Income, Poverty and Health Insurance Coverage in the U.S., 2016


[MUSIC] Good Morning and thanks for joining us
I’m Michael Cook, Division Chief of the Census Bureau’s Public Information
Office. I’m here with David Waddington Division Chief of the Chief Division
Chief of Social Economic and Housing Statistics today we’re releasing
findings from three reports Income, Poverty in the United States, Health
Insurance Coverage in the United States including state-level statistics from
the American Community Survey and the Supplemental Poverty Measure for 2016.
After the presentation we’ll open up the phone lines to answer questions from the
media. You can find resources on our homepage census.gov click on the slider
at the top of the page or go to the newsroom and you’ll find an electronic
press kit containing materials from today’s news conference and media
products including the News Release Visualizations and Sound bites. You can
also join the conversation on Twitter and Facebook by following @uscensusbureau. Without further delay here’s David Waddington, Division Chief of the
Social Economic and Housing Statistics to discuss today’s findings. Thanks for
joining us Dave. Great thank you Michael, glad to be here
thank you Michael. Good Morning and thank you for joining us today. We’re releasing
Income, Poverty and Health Insurance Coverage Estimates. Let me begin by
summarizing the main findings. Median household income for the nation was $59,000
in 2016, an increase in real terms of 3.2 percent from 2015
median of $57,200. The official poverty
rate in 2016 was 12.7 percent down 0.8 percentage points from
2015. In 2016 there is 40.6 million people in poverty, 2.5 million
fewer than in 2015. The Supplemental Poverty Rate in 2016 was 13.9, percent 0.6 percentage points lower than the SPM estimate for
2015. The percentage of people without health
insurance coverage for the entire calendar year was 8.8 percent or
28.1 million people. This was a decrease of 0.3 percentage points from
2015. We’re releasing 3 reports today Income and Poverty in the United States,
Health Insurance Coverage in the United States and the Supplemental Poverty
Measure all for 2016. Once again we are releasing the Supplemental Poverty
Measure or SPM estimates at the same time as the official Poverty Estimates.
The Income and Poverty Report and the SPM report are based on data from the
Current Population Surveys Annual Social and Economic Supplement. The Current
Population Survey is the longest-running survey conducted by the Census Bureau
and is the official source of the National Poverty Estimates. The estimates
of Official Poverty Rates are calculated in accordance with the Office of
Management and Budget’s Statistical Policy Directive 14. The Health Insurance Report
includes data from both the Current Population Survey and the American
Community Survey. The American Community Survey is an ongoing survey that has a
much larger sample size than the Current Population Survey making it the
recommended source of health insurance statistics for smaller populations and
levels of Geography. Let me start by giving more details about the changes we
observed in Income. This chart shows Median Household Income from 1967 to
2016 in real inflation adjusted dollars. Recessions as defined by the National
Bureau of Economic Research are depicted in this and all-time series
charts in light blue shading. The Median represents the point on the distribution
of household income at which half of the households have income below it and half
have income above it. Real Median Household Income was $59,000
in 2016, an increase in real terms of 3.2 percent from the 2015 median. This is the
second consecutive annual increase in Median Household Income.
Looking here at selected demographic characteristics
this chart shows Household Income by Age of Householder for 2015 and 2016. Notice
the pattern with householders aged 15 to 24 having the Lowest Median Income and
householders aged 45 to 54 having the Highest Median Income. The Real median
income of households maintained by householders aged under 65 increased 3.7
percent between 2015 and 2016 while the median income of households maintained
by householders aged 65 and over was not statistically different from their 2015
median. Next we show household income by race and Hispanic origin of the
householder. The real median income of households maintained by Non-Hispanic
Whites, Blacks and Hispanics increased by 2 percent, 5.7 percent and 4.3 percent
respectively between 2015 and 2016. This is the second annual increase in median
household income for Non-Hispanic White, Black and Hispanic households. Among the
race groups households maintained by Asians had the highest median income in
2016 at $81,400 though the 2015 – 2016 percent change in their real median
income was not statistically significant. Looking at household median income by
region households in the south and west experienced an increase in real median
income of 3.9 percent and 3.3 percent respectively between 2015 and 2016.
