Financial Reporting Problem Apple Inc.CT7.1 The financial statem

Financial Reporting Problem: Apple Inc.CT7.1 The financial
statements of Apple Inc. are presented in Appendix A. The
complete annual report, including the notes to its financial
statements, is available at the company’s website.
Instructions
Using the financial statements and reports, answer these
questions about Apple’s internal controls and cash.
a. What comments, if any, are made about cash in the “Report
of Independent Registered Public Accounting Firm”?
b. What data about cash and cash equivalents are shown in the
consolidated balance sheet (statement of financial position)?
c. What activities are identified in the consolidated statement of
cash flows as being responsible for the changes in cash during
2017?
d. How are cash equivalents defined in the Notes to
Consolidated Financial Statements?
e. Read the section of the report titled “Management’s Report
on Internal Control Over Financial Reporting.” Summarize the
statements made in that section of the report.
Journal of Vocational Rehabilitation 46 (2017) 149–158
DOI:10.3233/JVR-160851
IOS Press
149
Impairment, demographics and competitive
employment in vocational rehabilitation
John O’Neilla,∗ , Walter Kaczetowb, Joseph Pfallerc and Jay
Verkuilenb
a Kessler Foundation, East Hanover, NJ, USA

bProgram in Educational Psychology, City University of New
York Graduate Center, New York, NY, USA
cProgram in Rehabilitation Psychology, University of
Wisconsin-Madison, Madison, WI, USA
Revised/Accepted August 2016
Abstract.
BACKGROUND: There is a persistent gap in the employment
rate of working-age people with disabilities and those without
disabilities, with outcomes differing across impairment groups
and by demographics.
OBJECTIVE: Our goal is to identify differences in competitive
employment outcomes across 17 impairment groups included
in the RSA-911, including interaction effects with other
individual characteristics, among them age, gender,
race/ethnicity,
and educational attainment.
METHODS: We used logistic regression to examine differences
in competitive versus other employment closures among
vocational rehabilitation customers who were employed at
closure. The relationship between demographic variables and
type
of employment was allowed to vary by impairment.
RESULTS: Contrary to research that does not differentiate type
of employment, we find the odds of competitive employment
are lowest for VR clients who are blind or visually impaired.
They are also lower for those with mobility, orthopedic, or
mental impairments; women; older clients; and those with lower
levels of educational attainment. Interaction effects revealed
that the differences across demographic groups vary by type of
impairment.
CONCLUSION: Researchers and counselors should consider
type of employment at closure, and differences by impairment
and among demographic groups should be taken into
consideration when designing employment service programs.

Keywords: Vocational rehabilitation (VR), demographics, RSA-
911, competitive employment
1. Introduction
The benefits of employment for physical and psy-
chological health is well-documented for people with
and without disabilities (Bishop, Chapin, & Miller,
2008; Dutta, Gervey, Chan, Chou, & Ditchman,
2008). Individuals with disabilities who are employed
have lower rates of alcohol use, depression, and anxi-
ety and are found to have higher levels of self-esteem
∗ Address for correspondence: John O’Neill, Ph.D. Director,
Employment and Disability Research, Kessler Foundation,
120 Eagle Rock Ave., East Hanover, NJ 07936-3147, USA.
Tel.: +1 973 324 8387; Fax: +1 973 324 8373; E-mail:
[email protected]
and quality of life (Dutta et al., 2008). However,
individuals with disabilities have significantly lower
rates of employment compared to the general popu-
lation, with an estimated 32 percent of working-age
adults with disabilities employed compared to 73
percent of people without disabilities from 2010 to
2012 (U.S. Department of Labor, 2013). Recognizing
the importance of employment to the individual, the
state-federal vocational rehabilitation (VR) program
plays a critical role in reducing vocational disparities,
but only 60 percent of VR consumers success-
fully obtain employment. Despite poor employment
outcomes for people with disabilities overall, evi-
dence suggests that subgroups—defined by type of
1052-2263/17/$35.00 © 2017 – IOS Press and the authors. All
rights reserved

mailto:[email protected]
150 J. O’Neill et al. / Impairment, demographics and
employment in VR
impairment, educational attainment, or demographic
characteristics—have more robust employment
outcomes (Chan et al., 2016).
Furthermore, evidence suggests that competitive
employment provides the greatest benefit on a broad
range of rehabilitation outcomes for people with dis-
abilities. As a result, we undertook the current study
to utilize competitive employment as the outcome
measure since it represents the ideal VR case clo-
sure. Findings can then be more directly applied to
the state-federal VR programs in enacting the mission
of integrated employment outlined by the Workforce
Innovation and Opportunity Act (WIOA) of 2014 and
Rehabilitation Services Administration (RSA).
In this study we specifically examine differ-
ences in type of employment defined as competitive
versus not. While most studies of VR compare
closures with or without employment, recent pol-
icy changes have emphasized the importance of
employment in integrated settings. First, in 2001
RSA updated the definition of employment out-
come for the state-federal VR program to mean
work in an integrated setting (Rehabilitation Services
Administration, 2001). More recently, in 2014 WIOA
amended Title IV of the Rehabilitation Act of 1973
to emphasize competitive integrated employment at
competitive wages as a major initiative (U.S. Depart-

ment of Education, 2014).
The purpose of this study is to examine employ-
ment outcomes for 17 impairment types included
in the RSA-911. We hypothesize that differences
evident among types of impairment will vary
across personal and demographic characteristics
including age, gender, educational attainment, and
race/ethnicity. A better understanding of how impair-
ment type interacts with personal and demographic
factors can enable a greater understanding of facilita-
tors and barriers to vocational success. Moreover, this
improved understanding can be used to help direct
state-federal VR policy and intervention strategies to
improve vocational outcomes.
We find significant differences between type of
employment and impairment type, gender, age, and
education. In contrast to existing research examining
employment alone, we find competitive employment
is lowest among those who are blind or visually
impaired. Competitive employment is also lower for
those with mobility, orthopedic, or mental impair-
ments; women; older clients; and those with lower
levels of educational attainment. Notably, interaction
effects revealed that the differences across demo-
graphic groups vary by type of impairment.
2. Literature review
2.1. Impairment type
Impairment type has been found to be an important
predictor of employment outcomes in the state-
federal VR program. While the RSA-911 contains
19 impairments, research on employment outcomes

