock, par value $0.01 per share; 5,000,000 shares
authorized; none issued
Common stock, par value $0.01 per share

-25.00%
0.00%
10.28%
65.34%
Additional paid-in capital
-91.59%
44.39%
-0.43%
148.12%
Retained earnings
-28.05%
12.54%
-
-
Treasury stock, at cost; 9,758,091 and 50,248,909 shares held,
respectively
-79.41%
32.36%
7.67%
88.29%
Total Shareholders' Equity
13.38%
0.50%
24.14%
9.76%
Total Liabilities and Shareholders' Equity
13.79%
6.14%
12.02%
67.00%

HORIZONTAL ANALYSIS
Income Statement Items (%)
AutoNation
Lithia Motors
2014-2015
2013-2014
2014-2015
2013-2014
TOTAL REVENUE
9.17%
9.08%
45.90%
34.56%
Cost of Sales:
TOTAL COST OF SALES
9.18%
9.23%
46.46%
35.33%
Gross Profit:

TOTAL GROSS PROFIT
Selling, general, and administrative expenses
8.84%
7.47%
42.79%
30.49%
Depreciation and amortization
19.18%
12.17%
57.81%
31.54%
Franchise rights impairment
Other income, net
-3.76%
73.83%
-
-
OPERATING INCOME
6.37%
10.87%

26.45%
19.81%
Non-operating income (expense) items:
Floorplan interest expense
9.38%
-0.19%
46.59%
34.96%
Other interest expense
4.84%
-1.81%
30.55%
26.36%
Loss on debt extinguishment
Interest income
-50.00%
0.00%
24.80%
26.97%
Other income (loss), net
-144.83%
-48.21%

-131.56%
7.02%
INCOME FROM CONTINUING OPERATIONS BEFORE
INCOME TAXES
Income tax provision
6.29%
14.83%
8.72%
13.98%
NET INCOME FROM CONTINUING OPERATIONS
5.69%
11.71%
35.02%
28.83%
Loss from discontinued operations, net of income taxes
NET INCOME
5.71%
11.68%
31.92%
30.87%

VERTICAL ANALYSIS
As we mentioned earlier, vertical analysis computes the
proportions of balance sheet and income statement items by
comparing them with the total assets and total revenue
respectively. It therefore also indicates the similarities as well
as the differences between the AutoNation and Lithia Motors.
The key similarity is that both companies did not experience
significant changes in their accounts in the income statements
during the three years. For instance the proportion of coast of
sales remained stable around 84% for in the entire 3 year-
period. The same trend being seen at Lithia Motors whose cost
of sales stabilized around the same percentage. The most visible
difference between the two businesses is in the net income. For
instance, AutoNation net income was slightly low and stable
standing at around 2.12% in 2013; 2.19% in 2015 and 2.14% in
2016. This is in comparison to Lithia Motors whose net income
is increasing from 2.33% in 2015 to 2.65% in 2016.
To the balance sheet items, much variations is seen. If we begin
with inventory we realize Lithia Motors spent about 45.58% of
money on inventory compared to AutoNation’s 37.79% in
2016.Since inventory is a key current asset, its differential
composition has led to a big variation in current assets between
the two firms. Some instances of variation is also seen in the
stockholders equity where AutoNation reported its composition
at 24.58% compared to Lithia Motors 25.66%.
VERTICAL ANALYSIS

AutoNation
Lithia Motors
Balance Sheet Items (in %)
2014
2015
2016
2014
2015
2016
Cash & Short-Term Investments
0.87
0.9
0.78
1.37
1.04
1.39
Accounts Receivable
9.36
9.74
9.5
9.88
10.25
9.56
Inventory
35.72
34.51
37.79
49.79
43.38

45.58
Other Current Assets
2.43
2.46
1.23
1.64
1.41
1.69
Total Current Assets
48.39
47.61
49.29
62.69
56.08
58.22
Net PP&E
28.24
28.83
27.91
27.89
28.35
27.16
Intangibles
20.15
19.87
19.19
7
12.16
11.49
Other Long-Term Assets
3.21
3.68
3.61
2.41
3.42
3.13

