Cornell University -- Rehabilitation
Research and Training Center on Disability Demographics and Statistics
Disability
Statistics User Guide Series: A Guide to Disability Statistics from the Current
Population Survey - Annual Social and Economic Supplement (March CPS) Richard V. Burkhauser Andrew J. Houtenville Cornell University For additional information about this paper contact: Andrew J. Houtenville Employment and Disability Institute 303 ILR Extension Cornell University Ithaca, NY 14853 Ph: (607) 255-5702 Fax: (607) 255-2763 This paper is being distributed by the Rehabilitation Research and Training Center on Disability Demographics and Statistics at Cornell University. This center is funded to
Cornell University by the U.S. Department of Education, National Institute on
Disability and Rehabilitation Research (No. H133B031111). The contents of this
paper do not necessarily represent the policy of the Department of Education,
and you should not assume endorsement by the Federal Government (Edgar, 75.620
(b)). Conceptual Model of Disability Background, Survey Methods, and Data
Collection Coverage: Universe and Sample Design Accessing of Data and Statistics Definition of Disability and Other
Variables Comparisons with Other Data Sources Population and Prevalence Estimates Unique Features of the March CPS Measuring Employment Outcomes Using
Alternative Definitions of Disability Trends in the Employment of
Working-Age Men with Disabilities The Robustness of Findings across
Data Sets Introduction The mission of the Cornell StatsRRTC is to bridge the divide
between the sources of disability data and the users of disability statistics.
One product of this effort is a set of User Guides to national survey
data that collect information on the disability population. The purpose of
each User Guide is to provide: ·
an easily accessible guide to the disability information
available in the nationally representative survey; ·
a description of the unique features of the survey; ·
a set of estimates on persons with disabilities from the survey,
including estimates on the size of the population, the prevalence rate, the
employment rate and measures of economic well-being; ·
a set of estimates that highlight the unique features of the
survey; and ·
a description of how estimates from the survey compare to other
national surveys that are used to describe the population with disabilities. This User Guide addresses disability-related data available
in the Current Population Survey- Annual Social and Economic Supplement (March CPS),
also known as the March Supplement, Income Supplement, and Annual Demographic
Survey. The CPS program is one of the longest running nationally
representative surveys in the United States, if not the world. The CPS began
as an effort to measure labor market conditions, as a response to the lack of
data during the Great Depression of the 1930s. By 1945, the CPS surveyed
25,000 households using a complex probability sampling design— a new concept at
the time. The CPS continued to grow and evolve, and by 2005 the CPS sample reached
99,000 households. What was a brief monthly survey to collect unemployment
status has grown into an extensive survey program using computer-assisted
interview techniques, containing multiple supplements collecting data on a
variety of social topics (e.g., income, poverty, health insurance coverage,
school enrollment, and voting behavior).[1]
The strength of the CPS is its ability to generate time trends.
Electronic public-release data files are available from as far back as 1962. CPS
data is used extensively by government agencies, researchers, policy makers,
and journalists to evaluate employment, government programs, and the economic
well-being and behavior of individuals, families and households. CPS-based
statistics are used by government policymakers as indicators of the state of
the U.S. economy and for planning and evaluating government programs.
CPS-based statistics are often cited in the media.
Over most of its history the March CPS has attempted to capture household
income from all sources, including government programs targeted on working-age
people with disabilities (e.g., Social Security Disability Insurance,
Supplemental Security Income, state workers compensation programs). A work
limitation question was added to the March CPS in 1981 as a screener question
in an effort to better capture disability-related income. More recently, the
Bureau of Labor Statistics (BLS) has committed to more systematically capturing
the population with disabilities, and is developing a set of seven
disability-related items to add to the CPS program.[2] The use of a work limitation question to capture the working-age
population with disabilities in the March CPS has been the subject of
considerable debate, which we will discuss below. Before doing so, it is
important to discuss both how disability is conceptualized and how this concept
has been operationalized in survey questions. This will allow us to more
easily compare March CPS-based statistics on the working-age population with
disabilities to those from other data sources covered in our User Guide Series.
Conceptual Model of Disability One purpose
of the User Guide Series is to describe the information on disability
available in the various national surveys; as a result we need an operational
definition of disability. Unlike age and gender, which are for the most part
readily identifiable individual attributes, disability is usually defined as a
complex interaction between a person’s health condition and the social and
physical environment. The two major conceptual models of disability are the World
Health Organization’s International Classification of Functioning, Disability
and Health (ICF; WHO, 2001) and the disability model developed by Saad Nagi
(1965, 1976). Both models recognize disability as a dynamic process that
involves the interaction of a person’s health condition and personal
characteristics with the physical and social environments. Changes to any one
of these factors over time can have an impact on a person’s ability to function
and participate in activities. A detailed description and comparison of these
models is available in Jette and Badley (2000). We use ICF concepts to create operational definitions of
disability. The concepts used include impairment, activity
limitation, participation restriction, and disability (see World
Health Organization, 2001). A prerequisite to each of these concepts is the
presence of a health condition. Examples of health conditions are listed in
the International Classification of Diseases, Tenth Edition (World Health
Organization, 2006) and they encompass diseases, injuries, health disorders,
and other health-related conditions. An impairment is defined as a significant
deviation or loss in body function or structure. For example, the loss of a
limb or a vision loss may be classified as an impairment. In some surveys,
impairments are defined as long-lasting health conditions that limit a person’s
ability to see or hear, limit a person’s basic physical movement, or limit a
person’s mental capabilities. An activity limitation is defined as a difficulty an
individual may have in executing activities. For example, a person who
experiences difficulty dressing, bathing, or performing other activities of
daily living due to a health condition may be classified as having an activity
limitation. In some surveys, activity limitations are identified based upon a
standard set of activities of daily living questions (ADLs). A participation restriction is defined as a problem that
an individual may experience in involvement in life situations. For example, a
working-age person with a health condition may have difficulty participating in
employment as a result of the physical environment (e.g., lack of reasonable
employer accommodations) and/or the social environment (e.g., discrimination).
In some surveys, participation restrictions are identified by questions that
ask whether the person has a long-lasting health condition that limits his or
her ability to work, or whether a health condition affects his or her ability
to go outside the home to go shopping, to church, or to the doctor’s office. In the ICF, the term disability describes the presence of
an impairment, an activity limitation and/or a participation restriction.
While these concepts may seem to follow a progression—that is, an impairment
leading to an activity limitation leading to a participation restriction—this is
not necessarily the case. Figure 1 provides a useful summary of ICF concepts.
It is possible that a person may have a participation restriction without an
activity limitation or impairment. For example, a person diagnosed as HIV
positive may not have an evident impairment or activity limitation, but may not
be able to find employment due to discrimination resulting from his or her health
condition. Similarly, a person with a history of mental illness, but who no
longer has a loss in capacity or activity limitation, may also be unable to
find employment due to discrimination resulting from his health condition. Figure 1 illustrates that while there is an overlap across these
concepts, it is possible that one of them can occur without a relation to the
others. The universe of the ICF definition of a disability begins with a health
condition. Disability encompasses all conditions that fall into the categories
of impairment, activity limitation, and/or participation restrictions;
i.e., the union of these three categories. Figure 1. Conceptual Model of Disability Using ICF Concepts Figure 1 is a Venn diagram that shows a
box and three overlapping circles that are contained inside the box. The box
represents the health of the population. The first circle represents the ICF
impairment concept. The second represents the ICF activity limitation concept.
The third represents the ICF participation restriction concept. They overlap to
show the portions of the population can have any combination of an impairment,
an activity limitation and a participation restriction. The portions of each
circle that do not overlap with the other circles show that portions of the
population can have only one of the three ICF concepts. The portion of the box
that is outside of the three circles shows the portion of the population that
does not have any of the three ICF concepts. Translating the ICF concepts into operational definitions in
surveys and mapping existing survey questions to ICF concepts are not
straightforward tasks. In the User Guide Series, we were forced to use
our best judgment in classifying survey questions into one of the three
specific ICF categories since well-defined rules for doing so are not available
in the ICF. In some cases, the classification is straightforward. In others,
for example, the survey questions may be interpreted as both an activity
limitation and a participation restriction. Our approach in such cases was to
make clear and consistent judgments that would allow us to make comparisons of
various measures of disability across data sources within the ICF framework. Background,
Survey Methods, and Data Collection The
CPS program is a complex series of monthly surveys and supplements conducted by
the Bureau of the Census on behalf of the Bureau of Labor Statistics. The main
components of the CPS program are (1) the Basic Monthly Survey, which provides
monthly statistics on labor markets, and (2) the Annual Social and Economic
Supplement (March CPS) fielded in March, which contains the work limitation
question. There are numerous supplemental surveys to the Basic Monthly CPS
that delve deeper into a range of topics: ·
Annual Social and Economic Supplement (a.k.a., Annual Demographic
Survey, March Supplement, Income Supplement) ·
Contingent Workers and Alternative Employment ·
Displaced Workers ·
Job Tenure and Occupational Mobility ·
Race and Ethnicity ·
Tobacco Use ·
Voting and Registration ·
School Enrollment ·
Work Experience ·
Food Security ·
Work Schedules ·
Computer Ownership ·
Fertility and Marital History ·
Fertility and Birth Expectations These supplements may occur annually, every two years,
sporadically, or sometimes only once. They are fielded in various months. Coverage: Universe
and Sample Design The sample of the CPS program is designed to generate reliable
monthly statistics for each state and the District of Columbia. Over the
years, the sample design has changed to improve reliability and contain cost. Sample Design. The sample
is a multistage stratified sample of households in the U.S, to represent the civilian,
non-institutional population. A multistage stratified process is used to draw
the sample and ensure even coverage across the United States. The process
proceeds as follows: (1) the Decennial Census is used to divide the United States into primary sampling units (PSUs). In 2003, the year we highlight below, the
United States is divided into 2,007 PSUs based on the 1990 Census. A PSU is
a metropolitan area, a large county, or a group of small counties. PSUs do not
cross state boundaries. (2) Groups of PSUs are created (i.e., the PSUs are assigned
to strata) based on 1990 Census and other information, such that PSUs with
similar labor force, economic, and social characteristics are grouped
together. In 2003, 792 strata were created. (3) One PSU is selected from each
stratum. Selection is not random; rather the probability of selection for each
PSU in the stratum is proportional to its population size and is done in a way
to ensure each state is represented. (4) A sample of housing units (structures)
is drawn from each of the selected PSUs. The list of housing structures is
based on a variety of sources including a registry of building permits for new
construction. (Note that housing structures are being sampled not people.
This has implications later in our analysis.) The selection of housing units
within a selected PSU process ensures that each housing unit in the population has
one chance of selection and that all housing units in a state have the same
chance of selection. (For more detailed information on the sample design, go
to www.census.gov/prod/2002pubs/tp63rv.pdf.)
Non-Institutional Group Quarters.
The CPS also selects group quarters which contained housing units in which
residents shared common facilities or received formal or authorized care or
custody. These are housing units such as residential group homes, not nursing
homes. Rotation Scheme. The CPS program
uses a complex rotation system to refresh the sample. Each housing unit is
interviewed a total of eight times—a housing unit is interviewed for four
consecutive months and then dropped out of the sample for the next eight months
and is brought back in the following four months. The first and fifth
interviews are called the incoming rotations. The fourth and eight interviews
are called the outgoing rotation. Each month a new sub-sample (or panel) is
brought to replace the sub-sample that had its eighth interview. Figure 2 depicts the rotation scheme for a hypothetical 15 month
period and 17 panels (Panels A-Q). The first row shows that housing units in
Panel A had their first interview in March of Year 1, were out of the sample from
July though February, were brought back into the sample in March of Year 2 and
had their last surveys in June of Year 2. The first column shows that: March of
Year 1 is the first interview for Panel A, the last interview for Panel P, a
month off for Panels E through L, a return to the survey for Panel M, and the
outgoing rotations for Panels D and P. The second column also shows that:
Panel P is no longer being interviewed or scheduled to be interviewed and a new
panel, Panel Q, takes its place. In March of Year 1 and March of Year 2, half
of the housing units are surveyed, thus there is the ability to match up
housing units, as we do in the analysis below. Figure 2. Rotation: Assignment of the Eight Month in
the Sample for 17 Hypothetical Panels (A-Q) Panel Year 1 - Mar. Year 1 - Apr. Year 1 - May Year 1 - Jun. Year 1 - Jul. Year 1 - Aug. Year 1 - Sep. Year 1 - Oct. Year 1 - Nov. Year 1 - Dec. Year 2 - Jan. Year 2 - Feb. Year 2 - Mar. Year 2 - Apr. Year 2 - May Year 2 - Jun. A 1st 2nd 3rd 4th - - - - - - - - 5th 6th 7th 8th B 2nd 3rd 4th - - - - - - - - 5th 6th 7th 8th C 3rd 4th - - - - - - - - 5th 6th 7th 8th D 4th - - - - - - - - 5th 6th 7th 8th E - - - - - - - - 5th 6th 7th 8th F - - - - - - - 5th 6th 7th 8th G - - - - - - 5th 6th 7th 8th H - - - - - 5th 6th 7th 8th I - - - - 5th 6th 7th 8th J - - - 5th 6th 7th 8th K - - 5th 6th 7th 8th L - 5th 6th 7th 8th M 5th 6th 7th 8th N 6th 7th 8th O 7th 8th P Q 1st 2nd 3rd 4th - - - - - - - - 5th 6th 7th Adjusting of Sample Design. Sample
weights are provided to adjust point estimates—population size, proportions,
means, medians, etc.—for the complex sample design. Separate weights are
provided for the basic monthly survey, the ASES, and the outgoing rotations,
which have additional earnings-related questions. However, these sample weights
are not sufficient to adjust variance-related estimates—standard error,
coefficient of variation, etc. It is necessary to incorporate design factors.
See Houtenville (2000) and Census
Bureau (2002) for details on how to adjust variance-related estimates information.
Matched Sample. Since the CPS tracks
the same housing unit over a 16-month period, it is possible to create a
longitudinal file for that housing unit. It is common for researchers to match
housing units from March-to-March to obtain longitudinal information for two
ASESs. Short panel data sets of this type, matching individuals across March
files of the CPS, have been used to study a wide range of economic questions. But because, in general, researchers are interested in following
the people in a housing unit rather than the housing unit, it is critical to
take account of the fact that there may be changes in the people who occupy the
house over this period and account for that in the analysis. To assure that we
are following the same people, in our analysis below, we match on the housing
unit identifier and then match individuals based on age, race, and sex.
Duplicate observations are then matched on education level. One limitation of this
type of analysis is that it will systematically exclude people who move out of
the housing units where they lived in March of the first year and people who
move into those housing units by the following March. Furthermore, the March
1984 and March 1985 CPS data, as well as the March 1994 and March 1995 CPS
data, cannot be merged because revisions in the household identifiers
implemented to protect the confidentiality of survey respondents between these
years prevent matching. For details on matching CPS files, see Madrian and
Lefgren (2000), and Feng (2004). The collection mode may influence the quality of the information it
collects, especially with respect to accurately capturing the population with
disabilities. For instance, the use of telephone surveys may limit the ability
of people with hearing impairments to participate. While a Census Bureau
employee initially conducts a face-to-face interview with the head of the
household with the assistance of a computer—Computer Assisted Personal
Interview (CAPI), the interview is conducted via the telephone over the next
seven months. In those interviews, a Census Bureau employee talks with the
head of the household over the telephone with the assistance of a
computer—Computer Assisted Telephone Interview (CAPI). Information on other
household members is obtained from the head of household, i.e., via proxy
response. Accessing
of Data and Statistics The Census Bureau disseminates CPS data and statistics in two ways:
(1) public-use data files (i.e., raw data) and (2) pre-generated descriptive statistics
on a variety of topics. Public-Use Data Files. Public
versions of CPS data files are readily available. These files contain
individual records for each household, family and each family member. Of
course, these data are not truly raw data, directly from the survey
respondents. Many useful summary variables (e.g., the monthly labor force
recode) are provided, as well as imputations for missing values based on a
HotDeck method. In addition, certain information has been modified to maintain
confidentiality and limit the identifiability of respondents. For instance,
income values from each source are top-coded (see Burkhauser, Butler, Feng and
Houtenville, 2004; Feng, Burkhauser and Butler, 2006). There are several ways to access these data files: (1) download
complete files from a BLS and Census Bureau supported web site (http://www.bls.census.gov/ferretftp.htm); (2)
extract sub-files (and even do some preliminary calculations) using Census
Bureau’s web-based data extraction software, called DataFerrett (http://dataferrett.census.gov/); and (3) access through many
colleges and universities, where it is available through the Inter-University
Consortium for Political and Social Research (ICPSR). Descriptive Statistics. There
are two sources of pre-generated March CPS statistics related to disability.