often categorize disability type into three broad cat-
egories including: (1) sensory or communicative
disabilities (e.g., visual or hearing impairments);
(2) mental impairments (e.g., serious mental ill-
ness); and (3) physical disabilities (e.g., spinal cord
injury). These studies have found that individuals
with sensory or communicative disabilities typi-
cally have better employment outcomes, followed
by individuals with physical disabilities, and then
by individuals with mental impairments (Rosenthal,
Chan, Wong, Kundu, & Dutta, 2006). Other studies
have focused exclusively on a specific impairment
population, leaving little research examining differ-
ences across the many specific impairments within
the RSA-911. Our intention with the current study is
to systematically study employment outcomes across
17 impairments included in the RSA-911. We are
not able to include two of the 19 impairments due
to limited sample size.
2.2. Gender
The role of gender in employment outcomes of
those with disabilities is mixed in the literature
and not fully understood. It is clear that women
are typically employed at a lower rate when com-
pared to men. However, many studies have failed
to demonstrate a difference in successful case clo-
sure in the state-federal VR program by gender.
While other studies have found that despite having
no impact on the rate of employment, men have sig-
nificantly higher earnings than women (Ireys, Gimm,
& Liu, 2009).
Among people with disabilities, one recent study
found, while men with disabilities are employed

at higher rates than women, the employment gap
between individuals with disabilities and those with-
out disabilities is smaller for women (35 percentage
points) than for men (37 percentage points) (Sevak,
Houtenville, Brucker, & O’Neill, 2015). Those
authors suggest that while there is no theoreti-
cal explanation for this difference, it is possible
that men with disabilities face greater obstacles to
employment. Further research is needed to under-
J. O’Neill et al. / Impairment, demographics and employment in
VR 151
stand the interaction of gender, disability type, and
other personal and demographic factors.
2.3. Race/ethnicity
The rehabilitation literature has found considerable
differences between blacks and whites in VR eligi-
bility, service provision, and employment outcomes.
However, interpretation of these finding is complex,
as the relationship between race and employment out-
comes varies. In a seminal analysis examining race
and VR outcomes, researchers found African Ameri-
cans had lower rates of receipt of VR services, training,
job placement, and wages (Atkins et al., 1980). Con-
temporary analyses continue to find evidence of such
disparities, showing that whites are more likely to
be deemed eligible for VR services (Wilson, 2002;
Wilson, Alston, Harley, & Mitchell, 2002), that
African Americans receive less vocational training
or college and university training (Boutin & Wilson,
2012), and that African Americans are less likely to

be placed in competitive employment (Capella, 2002;
Feist-Price, 1995; Rosenthal et al., 2006; Rosenthal,
Ferrin, & Wilson, 2005; Wilson, 1999).
Despite being the fastest growing segment of the
U.S. population, Latinos have not been the focus of
many studies of VR. One study found that Hispanic
clients were deemed eligible to receive services at
a higher rate than non-Hispanics (including whites,
African Americans, Asians, and Native Americans)
(Wilson & Senices, 2005). Capella (2002) reported
that Hispanics were 1.77 times more likely to be
closed with competitive employment compared to
whites. One recent study found that Latinos had a
smaller disability employment gap than non-Latinos
(Sevak et al., 2015). That study also identified a
smaller gap among Asians.
Some studies have also noted racial differences by
specific health conditions. In an analysis of RSA-911
data, African Americans with a sensory or commu-
nicative disability were 20 percent less likely to obtain
employment through VR, while Native Americans
with a physical or mental impairment were 51 per-
cent and 50 percent less likely, respectively (Dutta
et al., 2008).
2.4. Education
While individuals with disabilities have lower rates
of educational attainment compared to the general
population (Gilmore & Bose, 2005), employment out-
comes are better among people with disabilities who
have higher levels of education than among those with
less education, and the employment gap progressively

declines with higher levels of educational attainment
(Sevak et al., 2015). One study found that individu-
als with disabilities in their twenties and thirties had a
23 percent greater chance of obtaining employment if
they completed high school (Loprest & Maag, 2007),
while another estimated that people with disabilities
have a 50 percent greater chance of employment when
completing college (Gilmore & Bose, 2005). Higher
educational attainment is also associated with higher
earnings for people with disabilities (Beveridge &
Fabian, 2007). Evidence also suggests that the support
from VR program for higher education can improve
employment outcomes and job quality and is one of
the strongest predictors of earnings (Boutin & Wilson,
2009; Manyibe, 2008; Migliore, Timmons, Butter-
worth, & Lugas, 2012). The positive benefit of college
and university training has been demonstrated across
a variety of disability populations, including individu-
als with psychiatric disabilities (Boutin & Accordino,
2011) and those with chronic arthritis (Mamboleo et
al., 2015). These findings suggest that the deployment
of education and training through VR might well work
as an intervention to improve employment outcomes
for people with disabilities.
2.5. Age
An aging population, combined with extensions in
the retirement age for receipt of full Social Security
benefits, will likely increase the need for VR services
for older adults. However, the relationship of age and
VR employment outcomes is unclear.
Several studies have found that, among individ-
uals with chronic health conditions, older age was
associated with lower employment ratings (Ipsen,