Total Assets
100
100
100
100
100
100
Accounts Payable
30.24
28.04
29.98
2.97
2.46
2.2
Short-Term Debt
0.38
0.3
6.41
41.79
42.02
41.92
Taxes Payable
—
—
—
—
—
—
Accrued Liabilities
—
—
—
5.46
5.33
5.18
Other Short-Term Liabilities

16.79
17.88
17.69
0.36
0.26
—
Total Current Liabilities
47.41
46.22
54.08
50.58
50.07
49.29
Long-Term Debt
22.87
25.04
18.35
14.23
21.14
18.79
Other Long-Term Liabilities
3.67
4.07
2.99
4.2
5.42
6.25
Total Liabilities
73.95
75.33
75.42
69
76.64
74.34
Total Stockholders' Equity
26.05

24.67
24.58
31
23.36
25.66
Total Liabilities & Equity
100
100
100
100
100
100
VERTICAL ANALYSIS
Income Statement Items (%)
AutoNation
Lithia Motors
Fiscal Year
2014
2015
2016
2014
2015
2016
Total Revenue
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
Cost of Sales:

TOTAL COST OF SALES
84.37%
84.36%
84.24%
85.05%
84.73%
84.25%
Gross Profit:
TOTAL GROSS PROFIT
15.63%
15.64%
15.76%
14.95%
15.27%
15.75%
Selling, general, and administrative expenses
10.85%
10.88%

11.05%
10.31%
10.48%
10.61%
Depreciation and amortization
0.61%
0.56%
0.54%
0.53%
0.49%
0.50%
Franchise rights impairment
0.07%
0.00%
0.00%
Other income, net
-0.09%
-0.10%
-0.06%
0.26%
0.00%
0.06%
OPERATING INCOME

4.19%
4.30%
4.23%
3.85%
4.30%
4.58%
Floorplan interest expense
-0.28%
-0.28%
-0.30%
-
-
-
Other interest expense
-0.44%
-0.45%
-0.50%
-
-
-
Loss on debt extinguishment
0.00%
-0.01%
0.00%
0.00%
0.00%
0.00%
Interest income
0.00%
0.00%
0.00%
-0.01%
0.06%
0.07%
Other income (loss), net
-0.01%

0.02%
0.03%
3.34%
3.91%
4.14%
Income from Continuing Operations before Income Taxes
3.46%
3.57%
3.45%
2.33%
2.51%
2.63%
Income tax provision
1.34%
1.37%
1.30%
0.00%
0.00%
0.00%
Net Income from Continuing Operations
2.13%
2.20%
2.15%
2.33%
2.51%
2.63%
Loss from discontinued operations, net of income taxes

-0.01%
-0.01%
-0.01%
0.00%
0.06%
0.02%
NET INCOME
2.12%
2.19%
2.14%
2.33%
2.57%
2.65%
IX. Comparative Analysis
a. Creditworthiness Evaluation
i. Short term
To evaluate short-term creditworthiness of AutoNation and
Lithia Motors then the short-term ratios must be employed
specifically the current and quick ratio. The Automobile
industry norm for the current ratio and quick ratio was
averagely at 1.05 and 0.21 respectively. If we begin with
AutoNation, in 2014, its current ratio reflected at1.02 in 2014;
1.03 in 2015 and closing at 0.91 in 2016 whereas the quick ratio
stood at 0.22 in 2014,0.23 in 2015 and 0.19 in 2016. In this
evaluation, AutoNation only met the industry standards in quick
ratio but it fell much below on the current ratio. Thus, I would
rule suggest that AutoNation is not creditworthy in the short
run.
However, Lithia Motors has had consistent current ratio and
quick ratio above the industry level in all the three years. The
current ratios were 1.24, 1.12 and 1.18 in 2014, 2015, and 2016
respectively whereas the quick ratio stood at 0.22 in 2013, 0.23
in 2015 and 0.22 in 2016 all these above industry norm. Thus I

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