Comparing Regional to National Household Median Income, the medians in the north
east and west were higher. The medians in the Midwest was not statistically
different and a median in the South was lower. While the median
represents one point on the distribution of household income, other points provide
additional information about the nation’s household income distribution
for example 10% of households had income below
$13,600. 10% of households had income above a $170,500 and 5% had incomes above $225,300. Changes in the relationship of these
income measures and the shares of income they possess shown in a full report can
indicate how income inequality is changing. Using the information about the
income distribution of household income from the Current Population Survey, we
can produce a Gini index, a widely used measure of inequality. The Gini Index
indicates higher inequality as the in dex approaches 1. The Gini index is
calculated using pre-tax cash income and was 0.481 in 2016, it
was not statistically different from 2015. These next slides switch to
earnings and work experience data for people aged 15 and older.
Here we see historical data on the real median earnings and female-to-male
earnings ratio for full-time year-round workers from 1960 to 2016. The median
earnings for men and women who worked full-time year-round were not
statistically different from their respective 2015 medians. The
female-to-male earnings ratio was 80.5% in 2016 an increase of 1.1% percentage point from 2015. This is the first time the female
to male earnings ratio has experienced a statistically significant
annual increase since 2007. This slide shows the number of workers historically
by work experience and sex between 2015 and 2016 the total number of people with
earnings regardless of work experience increased by about 1.2 million. In
addition the total number of men and women working full-time year-round with
earnings increased by 2.2 million between 2015 and 2016. This is suggesting
a shift from part year part time status to full-time year-round work
status. Now we will take a look at Poverty. This slide shows the official
poverty rate and a number of people in poverty. The official poverty rate in
2016 was 12.7% down from 13.5% in 2015.
In 2016 there was 40.6 million people in poverty down from
43.1 million in 2015. In 2016 a family with two adults and two
children was categorized as in poverty if its income was less than $24,339. The difference between the
poverty rate in 2016 and the poverty rate in 2007 was not statistically
significant. This is the first year since the most recent recession where the
poverty rate was not significantly higher than the pre recession period.
Here we demonstrate the difference in poverty trends across race and Hispanic
origin groups. For non-hispanic whites the poverty rate was 8.8% in 2016 not statistically different from the 2015 estimate. The
poverty rate for blacks decreased to 22.0% in 2016
down from 24.1% in 2015. For Hispanics the poverty rate
decreased to 19.4% in 2016
down from 21.4% in 2015. The change in the poverty rate
for Asians was not statistically significant. This slide looks at poverty
rates by age for children under age 18, 18% were in poverty in 2016
down from 19.7% in 2015. The poverty in 2016 decreased
for people 18 to 64 to 11.6%, down from 12.4%
in 2015 people aged 65 and older had a poverty rate of 9.3%
in 2016. The difference between the 2015 and 2016 poverty rate for this group was
not statistically significant the poverty rate for females has
historically been higher than the poverty rate for males but the
difference has narrowed over time. In 1966 the poverty rate for females was
3.3% percentage points higher than for males but by 2016 the
difference in rates across females and males had declined to 2.7%
percentage points, age however matters. The narrowing difference in poverty
rates across sexes from 1966 to 2016 was concentrated among individuals aged 65
and older. In 1966 the poverty rate was 8 point 5% percentage points higher among
females. By 2016 this difference had narrowed to 3.0% percentage points. The
average per-capita income deficit provides a measure of how much income
per person would be necessary to move individuals and families out of poverty.
Families with female householders with no husband present in 2016 required more
income to rise above the poverty line compared to other family types, while
unrelated individuals experienced a larger annual income deficit than those
living in families. While 12.7% of the population in 2016 were
in poverty 5.8% of the population had incomes below 50% of
their poverty threshold meaning the family or individual received less than
half the income necessary to meet their poverty threshold. Among those in poverty
in 2016 45.6% had incomes
below 50% of their poverty threshold. This slide looks at the proportion of
people in poverty in 2016 with income below 50% of their poverty threshold by
selected characteristics while forty five point six percent of the total
population in poverty had less than 50% of their income needed to reach their
poverty threshold this proportion was lower among the poor aged 65 years and
older as well as for Hispanics. Turning now to the Supplemental Poverty
Measure. The Supplemental Poverty Measure or SPM extends the official poverty
measure by taking into account many government programs designed to assist
low-income families and individuals that are not included in the official poverty
measure. Non-cash benefits such as Housing or Nutritional Assistance are
added to pre-tax cash income while necessary expenses such as taxes,
work and medical expenses are subtracted. The SPM rate does not replace the
official poverty measure and is not used for determining eligibility for
government programs. The SPM uses thresholds produced by the Bureau of
Labor Statistics from the Consumer Expenditure Survey. Separate thresholds
are created for renters, homeowners with a mortgage and those who own their homes
free and clear. While the poverty rate while the poverty
threshold is constant throughout the United States on the official poverty measure the SPM adjusts for Geographic differences in housing costs.