2006). One recent study found that the disability
employment gap was the largest during middle age
(Sevak et al., 2015), typically the highest earning
years in an individual’s career. Authors also noted
that decline for the workforce started at age 30
for people with disabilities, compared to age 50
for the general population (Sevak et al., 2015). In
contrast, one study focused on VR clients with a
sensory or communicative disability found that those
over the age of 65 were three times more likely to
successfully obtain competitive employment com-
pared to individuals between 16 and 34. However,
the older VR clients were also more likely to be
employed at application to VR and were seeking
services to maintain employment (Dutta et al., 2008).
employment in VR
An important caveat is that many in the general
population are exiting the workforce at this age, and
that the employment gap gets smaller as a result.
3. Methods
3.1. Data
We used case service data from the Rehabilita-
tion Services Administration Case Service Report
(RSA-911) from 2010 to 2013 for the analysis.
The RSA-911 details all cases closed by the state-
federal VR system in a fiscal year. The dataset
includes information about each case, including
demographic information, primary and secondary

disability, employment outcomes, and VR service
utilization. The RSA-911 provides an opportunity to
assess the efficacy of employment services provided
by the state-federal VR program and the context from
which each individual utilizes VR services, facili-
tating a greater understanding of factors that might
enhance successful employment outcomes.
Within states, vocational rehabilitation (VR) agen-
cies are administratively organized in two ways: one
general agency serving all individuals with disabili -
ties or two separate agencies, one for the blind and
one for everyone else. For this analysis, we used data
from all three kinds of agencies but nested individual
observations by state and impairment.
In addition to the data provided in the RSA-911, we
included a variety of state-level variables that could
be related to employment outcomes. These include
the yearly state unemployment rate (from the Bureau
of Labor Statistics); whether the agency was in order
of selection, which means some individuals were
placed on a wait list (from RSA-113 reports); and
the amount of federal funds allocated to the states for
VR per person with disability. The funds provided
per capita variable was calculated by dividing federal
funds provided by RSA (from RSA-113 reports) to
each state by the number of people with disabilities
in the state (from the American Community Survey).
We used single regression imputation (McKnight,
2007) to impute values when federal funds data were
incomplete.
3.2. Sample
Because our study is focused on the qual-

ity of employment outcomes, defined as having
competitive employment or not, the sample was
limited to individuals who were employed at closure.
The sample was further limited to individuals who
lived in the United States, were between the ages
of 18 to 65, were not employed at application, had
no previous closures, and had complete data on all
of the variables used in the models. Due to small
within group sample sizes, the 266 individuals who
were deaf and blind and the 1,018 individuals who
had other hearing impairments were dropped from
the study. The final sample size was 354,414.
The sample (see Table 1 Descriptive Statistics) was
63 percent white, 24 percent African American, and
10 percent Hispanic (any race). Only 1 percent of
the sample was Asian, and 2 percent of the sam-
ple was of other races or multiracial. The scarcity
of individuals in those two smaller race/ethnicity
groups made it very difficult to obtain good infer-
ences about them in the statistical model used later
Table 1
Descriptive statistics
N 354,414
Mean
Age 35.04
Gender Percent
Male 58.87
Female 41.13
Impairment

Blindness 2.53
Other visual 2.33
Deafness visual 1.47
Deafness auditory 0.49
Hearing loss visual 0.49
Hearing loss auditory 2.28
Communicative 0.83
Mobility orthopedic 4.79
Manipulation 2.01
Mobility manipulation 2.82
Other orthopedic 3.99
Respiratory 0.69
General physical 3.39
Other physical 6.56
Cognitive 28.6
Psychosocial 27.53
Other mental 9.2
Education
Less than high school 31.9
High school graduate 37.37
Some college 23.4
College graduate 7.33
Race
White 62.89
Black 23.64
Hispanic 9.75
Asian 1.27
Other 2.46
Employment
Competitively employed 95.97
Not competitively employed 4.03
Source: RSA-911 case service data from 2010 to 2013.

VR 153
in this paper. The average age of the clients was
35 years old. The most frequently observed edu-
cational outcome was a high school diploma (37
percent) followed closely by not finishing high school
(32 percent). Only 7 percent of the sample fin-
ished college. The remaining 23% had some college
or post high school educational experience. The
most frequent impairment category was cognitive
(29 percent).
3.3. Models
We estimated a sequence of five nested logistic
regression models using STATA v 14 (StataCorp,
2014). In these models the outcome variable was
lack of competitive employment. Since 96 percent of
the people in the study obtained competitive employ-
ment, only 4 percent of the sample did not.
In order to have a baseline for the subsequent
models, the null model, which only includes the inter-
cept, was fit. The first nontrivial model only fit the
state variable as a predictor. The second model added
yearly state characteristics such as unemployment
rate, order of selection, and the federal funding per
capita. The third model added the primary impair-
ment variable. The fourth model added educational
and demographic variables. The fifth model added
interactions between an individual’s primary impair-
ment and his or her educational and demographic

characteristics. Based on fit statistics, the fifth model
was chosen to be included in this article.
While our study focuses on differences by indi-
vidual characteristics and we were not primarily
interested in state variables, we did control for the
state variables described above (the unemployment
rate, the mean order of selection from 2010 to 2013,
and the federal grant per person with disability) to
isolate differences by impairment and demographics.
We also controlled for individual receipt of bene-
fits from Social Security disability benefit programs
(SSDI, SSI) because it has been shown to be closely
related to VR employment outcomes (Nord & Nye-
Lengerman, 2015; Schaller, Yang, Ji, & Zuna, 2013).
Due to space constraints, we do not present estimates
for the state variables.
4. Results
The final model contained 81 variables and 158
interacted variables. Given the large sample of
354,414, the traditional p-value of 0.05 could lead to
many false positives. In order to mitigate the poten-
tial for type 1 error, a p-value of 0.01 was used as
a threshold to determine statistical significance. The
large number of variables prohibits the reporting of
each estimate, so we largely limit our presentation of
results to those that are statistically significant. While
we discuss the main effects of variables in the text, we
note that their interpretation is limited and do not dis-
play them in tables. We do display tables and figures
of the estimated interaction effects between impair-
ment, educational attainment, and race/ethnicity.