The StatsRRTC-supported web site, www.disabilitystatistics.org,
which contains state-level estimates and time trends (1980-current) of the prevalence
rate, employment rate, poverty rate, and median household income. The Census
Bureau web site, http://www.census.gov/hhes/www/disability/disabcps.html,
which contains annual estimates from 1995–current
regarding prevalence, educational attainment, employment, unemployment, and earnings. Definition
of Disability and Other Variables A description of the survey questions and how we used these
questions to define disability, demographics, economic well-being, and
employment is shown in Tables 1a – 1d. Disability. Table 1a shows that the
March CPS has a work limitation question: “(Do you/Does anyone in this
household) have a health problem or disability which prevents (you/them) from
working or which limits the kind or amount of work (you/they) can do? If yes to
..., who is that? (Anyone else?).” Similar work limitation questions appear in
the American Community Survey (ACS), National Health Interview Survey (NHIS),
and the Survey of Income and Program Participation (SIPP). The March CPS work
limitation question has been used extensively in the economics literatures to
capture the working-age population with disabilities and compare its employment
and economic well-being with the working-age population without disabilities. See
Bound and Waidmann (1992), Burkhauser, Haveman, and Wolfe (1993), Acemoglu and
Angrist (2001), Burkhauser, Daly, and Houtenville (2001), Bound and Waidmann (2002),
Burkhauser, Daly, Houtenville and Nargis (2002), Autor and Duggan (2003), Daly
and Burkhauser (2003), Hotchkiss (2003), Hotchkiss (2004), Houtenville and
Burkhauser (2005), Jolls and Prescott (2005) Burkhauser, Houtenville and Rovba
(2006a), Burkhauser, Houtenville and Rovba (2006b). Some researchers and policy advocates dismiss these results as
fundamentally flawed, arguing that the set of individuals with self-reported
work limitations captured in the March CPS represent neither the actual
population with disabilities (Hale, 2001) nor its employment trends (Kaye, 2002;
Kirchner, 1996).[3]
While concerns about the accuracy and consistency of self-reported work limitations
questions are not new (see for example, Bound 1991; Chirikos and Nestel, 1984;
Chirikos, 1995; Bazolii, 1985; and Parsons 1980, 1982; Bound and Burkhauser,
1999, provide a detailed review of this literature), they currently are at the
center of the debate about what, if anything, should be done to reverse the
downward trend in employment among men and women with disabilities observed in
the March CPS.[4]
One concern with the March CPS work limitation question is that
it does not contain a reference period; therefore persons with very short-term work
limitations may respond affirmatively. To address this issue, Burkhauser,
Daly, Houtenville and Nargis (2002) and others since then, use the ability to
match a portion of the March CPS sample from March-to-March to define a
two-period work limitation—people who report a work limitation in March of
consecutive years.[5]
This measure better captures the longer-term and presumably more seriously
impaired population with disabilities. Demographics. Our analysis below
utilizes questions on age, sex, race, and ethnic origin. Table 1b shows that a
person’s sex is identified with the request, “Enter appropriate sex.” Age is
solicited with a series of questions that reflect a computer assisted design:
“[w]hat is (name's/your) date of birth? [Probe] As of last week, that would
make (name/you) ((age/approximately age/less than 1/over 98) years/year) old. Is
that correct? [Probe] Even though you don't know (name's/your) exact birth
date, what is your best guess as to how old (you/he/she) (were/was) on
(your/his/her) last birthday?” Hispanic origin is determined with question:
“[w]hat is (name's/your) origin or descent? [Show flashcard.] German, Italian,
Irish, French, Polish, Russian, English, Scottish, Mexican American, Chicano,
Mexican, Puerto Rican, Cuban, Central/South American, Other Hispanic,
Afro-American, Dutch, Swedish, Hungarian, Another Group, Don't Know.” In our
analysis, we code “Mexican American, Chicano, Mexican, Puerto Rican, Cuban,
Central/South American, Other Hispanic” as Hispanic. Race is asked with a
series of questions: “What is (name's/your) race? [Probe] (Are/Is) you/he/she)
White, Black, American Indian, Aleut or Eskimo, Asian or Pacific Islander or
something else?” Educational attainment is obtained with the question: “What is
the highest level of school [person] has completed or the highest degree
[person] has received?” If response indicates “less than 1st grade, 1st, 2nd,
3rd or 4th grade, 5th or 6th grade, 7th or 8th grade, 9th grade, 10th grade,
11th grade, 12th grade or no diploma, we code them as “less than high school.”
If response indicates high school graduate (high school diploma or equivalent),
we code them as “high school.” If respondents indicate some college but no
degree, associate's degree in college-occupational/vocational, or associate's
degree in college-academic, we code them as “some college.” If respondents
indicate one of the following: bachelor's degree (e.g., BA, BS, AB), master's degree
(e.g., MA, MS, MEng, MEd, MSW, MBA), professional school degree (e.g.: MD, DDS,
DVM, LLB, JD), or doctorate degree (e.g., PhD, EdD), we code them as
“bachelor's or more.” Employment Measures. There are
numerous employment measures available from the CPS program. Table 1c shows
that current employment is determined by the question, “last week, did [person]
do any work for either pay or profit?” in the Basic Monthly Survey. In the
ASES, employment in the previous calendar year is collected using two
questions: (1) “During [the previous calendar year] in how many weeks did
[person] work even for a few hours? Include paid vacation and sick leave as
work.” (2) “In the weeks that [person] worked [the previous calendar year],
how many hours did [person] usually work per week?” We used these two
questions to create variables reflecting employment in the previous year. If a
person worked at least 52 hours of work during the previous calendar year, we
coded him or her as “Employed Sometime in Previous Year,” which was determined
by multiplying usual hours per week by the number of weeks worked in past 12
months. If a person worked at least 50 weeks during the previous calendar year
and at least 35 hours per week, we coded him or her “Employed Full-time Year
Round,” which was determined by multiplying usual hours per week by the number
of weeks worked in past 12 months, determined by condition that weeks worked is
greater than or equal to 50 and usual hours per week is greater than or equal
to 35 hours. Income and Poverty. The
collection of information on the income and poverty of American households is one
of the core purposes of the March CPS. Table 1d lists the 23 possible sources
of income the March CPS collects on each person in a household: (1) labor
earnings, (2) self-employment income (3) farm income, (4) public assistance and
welfare, (5) unemployment compensation, (6) worker’s compensation, (7)
veteran’s benefits, (8) SSI program, (9) Social Security Old Age, Survivors and
Disability program, (10) educational assistance, (11) dividends, (12) interest
income, (13) rental income, (14) alimony, (15) child support, (16,17) two
sources of private retirement income, (18,19) two sources of private disability
income, (20, 21) two sources of private survivor’s income, (22) financial
assistance from outside the household, and (23) any other income. Capital
gains or capital losses, taxes and the value of non-cash benefits (such as food
stamps and housing subsidies) are not considered in this measure of income. Annual
household income is the sum of each household member’s income. Two other measures of economic well-being are included that use
both related and unrelated members of the household as the income-sharing
unit. The first measure is total household income, which does not adjust for
household size. The second measure is household size-adjusted income. It
assumes that the income needed to achieve a level of economic well-being is
lower for those who live in the same household than it is to live in separate
households. That is, by sharing housing and other resources, less income is
needed to achieve a certain level of economic well-being. The measure is
usually described by the following formula: Household
Adjusted Income = Household Income divided by (Household Size) raised to the eth
power where e is a parameter with a
value between 0 and 1 and represents the degree of sharing (i.e., economies of
scale) within the household. When e equals 0, the measure assumes that
income needed is independent of household size. For example, the measure
assumes a household with 5 members needs the same income as a household with
one member to achieve a certain level of economic well-being. When e
equals 1, the measure assumes that there is no sharing of resources within the
household. For example, the measure assumes that a household with 5 members
needs 5 times the income as a household with one member to achieve the same
level of economic well-being. While there is no universal agreement on the
value of the e parameter, there is empirical evidence that shows that setting e=0.5
makes a reasonable adjustment for the degree of sharing within the household
(see Ruggles 1990 p. 77; and Citro and Michael, 1995). Citro and Michael
(1995) provide a good description of household size-adjusted income and
economic well-being measures. We also provide poverty rates. The Census Bureau calculates the
poverty rate based on family income rather than household income. There can be
more than one family in a household. The poverty rate is derived from family
income and family composition (regarding size, number of children, and number
of older family members), along with standard poverty thresholds, to construct
a poverty measure. For more details, see the Census Bureau website,
www.census.gov/hhes/poverty/povdef.html. The poverty measure is computed based upon the standards defined
in Directive 14 from the Office of Management and Budget (OMB). These
standards use poverty thresholds created in 1982 and index these thresholds to
1999 dollars using poverty factors based upon the Consumer Price Index
(CPI-U). They use the family as the income sharing unit and family income is
the sum of total income from each family member living in the household. The
poverty threshold depends on the size of the family; the age of the householder
(i.e., the person who owns or pays rent for the housing unit and who fills out
the questionnaire for the household) for one member families and two member
families; and the number of related children under the age of 18. Family
income is compared to the relevant poverty threshold to determine the poverty
status of families. The poverty threshold for an unrelated household member is a
function of his or her own total income. The poverty threshold is different
for a member of a household who is unrelated to the householder compared to the
poverty threshold for a one-member household. A poverty measure is not created
for unrelated household members who are under the age of 15 because March CPS did
not collect income information from persons under the age of 15. Note that poverty statistics do not adjust for the additional
expenses that are the result of a health condition or a disability (e.g.,
personal assistance, equipment, medications, etc.). They also do not adjust
for in-kind benefits, such as health insurance, food stamps, housing,
transportation, child-care, etc. Nor do they take into consideration tax
credits such as the Earned Income Tax Credit or local, state or federal taxes
paid. For these reasons, household income relative to the poverty line is only
an approximation of actual disposable income available to households and is
especially so for a household that contains a person with a disability. In Tables 2, 3 and 4, we provide statistics for the population
with and without disabilities as measured by the work limitation question in
the cross-sectional sample of the CPS. Based on the March-to-March Matched CPS,
we provide statistics for those with a work limitation in both Marches
(longer-term work limitation), those with a work limitation in the second March
only, those with a work limitation in the first March only, and those with a
work limitation in neither. We limit our samples to civilians. Composition of the Populations with
Disabilities. Table 2 provides population estimates, disability prevalence
estimates, and sample sizes for non-institutionalized civilians. The
statistics are provided by age categories that are consistent with other User
Guides. As a concept, work limitation is most relevant for the working-age
population—here defined as ages 25-61. Those younger than 25 may still be in
school and not expected to work while those ages 62 and older may already be
retired. Among working-age civilian persons, 8.4 percent (12.1 million out of
144.7 million persons) report a work limitation in March 2004. Based on the
matched sample, 5.3 percent report a work limitation in both, 3.0 percent report
a work limitation in the second March only (March 2004), and 2.5 percent report
a work limitation in the first March only (March 2003). Not surprisingly, work
limitation is substantially higher for civilians ages 62-64 (18.9 percent), and
lower for civilians ages 18-24 (3.0 percent). Table 3 provides shared distributions across age, sex, race, and
education within each disability group. Table 3 focuses on comparisons within
categories in a single column. Within the population with work limitations, those
ages 55-64 represent the greatest portion, 21.8 percent, as compared to 12
percent for the population without work limitations. Slightly more than half
of those with work limitations are women (52.5 percent). More than three
quarters (78.0 percent) of those with work limitations are white. About a third
(30.3 percent) of those with work limitations have less than a high school degree
or equivalent, compared to 17.5 percent of those without work limitations. Employment. Table 4 shows three
employment measures for the working-age population (ages 25 to 61) by work
limitation type, disaggregated by sex, race, ethnicity, and educational level.
Of those without work limitations, 81.4 percent report being employed in the
reference period (prior week) compared to 19.6 percent of those with work
limitations. The full-time/full-year employment rate of those with work
limitations is 9.4 percent, compared to 65.3 percent for those without work
limitations. The difference between these two groups is also evident when
looking at our other employment measure “working sometime in the previous year”
(86.2 percent of those without work limitations vs. 27.9 percent of those with
work limitations). As expected, employment disparities are even greater for those
with longer-term work limitations: 13.0 percent employed in the prior week,
16.0 percent employed sometime in the previous year, and 3.5 percent working
full-time year-round. Turning to the demographic sub-groups, men with work limitations
were more likely to work than women with work limitations. But relative to those
without work limitations, men are relatively less likely to work. The relative
current employment rate of men with work limitations was 23.3 percent (i.e.,
20.6 percent / 88.4 percent multiplied by 100), even less than the relative
rate of 25.0 percent for women with work limitations. Among racial sub-groups,
Asians with work limitations had the highest employment rates in absolute and
relative terms. Across educational levels, those with more education fared
better in the labor market, in absolute and relative terms and regardless of
the employment measure. Economic Well-Being. Table 5 provides
statistics based on three measures of economic well-being—the poverty rate,
median household income, and median household size-adjusted income—for the working-age
population (ages 25 to 61) by work limitation type, further disaggregated by sex,
race, ethnicity and educational level. Of those with work limitations, 28.8
percent lived in families with incomes below the poverty line, compared to 8.0
percent of those without work limitations. This difference is evident in the
other two measures as well. The median household income of those with work
limitations was $27,995, compared to $61,999 for those without work
limitations. The median household size-adjusted income of those with work
limitations was $17,967, compared to $36,770 for those without work
limitations. As with employment, the economic well-being of those with
longer-term work limitations was even lower. Using the matched sample, the
poverty rate of those with longer-term work limitations was 30.2 percent; the
median household income was $25,048; and the median household size-adjusted
income was $16,085. As for comparisons across demographic characteristics, the
patterns in economic well-being closely mirror the patterns seen in employment
status. Comparisons with Other Data
Sources The March CPS is one of several nationally representative data
sources that provide estimates of the number, prevalence, employment, and
economic well-being of people with disabilities and related conditions. This
section compares the March CPS work limitation-based estimates with estimates
from other nationally representative surveys: the 2003 American Community
Survey (ACS), 2000 Census, the 2002 National Health Interview Survey (NHIS),
the 1994 National Health Interview Survey-Disability Supplement, the 2003 Panel
Study of Income Dynamics (PSID), and the 2002 Survey of Income and Program
Participation (SIPP). The year associated with each dataset represents the actual
year that the survey was administered. We use the 2004 March CPS for
comparison because, while work limitation information is collected in March
(with no explicit reference period), income and employment information is
collected for the 2003 calendar year. Details on the methods used to collect
information on persons with disabilities in each of these surveys may be found
in the corresponding Cornell StatsRRTC User Guide. Different surveys use different methods to collect information on
persons with disabilities, and these differences lead to differences in the
resulting estimates. Tables 6, 7, 8, and 9 use ICF terms to describe the
population with disabilities that are created from the various questions used
in these data sets. (The exact language for each of the questions used in these
data sets that are aggregated under these ICF headings is available in the
corresponding User Guides.) Each comparison table defines disability as
the presence of a participation restriction, an activity limitation, or an
impairment. Some data sources are limited to identifying a disability based on
a participation restriction as can be seen by looking across the columns that
identify the ICF disability concepts. A “NA” entry indicates that no
information is available in that survey for that ICF concept. In such cases,
overall disability is based only on the information available in the survey.
For example, the March CPS only contains information on a work limitation
(a.k.a. employment disability). The definition of disability in the March CPS
is therefore based solely on whether the person has a work limitation. In
Figure 1, this definition captures a portion of persons who fall within the
participation restriction circle. The authors of the User Guides for
each of the data sets listed in these tables made similar decisions about where
to place information from the questions on disability contained in their data
set. The comparisons are made across the working-age population,
because most of the nationally representative surveys focus on the working-age
population. In addition, among the subset of surveys that identify children
with disabilities, there are relatively large differences in the methods used
to define and identify disability, and it is difficult to make meaningful
comparisons. Further research on methods used to identify children with
disabilities is needed. Differences in estimates may be related to changes in the
population over time. Thus, it is important to pay special attention to the
survey year when comparing estimates across the surveys. For example, the 2000
Decennial Census Long Form is taken in April 2000, and its income reference
year is 1999. Changes in the population, the labor market and the economic
environment between 2000 and 2003/2004 can affect population, prevalence,
employment and economic well-being estimates. Population
and Prevalence Estimates Table 6 reveals differences across surveys in the size of the
population with disabilities. The 2004 CPS identifies about 12 million working-age
people with disabilities based on the work limitation question, which is the
lowest estimate across the six surveys. In contrast, the 2002 SIPP identifies
about 27 million working-age people with disabilities based on a series of 93 disability-related
questions. The User Guide Series shows that, in general, data sets that
ask more questions to identify a population with disabilities and that contain
a broader disability conceptualization will capture a larger disability
population. The single March CPS work limitation question misses a large part
of the broader population with disabilities based on an ICF disability
conceptualization. As mentioned earlier and as reflected in the tables, the
ICF is the union of impairment, activity limitation, and participation
restriction, as opposed to the Nagi framework in which only those with
participation restrictions would be considered to have a disability. Column 3 of Table 6 shows that the population estimates are more
closely aligned when looking specifically at employment disability (i.e., work
limitation) for persons ages 25 to 61: 204 March CPS -12,102,093 persons; 2003
ACS - 9,854,223 persons; 2002 NHIS - 13,725,000 persons, 2002 SIPP - 14,420,000
persons and 2003 PSID - 19,300,000 persons. Note that the PSID only surveys household
heads and spouses. As is shown in Table 7, the 2004 March CPS employment
disability prevalence rate estimate is 8.4 percent for those ages 25 to 61. Only
the 2003 ACS had a lower employment disability prevalence rate—6.9 percent. All
other employment disability prevalence estimates are higher (2002 NHIS - 9.9
percent; and 2002 SIPP - 10.1 percent; 2003 PSID - 13.5 percent). Nearly the
same ordering holds for the age sub-populations. Table 8 provides statistics for three measures of employment:
current employment (employment in the survey reference week), some attachment
(52 hours or more annually), and full-time/full-year (at least 50 weeks annually
with at least 35 hours per week). The current employment rate of people with
disabilities ages 25 to 61 varied considerably across data sources, but there
are some similarities. Not surprisingly, the 2004 CPS, with only its work
limitation question, which is likely to identify a population with more severe
disabilities, yielded the lowest current employment rate for people with
disabilities, 19.6 percent. In contrast, the current employment rates of the
2003 ACS, Census 2000, 2002 NHIS, and 2002 SIPP ranged from 39.3 percent to
48.9 percent, reflecting populations with less severe disabilities. However, focusing on people with employment disabilities, the current
employment rates of the 2004 CPS and the 2003 ACS were similar—19.6 percent and
18.9 percent, respectively. The 2002 NHIS and 2002 SIPP were higher but
similar to each other—29.8 percent and 27.7 percent, respectively. Similar
patterns were seen in the other two measures of employment. Table 9 provides statistics for three measures of economic well-being:
poverty rate, median household income, and median household size-adjusted
income. (Note: income estimates are not adjusted for inflation.) As is shown
in Table 9, the poverty rate of people with disabilities ages 25 to 61 varies
across data sources—the Census 2000 estimate (23.2 percent) falls at the upper
end of the range. Similar to the patterns in the employment rate, the 2004 CPS
provided the highest poverty rate for working-age people with disabilities,
28.8 percent. Looking at employment disability, the poverty rates of the 2004 CPS
and the 2003 ACS were most similar—28.8 percent and 29.6 percent,
respectively. The 2002 NHIS and 2002 SIPP were lower but similar to each other—26.5
percent and 26.0 percent, respectively. Similar patterns were seen in the other
two measures of income. It is clear from Tables 6-9 that the primary disadvantage of the
CPS is that it is limited to one disability-related question—work limitation. One
should use caution when using the CPS to address the level of disability and
the outcomes for people with disabilities. However, the March CPS has some
significant advantages over other data sources: consistently measured time
trends and information derived from the matched sample. In this section, we first use information from 1980-2005 CPS data
and the matched samples for these years. The use of a two-period definition of
disability provides a very different picture of the levels and at times the
trends in the demographics, employment, and economic well-being of persons with
a work limitation-based disability. We then compare our results with those
from other data sets to show the robustness of our findings across data sets. Unique
Features of the March CPS The comparative advantage of March CPS data over other datasets
is that it has continuously asked a nationally representative cross-section of
the United States working-age population the same work limitation
based-disability question since March 1980. Hence it is the only data set for
which trends in the prevalence of a consistently defined population with
disabilities as well as the employment and economic well-being outcomes of this
population is available for such a long time period. Furthermore, the March-to-March match makes it possible to identify
a longer-term population with disabilities that reports having a work
limitation-based disability in two consecutive periods one year apart. Researchers
have used the March CPS to identify persons who report a work limitation-based
disability using both a one- and two-period definition. Persons who have
experienced a disability over a longer time period may differ from persons who
have temporary disabilities or who have recently experienced the onset of a
longer-term disability. Most major surveys interview persons at one point in
time and are therefore unable to differentiate between persons with these
different disability experiences.[6]
Typically, researchers using the March CPS do not make use of the
opportunity to use the March CPS two-period definition of disability. However
there are exceptions. Burkhauser, Daly, Houtenville and Nargis (2002) do so to
show that while the yearly employment rates of working-age people with
disabilities in the March CPS using both the one- and two-period work
limitation-based definition of disability differ from those in the NHIS using
an impairment-based definition of disability, the yearly employment rate trends
in these three populations are not significantly different. Burkhauser,
Houtenville and Rovba (2006a) use the one- and two-period work limitation-based
definition of disability in the March CPS to trace the levels and trends in
poverty rates of these populations relative to their counterparts without
disabilities and Burkhauser, Houtenville and Rovba (2006b) do so to trace the
levels and trends in the employment rates of these two populations to their
counterparts without disabilities. Here we showcase the relative strength of the March CPS by using
all available years of data to trace the levels and trends in the prevalence
rate of disability in the working-age population with disabilities as well as
the relative poverty and employment rates of these populations to their
counterparts without disabilities using both the one- and two-period
definitions of disability available in the March CPS. Since those with a work limitation that has lasted less than one
year are included in our first measure but not in our second, a higher
percentage of the overall population will be considered to have a disability
using our first measure of disability. Their poverty rate is likely to
be lower since we are identifying, on average, a population with less severe
disabilities. Figure 3, taken from Burkhauser, Houtenville and Rovba (2006b),
reports levels and trends in the prevalence of disabilities among working-age
men (aged 21-58) from 1980-2004 using both a one- and a two-period measure of
disability. To be consistent in our measurement of key economic well-being and
employment outcomes, our report on the prevalence of disability is for the year
prior to the March report on a disability by our population in the one-period
case. In the two-period case, it is also for the year prior to the March
report of a disability, but only those who also reported a work limitation in
the previous March are considered to have a longer-term disability. Because
the work limitation question was first asked in the March 1981 CPS we are only
able to report on disability prevalence beginning in 1980 in the one-period
case and in 1981 in the two-period case. In addition, because of changes in
the March CPS survey design, it is not possible to match survey years 1985/1986
and 1995/1996 and thus to report our two-period measure for 1985 and 1995. Not surprisingly, the prevalence of disability using the standard
one-period work limitation-based measure is higher than that using the
longer-term measure in all years. But the trends in both are similar. In the
1980s, the prevalence of disability (using our one-period measure) among
working-age people with disabilities varied from a low of 6.33 percent to a
high of 6.91 percent with no discernable trend. Prevalence rates were higher in
1990s and early 2000s ranging from 6.70 percent in 2002 to 7.73 percent in 1993.