This map shows those differences with yellow areas having lower thresholds for
renters than the official poverty threshold and blue and green areas
having higher thresholds. This slide compares the SPM estimates for 2016 with
the SPM estimates for 2015 for all people and by age group. The 2016 SPM
rate for the entire population was 13.9%, 0.6% percentage points lower than the SPM rates for 2015. There were statistically
significant decreases in the poverty rates across our overall for children
under 18 and for people 18 to 64 between 2015 and 2016. The SPM rates for adults
aged 65 and older had a statistically significant increase of 0.8 percentage
points in 2016. This slide compares the SPM estimates for 2016 with the official
poverty for all people and by age group. The 2016
SPM rate for the entire population was 1.2 percentage points higher than the
official poverty rate for 2016. Looking at specific age categories the
SPM rate was lower than the official poverty rate for children but higher
than the official poverty rate for people aged 18 to 64 and people aged 65
and older. One important contribution that the SPM provides is allowing us to
gauge the effectiveness of tax credits and transfers in alleviating poverty. We
can also examine the effects of non discretionary expenses such as work and
medical expenses. This graph shows the impact on the 2016 SPM rate of the
addition or subtraction of a single resource element. Some of these elements
such as Social Security and unemployment insurance are included in the official
estimates. Other elements such as the Supplemental Nutrition Assistance
Program benefits and refundable tax credits are included only in the SPM
resource measure. Using this chart we can see that 26.1 million people were
taken out of poverty by Social Security benefits. 8.2 million people were taken
out of poverty by refundable tax credits. 3.6 million people were taken out of
poverty by SNAP benefits or food stamps. However subtracting medical expenses
from income increased the number of people in poverty by 10.5 million using
the SPM. Now I would like to turn to health insurance over time changes in
the rate of health insurance coverage and the distribution of coverage by type
may reflect economic trends shifts in the demographic composition of the
population and policy changes that affect access to care. Several such
policy changes occurred in 2014 when many provisions of the Patient
Protection and Affordable Care Act went into effect. Let me start by giving
details about coverage rates for the population as a whole. In 2016
most people 91.2 had health insurance coverage at some
point during the calendar year with more people having private health insurance
coverage 67.5% than government coverage at 37.3%. Of
the subtypes of health insurance coverage employer-based insurance
covered the most people. 55.7% of the population followed
by Medicaid, Medicare, Direct Purchase which includes health insurance
exchanges and military health care. According to the current population
survey the percentage of people covered by any type of health insurance
increased by 0.3% percentage points to 91.2% in 2016. Between 2015
and 2016 the rate of Medicare coverage increased by 0.4% percentage points to
cover 16.7% of people four part or all of 2016. Between
2015 and 2016 there was no statistically significant
change for any other subtype of health insurance. Here on the right we see the
change in health insurance coverage rates since 2013 the baseline year
before many provisions of the Affordable Care Act went into effect. The uninsured
rate decreased by 4.6% percentage points between 2013 and 2016.