We discuss the estimates as relative risks for ease
of interpretation. In models where one of the two out-
comes is very small, the odds ratios can be interpreted,
approximately, as the relative risk of lack of competi-
tive employment of the group relative to the reference
group (Agresti, 2013). The reference group used for
the analysis was white men from Alabama who had
hearing loss and communicated with speech and did
not graduate from high school.
4.1. Main effects
Because the model contains a series of interactions,
it is difficult to interpret the coefficients on the indi -
vidual variables, which are often called main effects.
They represent the level difference between the refer-
ence category and a group, whereas the coefficients
on the interacted variables represent the additional
differences between the reference category and a
group. To estimate the full difference in risk between
groups requires multiplying the odds ratios for each
group and its related interactions. We do this and
discuss those estimates in the next section.
Based on a comparison of the noninteracted vari-
ables for type of impairment, we find that blindness
is associated with the highest relative risk for lack
of competitive employment (θ = 7.73, p < 0.001), rel-
ative to the reference impairment group. Visual
impairment is associated with the next highest rela-
tive risk of lack of competitive employment (θ = 4.61,
p < 0.001). Mobility orthopedic impairment is asso-
ciated with the third highest relative risk of lack of
competitive employment (θ = 2.97, p < 0.001), fol-
lowed by other orthopedic impairments (θ = 2.68,
p < 0.01). Cognitive impairments and other mental

impairments were also at a higher risk for lack of com-
petitive employment (θ = 2.45, p < 0.001 and θ = 2.59,
p < 0.002). Lastly, other physical impairments and
psychosocial impairments were at higher risk for
lack of competitive employment (θ = 2.27, p < 0.012;
θ = 2.02, p < 0.015).
employment in VR
The odds ratios for noninteracted demographic
variables also revealed significant differences. In gen-
der, females had a greater risk for lack of competitive
employment compared to males (θ = 2.32, p < 0.001).
Greater age was also associated with a higher risk of
lack of competitive employment (θ = 1.05, p < 0.001).
Hispanic ethnicity was associated with half the rela-
tive risk (θ = 0.44, p < 0.001) of non-Hispanic, white
race/ethnicity.
Higher educational achievement was associated
with lower relative risk of lack of competitive
employment. High school completion was associ-
ated with half the relative risk (θ = 0.53, p < 0.001)
of competitive employment relative to those who had
not completed high school. Having an associate’s
degree or some college education is associated with
four times the likelihood of competitive employment
(θ = 0.27, p < 0.001), and having a college degree is
associated with six times the likelihood of competi-
tive employment (θ = 0.17, p < 0.001).
4.2. Interaction effects

As described above, the model included interac-
tions of impairment with gender, age, race/ethnicity,
and education. We first describe findings on inter-
actions between education level and impairment. In
general these interactions revealed that the lower
relative risk associated with higher educational attain-
ment was not as dramatic for most impairment
groups relative to the reference group of hearing
loss with auditory communication. For example,
we estimate odds ratios greater than one for edu-
cational attainment indicators interacted with other
visual (θHS = 1.78, p < 0.003; θSC = 2.66, p < 0.001;
θC = 2.82, p < 0.001) and mobility and manipula-
tion impairments (θHS = 1.99, p < 0.002; θSC = 3.59,
p < 0.001; θC = 6.09, p < 0.001). Additionally, hav-
ing some postsecondary education but not having
completed a bachelor’s degree is associated with
increased relative risk of lack of competitive
employment for people with the following impair-
ments: blindness (θ = 1.78, p < 0.003), deafness
with visual communication (θ = 1.980, p < 0.008),
mobility and orthopedic (θ = 1.97, p < 0.002), respi -
ratory (θ = 3.69, p < 0.003), psychosocial (θ = 2.98,
p < 0.001), and other mental problems (θ = 2.69,
p < 0.001). Lastly, compared to those with a bache-
lor’s degree in the reference group of hearing loss with
auditory communication, risks of non-competitive
outcomes were higher for those with a bache-
lor’s degree deafness with visual communication
Table 2
Estimated relative risk of noncompetitive employment outcome,
by education and impairment
Impairment High School Some College College

Blind 0.6943 0.4844∗ 0.2183
Other visual 0.8997∗ 0.7285∗ 0.4645∗
Deafness visual 0.5386 0.5416∗ 0.5137∗
Deafness auditory 0.6151 0.2425 0.0914
Hearing loss visual 0.6641 0.4508 0.6557∗
Communicative 0.9902 0.7735 0.8330∗
Mobility orthopedic 0.8073 0.5400∗ 0.5239∗
Manipulation 0.6126 0.5404 0.3067
Mobility manipulation 1.0527∗ 0.9818∗ 1.0041∗
Other orthopedic 0.6687 0.4379 0.4479∗
Respiratory 1.9580∗ 1.0574∗ 0.6227
General physical 1.2641 0.6694∗ 0.2531∗
Other physical 0.8134 0.5878∗ 0.4754∗
Cognitive 0.7213 0.4438 0.2513
Psychosocial 0.6790 0.5740∗ 0.4171∗
Other mental 0.8316 0.7361∗ 0.5023∗
Source: Authors’ analysis of the RSA-911 case service data
from
2010 to 2013. Notes: The relative risk of closure without
compet-
itive employment by education is calculated by multiplying the
odds ratios for education group and for the interactions of
impair-
ment and education groups. The logistic regression also
controlled
for age, gender, race/ethnicity, state characteristics by year, and
interactions of these variables with impairment type. ∗ Denotes
statistically significant differences at the 0.01 level.
(θ = 3.11, p < 0.002), hearing loss with visual
communication (θ = 3.98, p < 0.01), communica-
tive (θ = 5.05, p < 0.006), mobility and orthopedic
(θ = 3.18, p < 0.001), other orthopedic (θ = 2.72,
p < 0.006), general physical (θ = 2.45, p < 0.011), psy-