Using the two-period measure of disability, the prevalence of longer-term
disability also increased in the 1990s and 2000s. Prevalence rates ranged from
3.83 to 4.28 percent in the 1980s and from 3.92 to 5.34 percent thereafter.
Collectively these data suggest a rise in self-reported work limitation-based
disability rates since the passage of the Americans with Disabilities Act of
1990.[7]
Table 10, taken from Burkhauser, Houtenville, and Rovba (2006a),
documents the fluctuations in the poverty rate of working-age people with and
without a disability over the business cycles of the 1980s and the 1990s. Data
limitations prevent us from directly measuring the poverty rates of working-age
people with and without disabilities in 1979, the peak year of the 1970s
business cycle. But we see that the poverty rates of both groups follow the
business cycle, rising between 1980 and 1983, the first business cycle trough
year we will consider. Both populations’ poverty rates are sensitive to the
ebb and flow of economic activity over the next two business cycles (1983-1993
and 1993-2004), fluctuating in a similar manner over these years. But the net
change in their poverty rates over these two business cycles differ. The
poverty rate of working-age people with disabilities rose between 1983 and
1993, while the poverty rate of working-age people without disabilities fell. While
the poverty rates of both those with and without disabilities fell in the
1990s, the relative risk of poverty for those with disabilities rose. In 1983,
working-age people with disabilities were 2.83 times more likely to be in
poverty than were working-age people without disabilities. At the end of the
1980s business cycle in 1993, their relative risk had risen to 3.33. By 2004,
working-age people with disabilities were 3.40 times more likely to be in
poverty than were working-age people without disabilities. In Figure 4, we extend this typical analysis of the poverty rate
of working-age people with disabilities by comparing the level and the trend in
the yearly poverty rate of working-age people with disabilities over their
counterparts without disabilities using both a single-period and two-period
measure of disability. As can be seen in Figure 4, while the relative risk of
poverty is higher for both our disability populations, it is much more so for
those with longer-term disabilities. However the trends in these risk ratios
appear to be similar. We formally test these assertions below using regression
analysis. Business cycle theory suggests that indicators of economic
well-being are non-linear functions of time. (See Blanchard and Fischer, 1989.) Hence we allow for non-linearity by
including higher-order polynomial terms in our regression. A visual inspection
of time-trends leads us to use a quadratic function to model the trends for our
poverty risk rates for those with and without disabilities. Statistically,
adding more complex elements of time series analysis would not serve our
purpose, which is to test the equality of levels and trends of time series, not
to model the structural data generating process. The estimated regression equation, with t-statistic in
parentheses, is:[8] y = 2.41 + 0.26*t – 0.4*t-squared
+ 0.002*t-cubed – 0.00004*t-to-the-fourth-power + 1.38*d –
0.47*t*d + 0.07*t-squared*d – 0.004*t-cubed*d +
0.00007*t-to-the-fourth-power*d y = 2.41 (with a standard-error of 5.64)
+ 0.26*t (with a standard-error of 1.13) – 0.4*t-squared (with a
standard-error of -1.27) + 0.002*t-cubed (with a standard-error of 1.45)
– 0.00004*t-to-the-fourth-power (with a standard-error of -1.65) + 1.38*d
(with a standard-error of 1.70) – 0.47*t*d (with a standard-error of
-1.25) + 0.07*t-squared*d (with a standard-error of 1.36) – 0.004*t-cubed*d
(with a standard-error of -1.32) + 0.00007*t-to-the-fourth-power*d
(with a standard-error of 1.25) The regression estimates the levels of both relative poverty risk
series and their time trends between 1980 and 2004. The dependant variable is
the ratio of the poverty rate for working-age people who report a work
limitation-based disability in year (t) over the yearly poverty rate for
working-age people who do not report a work limitation-based disability in year
(t) or (y = pov subscript-t superscript-d-subscript-i
divided by pov subscript-t superscript-n*d-subscript-i),
where the definition of what constitutes a disability (i) varies from i=1,
a one-period disability measure to i=2, a two-period disability
measure. This dependent variable is regressed on the following explanatory
variables: a constant, which is the relative poverty risk using a one-period
disability definition; a time trend (t = 1, 2, ... 25), which is the
trend in that poverty risk; a dummy variable for the definition of disability (d
= 1 if the two-period definition is used, otherwise 0), which controls for
the difference between levels in the two relative poverty risk measures; (d)
and (t) interacted, which controls for the difference between the trends
in the two relative poverty risk measures; and, finally, higher-order
polynomial terms and their interactions with (d) to allow for
non-linearity of time trend. The level of relative poverty risk based on our two-period work
limitation-based measure of disability is significantly larger than the level
of relative poverty risk using our one-period measure. This is not surprising
since people with short-term work limitations are not included in the
population with disabilities in our two-period matched sample. Our null hypothesis for the trends is that they are the same for
both definitions of disability. Using an F-statistic, we find that the set of
interaction terms in our regression is not statistically different from zero at
any conventional level. Therefore, we fail to reject the null hypothesis that
the time-trends of the poverty risk ratios of our two disability definitions
are the same. Thus, we find that the levels of our relative poverty risks using
our one- and our two-period measures of disability are significantly different
over the period of our analysis, but the time-trends of these relative poverty
risks are not. Measuring
Employment Outcomes Using Alternative
Definitions of Disability Despite the fact that the March CPS has very limited information
on health and researchers using it must rely on its work limitation question
alone to capture the working-age population with disabilities, the CPS has been
widely used in the economics literature, cited above, to look at the employment
and/or economic well-being of working-age people with disabilities. Here we
demonstrate its value in providing such long-term employment series using both
a one- and two-period measure of work limitation-based disability by
reproducing figures and tables from Burkhauser, Houtenville and Rovba (2006b). Trends in
the Employment of Working-Age Men with Disabilities We will follow convention for the employment literature on
working-age people with disabilities by focusing on weeks worked in the
previous year. That is, the year prior to the March report of a work
limitation. While there are many alternative yearly measures of employment
that have been used in this literature (e.g. at least 52 hours of work in the
past year, full time or part time work in the past year, hours of work in the
past year, etc.) we choose the weeks worked measure because it is the one used
by Acemoglu and Angrist (2001). Like them, we also look at those aged 21-58.[9] Table 11 uses annual weeks worked to capture levels and trends in
the employment of working-age men with disabilities using both our one- and
two-period measures of disabilities. As in the previous tables, weeks worked
are influenced by both cyclical and secular events. However in all years,
mean weeks worked of working-age men with disabilities is lower than that of
working-age men without disabilities. And, the mean weeks worked of men with
longer-term disabilities is lowest of all. The employment of both those with and without disabilities is
impacted by the business cycle. As can be seen in column 1, employment is
lowest in the three business cycle trough years of 1982, 1993, and 2004. But
while overall employment rises slightly over these three trough years (column 5)—from
43.06 to 44.96 to 45.35 weeks per year—for working-age men without (one-period)
disabilities, it falls dramatically for those with disabilities (column 3)—from
16.90 to 14.84 to 11.61 weeks per year. Hence, over these two business cycles
the weeks worked of those with disabilities (using our one-period measure of
disabilities) falls from 0.39 of those without disabilities in 1982 to 0.33 in
1993 to 0.26 in 2004 (column 4). There is a substantial decline in the relative hours worked of
those with and without disabilities that occurred between 1992 and 1993 (column
4), a decline from 0.39 to 0.33. This one year decline of 0.06 in the relative
weeks worked of working-age men with disabilities is the largest single year
decline in the entire series of years covered in Table 11. It is this decline
that lead Acemoglu and Angrist (2001) to investigate whether or not the ADA, which was implemented in this year, was responsible for the decline. But, as Table 11
also shows, the next greatest yearly decline in this ratio was not captured by
Acemoglu and Angrist (2001) since they focused only on the years 1988-1996. It
occurred in the recession low year of 1982 when the ratio fell by 0.04 from
0.43 in 1981 to 0.39. This was the most important single year decline in our
series until the 0.06 decline that occurred simultaneously with the
implementation of the ADA and the depths of the 1990s recession in 1993. In
the replication and evaluation of the Acemoglu and Angrist work discussed in
Burkhauser, Houtenville and Rovba (2006b), we were motivated by this evidence
to extend the number of years used in their model to see if this altered their
controversial findings. But the most compelling initial evidence that led us to replicate
and test the sensitivity of their results can be seen in the four remaining
columns of Table 11. Here we show that the dramatic decline found between 1992
and 1993 in the one-period disability population used by Acemoglu and Angrist
is not found in the longer-term disability population, who presumably would be
more likely to be most impacted by the ADA, as well as by public disability
transfer policies. The employment of men with longer-term disabilities (column
6) is at a 1980s low of 8.42 mean weeks worked in 1982 and a 1980s low of 0.19
relative to those without longer-term disabilities. But it rises to a high of
11.63 weeks in 1986 before falling to a low of 9.43 weeks in 1990. It then
rises to 11.42 weeks in 1992 before falling slightly to 10.76 weeks in 1993 and
then falling dramatically to 7.78 weeks in 1994. Mean weeks worked then rise in
1996 only to fall thereafter to a low of 6.44 weeks in 2002. Most importantly, the trends in the ratio of mean weeks worked
for those with and without disabilities using our two-period measure of
disability (column 8) is also quite different from those found using our
one-period measure in column 4. The ratio rises to a high of 0.25 in 1986;
falls to 0.20 in 1990; rises to 0.25 in 1992; falls to 0.24 in 1993; and then
to 0.17 in 1994. It remains there except in 1996, until 1999, when it falls
again to a low of 0.14 in 2002 before rising back to 0.17 in 2004. Thus, over
the last two business cycles of the 20th Century while the relative
employment of working-age people with disabilities has declined using both a
one- and a two- period measure of this population, the timing of these declines
is quite different. The
Robustness of Findings across Data Sets As we have discussed above, some critics of the literature that
has used the March CPS to identify the working-age population with disabilities
have argued that this sample of the working-age people with disabilities created
from those who report a current work limitation may not accurately measure the true
working-age population with a disability (Hale, 2001). Unfortunately, no
consensus exists on the dimensions of the conceptually true population with
disabilities. However if this work limitation-based sample of it was random,
then the only effect of this type of measurement error would be to introduce
noise into the level of the working-age population with disabilities. A
potentially more serious problem is selection bias, i.e., that the work
limitation-based population with disabilities may represent a select portion of
the population with disabilities and hence, not adequately reflect outcomes,
such as employment, for the true population with disabilities. Burkhauser et al. (2002) show the population with impairments is
substantially understated by estimates that are based on the work-limitation
question in the NHIS, and although the severity of the impairment explains much
of the variance in work limitations, it does not explain all of it. As is
shown in Table 12, for example, of those who reported being "deaf in both
ears" or "blind in both eyes"—impairments that many would expect
to be work limiting—only 38 percent or 69 percent respectively, also reported
being “unable to work or to be limited in the kind or amount of work they do.” Burkhauser et al. (2002) also demonstrate that this mis-estimation
of the level of disability translates to difference in outcome measures. Table
12 shows that, for example, of those who report being "deaf in both ears"
or "blind in both eyes," those who reported these impairments but
reported no work limitation were 2.07 and 4.0 times more likely, respectively,
to be employed than were such persons who did report a work limitation. This
finding suggests that using a work-limitation question to define the impairment-based
population with disabilities will systematically understate its employment rate.
Table 13 replicates the Burkhauser et al. (2002) findings using both
a work limitation-based population with disabilities and an impairment-based
population with disabilities from the ACS. In 2003, the ACS collected
information from over 500,000 households. This is five times the households
surveyed in the 2003 March CPS and the NHIS. (For a detailed discussion of the
value of the ACS for disability research, see Weathers, 2005.) As is shown in
Table 13, the ACS employment disability question understates the population
with sensory, mental, physical, and self-care disabilities; i.e., not all
persons with these disabilities report an employment disability. In addition,
those with sensory, mental, physical, and/or self-care disabilities that also
report an employment disability have substantially lower employment rates than
those with sensory, mental, physical, and/or self-care disabilities who do not
report an employment disability. However, with regard to trends in the outcome measures, Burkhauser
et al. (2002) show that the employment trends of the work limitation disability
population mirror those of other populations with disabilities, including the
population with impairments, which is presumably less subject to selection bias
and less influenced by the social environment. They compare the employment
rates of those with a March CPS one-period work limitation-based disability for
the years 1983-1996 with those estimated from the National Health Interview
Survey (NHIS) for those years and find that there is no significant difference
in their levels and trends. When they compare them with the employment rates
for an impairment-based disability population in the NHIS over these years,
they find that while the employment rates in the March CPS population are
significantly lower, there is no significant difference in the trends in these
two measures. When they compare the employment rates of those with a March CPS two-period
work limitation-based disability with the NHIS employment rates, they also find
them to be significantly lower but not significantly different in trend. Figure 5, taken from Burkhauser, Houtenville and Rovba (2006b), also
uses data from the March CPS and NHIS to show that these same patterns hold
when we focus on the relative employment of men with disabilities using the
same age group (age 21-58) and measure of employment (relative weeks worked per
year) as Acemoglu and Angrist (2001). A decline in the relative employment of
working-age men with disabilities is found in all four populations. Because
the NHIS stopped asking the work limitation question as well as the same
detailed set of questions on impairments after 1996, it is not possible to
compare post-1996 employment values in the NHIS with those from 1983-1996. But
we can make comparisons across these years with the March CPS data. As can also
be seen in Figure 5, the decline in the relative employment of working-age men
with disabilities continued well after 1996. Trends across states also provide a way to gauge the robustness
of the March CPS results. Table 14 shows the prevalence of work limitations
for those ages 25-61, by state from the 2004 March CPS and 2003 ACS. The 2004
March CPS work limitation prevalence rate ranged from 5.3 percent in Nevada to 16.0 percent in West Virginia, while the 2003 ACS work limitation prevalence rate
ranged from 4.1 percent in Utah to 14.0 percent in West Virginia. These two
series are highly correlated—a correlation coefficient of 0.88. Table 14 also
contains the 2003 ACS overall disability prevalence rate, which ranges from 8.9
percent in New Jersey to 21.2 percent in West Virginia. The 2003 ACS overall
disability prevalence rate is highly correlated with both the 2003 ACS and 2004
March CPS work limitation rates—correlation coefficients of 0.95 and 0.87,
respectively. These results suggest that, much like the time trends, work
limitation questions should not be used to generate level-estimates, but are
discerning patterns across states. The March CPS is one of several national datasets that has been
used to perform research and policy analysis related to persons with disabilities.