The percentage of people covered by private health insurance increased by
3.3% percentage points in this four year period. However of the two
subtypes of private coverage only direct purchase health insurance had a
significant change. During this period the percentage of people with government
coverage increased by 2.7% percentage points. Among the subtypes of
government coverage the Medicare coverage rate increased by one point
zero percentage points and a Medicaid coverage rate increased by 1.9% percentage points. Now turning to socio-economic
characteristics, in 2016 people with lower household incomes had higher
uninsured rates than people with higher incomes. The uninsured rate for people in
households with an annual household income of less than $25,000 was 13.7% a
1.1% percentage point decrease from 2015. The uninsured rate for people in
households with incomes of $125,000 or more was 4.2% in 2016. In 2016 the
uninsured rate for full-time year-round workers was 9.8% for people
who work less than full-time year-round the uninsured rate was 14.8% – a 1% percentage point decrease from 2015. For people who did
not work at least one week the uninsured rate was 15.0%, also
a decrease from 2015. In 2016 the uninsured rate for Hispanic non-hispanic
whites was 6.3%, a decrease from 2015 this rate was lower
compared with other groups. The uninsured rate was 10.5% for
blacks and 7.6% for Asians. Hispanics had the highest uninsured rate
in 2016 at 16.0%. As I mentioned at the beginning of the
presentation, the American Community Survey has a much larger sample size
than the current population survey the larger sample size of the American
Community Survey make it a useful source for measuring characteristics that we
cannot measure or distinguish with other surveys. The large sample size also makes
it ideal for looking closely at year-to-year changes in small subgroups
of the population such as single year ages. This figure shows the uninsured
rate by single year of age from 2013 in the lightest blue to 2016 in the darkest
blue. According to the American Community Survey the percentage of people without
health insurance coverage at the time of the interview who dropped for most ages
under 65 between 2015 and 2016. These declines in the uninsured rate followed
two years of decreases for all ages under 65.
Younger adults tended to experience a larger decline than
older adults, for example the uninsured rate decreased
by 2% points for 26 year olds and 0.6% percentage points for 64
year olds. Adults age 26 continued to have the highest uninsured rate at
17.5% in 2016. Three notable sharp differences remained
in 2016 between single age years. Specifically between 18 and
19 year olds between 25 and 26 year olds and between 64
and 65 year olds. The American Community Survey is also a useful source for
estimating and identifying changes in uninsured rates at the state level. On
this map the darkest blue represents uninsured rates of 14% or
more. The lighter shades represent lower uninsured rates and the lightest blue
category represents an uninsured rate of less than 8%. Here beginning
in 2013 the year before many provisions of the Affordable Care Act went into
effect most states are in the darkest category. Only three states in the
District of Columbia were in the lightest category. Here is the map for
2014 the year many provisions of the health care law went into effect. In
general the colors on the map are lighter as now 11 states in the
District of Columbia are in the lowest category. Here is the map for 2015
generally the colors on the map continued to lighten and here again is
the map for 2016. Between 2015 and 2016 the uninsured rate decreased in 39
states. Statistically significant decreases ranged from 0.3% percentage
points in Massachusetts to 3.5% percentage points in Montana. Now 25
states and the District of Columbia are in a lightest shade of blue with an
uninsured rate of less than 8% Since 2013
the uninsured rate has dropped in all 50 states and the District of Columbia. Variations in the uninsured rate by
state may be related to whether the state expanded Medicaid eligibility
beginning in 2014 as part of the Affordable Care Act. The two maps shown
here highlight whether or not States expanded Medicaid
eligibility. The map on the left shows states that expanded Medicaid
eligibility referred to as expansion states and the map on the right shows
us states that did not expand Medicaid eligibility referred to here as
non-expansion States. As of January 1 2016, 30 states and the District of
Columbia expanded Medicaid eligibility. In expansion States the uninsured rate
in 2016 was 6.5%. In non-expansion States the rate was higher at
11.7%. Uninsured rates in expansion States ranged from
2.5% in Massachusetts to 14.0% in Alaska. uninsured rates in
non-expansion States for 2016 ranged from 5.3% in Wisconsin to 16.6%. in Texas. Between 2015 and 2016 the overall decrease in the
uninsured rate was 0.9% percentage points in expansion States compared with 0.7%
percentage points in non-expansion States. Medicaid eligibility and therefore the
uninsured rate is often related to poverty status. The population with lower
income may be eligible for Medicaid coverage particularly if they reside in
one of the states that expanded Medicaid eligibility. In 2014 through 2016 the
uninsured rate was higher in non-expansion States than in expansion
States at all levels of poverty. The uninsured rate decreased at each level