chosocial (θ = 2.53, p < 0.001), and other mental
(θ = 3.05, p < 0.001) impairments.
To facilitate interpretation of the differences in rel -
ative risk by impairment and educational attainment,
in Table 2 we combine the relative risk estimated on
the noninteracted education variables and the educa-
tion variables. These risks can be interpreted relative
to the risk for the reference group hearing loss with
auditory communication with educational attainment
less than high school completion.
The difference in relative risk from one column
to the next can be interpreted as the change in rela-
tive risk by educational attainment. For people with
other visual impairments, an increase in education
from completing high school to having some col-
lege reduces the relative risk of lack of competitive
employment by 19 percent, and an increase in educa-
tion from having some college to completing college
reduces the relative risk by 37 percent. People whose
primary disability is in the mobility and orthopedic
category enjoy a relative risk decrease of 3 per-
cent if they graduate from college instead of having
VR 155
only some postsecondary education. Individuals with
mobility and manipulation impairments benefit from
a 7 percent relative risk reduction if they possess some
postsecondary education but did not earn a bachelor’s
degree. Oddly, persons with a bachelor’s degree in
this impairment category have a 1.7 percent increase

in relative risk compared to people who had only
some postsecondary education. People with a respi-
ratory impairment who possess some postsecondary
education less than a bachelor’s degree have 46 per-
cent reduction in relative risk compared to people who
only graduated high school. Persons with a bachelor’s
degree in the impairment categories general physical,
psychosocial, and other mental have a 37 percent, 27
percent, or 32 percent reduction in relative risk com-
pared to people who had some postsecondary but not
a bachelor’s degree.
Interactions between age and impairment were sta-
tistically significant for the following impairments:
deafness with visual communication (θ = 0.97,
p < 0.002), communicative (θ = 0.96, p < 0.01),
mobility and orthopedic (θ = 0.96, p < 0.001),
mobility and manipulation (θ = 0.97, p < 0.001),
other orthopedic (θ = 0.96, p < 0.001), general
physical (θ = 0.97, p < 0.00), other physical (θ = 0.96,
p < 0.001), cognitive (θ = 0.97, p < 0.001), psy-
chosocial (θ = 0.956, p < 0.001), and other mental
(θ = 0.950, p < 0.001). These estimates indicate that
the increase in relative risk of lack of competitive
employment with increased age is smaller for
these groups. At first glance, the interaction effects
may seem trivial since they are all just slightly
less than one. In reality they are not at all trivial.
Since age is a continuous predictor, the product
of its effect interacting with any variable grows
exponentially. The cumulative age effects graph
(see Fig 1) shows different impairment groups
experience different degrees of relative risk of
lack of competitive employment as they age. For
example, the relative risk of lack of competitive
employment hardly changes over time for those with

psychosocial and other mental impairments. Those
with deafness who communicate visually, however,
have almost a fourfold increase in the relative risk
of lack of competitive employment as they age. The
other five impairment groups fall somewhere in
between.
While the impairment interactions were most
notable by age and education, some additional
interactions were notable. Hispanics with cognitive
impairments were over three times as likely to not be
competitively employed as non-Hispanics if they had
Fig. 1. Estimated relative risk of noncompetitive employment
out-
come, by age and impairment. Source: Authors’ analysis of the
RSA-911 case service data from 2010 to 2013. Notes: The rel -
ative risk of closure without competitive employment by age is
calculated by combining the odds ratios for each age and for
the interaction of age with each impairment group. To simplify
the graph, similar impairment categories with similar growth
rate
were averaged. The logistic regression also controlled for age,
gen-
der, race/ethnicity, state characteristics by year, and
interactions of
these variables with impairment type.
hearing loss with primarily auditory communication
(θ = 3.270, p < 0.001). Women had a reduced relative
risk of lack of competitive employment compared to
men who had a hearing loss whose primary mode
of communication was auditory in five impairment
categories. These were general physical (θ = 0.66,
p < 0.01), other physical (θ = 0.64, p < 0.003), mobil -
ity orthopedic (θ = 0.65, p < 0.005), mobility and

manipulation (θ = 0.591, p < 0.001), and cognitive
(θθ = 0.50, p < 0.001).
While the estimated relative risks for any variable
or interaction may seem large, the predicted prob-
abilities of noncompetitive closure implied by the
model, when taking into account all estimates, were
quite similar. It is important to note two things about
predicted probabilities: (1) small absolute changes
in predicted probabilities can be very meaningful if
all of the predicted probabilities are small; and (2)
they are generated by averaging all the variables in
the model. In this sample, the overall probability of
lack of competitive employment was 4 percent, so
we expect to see the predicted probabilities being
close to 4 percent. All of the predicted probabilities
by any impairment or demographic were between
2 percent and 6 percent except those for blindness
and other visual impairments, which were 22 per-
cent and 18 percent respectively (not shown). This
is not surprising since the approximate relative risks
for those impairments were much higher than for the
other impairments.
employment in VR
5. Summary and discussion
We first summarize the results for main effects
and interactions and then discuss some of the impli-
cations for policy and practice. The relative risk of
competitive employment varied across impairment
groups. Women were more likely to not be com-