It is a nationally representative sample of the population of United States households and is the primary data set used by the Bureau of the Census to capture
employment and economic well being of Americans. Official United States Bureau
of the Census employment rates, income levels, and poverty rates are all based
on data from the March CPS. Since 1981 the March CPS has asked the householder
for information on the work limitations of members of the household. Hence it
offers the longest continuous data on a consistently measured population with
disabilities. Furthermore because it re-interviews households, researchers can
follow a two-period population with disabilities. Most other national datasets
only interview sample members once and are unable to describe the dynamic
aspects of disability. Researchers have used the March CPS re-interviews to
separately consider the subset of persons who have long-term disabilities by
examining the responses to the work limitation question in two March CPS
interviews. This User Guide describes how the patterns in the
disability prevalence rates and the poverty and employment rates of working-age
persons with disabilities change over time using these two alternative measures
of disability. A subpopulation of those with disabilities are longer-term
disabled. But this sub-population has a substantially greater risk of being in
poverty and a substantially lower probability of being employed. But the March CPS also has its weaknesses. Its work limitation
measure of disability only captures a portion of the broader population with
disabilities that has been captured with other data sets using a wider range of
questions related to the ICF conceptualization of disability. And the March CPS
work limitation-based employment rates are likely to understate the employment
rate of this larger population since it is likely that those who, controlling
for the severity of the disability, report a work limitation are more likely
not to be working (as shown in Table 12). However, while work limitation questions are limited in their
ability to measure the level of disability, they are useful for looking at
trends over time and across states. Evidence from the CPS, NHIS, and ACS,
suggests that measurement error introduced by the narrowness of work limitation
questions relative to the broader ICF concept of disability does not influence
comparisons of outcomes over time and across states—in other words, the
measurement error does not vary over time and across state. This plays into
the tremendous advantage of the March CPS—its consistent collection of work
limitation and outcomes data since 1980—something that can’t be matched by the
ACS, SIPP, and NHIS. Ultimately, the choice of a data source depends upon the
specific needs of the user. The March CPS provides a valuable source, and in
some cases the only source, to understand the effect of disability over time.
However, it also has limitations related to the breadth of questions used to
identify disability. For estimates of numbers of persons with disabilities
that do not require re-interviews of sample members or a historical
perspective, users are encouraged to investigate other data sources described
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Table of Contents
Figure 3. Disability Prevalence for Working-Age (Ages 21-58) Men in the Cross-sectional March CPS Data and Matched CPS Data
|
Year |
Percent with One-Period Work Limitation |
Percent with Two-Period Work Limitation |
|
1980 |
6.69% |
|
|
1981 |
6.53% |
4.00% |
|
1982 |
6.33% |
4.03% |
|
1983 |
6.44% |
3.83% |
|
1984 |
6.90% |
3.83% |
|
1985 |
6.83% |
|
|
1986 |
6.91% |
4.28% |
|
1987 |
6.57% |
3.88% |
|
1988 |
6.49% |
3.90% |
|
1989 |
6.74% |
3.85% |
|
1990 |
6.71% |
4.26% |
|
1991 |
6.97% |
3.92% |
|
1992 |
7.44% |
4.70% |
|
1993 |
7.73% |
4.88% |
|
1994 |
7.48% |
4.50% |
|
1995 |
7.14% |
|
|
1996 |
7.26% |
4.32% |
|
1997 |
6.90% |
4.98% |
|
1998 |
7.12% |
4.58% |
|
1999 |
7.10% |
4.84% |
|
2000 |
6.83% |
4.60% |
|
2001 |
7.08% |
5.16% |
|
2002 |
6.70% |
4.57% |
|
2003 |
7.46% |
5.18% |
|
2004 |
7.45% |
5.34% |
Source: Authors' calculations using the Current Population Survey, 1981-2005.
Figure 4. Trends in the Ratio of Poverty Rates of People With and Without Work Limitations using Cross-Sectional and Matched CPS Data, 1980-2004
|
Year |
One-Period Sample Ratio |
Two-Period Sample Ratio |
|
1980 |
3.18 |
|
|
1981 |
3.09 |
4.11 |
|
1982 |
2.75 |
3.11 |
|
1983 |
2.83 |
3.11 |
|
1984 |
2.98 |
3.18 |
|
1985 |
3.02 |
|
|
1986 |
3.12 |
3.63 |
|
1987 |
3.33 |
4.33 |
|
1988 |
3.31 |
3.74 |
|
1989 |
3.48 |
4.66 |
|
1990 |
3.49 |
4.34 |
|
1991 |
3.17 |
4.19 |
|
1992 |
3.23 |
3.93 |
|
1993 |
3.33 |
4.15 |
|
1994 |
3.37 |
4.25 |
|
1995 |
3.29 |
|
|
1996 |
3.49 |
4.51 |
|
1997 |
3.56 |
4.72 |
|
1998 |
3.80 |
4.94 |
|
1999 |
3.85 |
4.54 |
|
2000 |
4.13 |
5.28 |
|
2001 |
3.78 |
4.53 |
|
2002 |
3.77 |
4.94 |
|
2003 |
3.60 |
4.50 |
|
2004 |
3.40 |
4.20 |
Source: Author’s calculations based on the March CPS (1981-2005).
Figure 5. Trends in the Relative Employment of Working-Age (21-58) Men in the March CPS and NHIS Data, using Alternative Definitions of Disability
|
Year |
CPS One-Period Work Limitation |
CPS Two-Period Work Limitation |
NHIS Work Limitation |
NHIS Impairment |
|
1980 |
39.7 |
|
|
|
|
1981 |
40.6 |
24.1 |
|
|
|
1982 |
38.9 |
20.6 |
|
|
|
1983 |
39.1 |
19.8 |
59.1 |
94.4 |
|
1984 |
39.6 |
23.0 |
60.7 |
90.9 |
|
1985 |
40.2 |
|
57.5 |
92.7 |
|
1986 |
39.5 |
26.5 |
60.8 |
90.4 |
|
1987 |
40.1 |
23.4 |
57.3 |
94.1 |
|
1988 |
39.8 |
23.3 |
59.2 |
94.1 |
|
1989 |
41.3 |
22.9 |
59.5 |
94.3 |
|
1990 |
38.8 |
22.1 |
57.2 |
95.0 |
|
1991 |
38.9 |
20.5 |
55.2 |
92.3 |
|
1992 |
38.9 |
24.7 |
52.6 |
93.5 |
|
1993 |
35.6 |
22.0 |
55.1 |
95.0 |
|
1994 |
36.7 |
20.5 |
54.3 |
92.4 |
|
1995 |
34.4 |
|
51.4 |
88.4 |
|
1996 |
35.9 |
20.5 |
49.6 |
88.6 |
|
1997 |
32.6 |
19.1 |
|
|
|
1998 |
32.0 |
17.0 |
|
|
|
1999 |
33.5 |
18.3 |
|
|
|
2000 |
31.5 |
15.7 |
|
|
|
2001 |
30.8 |
17.4 |
|
|
|
2002 |
28.8 |
16.0 |
|
|
Source: Authors' calculations using the Current Population Survey, 1981-2003, and National Health Interview Survey, 1983-1996.
Table 1a. Disability Definitions from the 2002 CPS
|
ICF Category |
Variable |
Question |
Universe |
|
Participation Restriction |
Work Limitation |
(Do you/Does anyone in this household) have a health problem or disability which prevents (you/them) from working or which limits the kind or amount of work (you/they) can do? If yes to ..., who is that? (Anyone else?) |
15 to 80 |
|
Matched Work Limitation |
For a portion of the CPS sample, information is available from the previous March. As a result, persons reporting work limitation in the current and previous March can be identified. |
16 to 80 |
Source: Author's adaptation from CPS website http://www.bls.census.gov/cps/bqestair.htm.
Table 1b. Demographic Definitions from the 2004 March CPS
|
Variable |
Question/Recode |
Universe |
|
Gender |
Enter appropriate sex. |
All Ages |
|
Age |
What is (name's/your) date of birth? [Probe] As of last week, that would make (name/you) ((age/approximately age/less than 1/over 98) years/year) old. Is that correct? [Probe] Even though you don't know (name's/your) exact birth date, what is your best guess as to how old (you/he/she) (were/was) on (your/his/her) last birthday? |
All Ages |
|
Race |
>RACE-scrn< What is (name's/your) race? [Probe] (Are/Is) you/he/she) White, Black, American Indian, Aleut or Eskimo, Asian or Pacific Islander or something else? |
All Ages |
|
Ethnicity |
What is (name's/your)
origin or descent? [Show flashcard.] |
All Ages |
|
Ethnicity - Hispanic |
Recoded to 1 if Mexican American, Chicano, Mexican, Puerto Rican, Cuban, Central/South American, Other Hispanic. |
All Ages |
|
Education |
What is the highest level of school [person] has completed or the highest degree [person] has received? |
All Ages |
|
Education - Less than High School |
If response indicates less than 1st grade, 1st, 2nd, 3rd or 4th grade, 5th or 6th grade, 7th or 8th grade, 9th grade, 10th grade, 11th grade, 12th grade or no diploma. |
All Ages |
|
Education - High School |
If response indicates high school graduate (high school diploma or equivalent). |
All Ages |
|
Education - Some College |
If response indicates some college but no degree, associate's degree in college-occupational/vocational, or associate's degree in college-academic. |
All Ages |
|
Education - Bachelor's or More |
If response indicates one of the following: bachelor's degree (e.g., BA, BS, AB), master's degree (e.g., MA, MS, MEng, MEd, MSW, MBA), professional school degree (e.g.: MD, DDS, DVM, LLB, JD), or doctorate degree (e.g., PhD, EdD). |
All Ages |
Source: Author's adaptation from CPS website http://www.bls.census.gov/cps/bqestair.htm
Table 1c. Employment Definitions from the 2004 March CPS
|
Variable |
Question(s)/Recode |
Universe |
|
Emloyment Status Questions - Current Employment |
Last week, did [person] do any work for either pay or profit? |
All Persons |
|
Emloyment Status Questions - Weeks Worked |
During [the previous calendar year] in how many weeks did [person] work even for a few hours? Include paid vacation and sick leave as work. |
Ages 15 and older |
|
Emloyment Status Questions - Hours Work per Week |
In the weeks that [person] worked [the previous calendar year], how many hours did [person] usually work per week? |
Ages 15 and older |
|
Employment Variables - Employed in Reference Period |
The person is classified as employed if he or she, in week prior to survey, did any work for either pay or profit? |
All Persons |
|
Employment Variables - Employed Sometime in Previous Year |
At least 52 hours of work during the previous calendar year. Determined by multiplying usual hours per week by the number of weeks worked in past 12 months. |
Ages 15 and older |
|
Employment Variables - Employed Full-time Year Round |
At least 50 weeks during the previous calendar year and at least 35 hours per week. Determined by condition that weeks worked is greater than or equal to 50 and usual hours per week is greater than or equal to 35 hours. |
Ages 15 and older |
Source: Author's adaptation from CPS website http://www.bls.census.gov/cps/bqestair.htm.
Table 1d. Economic Well-Being Measures from the 2004 March CPS
|
Variable |
Question/Recode |
Universe |
|
Income |
The CPS collects data on 23 sources of income for each person: (1) labor earnings, (2) self-employment income (3) farm income, (4) public assistance and welfare, (5) unemployment compensation, (6) worker’s compensation, (7) veteran’s benefits, (8) Supplemental Security Income program, (9) Social Security Old Age, Survivors and Disability program, (10) educational assistance, (11) dividends, (12) interest income, (13) rental income, (14) alimony, (15) child support, (16,17) two sources of private retirement income, (18,19) two sources of private disability income, (20,21) two sources of private survivor’s income, (22) financial assistance from outside the household, and (23) any other income. Capital gains or capital losses, taxes and the value noncash benefits (such as food stamps and housing subsidies) are not considered in this measure of income. If a person lives with a family, add up the incomeof all family members. (Non-relatives, such as housemates, do not count.) |
Ages 15 and older |
|
Family Poverty |
The Census Bureau calculates the poverty rate based on family income rather than household income. There can be more than one family in a household. The poverty rate is derived from family income and family composition (regarding size, number of children and number of eldery family members), along with standard poverty thresholds, to construct a poverty measure. See the Census Bureau website http://www.census.gov/hhes/poverty/povdef.html for details. |
All ages except unrelated Household members below the age of 15. |
|
Household Size |
Author's calculations using the household sequence number. |
All Ages |
|
Household Income |
The sum of income for each household member age 15 and older in the household unit. |
All Ages |
|
Household Size Adjusted Income |
Household income divided by the square root of household size. See Citro and Michael (1995) page 176 for further information. |
All Ages |
Source: Author's adaptation from CPS website http://www.bls.census.gov/cps/bqestair.htm.
Table 2. Population and Prevalence Estimates by Work Limitation Status
|
Category/Statistic |
Cross-Sectional Sample - No Work Limitation |
Cross-Sectional Sample - Work Limitation |
Matched Sample - No Work Limitation in Either March |
Matched Sample - Work Limitation in Both Marches |
Matched Sample - Work Limitation in Second March Only |
Matched Sample - Work Limitation in First March Only |
|
All, Age 16-80a - Population Estimate |
197,926,055 |
21,012,701 |
190,760,111 |
12,580,229 |
8,339,394 |
7,056,858 |
|
All, Age 16-80a - Prevalence Rate |
90.4 |
9.6 |
87.2 |
5.8 |
3.8 |
3.2 |
|
All, Age 16-80a - Sample Size |
152,968 |
152,968 |
40,300 |
40,300 |
40,300 |
40,300 |
|
Ages 16 to 17a - Population Estimate |
8,551,550 |
165,948 |
8,509,027 |
41,453 |
99,156 |
37,294 |
|
Ages 16 to 17a - Prevalence Rate |
98.1 |
1.9 |
98.0 |
0.5 |
1.1 |
0.4 |
|
Ages 16 to 17a - Sample Size |
7,607 |
7,607 |
1,817 |
1,817 |
1,817 |
1,817 |
|
Ages 18 to 24 - Population Estimate |
26,803,529 |
816,662 |
26,402,150 |
424,216 |
367,936 |
351,410 |
|
Ages 18 to 24 - Prevalence Rate |
97.0 |
3.0 |
95.8 |
1.5 |
1.3 |
1.3 |
|
Ages 18 to 24 - Sample Size |
18,438 |
18,438 |
3,782 |
3,782 |
3,782 |
3,782 |
|
Ages 25 to 61 - Population Estimate |
132,649,606 |
12,102,093 |
129,030,935 |
7,683,107 |
4,393,052 |
3,617,462 |
|
Ages 25 to 61 - Prevalence Rate |
91.6 |
8.4 |
89.2 |
5.3 |
3.0 |
2.5 |
|
Ages 25 to 61 - Sample Size |
104,432 |
104,432 |
28,425 |
28,425 |
28,425 |
28,425 |
|
Ages 62 to 64 - Population Estimate |
5,482,126 |
1,278,528 |
5,110,982 |
823,435 |
450,606 |
353,229 |
|
Ages 62 to 64 - Prevalence Rate |
81.1 |
18.9 |
75.9 |
12.2 |
6.7 |
5.2 |
|
Ages 62 to 64 - Sample Size |
4,201 |
4,201 |
1,545 |
1,545 |
1,545 |
1,545 |
|
Ages 65 to 80a - Population Estimate |
24,439,244 |
6,649,469 |
21,707,018 |
3,608,018 |
3,028,645 |
2,697,463 |
|
Ages 65 to 80a - Prevalence Rate |
78.6 |
21.4 |
69.9 |
11.6 |
9.8 |
8.7 |
|
Ages 65 to 80a - Sample Size |
18,290 |
18,290 |
4,731 |
4,731 |
4,731 |
4,731 |
Source: Author's calculations using the March 2003, 2004 Current Population Survey, Annual Social and Economic Supplement.
aAge range differs from other User Guides.
Table 3. Demographic Characteristics by Work Limitation Status
|
Category/Statistic |
Cross-Sectional Sample - No Work Limitation |
Cross-Sectional Sample - Work Limitation |
Matched Sample - No Work Limitation in Either March |
Matched Sample - Work Limitation in Both Marches |
Matched Sample - Work Limitation in Second March Only |
Matched Sample - Work Limitation in First March Only |
|
Age - % 16 to 24a |
17.9 |
4.7 |
18.3 |
3.7 |
5.6 |
5.5 |
|
Age - % 25 to 34 |
18.8 |
7.9 |
15.3 |
5.0 |
6.4 |
7.4 |
|
Age - % 35 to 44 |
20.4 |
13.5 |
19.0 |
12.0 |
11.8 |
12.2 |
|
Age - % 45 to 54 |
18.5 |
20.5 |
21.3 |
24.4 |
18.0 |
17.0 |
|
Age - % 55 to 64 |
12.0 |
21.8 |
14.8 |
26.2 |
21.8 |
19.6 |
|
Age - % 65 to 74 |
7.5 |
16.4 |
8.2 |
19.7 |
21.0 |
24.8 |
|
Age - % 75 to 80a |
4.9 |
15.3 |
3.2 |
9.0 |
15.3 |
13.5 |
|
Age - % 85 or older |
NA |
NA |
NA |
NA |
NA |
NA |
|
Gender - % Male |
48.5 |
47.5 |
48.6 |
48.8 |
45.7 |
46.7 |
|
Gender - % Female |
51.5 |
52.5 |
51.4 |
51.2 |
54.3 |
53.3 |
|
Race - % Asian |
4.6 |
1.8 |
4.6 |
1.3 |
2.4 |
2.4 |
|
Race - % Black |
11.1 |
17.3 |
10.9 |
19.0 |
14.6 |
16.6 |
|
Race - % Native American |
0.7 |
0.9 |
0.7 |
0.8 |
0.7 |
0.5 |
|
Race - % White |
82.1 |
78.0 |
82.2 |
76.6 |
80.9 |
78.5 |
|
Race - % Some Other Race |
0.3 |
0.3 |
0.3 |
0.3 |
0.1 |
0.1 |
|
Ethnicity - % Hispanic |
13.0 |
8.6 |
13.1 |
6.3 |
11.4 |
9.0 |
|
Education - % Less than High School |
17.5 |
30.3 |
17.0 |
32.3 |
27.2 |
25.9 |
|
Education - % High School/Equivalent |
29.9 |
36.4 |
29.1 |
35.8 |
36.9 |
37.6 |
|
Education - % Some College |
26.8 |
22.2 |
27.6 |
23.0 |
22.4 |
22.5 |
|
Education - % Bachelor's or More |
25.7 |
11.1 |
26.3 |
8.9 |
13.5 |
14.0 |
|
Total |
197,926,055 |
21,012,701 |
190,760,111 |
12,580,229 |
8,339,394 |
7,056,858 |
Source: Author's calculations using the March 2003, 2004 Current Population Survey, Annual Social and Economic Supplement.
a Age range differs from other User Guides.