of poverty between 2015 and 2016 except for people living at or above 400% of
the poverty in non-expansion States. However the overall decrease in the
uninsured rate was greater in expansion states than in
non-expansion States for all poverty status groups. That concludes my part of
the presentation here again are the highlights. Median household income for
the nation was $59,000 in 2016 an increase in real terms of 3.2% from the 2015 median of $57,200 The
official poverty rate in 2016 was 12.7% down 0.8 percentage
points from 2015. In 2016 there was 40.6 million people in poverty 2.5
million fewer than in 2015. The SPM rate in 2016 was 13.9% –
0.6% percentage points lower than the SPM estimate for 2015 and the
percentage of people without health insurance coverage for the entire
calendar year was 8.8% or 28.1
million people. This was a decrease of 0.3% percentage
points from 2015. Thank you and now I’ll turn it back over to Michael. Thank you
David. Now we’ll take a brief break as we prepare for the question and answer
session for media. If you’re a member of the media who would like to ask the
question please dial 888-917-8045 and
enter passcode 6135618 when prompted. We’ll be right
back [MUSIC] Welcome back now let’s open the
discussion to questions please state your name and media affiliation when you
ask a question. We want to give everyone an opportunity so we’re allowing just
one question and one follow-up question. Joining us now in addition to David
Waddington are his counterparts from our Social Economic and Housing Statistics
Division Trudi Renwick, Assistant Division Chief for Economic
Characteristics and Jennifer Cheeseman Day, Assistant Division Chief for
Employment Characteristics. If you have additional questions following the news
conference please call the Public Information Office at 301-763-3030. Operator do we have your first caller? Operator: Our first question comes from Chris with the Associated Press. Caller: Hi
Chris! Hi how are you? to clarify can you give us the historical context for the
median household income which appears to be high having just barely top 1999 and give
us a breakdown and remind us of the racial and ethnic breakdowns for those numbers as well. Thank you. Thank you Chris I’m gonna
throw that income question over to Trudi Renwick Hi Chris! Well that’s a
that’s an interesting question if you’ll notice on our charts you’ll see a break
in the line series and that’s because we introduced some new income questions in
2014 referring to income in 2013 and because
of those new income questions we are not making historical comparisons to any
time before 2013. Thank you for that question
operator do we have another call. Thank you next question is Ben with the
Wall Street Journal your line is open. Caller Ben: I have a you may not be able to answer
this question either for the same reason but I’m wondering when the last time it
was we had such strong back-to-back gains it seems like this is a pretty
significant two-year increase in the median household income.
Thanks Ben I’m gonna throw that income question again back to Trudy. We can’t go
back two years because we’ve been using the new income questions now since 2014
and you’re correct these are two consecutive years of strong income gains.
I haven’t made the statistical comparisons to the previous periods but
this has been two consecutive years of a very strong income growth. Thanks
for that question Ben. Operator do we have another caller on the line? Operator: Next is Heather L. from the Washington Post, you line is open. Hi Heather
thanks for doing this I know this we keep asking the same question but can
you just clarify is it wrong to say that it’s the highest median income ever I think that’s what a lot of people are
going to look at this and take away they’re seeing the biggest number on
table a1 of all-time. We discourage people from making those comparisons
because we really cannot tease out what is the impact of the change in the
income questions and which was big purpose of which was to gather more
income and the real changes in the economy so for median household income
there was a 3% increase in income when we changed the income questions and so
we are we would discourage people from making those historical comparisons.
Thanks for that question Operator do we have another call? Operator: next question is from Tammy L. from CNN. Your line is open. e-check with you whether the poverty numbers are also subject to that
change or can we compare historical poverty numbers and I’m gonna throw that
poverty question over to Trudi. Well when made the change in the
questions we did it and what we call a split panel so that we took a part of
the sample and asked some of the old questions and a part of the sample the
new questions for 2013 for income year 2013 and we found when we did that
analysis is that the change in poverty across the questions was not
statistically significant so we are making those poverty comparisons going
back that’s why we could say that the poverty rate this year was not was the
first year that we had a poverty rate that was not higher than the pre
recession 2007 poverty rate. Caller: And do the numbers change number because you haven’t updated yet your historical chart basically it’ll show 2015 as the most recent but those facts don’t change they don’t get
income adjusted like income does right? Right they do not and if you refresh your
browser I think the new the new data should be up and live now okay thank you.