petively employed than men, though this relationship
was attenuated, but not totally eliminated, for a num-
ber of impairment groups. Hispanics were more likely
to be competively employed than whites, which is
consistent with the literature (Capella, 2002); how -
ever, the relationship was opposite for Hispanics with
cognitve impairments. Increasing levels of education
contributed as much as a sixfold decrease in the risk
of not being competivel y employed, which is con-
sistent with previous research (Boutin & Accordino,
2011; Loprest & Maag, 2007; Mamboleo et al., 2015;
Sevak et al., 2015). However, these positive effects
were somewhat attenuated when we looked at edu-
cation interacting with the impairments. Consistent
with prior research (e.g., Giesen & Cavenaugh, 2013;
Ipsen, 2006), we found that increasing age is a signifi -
cant predictor of poor employment outcomes, but this
effect is substantively smaller for some impairment
groups.
Of particular interest in the findings by impairment
group is that the blind and those with other visual
impairments have a greater risk of not being compet-
itively employed. This finding shows that not all VR
clients with sensory or communicative impairments
have similar employment outcomes and suggests that
combining these groups for analysis runs the risk of
losing important details (Rosenthal et al., 2006).
Women being at greater risk of not becoming
competitively employed may be a consequence of
powerful social role expectations despite changes in
favor of more equality in the professional and domes-
tic lives of men and women (Kvam, Eide, & Vik,
2013). Vocational rehabilitation professionals as well
as family and friends can also have an influence on

women with disabilities not becoming employed by
focusing on family participation instead of employ-
ment (Kvam et al., 2013). Researchers (Doren, Gau,
& Lindstrom, 2011) have recommended that school
and agency personnel who are providing employment
and career services to yong women with disabilities
ensure that these services are free of stereotypical per -
ceptions of womens’ roles related to work and family.
More specifically, they recommend that school and
agency staff engage gender-neutral career assess-
ments and career-related learning experiences and
that young women with disablilties be exposed to
female role models with diabilities who are employed
in high-skill, high-wage jobs to expand career aspi-
rations.
We found that higher levels of educational attain-
ment were associated with significantly reduced risk
of not being competitively employed. This was true
for 12 impairment groups, and the risk reduction
ranged from 3 percent to 46 percent. The good news
is that rates of postsecondary education access are
increasing for students with disabilities, though rates
of completion remain relatively low when compared
to students without disabilities (Madaus, Grigal, &
Hughes, 2014). While our evidence is correlational,
it is consistent with research that suggests relation-
ships between students and academic advisors and
social integration in nonacademic activities while in
postsecondary educational programs may be instru-
mental for students with disabilities persisting to
degree completion (Koch, Mamiseishvili, & Higgins,
2014). These findings point to the importance of
vocational rehabilitation staff working closely with
college disability service staff to focus on more than

accommodations. There is also longitudinal research
pointing to antecedent secondary educational factors
related to completion of postsecondary education;
these factors include students with disabilities self-
advocating, participating in extracurricular activities,
and having opportunities to develop vocational skills
through work-study or paid employment (Achola,
2014). Evidence such as this provides direction to
state vocational rehabilitation agencies as they take
on additional responsibilities under WIOA devoting
15 percent of their budgets to working with special
educational students to ensure a meaningful transi-
tion from high school to postsecondary education and
ultimately competitive employment.
We found a more nuanced story for aging than is
presented in previous studies (e.g., Giesen & Cave-
naugh, 2013; Ipsen, 2006) when we look at the
interaction of age with impairment. We saw great
variation in the degree to which aging is associated
with poorer employment outcomes across impair-
ment groups. This finding is consistent with the more
general observation that older workers are remain-
ing in the labor force for longer. It is estimated that
by 2050 22 percent of the U.S. population will be
over the age of 60 and this aging population will
increase the demand for VR services considering two
factors: (1) many older adults are wanting or needing
to work well beyond the traditional retirement age;
and (2) aging brings with it related chronic illness
VR 157

and disability conditions that can benefit from reha-
bilitation services to enhance productive capacity.
Moreover, employment for older adults is a protective
factor for health and wellness, improves psychosocial
well-being, and life satisfaction (Momtaz, Hamid,
Haron, & Bagat, 2016; Wahrendorf, 2015).
This trend toward older workers staying employed
presents opportunities for vocational rehabilitation
staff to support older workers as they approach
retirement age. For example, among older work-
ers who want to stay in their current jobs either
full time or part time for psychological or finan-
cial reasons, some without disability histories will
develop age-related impairments and need services
to stay employed. In addition, there are individuals
who have had disabilities for some time and who
acquire additional age-related impairments and need
services to keep their jobs. There may also be older
workers with disabilities approaching retirement that
want to leave their current employment situation and
shift to another field of work and look to vocational
rehabilitation practitioners to assist them with career
exploration and securing meaningful employment.
Regardless of the older consumer’s employment aspi-
rations, vocational rehabilitation counselors need to
appreciate that movement into retirement is fraught
with issues related to identity disruption, decision
anxiety, loss of self-assurance, disruption of social
supports, and existential anxiety (Osborne, 2012).
Hershenson (2014) even recommends that counselors
develop an individual retirement plan in addition to an
individual plan for employment for older vocational
rehabilitation consumers.
Acknowledgments

This project was funded by the National Institute
on Disability, Independent Living, and Rehabilitation
Research (U.S. Department of Health and Human
Services) Rehabilitation and Research Training Cen-
ter on Individual Characteristics, under cooperative
agreement 90RT5017-01-01. The findings and con-
clusions are those of the authors and do not represent
the policy of HHS or NIDILRR. The authors retain
sole responsibility for any errors or omissions.
Conflict of interest
The authors have no conflict of interest to report.
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Annual Report on Disability Statistics

1
State Level Statistics
Lewis Kraus
Center on Disability at the Public Health Institute
1
I am Lewis Kraus from the Center on Disability at the Public
Health Institute and the lead author of the Disability Statistics
Annual Report. I wanted to review the state level data from the
Annual Report with you today. As some of you are familiar
with the Annual Report, you know that the graphical display of
data by state lends itself to a more nuanced understanding of the
data.
People with Disabilities Living in the Community as a
Percentage of the US Population, by State, 2016
Kraus, L., Lauer, E., Coleman, R., and Houtenville, A. (2018).
2017 Disability Statistics Annual Report. Durham, NH:
University of New Hampshire.
http://disabilitycompendium.org/sites/default/files/user -
uploads/2017AnnualReportSlideDeck
Data Source: 2016 American Community Survey, American
FactFinder, Table B1810