NA refers to statistics that are not available in the data.
Table 4. Employment Rates, Ages 25 to 61
|
Category/Statistic |
Cross-Sectional Sample - No Work Limitation |
Cross-Sectional Sample - Work Limitation |
Matched Sample - No Work Limitation in Either March |
Matched Sample - Work Limitation in Both Marches |
Matched Sample - Work Limitation in Second March Only |
Matched Sample - Work Limitation in First March Only |
|
All - Reference Period (Prior Week) |
81.4 |
19.6 |
82.8 |
13.0 |
31.0 |
51.4 |
|
All - Sometime in Previous Year |
86.2 |
27.9 |
87.1 |
16.0 |
46.5 |
56.1 |
|
All - Full-Time in Previous Year |
65.3 |
9.4 |
67.6 |
3.5 |
19.3 |
35.8 |
|
Men - Reference Period (Prior Week) |
88.4 |
20.6 |
89.6 |
14.8 |
32.7 |
59.8 |
|
Men - Sometime in Previous Year |
93.3 |
28.8 |
94.0 |
17.5 |
51.5 |
67.0 |
|
Men - Full-Time in Previous Year |
77.4 |
11.0 |
79.5 |
4.6 |
24.0 |
47.9 |
|
Women - Reference Period (Prior Week) |
74.7 |
18.7 |
76.2 |
11.2 |
29.4 |
44.4 |
|
Women - Sometime in Previous Year |
79.3 |
27.1 |
80.3 |
14.4 |
41.9 |
46.8 |
|
Women - Full-Time in Previous Year |
53.7 |
7.9 |
56.1 |
2.4 |
15.0 |
25.7 |
|
Asian - Reference Period (Prior Week) |
82.1 |
21.4 |
83.4 |
14.9 |
32.2 |
52.7 |
|
Asian - Sometime in Previous Year |
86.6 |
30.3 |
87.5 |
18.4 |
49.1 |
57.5 |
|
Asian - Full-Time in Previous Year |
65.4 |
10.0 |
67.6 |
4.3 |
19.9 |
38.3 |
|
Black - Reference Period (Prior Week) |
76.2 |
16.6 |
77.6 |
15.1 |
27.5 |
60.4 |
|
Black - Sometime in Previous Year |
81.2 |
29.6 |
82.1 |
18.9 |
51.3 |
59.1 |
|
Black - Full-Time in Previous Year |
60.6 |
7.9 |
63.4 |
3.8 |
20.3 |
45.8 |
|
Native American - Reference Period (Prior Week) |
79.2 |
11.8 |
82.4 |
5.6 |
23.3 |
45.4 |
|
Native American - Sometime in Previous Year |
85.8 |
17.9 |
87.2 |
6.8 |
30.6 |
48.0 |
|
Native American - Full-Time in Previous Year |
66.3 |
7.2 |
70.0 |
0.8 |
17.4 |
25.2 |
|
White - Reference Period (Prior Week) |
72.2 |
11.1 |
74.6 |
10.4 |
2.4 |
37.0 |
|
White - Sometime in Previous Year |
79.0 |
24.1 |
82.1 |
12.7 |
37.1 |
42.1 |
|
White - Full-Time in Previous Year |
53.9 |
3.6 |
57.3 |
1.9 |
0.0 |
3.6 |
|
Hispanic - Reference Period (Prior Week) |
77.0 |
26.0 |
75.9 |
20.4 |
51.8 |
61.3 |
|
Hispanic - Sometime in Previous Year |
80.4 |
33.9 |
81.1 |
22.2 |
70.3 |
70.5 |
|
Hispanic - Full-Time in Previous Year |
62.8 |
13.5 |
63.9 |
8.0 |
26.9 |
44.4 |
|
Less than High School - Reference Period (Prior Week) |
69.0 |
9.1 |
70.5 |
4.0 |
20.6 |
39.4 |
|
Less than High School - Sometime in Previous Year |
76.0 |
15.8 |
76.6 |
5.6 |
29.3 |
38.7 |
|
Less than High School - Full-Time in Previous Year |
52.3 |
4.0 |
54.9 |
1.4 |
8.8 |
19.7 |
|
High School - Reference Period (Prior Week) |
79.6 |
18.4 |
81.2 |
14.1 |
29.2 |
51.5 |
|
High School - Sometime in Previous Year |
84.9 |
25.4 |
86.0 |
17.3 |
41.2 |
53.7 |
|
High School - Full-Time in Previous Year |
64.6 |
8.0 |
66.8 |
2.8 |
18.6 |
36.5 |
|
More Than High School - Reference Period (Prior Week) |
84.7 |
27.8 |
85.6 |
17.9 |
38.4 |
57.1 |
|
More Than High School - Sometime in Previous Year |
88.7 |
38.4 |
89.3 |
21.6 |
61.1 |
66.5 |
|
More Than High School - Full-Time in Previous Year |
68.0 |
14.3 |
70.1 |
5.8 |
25.8 |
43.0 |
Source: Author's calculations using the March 2003, 2004 Current Population Survey, Annual Social and Economic Supplement.
Table 5. Economic Well Being Measures, Ages 25 to 61
|
Category/Statistic |
Cross-Sectional Sample - No Work Limitation |
Cross-Sectional Sample - Work Limitation |
Matched Sample - No Work Limitation in Either March |
Matched Sample - Work Limitation in Both Marches |
Matched Sample - Work Limitation in Second March Only |
Matched Sample - Work Limitation in First March Only |
|
All - % Below Poverty Line |
8.0 |
28.8 |
6.3 |
30.2 |
23.3 |
20.5 |
|
All - Median Household Income |
61,999 |
27,955 |
65,100 |
25,048 |
35,770 |
36,000 |
|
All - Median HH Size Adjusted Income |
36,770 |
17,967 |
39,500 |
16,085 |
23,560 |
23,170 |
|
Men - % Below Poverty Line |
6.7 |
26.7 |
5.3 |
27.5 |
21.7 |
18.0 |
|
Men - Median Household Income |
64,000 |
28,594 |
66,958 |
25,000 |
36,000 |
41,250 |
|
Men - Median HH Size Adjusted Income |
38,003 |
18,044 |
40,189 |
16,111 |
24,000 |
25,600 |
|
Women - % Below Poverty Line |
9.3 |
31.0 |
7.2 |
32.9 |
24.9 |
22.7 |
|
Women - Median Household Income |
60,000 |
27,364 |
64,000 |
25,201 |
35,238 |
31,948 |
|
Women - Median HH Size Adjusted Income |
35,394 |
17,845 |
38,847 |
16,041 |
23,188 |
21,213 |
|
Asian - % Below Poverty Line |
6.9 |
26.1 |
5.6 |
27.6 |
20.0 |
16.3 |
|
Asian - Median Household Income |
64,365 |
30,420 |
67,655 |
26,498 |
38,202 |
41,703 |
|
Asian - Median HH Size Adjusted Income |
38,223 |
19,549 |
41,132 |
17,680 |
25,105 |
26,870 |
|
Black - % Below Poverty Line |
16.8 |
35.9 |
14.3 |
42.7 |
30.6 |
14.9 |
|
Black - Median Household Income |
42,000 |
24,000 |
44,800 |
22,904 |
27,800 |
40,800 |
|
Black - Median HH Size Adjusted Income |
22,389 |
13,695 |
23,914 |
10,766 |
16,528 |
21,103 |
|
Native American - % Below Poverty Line |
14.5 |
38.9 |
10.8 |
38.4 |
42.0 |
33.3 |
|
Native American - Median Household Income |
44,600 |
20,000 |
48,000 |
17,687 |
16,670 |
22,477 |
|
Native American - Median HH Size Adjusted Income |
27,135 |
12,506 |
29,318 |
11,778 |
11,486 |
12,430 |
|
White - % Below Poverty Line |
17.9 |
43.4 |
11.2 |
41.8 |
54.0 |
61.9 |
|
White - Median Household Income |
47,932 |
20,582 |
48,462 |
19,292 |
28,531 |
6,300 |
|
White - Median HH Size Adjusted Income |
25,101 |
12,883 |
24,328 |
11,167 |
16,472 |
6,300 |
|
Hispanic - % Below Poverty Line |
9.4 |
30.1 |
6.9 |
7.9 |
9.4 |
33.8 |
|
Hispanic - Median Household Income |
71,000 |
29,132 |
78,058 |
44,720 |
42,148 |
50,058 |
|
Hispanic - Median HH Size Adjusted Income |
40,250 |
17,680 |
43,132 |
25,328 |
24,334 |
26,586 |
|
Less than High School - % Below Poverty Line |
22.8 |
42.2 |
20.8 |
42.5 |
38.9 |
38.3 |
|
Less than High School - Median Household Income |
34,000 |
19,912 |
34,120 |
17,324 |
22,374 |
20,504 |
|
Less than High School - Median HH Size Adjusted Income |
18,200 |
11,880 |
18,200 |
11,304 |
12,660 |
12,500 |
|
High School - % Below Poverty Line |
9.4 |
27.7 |
6.9 |
27.8 |
23.4 |
19.5 |
|
High School - Median Household Income |
52,000 |
28,718 |
54,080 |
25,714 |
36,734 |
32,430 |
|
High School - Median HH Size Adjusted Income |
30,518 |
18,055 |
32,625 |
16,100 |
24,533 |
23,170 |
|
More than High School - % Below Poverty Line |
4.6 |
21.2 |
3.6 |
24.4 |
14.7 |
13.0 |
|
More than High School - Median Household Income |
74,500 |
36,262 |
78,058 |
28,746 |
44,190 |
50,577 |
|
More than High School - Median HH Size Adjusted Income |
44,725 |
24,092 |
47,947 |
21,319 |
32,000 |
31,990 |
Source: Author's calculations using the March 2003, 2004 Current Population Survey, Annual Social and Economic Supplement.
Table 6. Estimated Population of Persons with Disabilities, by Data Source
|
Category/Statistic |
No Disability |
Disability |
Participation Restriction - Employment |
Participation Restriction - IADL |
Activity Limitation - Self-Care |
Impairment - Mental |
Impairment - Physical |
Impairment - Sensory |
|
Ages 18 to 24, 2004 March CPS |
26,803,529 |
816,662 |
816,662 |
NA |
NA |
NA |
NA |
NA |
|
Ages 18 to 24, 2004 March CPS - Census 2000 |
24,790,000 |
1,442,000 |
NA |
NA |
207,000 |
883,000 |
456,000 |
326,000 |
|
Ages 18 to 24, 2004 March CPS - ACS 2003 |
24,194,401 |
1,667,355 |
714,229 |
399,423 |
187,904 |
953,448 |
535,666 |
356,820 |
|
Ages 18 to 24, 2004 March CPS - NHIS, 2002 |
25,225,000 |
2,126,000 |
927,000 |
228,000 |
147,000 |
786,000 |
859,000 |
78,000 |
|
Ages 18 to 24, 2004 March CPS - PSID, 2003 |
7,660,000 |
2,152,000 |
1,131,000 |
416,000 |
157,000 |
1,477,000 |
NA |
NA |
|
Ages 18 to 24, 2004 March CPS - SIPP, 2002 |
24,820,000 |
2,426,337 |
1,209,000 |
366,000 |
146,000 |
1,076,000 |
982,000 |
533,000 |
|
Ages 25 to 61, 2004 March CPS |
132,649,606 |
12,102,093 |
12,102,093 |
NA |
NA |
NA |
NA |
NA |
|
Ages 25 to 61, 2004 March CPS - Census 2000 |
124,493,000 |
14,005,000 |
NA |
NA |
2,627,000 |
5,218,000 |
9,447,000 |
3,346,000 |
|
Ages 25 to 61, 2004 March CPS - ACS 2003 |
126,649,510 |
17,146,845 |
9,854,223 |
4,227,427 |
2,925,715 |
5,745,569 |
10,819,521 |
3,944,388 |
|
Ages 25 to 61, 2004 March CPS - NHIS, 2002 |
115,934,000 |
23,192,000 |
13,725,000 |
3,169,000 |
1,350,000 |
4,627,000 |
14,545,000 |
2,730,000 |
|
Ages 25 to 61, 2004 March CPS - PSID, 2003 |
112,556,000 |
30,656,000 |
19,300,000 |
12,375,000 |
9,395,000 |
13,896,000 |
NA |
NA |
|
Ages 25 to 61, 2004 March CPS - SIPP, 2002 |
115,900,000 |
26,620,000 |
14,420,000 |
4,931,000 |
3,362,000 |
4,394,000 |
18,790,000 |
6,490,000 |
|
Ages 62 to 64, 2004 March CPS |
5,482,126 |
1,278,528 |
1,278,528 |
NA |
NA |
NA |
NA |
NA |
|
Ages 62 to 64, 2004 March CPS - Census 2000 |
4,806,000 |
1,413,000 |
NA |
NA |
257,000 |
348,000 |
1,134,000 |
373,000 |
|
Ages 62 to 64, 2004 March CPS - ACS 2003 |
4,941,802 |
1,795,533 |
1,111,762 |
404,875 |
293,507 |
393,782 |
1,292,381 |
455,364 |
|
Ages 62 to 64, 2004 March CPS - NHIS, 2002 |
4,239,000 |
2,045,000 |
1,281,000 |
300,000 |
127,000 |
144,000 |
1,466,000 |
310,000 |
|
Ages 62 to 64, 2004 March CPS - PSID, 2003 |
3,677,000 |
2,276,000 |
1,873,000 |
1,536,000 |
1,252,000 |
472,000 |
NA |
NA |
|
Ages 62 to 64, 2004 March CPS - SIPP, 2002 |
3,958,000 |
2,581,000 |
1,496,000 |
567,000 |
376,000 |
252,000 |
2,165,000 |
672,000 |
|
Ages 18 to 64, 2004 March CPS - |
164,935,261 |
14,197,283 |
14,197,283 |
NA |
NA |
NA |
NA |
NA |
|
Ages 18 to 64, 2004 March CPS - Census 2000 |
154,091,000 |
16,861,000 |
NA |
NA |
3,093,000 |
6,450,000 |
11,039,000 |
4,046,000 |
|
Ages 18 to 64, 2004 March CPS - ACS 2003 |
155,785,713 |
20,609,733 |
11,680,214 |
5,031,725 |
3,407,126 |
7,092,799 |
12,647,568 |
4,756,572 |
|
Ages 18 to 64, 2004 March CPS - NHIS, 2002 |
145,399,000 |
27,363,000 |
15,934,000 |
3,697,000 |
1,626,000 |
5,558,000 |
16,871,000 |
3,119,000 |
|
Ages 18 to 64, 2004 March CPS - PSID, 2003 |
123,903,000 |
35,084,000 |
22,304,000 |
14,327,000 |
10,804,000 |
15,845,000 |
NA |
NA |
|
Ages 18 to 64, 2004 March CPS - SIPP, 2002 |
144,678,000 |
31,627,000 |
17,126,000 |
5,864,000 |
3,885,000 |
5,723,000 |
21,938,000 |
7,695,000 |
Source: Calculations from the various Cornell StatsRRTC User Guides.
Note: (1) For the Census 2000, the disability column is represented by those persons with sensory, physical, mental, and/or self-care disabilities.
Note: (2) Instrumental Activities of Daily Living (IADLs) include a broader set of participation restrictions than the “go-outside-home” definition in the American Community Survey. It also includes participation restrictions that affect the ability to: manage money and keep track of bills, prepare meals, and do work around the house.
Note: (3) The March 2004 Current Population Supplement collects 2003 calendar year information on poverty and household income. Population and prevalence estimates are collected in March 2004.
Note: (4) The PSID only asks this question for the Head and Wife of the Household. Children of the Head and Wife are not asked this question, and the PSID assigns missing values to children for this question.
Note: Standard errors for Census 2000 estimates are in Appendix Table 1. Standard errors for other datasets available in respective user guides.