Thanks for that question. Operator do we have another call? Operator: queston is from Dominique R. with The Guardian. [Caller]: Just to
go back everyone’s can ask the same question trying to get at some handle on
how we do compare this figure to medium figures how can we compare I mean know
you’re discouraging us from doing this but everyone’s going to continue try and
give us a bit wider context on this year’s figure? Trudi can you shed some
more light on that? Well okay well this year’s figure you could we can see that
there was a significant increase in income over the last year and almost
every group had an increase in income relative to last year and for most
groups it was the second consecutive year of an increase in median household
income unfortunately when you want to go back further you’re going to there’s
difficulty because of that change in the questionnaire
after many years of research and and lots of consultation we realized that we
could do a better job of collecting income and and that’s why we introduced
the new questions in 2014 but that makes idifficult to compare across that
divide. [Caller] : would it be possible though to compare it how income recovered from the
last recession to this I mean I know that you’re not comparing exactly like
for light but there’s there a way can you can you talk a bit about how income
has recovered since the recession compared to how its recovered in
previous recessions well I would I would well one thing I would suggest for this
recession is on Thursday when we released the American Community Survey
data that does not have we did not change the questionnaire for the
American Community Survey so on Thursday you’ll be able to look at
American Community Survey and and look at the trends and median income back to
2007. Thanks for that follow up question Dominique. operator do we have another caller thank
you next question is from Melissa Janko with American Academy of Pediatrics your
line is open hello Melissa could you say that one
more time had a little difficulty hearing it I was able to find the answer
in your report so I’m all set. okay thank you very much operator next
caller thank you next question is Maria from the opinion your line is open Hispanics from the data that I’m looking
at it looks like they’ve improved overall in terms of poverty and income
and I’m wondering if that reflects the previous administration’s policies and
what is that for tend to the current debate over Obamacare thank you thank
you for that question Maria I’m going to throw that overall question
to Dave Waddington. initially what I can say is that we did as you pointed out as
it did see some of the overall findings that there were improvements in median
household income as well as declines in poverty for the Hispanic population what
we here what we’re doing here is we can reflect 2016 from the current population
survey that we collected the data in in February through April this past year so
it reflects data for 2016 we can’t really speculate as to what the causes
are but I can tell you is we’ve been accurately collecting these data for
over 50 years and we’re reporting them and we’ll continue to report and track
these changes as we go into future years that question operator another call
thank you as a reminder for parties from star one for questions or comments next
question is from Phil kaiser Health News your line is open
a similar question to the last one how much of the reads chopping the uninsured
you should be to the improving economy versus the changes in health policy that
insurance question I’m going to see that up and throw it over to Jennifer Thank
You Phil it’s a good question we really can’t tease out that change between what
be the change in policy versus changing the economy with our data certainly we
saw an improvement we’ve seen improvements in the uninsured rate since
after 2013 when many of the effects of the Affordable Care Act went into effect
thanks for that question Phil operator do we have another call and while we’re waiting for our next
caller just to remind everyone if you navigate to census gov you’ll see in our
slider image a direct link to today’s press kit and in that press kit after
the presentation you’ll be able to access the archived version of our video
as well as all of our background documents operator your line is open thanks very much for
doing this I’d know everyone keeps asking about this but I want to get back
to the comparability of data because it kind of blows my mind that you all can’t
comment on the comparability of data that’s surely the purpose of this data
and I wonder if you can address why it is that the Census can to tell us how
this compares to the historical pattern of household median income I’m gonna
throw that question back over the Trudi okay well once again after many years of
research on our income questions in 2014 we made a number of changes to the way
we asked income questions in our survey and as a result of those changes in the
questionnaire we found we had an increase of 3.2 percent in income across
the people who got the old questions versus the people who got the new
questions and so it’s impossible for us to tease out now when we compare income
in 2016 to income from the old that was collected from the old questions we
don’t know what is what what’s driving that the new questions or the changes in
the economy unfortunately this happens when we want to try to improve our
survey and so we did a split set a split panel in 2013 so we could make that
comparison between the old questions and the new questions but that does mean
that we it we can only compare with caution going back you may infer that
that that that difference in 2013 is sort of a range of possibilities it can
be applied to this again you could yes I think that you could thank you for that
question operator phone line your line Operator: Next Call is from Jan P. with Dateline your line is open
hi thank you so much for doing this so I’m just wondering how to use this data