2
First, the percentage of people with disabilities.
In 2016, the state with the lowest percentage of its population
having disabilities was Utah (9.9%).
The state with the highest percentage of people with
disabilities, West Virginia, was more than twice as high with a
percentage of 20.1%. For the most part, higher percentages of
people with disabilities were clustered in the southern US,
around the lower Mississippi river region, with concentrations
also high in the states of Maine, New Mexico, Oklahoma, and
Oregon.
2
People with Disabilities Ages Under 5 Years Living in the
Community, by State, 2016
Data Source: 2016 American Community Survey, FactFinder
Table B1810
3

Looking at the percentage of people with disabilities by age
group, we can see that among children under 5 years old, the
percentage of those with disabilities was very low, about 0.7%
nationally, and 2.8% or less in every state. The states with the
highest percentages were Nevada and Rhode Island. Forty states
had percentages equal to or less than 1.0%.
3
People with Disabilities Ages 5-17 Years Living in the
Table B1810
4
For children ages 5-17, the percentages of those with
disabilities ranged from 3.6% in Hawaii to more than twice that
percentage in Maine at 8.3%. In general, percentages for this
age group were lower in the states around the Rockies, the
upper Great Plains, the Pacific Coast and Hawaii, and more
concentrated in the eastern and southern US.
4
People with Disabilities Ages 18-64 Years Living in the

Table B1810
5
For adults ages 18-64, the highest percentages of people with
disabilities were in states in the southern US from Oklahoma to
West Virginia, and also Maine and Vermont. The percentage
was lowest in New Jersey and Hawaii (7.9%) and more than
twice as high in West Virginia (17.8%).
5
People with Disabilities Ages 65 and Over Living in the
Table B1810

6
As I am sure you are aware, the highest percentages of people
with disabilities were in the US population ages 65 and over;
more than one third of the civilian population for this age group
(35.2%) had disabilities. In nine states, primarily in the South,
the percentage of people ages 65 and over with disabilities was
40% or over, or more than two in every five elderly people:
West Virginia, Kentucky, Oklahoma, Mississippi, Alabama,
Arkansas, New Mexico, Alaska, and Louisiana.
The percentages of people with disabilities were generally
lowest in the Northeast, the central Atlantic states, and some
upper Midwest states; fourteen states had disability percentages
of less than one third (33.3%) of elderly: New Hampshire,
Delaware, Vermont, Maryland, Colorado, Minnesota, Rhode
Island, Connecticut, Wisconsin, Iowa, Massachusetts, New
Jersey, Virginia, and New York.
6
People with Disabilities Living in the Community, by Age
Group and State, 2016
7
Under 5

5-17
18-64
65 and over
Kraus, L., Lauer, E., Coleman, R., and Houtenville, A.
(2018).2017 Disability Statistics Annual Report. Durham, NH:
http://disabilitycompendium.org/sites/default/files/user-
Table B1810
Now if we look at them all together, you can see a pattern
emerging. As the population ages it moves from a disparate,
almost random smattering of high and low disability states for
those under 5 in the upper left map to a slow, but steady move
to the Southern states and Maine and Vermont in the working
ages, ending with a solid block of high disability percentage
states in the central southern US, along with Wyoming and
Alaska for those age 65 and over.
7
Percent Employed Among People with Disabilities, by State,
2016

8
Now let’s turn to a familiar topic – employment. This slide
depicts how rates of employment varied by state. For people
with disabilities, employment rates ranged from a high of 54.0%
(North Dakota) to a low of 27.4% (West Virginia). But you can
see a solid block of high disability employment states in the
upper Midwest and a generally low disability employment
segment in the southeast.
8
Percent Employed Among People without Disabilities, by State,
2016
9
This slide shows that for those without disabilities, the
employment ranged from 70.8% (West Virginia) to 84.2%
(North Dakota).

9
10
Percent of Persons With and Without Disabilities Employed, by
State, 2016
10
With Disabilities Without Disabilities
If you now look at them side by side, you can see that the
general rates of employment follow similar patterns for those
with and without disabilities for the upper Midwest where we
see high rates of employment and the Southeast where we see
low rates of employment. So we chose to present this as a gap
to show where there may be something particular happening for
people with disabilities…[next slide]
10
Gap of Percent Employed Among People with and without
Disabilities, by State, 2016

11
This slide shows the gap in percent employment between those
with and without disabilities by state in 2016. Now those upper
Midwest states’ high employment rates for both people with and
without disabilities change the map. What we are left with is
that states with the largest gap were concentrated generally
from Missouri eastward and California. While the states’
employment gaps narrowed from the previous year, in thirty
four (34) states, the employment percentage gap was 30
percentage points or greater. The highest gaps were in Rhode
Island (39.5 points), Maine (36.4 points), District of Columbia
(35.7 points), New York (35.6 points), Illinois (35.3 points) and
Florida (35.1 points). In only three states was the gap less than
23 percentage points - Alaska (19.8 points), and North and
South Dakota (22.4 points).
11
State Median Earnings, Past 12 Months, Ages 16 and Over with
Disability, 2016

12
http://disabilitycompendium.org/si tes/default/files/user-
Looking now at median earnings by state, this slide shows the
range of median earnings in states for people with disabilities in
2016 was $17,480 in West Virginia to $30,559 in Alaska. In
eleven states (Alaska, Maryland, District of Columbia, New
Jersey, Hawaii, Nevada, Virginia, Delaware, Connecticut, North
Dakota, and Washington), the median earnings for people with
disabilities was over $25,000, while six states had median
earnings for people with disabilities lower than $20,000
(Minnesota, Wisconsin, Maine, Michigan, Montana, and West
Virginia).
12
State Median Earnings, Past 12 Months, Ages 16 and Over
without Disability, 2016