Table 7. Estimated Disability Prevalence Rates, By Data Source
|
Category/Statistic |
No Disability |
Disability |
Participation Restriction - Employment |
Participation Restriction - IADL |
Activity Limitation - Self-Care |
Impairment - Mental |
Impairment - Physical |
|
Ages 18 to 24 - 2004 March CPS |
3.0 |
3.0 |
NA |
NA |
NA |
NA |
NA |
|
Ages 18 to 24 - Census 2000 |
5.5 |
NA |
NA |
0.8 |
3.4 |
1.7 |
1.2 |
|
Ages 18 to 24 - ACS 2003 |
6.5 |
2.8 |
1.5 |
0.7 |
3.7 |
2.1 |
1.4 |
|
Ages 18 to 24 - NHIS, 2002 |
7.8 |
3.4 |
0.8 |
0.5 |
2.9 |
3.1 |
0.3 |
|
Ages 18 to 24 - PSID, 2003 |
21.7 |
11.4 |
4.2 |
1.6 |
14.9 |
NA |
NA |
|
Ages 18 to 24 - SIPP, 2002 |
8.9 |
4.4 |
1.3 |
0.5 |
4.0 |
3.6 |
2.0 |
|
Ages 25 to 61 - 2004 March CPS |
8.4 |
8.4 |
NA |
NA |
NA |
NA |
NA |
|
Ages 25 to 61 - Census 2000 |
10.1 |
NA |
NA |
1.9 |
3.8 |
6.8 |
2.4 |
|
Ages 25 to 61 - ACS 2003 |
11.9 |
6.9 |
2.9 |
2.0 |
4.0 |
7.5 |
2.7 |
|
Ages 25 to 61 - NHIS, 2002 |
16.7 |
9.9 |
2.3 |
1.0 |
3.3 |
10.5 |
2.0 |
|
Ages 25 to 61 - PSID, 2003 |
21.4 |
13.5 |
8.6 |
6.6 |
9.7 |
NA |
NA |
|
Ages 25 to 61 - SIPP, 2002 |
18.7 |
10.1 |
3.5 |
2.4 |
3.1 |
13.2 |
4.6 |
|
Ages 62 to 64 - 2004 March CPS |
18.9 |
18.9 |
NA |
NA |
NA |
NA |
NA |
|
Ages 62 to 64 - Census 2000 |
26.7 |
16.5 |
6.0 |
4.4 |
5.8 |
19.2 |
6.8 |
|
Ages 62 to 64 - ACS 2003 |
22.7 |
NA |
NA |
4.1 |
5.6 |
18.2 |
6.0 |
|
Ages 62 to 64 - NHIS, 2002 |
32.5 |
20.4 |
4.8 |
2.0 |
2.3 |
23.3 |
4.9 |
|
Ages 62 to 64 - PSID, 2003 |
38.2 |
31.5 |
25.8 |
21.0 |
7.9 |
NA |
NA |
|
Ages 62 to 64 - SIPP, 2002 |
39.5 |
22.9 |
8.7 |
5.8 |
3.9 |
33.1 |
10.3 |
|
Ages 18 to 64 - 2004 March CPS - |
7.9 |
7.9 |
NA |
NA |
NA |
NA |
NA |
|
Ages 18 to 64 - Census 2000 |
9.9 |
NA |
NA |
1.8 |
3.8 |
6.5 |
2.4 |
|
Ages 18 to 64 - ACS 2003 |
11.7 |
6.6 |
2.9 |
1.9 |
4.0 |
7.2 |
2.7 |
|
Ages 18 to 64 - NHIS, 2002 |
15.8 |
9.2 |
2.1 |
0.9 |
3.2 |
9.8 |
1.8 |
|
Ages 18 to 64 - PSID, 2003 |
22.1 |
14.0 |
9.0 |
6.8 |
10.0 |
NA |
NA |
|
Ages 18 to 64 - SIPP, 2002 |
17.9 |
9.7 |
3.3 |
2.2 |
3.2 |
12.4 |
4.4 |
Source: Calculations from the various Cornell StatsRRTC User Guides.
Note: (2) Instrumental Activities of Daily Living (IADLs) include a broader set of participation restrictions than the “go-outside-home” definition in the American Community Survey. It also includes participation restrictions that affect the ability to: manage money and keep track of bills, prepare meals, and do work around the house.
Note: (3) The March 2004 Current Population Supplement collects 2003 calendar year information on poverty and household income. Population and prevalence estimates are collected in March 2004.
Note: (4) The PSID only asks this question for the Head and Wife of the Household. Children of the Head and Wife are not asked this question, and the PSID assigns missing values to children for this question.
Note: Standard errors for Census 2000 estimates are in Appendix Table 1. Standard errors for other datasets available in respective user guides.
Table 8. Estimated Employment Rates for Persons With Disabilities Ages 25 to 61, By Data Source
|
Category/Statistic |
No Disability |
Disability |
Participation Restriction - Employment |
Participation Restriction - IADL |
Activity Limitation - Self-Care |
Impairment - Mental |
Impairment - Physical |
Impairment - Sensory |
|
Reference Week, Ages 25 to 61 - 2004 March CPS |
81.4 |
19.6 |
19.6 |
NA |
NA |
NA |
NA |
NA |
|
Reference Week, Ages 25 to 61 - Census 2000 |
78.8 |
41.8 |
NA |
NA |
21.7 |
30.2 |
35.6 |
52.1 |
|
Reference Week, Ages 25 to 61 - ACS, 2003 |
79.5 |
39.3 |
18.9 |
17.9 |
18.3 |
28.2 |
33.8 |
49.9 |
|
Reference Week, Ages 25 to 61 - NHIS, 2002 |
83.3 |
47.3 |
29.8 |
18.3 |
14.1 |
37.1 |
43.8 |
58.6 |
|
Reference Week, Ages 25 to 61 - PSID, 2003 |
85.4 |
62.5 |
61.7 |
45.1 |
47.9 |
51.9 |
NA |
NA |
|
Reference Week, Ages 25 to 61 - SIPP, 2002 |
82.4 |
48.9 |
27.7 |
20.3 |
22.8 |
37 |
46.4 |
53.5 |
|
Sometime Previous Year, Ages 25 to 61 - 2004 March CPS |
86.2 |
27.9 |
27.9 |
NA |
NA |
NA |
NA |
NA |
|
Sometime Previous Year, Ages 25 to 61 - Census 2000 |
86.3 |
51.9 |
NA |
NA |
31.9 |
40.4 |
45.4 |
61.1 |
|
Sometime Previous Year, Ages 25 to 61 - ACS, 2003 |
87.1 |
48.9 |
28.3 |
25.8 |
26.2 |
37.2 |
42.8 |
58.1 |
|
Sometime Previous Year, Ages 25 to 61 - NHIS, 2002 |
88.3 |
57.9 |
42 |
25.7 |
19.9 |
51.8 |
53.8 |
66.6 |
|
Sometime Previous Year, Ages 25 to 61 - PSID, 2003 |
91.5 |
73.8 |
72.2 |
58.3 |
58.8 |
64.3 |
NA |
NA |
|
Sometime Previous Year, Ages 25 to 61 - SIPP, 2002 |
90.6 |
61.1 |
41 |
34.1 |
38.8 |
46.3 |
59 |
63.7 |
|
Full-Year Full-Time, Ages 25 to 61 - 2004 March CPS |
65.3 |
9.4 |
9.4 |
NA |
NA |
NA |
NA |
NA |
|
Full-Year Full-Time, Ages 25 to 61 - Census 2000 |
58.8 |
27.1 |
NA |
NA |
13.1 |
16.7 |
22.6 |
37.4 |
|
Full-Year Full-Time, Ages 25 to 61 - ACS, 2003 |
59.6 |
24.5 |
9.1 |
9 |
9.4 |
15 |
20.3 |
34.5 |
|
Full-Year Full-Time, Ages 25 to 61 - NHIS, 2002 |
62.8 |
29.8 |
16.3 |
9.3 |
6.2 |
21.3 |
27.2 |
43.4 |
|
Full-Year Full-Time, Ages 25 to 61 - PSID, 2003 |
67.8 |
43.4 |
41.7 |
30.0 |
32.2 |
34.3 |
NA |
NA |
|
Full-Year Full-Time, Ages 25 to 61 - SIPP, 2002 |
58.1 |
31.2 |
15.3 |
12 |
15 |
20.3 |
29.6 |
35.6 |
Source: Calculations from the various Cornell StatsRRTC User Guides.
Note: (1) For the Census 2000, the disability column is represented by those persons with sensory, physical, mental, and/or self-care disabilities.
Note: (2) Instrumental Activities of Daily Living (IADLs) include a broader set of participation restrictions than the “go-outside-home” definition in the American Community Survey. It also includes participation restrictions that affect the ability to: manage money and keep track of bills, prepare meals, and do work around the house.
Note: (3) The March 2004 Current Population Supplement collects 2003 calendar year information on poverty and household income. Population and prevalence estimates are collected in March 2004.
Note: (4) The PSID only asks this question for the Head and Wife of the Household. Children of the Head and Wife are not asked this question, and the PSID assigns missing values to children for this question.
Note: Standard errors for Census 2000 estimates are in Appendix Table 3. Standard errors for other datasets available in respective user guides.
Table 9. Economic Well Being Estimates for Persons with Disabilities Ages 25 to 61, By Data Source
|
Category/Statistic |
No Disability |
Disability |
Participation Restriction - Employment |
Participation Restriction - IADL |
Activity Limitation - Self-Care |
Impairment - Mental |
Impairment - Physical |
Impairment - Sensory |
|
Poverty Rates, Ages 25 to 61 - 2004 March CPS |
8.0 |
28.8 |
28.8 |
NA |
NA |
NA |
NA |
NA |
|
Poverty Rates, Ages 25 to 61 - Census 2000 |
7.9 |
23.2 |
NA |
NA |
30.0 |
30.6 |
24.2 |
20.1 |
|
Poverty Rates, Ages 25 to 61 - ACS, 2003 |
7.7 |
23.7 |
29.6 |
29.7 |
28.9 |
30.8 |
25.0 |
20.8 |
|
Poverty Rates, Ages 25 to 61 - NHIS, 2002 |
7.5 |
21.2 |
26.5 |
32.3 |
30.1 |
29.8 |
22.1 |
20.7 |
|
Poverty Rates, Ages 25 to 61 - PSID, 2003 |
4.9 |
13.2 |
14.4 |
18.6 |
18.0 |
16.6 |
NA |
NA |
|
Poverty Rates, Ages 25 to 61 - SIPP, 2002 |
6.5 |
18.8 |
26.0 |
26.3 |
25.1 |
24.9 |
19.1 |
17.6 |
|
Median Household Income, Ages 25 to 61 - 2004 March CPS |
$61,999 |
$27,955 |
$27,955 |
NA |
NA |
NA |
NA |
NA |
|
Median Household Income, Ages 25 to 61 - Census 2000 |
$56,860 |
$33,600 |
NA |
NA |
$27,200 |
$26,170 |
$32,000 |
$37,400 |
|
Median Household Income, Ages 25 to 61 - ACS, 2003 |
$60,000 |
$34,600 |
$28,000 |
$28,600 |
$28,000 |
$27,400 |
$32,100 |
$38,000 |
|
Median Household Income, Ages 25 to 61 - NHIS, 2002 |
$55,000 - $64,000 |
$25,000 - $34,999 |
$25,000 - $34,999 |
$20,000 - $24,999 |
$20,000 - $24,999 |
$20,000 - $24,999 |
$25,000-$34,999 |
$35,000-$44,999 |
|
Median Household Income, Ages 25 to 61 - PSID, 2003 |
$64,000 |
$40,788 |
$36,240 |
$35,192 |
$36,000 |
$37,900 |
NA |
NA |
|
Median Household Income, Ages 25 to 61 - SIPP, 2002 |
$53,313 |
$33,895 |
$25,664 |
$24,989 |
$26,735 |
$26,218 |
$33,490 |
$33,776 |
|
Median Size-Adjusted Household Income, Ages 25 to 61 - 2004 March CPS |
$36,770 |
$17,967 |
$17,967 |
NA |
NA |
NA |
NA |
NA |
|
Median Size-Adjusted Household Income, Ages 25 to 61 - Census 2000 |
$33,234 |
$20,412 |
NA |
NA |
$16,330 |
$16,000 |
$19,676 |
$22,617 |
|
Median Size-Adjusted Household Income, Ages 25 to 61 - ACS, 2003 |
$35,796 |
$21,304 |
$17,487 |
$17,615 |
$17,667 |
$17,321 |
$20,207 |
$23,415 |
|
Median Size-Adjusted Household Income, Ages 25 to 61 - NHIS, 2002 |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
|
Median Size-Adjusted Household Income, Ages 25 to 61 - PSID, 2003 |
$39,202 |
$27,365 |
$25,525 |
$23,132 |
$23,430 |
$24,447 |
NA |
NA |
|
Median Size-Adjusted Household Income, Ages 25 to 61 - SIPP, 2002 |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
Source: Calculations from the various Cornell StatsRRTC User Guides.
Note: (1) For the Census 2000, the disability column is represented by those persons with sensory, physical, mental, and/or self-care disabilities.
Note: (2) Instrumental Activities of Daily Living (IADLs) include a broader set of participation restrictions than the “go-outside-home” definition in the American Community Survey. It also includes participation restrictions that affect the ability to: manage money and keep track of bills, prepare meals, and do work around the house.
Note: (3) The March 2004 Current Population Supplement collects 2003 calendar year information on poverty and household income. Population and prevalence estimates are collected in March 2004.
Note: (4) The PSID only asks this question for the Head and Wife of the Household. Children of the Head and Wife are not asked this question, and the PSID assigns missing values to children for this question.
Table 10. Poverty Rate for Selected Economically Vulnerable Working-Aged Populations (Aged 25-61) a,b
|
Income Year |
Total Population |
Work Limitation (1) |
No work Limitation (2) |
Relative Poverty Risk (1)/(2) |
|
1979 |
8.06 |
-- |
-- |
-- |
|
1980 |
9.44 |
25.61 |
8.06 |
3.18 |
|
1981 |
10.26 |
27.22 |
8.81 |
3.09 |
|
1982 |
11.39 |
27.72 |
10.07 |
2.75 |
|
1983 |
11.49 |
28.61 |
10.10 |
2.83 |
|
1984 |
10.86 |
28.00 |
9.41 |
2.98 |
|
1985 |
10.45 |
27.33 |
9.04 |
3.02 |
|
1986 |
10.08 |
27.09 |
8.68 |
3.12 |
|
1987 |
9.60 |
27.35 |
8.22 |
3.33 |
|
1988 |
9.40 |
26.69 |
8.06 |
3.31 |
|
1989 |
9.27 |
27.26 |
7.83 |
3.48 |
|
1990 |
9.77 |
28.72 |
8.24 |
3.49 |
|
1991 |
10.35 |
28.14 |
8.88 |
3.17 |
|
1992 |
10.58 |
29.12 |
9.02 |
3.23 |
|
1993 |
11.23 |
31.28 |
9.40 |
3.33 |
|
1994 |
10.77 |
30.35 |
9.00 |
3.37 |
|
1995 |
10.20 |
28.20 |
8.57 |
3.29 |
|
1996 |
10.19 |
29.49 |
8.45 |
3.49 |
|
1997 |
9.74 |
28.78 |
8.07 |
3.56 |
|
1998 |
9.43 |
29.30 |
7.72 |
3.80 |
|
1999 |
8.66 |
27.20 |
7.06 |
3.85 |
|
2000 |
8.46 |
28.07 |
6.79 |
4.13 |
|
2001 |
8.94 |
27.51 |
7.28 |
3.78 |
|
2002 |
9.48 |
29.38 |
7.80 |
3.77 |
|
2003 |
9.76 |
28.85 |
8.02 |
3.60 |
|
2004 |
10.06 |
28.49 |
8.37 |
3.40 |
Source: Adapted from Burkhauser, Houtenville and Rovba (2006b).
a In April of survey year 1984, sample weights based on the 1970 Census were replaced with sample weights based on the 1980 Census and the sample design was changed to increase the accuracy of state estimates. In survey year 1994 there were several changes in the CPS. It moved fully to computer-assisted survey interviews. Sample weights based on the 1980 Census were replaced with sample weights based on the 1990 Census. The Monthly Basic Survey was revised, and three new disabilities questions were added. It is possible that these changes affected the measurement of the population with disabilities either through changes in the sample weights or in the way respondents answered disabilities questions.
b Persons with work limitations are defined as those who report having (or are reported by the household's respondent as having), at the time of the survey, "a health problem or disabilities which prevents them from working or which limits the kind or amount of work they can do."
Table 11. Mean Annual Weeks Worked for Working-Age (Ages 21-58) Men with and without Disabilities in the Cross-sectional and Matched CPS Data
|
Income Year |
One-Period Sample - Total One-Period Population |
One-Period Sample - One-Period Work Limitation (1) |
One-Period Sample - No One-Period Work Limitation (2) |
One-Period Sample - Ratio (1)/(2) |
Two-Period Sample - Total Two-Period Population |
Two-Period Sample - Two-Period Work Limitation (3) |
Two-Period Sample - No Two-Period Work Limitation (4) |
Two-Period Sample - Ratio (3)/(4) |
|
1980 |
43.16 |
18.24 |
44.95 |
0.41 |
-- |
-- |
-- |
-- |
|
1981 |
42.80 |
18.98 |
44.46 |
0.43 |
44.66 |
12.06 |
46.02 |
0.26 |
|
1982 |
41.40 |
16.90 |
43.06 |
0.39 |
43.06 |
8.42 |
44.52 |
0.19 |
|
1983 |
41.54 |
17.10 |
43.22 |
0.40 |
43.09 |
9.27 |
44.43 |
0.21 |
|
1984 |
42.50 |
17.48 |
44.36 |
0.39 |
44.36 |
9.34 |
45.75 |
0.20 |
|
1985 |
42.83 |
17.71 |
44.67 |
0.40 |
-- |
-- |
-- |
-- |
|
1986 |
43.09 |
17.76 |
44.97 |
0.39 |
44.69 |
11.63 |
46.17 |
0.25 |
|
1987 |
43.35 |
17.68 |
45.15 |
0.39 |
45.12 |
10.52 |
46.51 |
0.23 |
|
1988 |
43.76 |
17.54 |
45.58 |
0.38 |
45.25 |
9.66 |
46.69 |
0.21 |
|
1989 |
44.50 |
18.73 |
46.36 |
0.40 |
45.74 |
10.70 |
47.14 |
0.23 |
|
1990 |
44.00 |
17.25 |
45.93 |
0.38 |
44.91 |
9.43 |
46.49 |
0.20 |
|
1991 |
43.16 |
16.71 |
45.14 |
0.37 |
44.45 |
9.47 |
45.87 |
0.21 |
|
1992 |
42.80 |
17.29 |
44.85 |
0.39 |
43.63 |
11.42 |
45.22 |
0.25 |
|
1993 |
42.63 |
14.84 |
44.96 |
0.33 |
43.98 |
10.76 |
45.68 |
0.24 |
|
1994 |
43.23 |
15.50 |
45.47 |
0.34 |
44.01 |
7.78 |
45.72 |
0.17 |
|
1995 |
43.43 |
14.91 |
45.63 |
0.33 |
-- |
-- |
-- |
-- |
|
1996 |
43.74 |
15.73 |
45.93 |
0.34 |
44.81 |
10.81 |
46.34 |
0.23 |
|
1997 |
44.01 |
14.26 |
46.22 |
0.31 |
44.53 |
7.90 |
46.45 |
0.17 |
|
1998 |
44.38 |
14.81 |
46.65 |
0.32 |
45.43 |
8.57 |
47.21 |
0.18 |
|
1999 |
44.27 |
14.47 |
46.55 |
0.31 |
44.84 |
7.88 |
46.72 |
0.17 |
|
2000 |
44.47 |
13.43 |
46.74 |
0.29 |
45.14 |
7.19 |
46.97 |
0.15 |
|
2001 |
43.68 |
13.41 |
45.99 |
0.29 |
44.14 |
7.57 |
46.13 |
0.16 |
|
2002 |
43.08 |
12.57 |
45.27 |
0.28 |
43.66 |
6.44 |
45.44 |
0.14 |
|
2003 |
42.63 |
11.76 |
45.11 |
0.26 |
43.20 |
7.50 |
45.16 |
0.17 |
|
2004 |
42.84 |
11.61 |
45.35 |
0.26 |
43.13 |
7.58 |
45.14 |
0.17 |
Source: Adapted from Houtenville and Burkhauser (2005).