on the state level or if I should rely mainly on the ACS data to come out later
this week thanks for that question. I’m going to throw that question over to Dave. yeah I think that your
irresponsive answered your own question is you’re exactly right is that the data
from the American Community Survey which I
much larger sample size will be released on Thursday that embargo actually the
embargo released on the ACS data is at noon today and you could be able to
access that data but that that data will provide much more information at the
state level and all the way down into counties and and lower communities okay
thank you report which shows the health insurance by state great thanks
thanks for that question operator thank you next question is Jordan yeah do
Bloomberg your line is open Jordan hey how are you I’m just a
question I was looking through the message I mean you guys ask questions on
about 50 different income sources money money sources are you able to see which
which contributed to the 3.2 percent gain or if it was it was mainly job
growth itself as opposed to increases in any of those category thanks man with
all that internal question over the truth it okay well that’s a kind of a
complicated question you can look at our detailed tables and that will tell you
by income source what the change in income has been you notice that our
household income went up by three point two percent but our median earnings for
full-time year-round workers were it was flat relative to last year what we did
look at this a little bit and we found that the earnings of those households in
the middle the ones who are making up the median household income their
earnings were their earnings were up but we also saw a big jump in the number of
people working and the number of people working full-time year-round thank you
for that question then operator we have Mike your line is open
that’s it so there thanks for taking our questions I had a question about the
room median income household breakdown by age I noticed that the income gains
for the 15 to 24 cohort were most three or four times as large as the other
groups and I was wondering if there’s any kind of explanation for that is it
just because that group was to begin with and it was easier to put
them to make gains or is there some other you know possible explanation for
why those games were so high and that income question again we’ll go through
these very popular today all right thank you well first of all I think the first
thing to point out is that it’s a very small group that that’s about six
million households out of 120 million households so it’s a it’s a pretty small
group and if you’ll notice from our detailed tables it has a fairly large
margin of error about five percentage points plus or minus from that estimate
but that said it did have the the largest percentage increase and you are
right it starts from a low number so it’s easier to have a higher percent
increase but that said it had the largest percent increase of any group
and we looked at that a little bit and it’s definitely driven by an increase in
the share who are working and an increase in the share who are working
full-time year-round thanks thank you operator and that’s call great we’ll
wait one second to see if we have any additional callers but just to remind
folks about this release specifically if you have any additional question that
you weren’t able to get in feel free to call the public information office at
301-763-3030 operator we’ll just check one
last time to see if there’s any additional calls well then thank you for
joining us today for today’s news conference before we wrap I’d like to
direct your attention to several key products scheduled for release starting
at noon eastern time today results from the 2016 American Community Survey will
be made available under embargo for publication on Thursday September 14th
this data set will provide single year estimates of median house income poverty
and health insurance coverage for all states and counties places and other
geographic units with populations of 65,000 or more it also includes
estimates for numerous social economic and housing characteristics
such as language education the commute to work employment mortgage status and
rent as already noted the 2016 American Community Survey health insurance
statistics four states have just been released additional American Community
Survey estimates will be released later this year on December 5th we will
embargo estimates aggregating statistics over a five year period from 2012
through 2016 for public release December seventh these estimates will be
available for all areas regardless of population size down to the block group
level if you have additional questions or wish to arrange interviews on the
topics covered in today’s news conference please call the Census
Bureau’s public information office at 301-763-3030 in addition the general public may call our customer service center at
1800-923-8282 for assistance I
would like to also urge you to visit random samplings the official census
bureau blog you will find a link to the blogs in the upper right hand corner of
our home page we have posted separate entries that dig deeper into the income
poverty and health insurance findings we have just released and just a reminder
that you can also join the conversation on Twitter and Facebook following at US
Census Bureau please be sure to tag at US Census Bureau and your stories for
social media i’d also like to take a moment to thank our survey respondents
the Census Bureau conducts more than 130 surveys each year including the American
Community Survey and the current population survey information from this
and other surveys generates data that helps determine how billions of federal
and state dollars are distributed each year respondents make this possible for
David Waddington Trudi Renwick and Jennifer Cheeseman Day, I’m Michael Cook thanks for joining us. [MUSIC]

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