13
uploads/2017AnnualReportSlideDec k
In comparison to the last slide, the median earnings for people
without disabilities ages 16 and over ranged from $27,431 in
Idaho to $51,302 in the District of Columbia in 2016.
13
Median Earnings Gap of People 16 Years and Over in the Past
12 Months, by State, 2016
14
Now, using the gap map again, we can see that while states
varied widely in earnings gap – from a low of $5,242 in Idaho

to a high of $23,144 in the District of Columbia, generally,
states in the northeastern US had a higher earnings gap; states
in the southern US had a lower earnings gap
14
Poverty Percentage Gap Among People with and without
Disabilities, by State, 2016
15
Moving on to Poverty. Here is the poverty gap between those
with and without disabilities by state in 2016. The highest
poverty gaps were seen mostly in the Northeast US, states
bordering the Great Lakes, Kentucky, Missouri, and South
Dakota. Gaps ranged from a high of 14.0 percentage points
(District of Columbia) to a low of 1.5 percentage points in New
Mexico.
15
Poverty Percentage Gap Among People
Ages 5 and Under with and without Disabilities,
by State, 2016

16
For children under age 5, the poverty gap was highest in New
Hampshire (60.3 percentage points), Arkansas (47.2), and
Mississippi (42.6). For children ages 5 and under, fifteen states
had a negative poverty gap (a higher percentage of those
without disabilities were in poverty than those with
disabilities).
16
Ages 5-17 with and without Disabilities,
by State, 2016
17

The poverty gap for those ages 5-17 with and without
disabilities ranged from a low of 1.3 percentage points in
Hawaii to 19 points in Maine.
There are nine states with a gap of at least 15 points and 26
with a gap of at least 10 points, meaning that in those states the
poverty rates were 10-15 or more percentage points higher for
those with disabilities than for those without disabilities.
17
Poverty Percentage Gap Among People Ages 18-64 with and
without Disabilities,
by State, 2016
18

For people in the 18-64 year old working- age, the poverty gap
between those with and without disabilities ranged from a low
of 7.4 percentage points in Delaware to a high of 24.8 poi nts in
District of Columbia. Nearly half of the states (24) had gaps of
15 points or more. All but 3 states had gaps over 10 points or
more.
18
Ages 65 and Over with and without Disabilities, by State, 2016
19
http://disabilitycompendium.org/si tes/default/files/user-
Poverty gaps for those age 65 and over with and without
disabilities had a low of 1.7 percentage points (Nevada) to 8.6
points (South Dakota) in 2016. Three states had gaps below 3
points (Nevada, Vermont, and Delaware).
19
Smoking Percentages Gap Among People
with and without Disabilities By State, 2016

Data Source: Authors' calculations using data from the 2016
Behavioral Risk Factor Surveillance Survey BRFSS *
20
Turning now to health, the gap between smokers with and
without disabilities by state in 2016 ranged from a low of 5.2
percentage points in South Dakota to a high of 16.6 points in
Missouri. Thirty six states had a gap of 10 percentage points or
higher; South Dakota was the only state to have a gap of 6
percentage points or lower.
*- Note that this data is from the Behavioral Risk Factor
Surveillance System (BRFSS), which in 2016 changed the
questions used measure disability to match those used in the
American Community Survey (ACS).
20
Obesity Percentages Gap Among People
with and without Disabilities, by State, 2016
Behavioral Risk Factor Surveillance Survey BRFSS

21
This slide shows that the gap in obesity percentages for states
ranged from a high of 16.8% in Rhode Island to a low of 7.3%
in Mississippi. Nine states had a gap under 10 percentage points
while seven states had a gap of 15 points or more.
21
Binge Drinking Percentage Gap Among
People with and without Disabilities,
by State, 2016
Behavioral Risk Factor Surveillance Survey BRFSS
22

This slide shows gaps in binge drinking for people with and
without disabilities by state in 2016. Gaps in binge drinking for
those ages 18 and over ranged from 11.7 points less (thus more
people without disabilities binge drinking than those with
disabilities) in District of Columbia to 1.6 points less in Utah.
Twenty one states had a gap of less than 5 points.
22
For more information
Lewis Kraus
Center on Disability at the Public Health Institute
510-285-5600
[email protected]
23
23
1187326 - Wiley US ©
Appendix A
Specimen Financial Statements: Apple
Inc.
Once each year, a corporation communicates to its stockholders

and other interested
parties by issuing a complete set of audited financial
statements. The annual report, as
this communication is called, summarizes the financial results
of the company's
operations for the year and its plans for the future. Many annual
reports are attractive,
multicolored, glossy public relations pieces, containing pictures
of corporate officers and
directors as well as photos and descriptions of new products and
new buildings. Yet the
basic function of every annual report is to report financial
information, almost all of which
is a product of the corporation's accounting system.
The content and organization of corporate annual reports have
become fairly
standardized. Excluding the public relations part of the report
(pictures, products, etc.), the
following are the traditional financial portions of the annual
report:
Financial Highlights
Letter to the Stockholders
Management's Discussion and Analysis
Financial Statements
Notes to the Financial Statements
Management's Responsibility for Financial Reporting
Management's Report on Internal Control over Financial
Reporting

Report of Independent Registered Public Accounting Firm
Selected Financial Data
The official SEC filing of the annual report is called a Form 10-
K, which often omits the
public relations pieces found in most standard annual reports.
On the following pages, we
present Apple Inc.'s financial statements taken from the
company's 2017 Form 10-K. The
complete Form 10-K, including notes to the financial
statements, is available at the
company's website.
1187326 - Wiley US ©
1187326 - Wiley US ©
1187326 - Wiley US ©
1187326 - Wiley US ©
1187326 - Wiley US ©

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