Table 12. Impairment, Work Limitations, and Employment in the NHIS, Ages 25-61
|
NHIS Category |
Total Population - Percentage |
Total Population - Employment Rate |
Pop. with Work Limitations - Percentage |
Pop. with Work Limitations - Employment Rate |
Pop. without Work Limitations - Percentage |
Pop. without Work Limitations - Employment Rate |
|
Any Impairment |
19.5 |
72.5 |
25.9 |
41.5 |
74.1 |
83.4 |
|
Blind in Both Eyes |
0.2 |
39.1 |
69.0 |
20.3 |
31.0 |
81.1 |
|
Other Visual Impairments |
1.8 |
63.0 |
36.2 |
31.6 |
63.8 |
80.9 |
|
Deaf in Both Ears |
0.4 |
68.0 |
38.0 |
40.8 |
62.0 |
84.6 |
|
Other Hearing Impairments |
7.5 |
73.6 |
23.4 |
39.6 |
76.6 |
83.9 |
|
Stammering and Stuttering |
0.4 |
65.4 |
33.4 |
23.7 |
66.6 |
86.3 |
|
Other Speech Impairments |
0.3 |
44.0 |
64.9 |
29.1 |
35.1 |
71.6 |
|
Paraplegia, Hemiplegia, Quadriplegia |
0.1 |
25.1 |
90.3 |
20.2 |
9.8 |
72.4 |
|
Paraparesis or Hemiparesis |
0.1 |
31.2 |
88.6 |
26.6 |
11.5 |
66.7 |
|
Cerebral Palsy |
0.1 |
42.4 |
74.5 |
32.4 |
25.5 |
71.7 |
|
Mental Retardation |
0.3 |
30.6 |
90.2 |
28.4 |
9.8 |
51.6 |
|
Other Impairments |
11.7 |
72.6 |
27.2 |
45.2 |
72.8 |
83.3 |
Source: Adapted from Burkhauser, Daly, Houtenville, and Nargis (2002).
Table 13. Impairment, Employment Disability, and Employment in the ACS, Ages 25-61
|
ACS Category |
Total Population - Percentage |
Total Population - Employment Rate |
Pop. with Work Limitations - Percentage |
Pop. with Work Limitations - Employment Rate |
Pop. without Work Limitations - Percentage |
Pop. without Work Limitations - Employment Rate |
|
Any of these Disabilities |
11.4 |
38.1 |
83.8 |
15.3 |
5.6 |
64.9 |
|
Sensory Disability |
2.9 |
47.4 |
15.8 |
13.2 |
1.9 |
69.7 |
|
Physical Disability |
8.1 |
32.0 |
69.4 |
14.7 |
3.2 |
61.2 |
|
Mental Disability |
4.1 |
27.1 |
39.0 |
13.0 |
1.3 |
59.5 |
|
Self-Care Disability |
2.1 |
17.3 |
26.0 |
13.2 |
0.3 |
50.3 |
Source: Authors’ calculations using the 2003 American Community Survey.
Table 14. Comparison of State Level Prevalence Estimates for Those Ages 25-61 from 2004 March CPS and 2003 ACS
|
State |
2004 March CPS - Work Limitation |
2003 ACS - Work Limitation |
2003 ACS - Overall Disability |
|
Alabama |
11.4 |
10.4 |
16.7 |
|
Alaska |
7.7 |
6.7 |
14.3 |
|
Arizona |
6.9 |
7.1 |
11.9 |
|
Arkansas |
9.8 |
11.1 |
17.2 |
|
California |
7.1 |
6.0 |
10.7 |
|
Colorado |
5.9 |
4.4 |
9.0 |
|
Connecticut |
7.3 |
5.0 |
9.2 |
|
Delaware |
7.3 |
5.9 |
11.8 |
|
Dist. of Columbia |
8.2 |
5.6 |
11.5 |
|
Florida |
7.4 |
7.0 |
11.8 |
|
Georgia |
7.6 |
7.1 |
12.0 |
|
Hawaii |
6.7 |
5.7 |
10.3 |
|
Idaho |
6.4 |
7.2 |
14.7 |
|
Illinois |
6.5 |
5.0 |
9.2 |
|
Indiana |
7.6 |
7.4 |
13.3 |
|
Iowa |
7.4 |
6.7 |
12.2 |
|
Kansas |
8.7 |
6.1 |
11.2 |
|
Kentucky |
11.8 |
11.7 |
18.0 |
|
Louisiana |
9.9 |
9.4 |
15.2 |
|
Maine |
10.7 |
9.7 |
15.4 |
|
Maryland |
5.7 |
5.6 |
10.6 |
|
Massachusetts |
7.4 |
6.1 |
9.7 |
|
Michigan |
9.7 |
7.1 |
12.4 |
|
Minnesota |
6.6 |
4.9 |
9.2 |
|
Mississippi |
12.9 |
12.2 |
19.2 |
|
Missouri |
6.9 |
7.3 |
12.5 |
|
Montana |
11.6 |
7.5 |
14.2 |
|
Nebraska |
7.8 |
7.0 |
12.4 |
|
Nevada |
5.3 |
5.3 |
10.1 |
|
New Hampshire |
5.7 |
5.4 |
9.9 |
|
New Jersey |
6.2 |
5.1 |
8.9 |
|
New Mexico |
9.1 |
8.2 |
14.5 |
|
New York |
7.5 |
6.5 |
10.8 |
|
North Carolina |
9.9 |
8.5 |
14.2 |
|
North Dakota |
5.8 |
5.1 |
10.9 |
|
Ohio |
7.6 |
7.8 |
13.1 |
|
Oklahoma |
9.1 |
8.2 |
15.6 |
|
Oregon |
10.3 |
7.7 |
13.2 |
|
Pennsylvania |
7.9 |
7.4 |
12.3 |
|
Rhode Island |
8.6 |
6.8 |
12.0 |
|
South Carolina |
11.3 |
8.8 |
14.8 |
|
South Dakota |
5.4 |
4.7 |
9.5 |
|
Tennessee |
10.0 |
8.9 |
15.1 |
|
Texas |
6.7 |
5.8 |
10.9 |
|
Utah |
7.1 |
4.1 |
9.9 |
|
Vermont |
9.1 |
7.8 |
13.9 |
|
Virginia |
6.2 |
6.4 |
11.1 |
|
Washington |
7.8 |
6.7 |
12.7 |
|
West Virginia |
16.0 |
14.0 |
21.2 |
|
Wisconsin |
6.6 |
6.3 |
11.4 |
|
Wyoming |
7.7 |
6.1 |
12.7 |
Source: Authors' calculations using the 2004 CPS and Weathers (2005).
Appendix Table 1A. Definitions of Disability and Employment in March CPS, NHIS, ACS
|
Measure/Source |
Definitions |
|
Disability: One-Period Work Limitation - March CPS |
The CPS March Supplement asks “[d]oes anyone in this household have a health problem or disability which prevents them from working or which limits the kind or amount of work they can do? [If so,] who is that? (Anyone else?)" Those who answer yes to this question are considered to report a work limitation. |
|
Disability: One-Period Work Limitation - NHIS |
The NHIS asks “[d]oes any impairment or health problem NOW keep [person] from working at a job or business? Is [person] limited in the kind OR amount of work [person] can do because of any impairment?” Those who answer yes to either questions are considered to report a work limitation. |
|
Disability: One-Period Work Limitation - ACS |
Because of a physical, mental, or emotional condition lasting 6 months or more, does this person have any difficulty in doing any of the following activities: ... Working at a job or business? |
|
Disability: Two-Period Work Limitation - March CPS |
A portion of the March Supplement participants where asked about work limitation in two consecutive years. Those who report work limitations in two consecutive years (March to March) are considered to report a two period work limitation. The years 1986 and 1996 are not applicable because the Census Bureau changed the sampling frame and the thus housing units were not consecutively interviews. Also note, the CPS follows housing units not the people in the households, so that matched files do not contain movers. |
|
Disability: Two-Period Work Limitation - NHIS |
Not Available. |
|
Disability: Two-Period Work Limitation - ACS |
Not Available. |
|
Disability: Impairment - March CPS |
Not Available. |
|
Disability: Impairment - NHIS |
Respondents receive one of
six condition lists that ask them if they have a specific condition (we focus
on conditions in list #2). This method yields a random sample because being
asked about a condition is not dependent on one’s response to another
question. This method captures those with specific conditions but who may or
may not report having no health or functioning difficulties. Only one-sixth
of the sample is directly asked about a specific condition. The set of
impairments used in this paper are blindness in both eyes, other visual
impairments, deafness in both ears, other hearing impairments, stammering and
stuttering, other speech impairments, mental retardation, absence of both
arms/hands, one arm/hand, fingers, one or both legs, feet/toes, kidney,
breast, muscle of extremity, tips of fingers, and/or toes, complete paralysis
of entire body, one side of body, both legs, other extremity; cerebral palsy,
partial paralysis one side of body, legs, other extremity, other complete or
partial paralysis, curvature or other deformity of back or spine, orthopedic
impairment of the back, spina bifida, deformity/orthopedic impairment of
hand, fingers, |
|
Disability: Impairment - ACS |
Not Available. |
|
Employment: Current Employment - March CPS |
(Beginning in 1994) Last week, did [person] do any work for either pay or profit? |
|
Employment: Current Employment - NHIS |
(Prior to 1997) During the previous two weeks], did [person] work at any time at a job or business not counting work around the house? (Include unpaid work in the family farm/business.) Even though [person] did not work during those 2 weeks, did [person] have a job a job or business? ... “Earlier you said that [person] has a job or business but didn’t work last week or the week before. Was [person] ... on layoff from a job. |
|
Employment: Current Employment - NHIS |
(After 1996) Which of the following {were/was} {you/subject name} doing last week? … ‘working for pay at a job or business’ or ‘with a job or business, but not at work’. |
|
Employment: Current Employment - ACS |
LAST WEEK, did this person do ANY work for either pay or profit? Mark the "Yes" box even if the person worked for only 1 hour, or helped without pay in a family business or farm for 15 hours or more, or was on active duty in the Armed Forces. LAST WEEK, was the person TEMPORARILY absent from a job or business? (Yes, on vacation, temporary illness, labor dispute, etc.) |
|
Employment: Some Employment - March CPS |
A At least 52 hours of work during the previous year. Determined by multiplying usual hours per week by the number of weeks worked in past 12 months, which are derived from the following questions. During [the previous calendar year] in how many weeks did [person] work even for a few hours? Include paid vacation and sick leave as work. In the weeks that [person] worked [the previous calendar year], how many hours did [person] usually work per week? |
|
Employment: Some Employment - NHIS |
Did {you/he/she} work for pay at any time in {last year in 4 digit format}? Yes. |
|
Employment: Some Employment - ACS |
At least 52 hours of work during the previous year. Determined by multiplying usual hours per week by the number of weeks worked in past 12 months, which are derived from the following questions. During the PAST 12 MONTHS, how many WEEKS did this person work? Count paid vacation, paid sick leave and military service. During the PAST 12 MONTHS, in the WEEKS WORKED, how many hours did this person usually work each WEEK? |
|
Employment: Full-Time, Full-Year - March CPS |
At least 50 weeks during the previous year and at least 35 hours per week, as determined from the following questions. During [the previous calendar year] in how many weeks did [person] work even for a few hours? Include paid vacation and sick leave as work. In the weeks that [person] worked [the previous calendar year], how many hours did [person] usually work per week? |
|
Employment: Full-Time, Full-Year - NHIS |
Those answering 35 or greater weeks and 12 months to the following questions. How many hours did {you/subject name} work LAST WEEK at all jobs or businesses? OR How many hours {do/does} {you/subject name} USUALLY work at all jobs or businesses? How many months in {last year in 4 digit format} did {you/subject name} have at least one job or business? |
|
Employment: Full-Time, Full-Year - ACS |
At least 50 weeks during the previous year and at least 35 hours per week, as determined from the following questions. During the PAST 12 MONTHS, how many WEEKS did this person work? Count paid vacation, paid sick leave and military service. During the PAST 12 MONTHS, in the WEEKS WORKED, how many hours did this person usually work each WEEK? |
Source: Adapted from Burkhauser, Houtenville and Wittenburg (2003), Weathers (2005), and Harris, Hendershot, and Stapleton (2005).
Appendix Table 2A. Data for Figure 5—Annual Weeks Worked of Working-Age People with Disabilities
|
Year |
Men Ages 21-39 - With Work Limitation |
Men Ages 21-39 - Without Work Limitation |
Men Ages 21-39 - Relative Rate |
Men Ages 40-58 - With Work Limitation |
Men Ages 40-58 - Without Work Limitation |
Men Ages 40-58 - Relative Rate |
Women Ages 21-39 - With Work Limitation |
Women Ages 21-39 - Without Work Limitation |
Women Ages 21-39 - Relative Rate |
Women Ages 40-58 - With Work Limitation |
Women Ages 40-58 - Without Work Limitation |
Women Ages 40-58 - Relative Rate |
|
1980 |
44.4 |
21.2 |
47.8 |
30.9 |
15.3 |
49.7 |
48.0 |
16.7 |
34.8 |
31.1 |
9.8 |
31.4 |
|
1981 |
44.0 |
22.3 |
50.8 |
31.2 |
14.9 |
47.8 |
47.8 |
17.6 |
36.8 |
31.4 |
9.7 |
30.9 |
|
1982 |
42.3 |
20.6 |
48.6 |
31.3 |
15.5 |
49.7 |
46.6 |
15.2 |
32.7 |
31.0 |
9.5 |
30.8 |
|
1983 |
42.5 |
19.0 |
44.8 |
31.9 |
15.5 |
48.4 |
46.9 |
16.5 |
35.2 |
32.0 |
9.9 |
30.9 |
|
1984 |
44.1 |
20.8 |
47.2 |
33.0 |
15.6 |
47.2 |
47.4 |
16.1 |
34.0 |
32.9 |
11.0 |
33.4 |
|
1985 |
44.7 |
20.5 |
45.9 |
33.2 |
17.0 |
51.1 |
47.4 |
16.3 |
34.3 |
33.5 |
10.9 |
32.7 |
|
1986 |
44.9 |
20.6 |
45.9 |
34.0 |
16.8 |
49.5 |
47.5 |
16.2 |
34.0 |
34.3 |
10.8 |
31.6 |
|
1987 |
45.1 |
20.4 |
45.2 |
34.6 |
17.7 |
51.2 |
47.5 |
16.4 |
34.6 |
35.1 |
11.2 |
31.9 |
|
1988 |
45.6 |
20.4 |
44.7 |
35.1 |
17.3 |
49.3 |
47.7 |
16.0 |
33.5 |
36.2 |
12.8 |
35.4 |
|
1989 |
45.6 |
22.8 |
50.1 |
35.0 |
19.8 |
56.5 |
47.9 |
16.1 |
33.7 |
36.5 |
11.7 |
31.9 |
|
1990 |
45.2 |
19.7 |
43.6 |
34.9 |
17.6 |
50.3 |
47.5 |
15.8 |
33.4 |
36.7 |
11.9 |
32.3 |
|
1991 |
44.2 |
18.9 |
42.7 |
35.2 |
18.8 |
53.5 |
46.9 |
15.9 |
33.8 |
37.2 |
11.5 |
30.8 |
|
1992 |
43.9 |
19.7 |
44.9 |
35.1 |
16.4 |
46.9 |
46.6 |
16.1 |
34.6 |
37.6 |
11.7 |
31.2 |
|
1993 |
44.3 |
17.8 |
40.2 |
35.1 |
14.0 |
40.0 |
46.9 |
13.6 |
29.0 |
37.9 |
13.3 |
35.0 |
|
1994 |
44.8 |
18.4 |
41.0 |
35.6 |
14.9 |
41.9 |
47.3 |
14.6 |
30.8 |
38.0 |
13.8 |
36.2 |
|
1995 |
45.1 |
17.4 |
38.7 |
35.9 |
16.1 |
44.9 |
47.2 |
14.3 |
30.3 |
38.9 |
11.8 |
30.2 |
|
1996 |
45.1 |
17.7 |
39.2 |
36.0 |
15.4 |
42.8 |
47.5 |
15.7 |
33.1 |
39.2 |
12.8 |
32.7 |
|
1997 |
45.5 |
15.7 |
34.4 |
36.8 |
14.7 |
40.1 |
47.7 |
14.3 |
29.9 |
39.6 |
12.1 |
30.6 |
|
1998 |
45.9 |
16.0 |
34.7 |
36.7 |
15.1 |
41.1 |
48.0 |
14.7 |
30.7 |
39.6 |
10.7 |
27.0 |
|
1999 |
45.8 |
18.6 |
40.6 |
37.0 |
15.6 |
42.1 |
47.8 |
13.2 |
27.7 |
40.2 |
12.8 |
31.9 |
|
2000 |
45.8 |
14.1 |
30.7 |
37.3 |
17.1 |
45.9 |
47.9 |
13.2 |
27.6 |
39.9 |
11.8 |
29.7 |
|
2001 |
45.1 |
17.4 |
38.7 |
36.2 |
13.5 |
37.3 |
47.5 |
12.4 |
26.1 |
39.9 |
11.4 |
28.5 |
|
2002 |
44.3 |
15.4 |
34.7 |
35.3 |
12.4 |
35.1 |
47.0 |
12.0 |
25.5 |
39.5 |
10.3 |
26.0 |
Source: Adapted from Houtenville and Burkhauser (2005).
Table 1se. Standard Errors for Population and Prevalence Estimates by Work Limitation Status
|
Category/Statistic |
Cross-Sectional Sample - No Work Limitation |
Cross-Sectional Sample - Work Limitation |
Matched Sample - No Work Limitation in Either March |
Matched Sample - Work Limitation in Both Marches |
Matched Sample - Work Limitation in 2nd March Only |
Matched Sample - Work Limitation in 1st March Only |
|
All, Age 16-80a - Population Estimate |
22,648 |
172,609 |
106,912 |
136,697 |
112,561 |
103,893 |
|
All, Age 16-80a - Prevalence Rate |
0.08 |
0.08 |
0.09 |
0.06 |
0.05 |
0.05 |
|
Ages 16 to 17a - Population Estimate |
113,920 |
16,216 |
113,649 |
8,107 |
12,537 |
7,690 |
|
Ages 16 to 17a - Prevalence Rate |
0.18 |
0.18 |
0.19 |
0.10 |
0.14 |
0.09 |
|
Ages 18 to 24 - Population Estimate |
191,737 |
35,915 |
190,518 |
25,911 |
24,134 |
23,587 |
|
Ages 18 to 24 - Prevalence Rate |
0.13 |
0.13 |
0.15 |
0.09 |
0.09 |
0.09 |
|
Ages 25 to 61 - Population Estimate |
263,846 |
134,247 |
267,304 |
108,227 |
82,541 |
75,051 |
|
Ages 25 to 61 - Prevalence Rate |
0.09 |
0.09 |
0.10 |
0.07 |
0.06 |
0.05 |
|
Ages 62 to 64 - Population Estimate |
91,947 |
44,885 |
88,865 |
36,063 |
26,703 |
23,648 |
|
Ages 62 to 64 - Prevalence Rate |
0.60 |
0.60 |
0.66 |
0.50 |
0.38 |
0.34 |
|
Ages 65 to 80a - Population Estimate |
184,343 |
100,957 |
175,094 |
74,954 |
68,775 |
64,961 |
|
Ages 65 to 80a - Prevalence Rate |
0.29 |
0.29 |
0.33 |
0.23 |
0.21 |
0.20 |
Source: Author's calculations using the March 2003, 2004 Current Population Survey, Annual Social and Economic Supplement.
a Age range differs from other User Guides.
Table 2se. Standard Errors for Demographic Characteristics by Work Limitation Status
|
Category/Statistic |
Cross-Sectional Sample - No Work Limitation |
Cross-Sectional Sample - Work Limitation |
Matched Sample - No Work Limitation in Either March |
Matched Sample - Work Limitation in Both Marches |
Matched Sample - Work Limitation in 2nd March Only |
Matched Sample - Work Limitation in 1st March Only |
|
Age - % 16 to 24a |
0.11 |
0.18 |
0.11 |
0.21 |
0.32 |
0.34 |
|
Age - % 25 to 34 |
0.11 |
0.23 |
0.10 |
0.24 |
0.34 |
0.39 |
|
Age - % 35 to 44 |
0.11 |
0.30 |
0.11 |
0.36 |
0.44 |
0.49 |
|
Age - % 45 to 54 |
0.11 |
0.35 |
0.12 |
0.48 |
0.53 |
0.56 |
|
Age - % 55 to 64 |
0.09 |
0.36 |
0.10 |
0.49 |
0.57 |
0.60 |
|
Age - % 65 to 74 |
0.07 |
0.32 |
0.08 |
0.45 |
0.56 |
0.65 |
|
Age - % 75 to 80a |
0.06 |
0.31 |
0.05 |
0.32 |
0.50 |
0.51 |
|
Age - % 85 or older |
NA |
NA |
NA |
NA |
NA |
NA |
|
Gender - % Male |
0.14 |
0.43 |
0.14 |
0.56 |
0.69 |
0.75 |
|
Gender - % Female |
0.14 |
0.43 |
0.14 |
0.56 |
0.69 |
0.75 |
|
Race - % Asian |
0.06 |
0.12 |
0.06 |
0.13 |
0.21 |
0.23 |
|
Race - % Black |
0.09 |
0.33 |
0.09 |
0.44 |
0.49 |
0.56 |
|
Race - % Native American |
0.02 |
0.08 |
0.02 |
0.10 |
0.11 |
0.11 |
|
Race - % White |
0.11 |
0.36 |
0.11 |
0.48 |
0.54 |
0.62 |
|
Race - % Some Other Race |
0.02 |
0.05 |
0.02 |
0.06 |
0.04 |
0.05 |
|
Ethnicity - % Hispanic |
0.10 |
0.24 |
0.10 |
0.27 |
0.44 |
0.43 |
|
Education - % Less than High School |
0.11 |
0.40 |
0.11 |
0.53 |
0.61 |
0.66 |
|
Education - % High School/Equivalent |
0.13 |
0.42 |
0.13 |
0.54 |
0.67 |
0.73 |
|
Education - % Some College |
0.13 |
0.36 |
0.13 |
0.47 |
0.57 |
0.63 |
|
Education - % Bachelor's or More |
0.12 |
0.27 |
0.13 |
0.32 |
0.47 |
0.52 |
Source: Author's calculations using the March 2003, 2004 Current Population Survey, Annual Social and Economic Supplement.
a Age range differs from other User Guides.
NA refers to statistics that are not available in the data.
Table 3se. Standard Error for Employment Rates, Ages 25 to 61
|
Category/Statistic |
Cross-Sectional Sample - No Work Limitation |
Cross-Sectional Sample - Work Limitation |
Matched Sample - No Work Limitation in Either March |
Matched Sample - Work Limitation in Both Marches |
Matched Sample - Work Limitation in 2nd March Only |
Matched Sample - Work Limitation in 1st March Only |
|
All - Reference Period (Prior Week) |
0.13 |
0.45 |
0.13 |
0.48 |
0.88 |
1.05 |
|
All - Sometime in Previous Year |
0.12 |
0.51 |
0.12 |
0.53 |
0.95 |
1.04 |
|
All - Full-Time in Previous Year |
0.16 |
0.33 |
0.16 |
0.26 |
0.75 |
1.00 |
|
Men - Reference Period (Prior Week) |
0.16 |
0.66 |
0.15 |
0.72 |
1.29 |
1.52 |
|
Men - Sometime in Previous Year |
0.12 |
0.74 |
0.12 |
0.77 |
1.37 |
1.46 |
|
Men - Full-Time in Previous Year |
0.21 |
0.51 |
0.20 |
0.43 |
1.17 |
1.55 |
|
Women - Reference Period (Prior Week) |
0.21 |
0.63 |
0.21 |
0.64 |
1.20 |
1.41 |
|
Women - Sometime in Previous Year |
0.20 |
0.71 |
0.20 |
0.71 |
1.30 |
1.42 |
|
Women - Full-Time in Previous Year |
0.24 |
0.43 |
0.24 |
0.31 |
0.94 |
1.24 |
|
Asian - Reference Period (Prior Week) |
0.15 |
0.54 |
0.14 |
0.59 |
1.00 |
1.21 |
|
Asian - Sometime in Previous Year |
0.13 |
0.60 |
0.13 |
0.65 |
1.07 |
1.20 |
|
Asian - Full-Time in Previous Year |
0.18 |
0.39 |
0.18 |
0.34 |
0.85 |
1.18 |
|
Black - Reference Period (Prior Week) |
0.40 |
1.37 |
0.40 |
1.90 |
2.32 |
2.91 |
|
Black - Sometime in Previous Year |
0.37 |
1.68 |
0.37 |
2.08 |
2.59 |
2.92 |
|
Black - Full-Time in Previous Year |
0.46 |
0.99 |
0.46 |
1.02 |
2.09 |
2.96 |
|
Native American - Reference Period (Prior Week) |
0.42 |
0.85 |
0.40 |
0.72 |
2.00 |
2.31 |
|
Native American - Sometime in Previous Year |
0.36 |
1.01 |
0.35 |
0.79 |
2.18 |
2.32 |
|
Native American - Full-Time in Previous Year |
0.49 |
0.68 |
0.49 |
0.28 |
1.80 |
2.01 |
|
White - Reference Period (Prior Week) |
1.80 |
3.55 |
1.78 |
4.27 |
3.40 |
12.16 |
|
White - Sometime in Previous Year |
1.64 |
4.83 |
1.56 |
4.65 |
10.72 |
12.43 |
|
White - Full-Time in Previous Year |
2.01 |
2.10 |
2.02 |
1.91 |
0.00 |
4.69 |
|
Hispanic - Reference Period (Prior Week) |
0.66 |
3.69 |
0.67 |
5.08 |
5.78 |
6.37 |
|
Hispanic - Sometime in Previous Year |
0.62 |
3.98 |
0.62 |
5.24 |
5.29 |
5.97 |
|
Hispanic - Full-Time in Previous Year |
0.76 |
2.88 |
0.76 |
3.42 |
5.13 |
6.50 |
|
Less than High School - Reference Period (Prior Week) |
0.49 |
0.66 |
0.51 |
0.57 |
1.63 |
2.27 |
|
Less than High School - Sometime in Previous Year |
0.45 |
0.83 |
0.47 |
0.66 |
1.84 |
2.26 |
|
Less than High School - Full-Time in Previous Year |
0.53 |
0.45 |
0.55 |
0.34 |
1.14 |
1.85 |
|
High School - Reference Period (Prior Week) |
0.25 |
0.73 |
0.25 |
0.80 |
1.41 |
1.72 |
|
High School - Sometime in Previous Year |
0.22 |
0.82 |
0.22 |
0.87 |
1.52 |
1.71 |
|
High School - Full-Time in Previous Year |
0.30 |
0.51 |
0.30 |
0.38 |
1.20 |
1.65 |
|
More Than High School - Reference Period (Prior Week) |
0.16 |
0.83 |
0.16 |
0.91 |
1.46 |
1.59 |
|
More Than High School - Sometime in Previous Year |
0.14 |
0.91 |
0.14 |
0.98 |
1.46 |
1.52 |
|
More Than High School - Full-Time in Previous Year |
0.21 |
0.65 |
0.21 |
0.56 |
1.31 |
1.59 |
Source: Author's calculations using the March 2003, 2004 Current Population Survey, Annual Social and Economic Supplement.
Table 4se. Standard Errors for Economic Well Being Measures, Ages 25 to 61
|
Category/Statistic |
Cross-Sectional Sample - No Work Limitation |
Cross-Sectional Sample - Work Limitation |
Matched Sample - No Work Limitation in Either March |
Matched Sample - Work Limitation in Both Marches |
Matched Sample - Work Limitation in 2nd March Only |
Matched Sample - Work Limitation in 1st March Only |
|
All - % Below Poverty Line |
0.09 |
0.52 |
0.09 |
0.66 |
0.80 |
0.85 |
|
All - Median Household Income |
224 |
468 |
438 |
945 |
1,623 |
1,455 |
|
All - Median HH Size Adjusted Income |
135 |
287 |
268 |
595 |
993 |
910 |
|
Men - % Below Poverty Line |
0.12 |
0.72 |
0.11 |
0.91 |
1.13 |
1.19 |
|
Men - Median Household Income |
325 |
648 |
628 |
1,182 |
2,611 |
2,135 |
|
Men - Median HH Size Adjusted Income |
196 |
408 |
384 |
742 |
1,670 |
1,407 |
|
Women - % Below Poverty Line |
0.14 |
0.74 |
0.13 |
0.96 |
1.14 |
1.19 |
|
Women - Median Household Income |
310 |
674 |
611 |
1,461 |
1,998 |
1,986 |
|
Women - Median HH Size Adjusted Income |
185 |
403 |
373 |
921 |
1,140 |
1,188 |
|
Asian - % Below Poverty Line |
0.10 |
0.58 |
0.09 |
0.75 |
0.86 |
0.90 |
|
Asian - Median Household Income |
252 |
569 |
482 |
1,146 |
1,800 |
1,712 |
|
Asian - Median HH Size Adjusted Income |
152 |
352 |
297 |
732 |
1,131 |
1,078 |
|
Black - % Below Poverty Line |
0.35 |
1.76 |
0.33 |
2.63 |
2.39 |
2.12 |
|
Black - Median Household Income |
440 |
1,182 |
1,154 |
3,720 |
4,266 |
3,884 |
|
Black - Median HH Size Adjusted Income |
240 |
620 |
639 |
1,740 |
2,357 |
1,909 |
|
Native American - % Below Poverty Line |
0.36 |
1.28 |
0.33 |
1.53 |
2.34 |
2.19 |
|
Native American - Median Household Income |
525 |
797 |
1,259 |
1,643 |
2,959 |
2,277 |
|
Native American - Median HH Size Adjusted Income |
315 |
466 |
727 |
866 |
1,837 |
1,467 |
|
White - % Below Poverty Line |
1.54 |
5.60 |
1.29 |
6.90 |
11.06 |
12.23 |
|
White - Median Household Income |
1,390 |
2,100 |
3,490 |
4,286 |
7,019 |
2,158 |
|
White - Median HH Size Adjusted Income |
853 |
1,258 |
2,188 |
2,111 |
4,054 |
1,327 |
|
Hispanic - % Below Poverty Line |
0.46 |
3.86 |
0.40 |
3.40 |
3.38 |
6.19 |
|
Hispanic - Median Household Income |
1,158 |
3,242 |
2,354 |
4,867 |
13,695 |
14,846 |
|
Hispanic - Median HH Size Adjusted Income |
669 |
1,776 |
1,307 |
3,070 |
5,939 |
8,595 |
|
Less than High School - % Below Poverty Line |
0.44 |
1.13 |
0.45 |
1.43 |
1.97 |
2.26 |
|
Less than High School - Median Household Income |
391 |
621 |
969 |
1,151 |
1,708 |
2,514 |
|
Less than High School - Median HH Size Adjusted Income |
215 |
347 |
541 |
697 |
1,003 |
1,182 |
|
High School - % Below Poverty Line |
0.18 |
0.84 |
0.16 |
1.04 |
1.31 |
1.36 |
|
High School - Median Household Income |
293 |
742 |
590 |
1,649 |
2,563 |
2,243 |
|
High School - Median HH Size Adjusted Income |
174 |
421 |
361 |
1,032 |
1,338 |
1,376 |
|
More than High School - % Below Poverty Line |
0.09 |
0.76 |
0.08 |
1.02 |
1.06 |
1.08 |
|
More than High School - Median Household Income |
328 |
880 |
614 |
1,665 |
2,919 |
2,374 |
|
More than High School - Median HH Size Adjusted Income |
197 |
566 |
374 |
1,051 |
1,919 |
1,526 |
Source: Author's calculations using the March 2003, 2004 Current Population Survey, Annual Social and Economic Supplement.
[1]A history of the CPS is available at the Census Bureau/Bureau of Labor Statistics web site, http://www.bls.census.gov/cps/bhistory.htm.
[2] The BLS will not be adding new questions to the CPS-Annual Social and Economic Supplement, but will be to the monthly surveys conducted in the first and fifth interview months. We discuss the complex structure of the CPS program below.
[3] Other critics include Kruse and Schur (2000) and McNeil (2000).
[4] The importance of this issue is apparent in a research summary by Hale (2001) in the Monthly Labor Review. Hale argues that because the CPS is not designed to measure a specific definition of disability, the burden of proof of its reasonableness is on those who use it. He then writes, “To proceed as though the data are valid measures of disabilities turns a data issue into a policy issue.”
[5] See Houtenville and Burkhauser (2005) and Burkhauser, Houtenville and Rovba (2006a, 2006b).
[6] The Census 2000, the ACS, and the NHIS are examples of such surveys. The PSID because of its longitudinal structure interviews household heads and their spouses over the entire period they are in the sample. See Burkhauser, Schroeder and Weathers (2006) for a discussion of the relative merits of the PSID for disability research. It is also possible to use the SIPP to construct multi-period measures of disability. See Wittenburg and Nelson (2006) for information on how this is done.
[7]Kirchner (1996), in one of the first criticisms of the use of work limitation-based disability measures from the CPS in estimations of the employment rates of working-age people with disabilities, argued that falling employment rates in this population could be caused by a change in the attitudes of people with disabilities after the passage of the ADA that would lead those who were employed to be less likely to describe themselves as having a work limitation and, hence, artificially decreasing the employment rates of those with disabilities who did report a work limitation. This explanation, however, is inconsistent with the rise in self-reported work limitations since 1990 found in the data. Burkhauser, Daly, Houtenville and Nargis (2002) show that while the employment rate levels in the March CPS are lower than in similar age populations drawn from the National Health Interview Study between 1983-1996—that uses an impairment-based measure of the working-age population with disabilities—the employment trends in the two populations are not significantly different from one another. Hence, the trends in the relative employment of working-age people with disabilities in the NHIS, using this arguably less sensitive measure to potential changes in the attitudes of those with disabilities, do not change differently from those found in the CPS after the passage of the ADA. Because the disability questions in the NHIS were dramatically changed after 1996, it is not possible to use these data to compare employment rates before and after 1996.
[8] Because the dependent variable in our regression is an estimate itself, the regression is weighted by the reciprocals of the standard errors of the ratio of poverty rates y = pov subscript-t superscript-d divided by pov subscript-t superscript-n*d. Several methods exist to estimate standard errors of ratio. The first method proposed for this purpose is the “delta” method that estimates asymptotic variance of y using a second-order Taylor series approximation. However, the Taylor series approximation does not generally work well for ratios, and the assumption of well-behaved parametric distribution for y is questionable. For example, if poverty rates for disabled and non-disabled populations are distributed independent-unit normal, then y follows a Cauchy distribution, which has no mean and infinite variance. An alternative approach that avoids some of the delta method’s pitfalls is non-parametric bootstrapping. We use this method to estimate standard errors of y. Also, we test for the presence of autocorrelation in our regression, since autocorrelation can either inflate or deflate the standard errors of the estimates. Based on both Breush-Godfrey and Durbin alternative tests, we fail to reject the null hypothesis of no autocorrelation. Therefore, no further modifications to the regression are necessary. Our OLS estimates are unbiased, consistent, and efficient.
[9] In Houtenville and Burkhauser (2005) we replicate the Acemoglu and Angrist (2001) findings for all four groups—younger men (21-44), older men (45-61), younger women (21-44) and older women (45-61).