News Conference: Income, Poverty, and Health Insurance Coverage in the U.S., 2019
Table of Contents
- [Coordinator] Thank you for standing by. At this time.
- $57,500 increased by 2.1% while the median earnings of women, $47,300 increased 3%.
- One important contribution that the SPM provides is allowing us to gauge...
- This actual online news conference archived later today.
- [Sharon Stern] Hello. This is Sharon Stern speaking. Indeed, we do have those tables online.
- Either not functioning right or maybe it was written wrong but they should be posted right now.
00:00
[Coordinator] Thank you for standing by. At
this time, all participants are on a listen-only
mode until the question-and-answer session of
today's conference. At that time, if you are an
accredited member of the media, you may press
“star,” “1” on your phone to ask a question.
I would now like to turn the conference over
to Michael Cook. Thank you. You may begin.
This conference is also being
recorded today. Thank you.
[Michael Cook] Good morning and thanks
for joining us. I'm Michael Cook,
Chief of the Public Information
Office for the U.S. Census Bureau.
Today, we are releasing the latest Income,
Poverty and Health Insurance findings for the
nation. We'll have four presenters today to cover
these topics. Immediately after the presentation,
we'll open up the phone lines to
answer questions from reporters.
By the way, resources for today's news
conference can be found on census.gov
including the slide decks
from today's presentation.
That'll be posted in a few minutes as part of our
ongoing electronic press kit for today's event.
Look for the "information for" tab at the top of
the census Web page then click on media/newsroom.
01:09
If you have any issues with today's
presentation using WebEx, be sure to try
logging in with Google Chrome. We've determined
or established that that works best. But, again,
the slide deck will be posted shortly on our
Web site and you can also follow along that way.
Without further delay, I'd like to
turn it over first to David Waddington,
Chief of our Social, Economic, and
Housing Statistics Division. David?
[David Waddington] All right. Thank you, Michael.
Good morning and thank you for joining us.
Today, we are releasing three reports -
Income and Poverty in the United States 2019;
The Supplemental Poverty Measure 2019; Health
Insurance Coverage in the United States 2019.
The incoming Income and Poverty report
and the SPM report are based on data
from the Current Population Survey's
Annual Social and Economic Supplement
or CPS ASEC. The Current Population Survey
is the longest-running survey conducted by
the Census Bureau and is the official
source of national poverty estimates.
02:14
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
small populations and levels of geography.
As noted in the referenced year for the report,
the estimates released today cover calendar
year 2019, the last year of the economic expansion
that span from June 2009 through February of 2020.
I also want to note that interviewing for
this year's CPS ASEC was disrupted by the
COVID-19 pandemic and the survey response rate
and sample composition reflect those disruptions.
While the Census Bureau went to great
lengths to complete the interviews,
the response rate for the CPS household survey
was lower than preceding months in the same
period in 2019 as you can see on this figure.
To provide better understanding of the
potential impacts of the COVID-19 pandemic
on data collection, we are releasing
two working papers and an associated
blog that provide some insights and
analysis of the potential impacts.
03:23
Now, let's move on to the main findings.
Median household income was $68,700
in 2019, a 6.8% increase from 2018.
The official poverty rate in 2019 was 10.5%, down
1.3 percentage points from 2018. In 2019, there
were 34 million people in poverty, a decrease of
4.2 million people from 2018. The Supplemental
Poverty Measure or SPM rate for 2019 was 11.7%.
This was a 1 percentage point lower than in 2018.
The percentage of people with health insurance
coverage for some or all of calendar year 2019
was 92%. Private health insurance coverage was
more prevalent than public coverage, covering 68%
of the population at some point during the year;
34.1% of the population had some kind of public
coverage during 2019. The employment-based
insurance remains the most common subtype.
04:32
The American Community Survey which provides
data for 2018 and 2019 that were collected
prior to the COVID-19 pandemic
saw that the percentage of people
without health insurance coverage increased by
0.3 percentage points between 2018 and 2019.
Now, let's t urn to our subject matter
experts to take a closer look at the findings
starting with Trudi Renwick who
will start with income and poverty.
And as a reminder, immediately following these
presentations, we'll take your questions.
[Trudi Renwick] Thank you, Dave. Good morning.
Income and poverty statistics help us to gauge
the health of the U.S. economy. Let me
begin by summarizing the main findings
regarding changes to income, earnings and
work experience between 2018 and 2019.
Income is a measure of all cash or
money resources coming into a household.
It includes wages and earnings from work
as well as social security benefits,
retirement income, interest, dividends and public
assistance. It does not account for taxes paid,
05:37
tax credits or non-cash assistance such
as SNAP benefits, Medicaid and Medicare.
Real median household income increased 6.8% to
$68,700. The median is the point that divides
the household income distribution into half -
one half with income above the median and the
other with income below the median. The real
median earnings of all workers increased 1.4%
while the real median earnings of full
time year-round workers increased 0.8%.
The total number of people with
earnings increased by about 2.2 million.
The number of full time year-round workers
increased by approximately 1.2 million.
Let's look at some more details about the
changes we observed in household median income.
This chart shows median household income from
1967 to 2019 in real inflation-adjusted dollars.
Median household income increased 6.8%
from $64,300 in 2018 to $68,700 in 2019.
Recessions as defined by the National Bureau of
Economic Research, NBER, are depicted in this,
06:52
an all-time series chart in light shading. On
June 8, 2020 NBER determined that the expansion
that began in June 2009 peaked in February
2020 indicating the beginning of a recession.
Since estimates in this report
are for calendar year 2019,
this current recession is not
shown in any of our graphs.
It application pears appears that $68,700 was
the highest median household income since 1967,
the first year for which household
income statistics are available.
However, making comparisons overtime requires
caution since these estimates reflect changes
implemented to the survey including the redesign
of the income questionnaire for data year 2013
and an update to our processing system for 2018.
As a result, some of the apparent differences
over time could be due to these recent
improvements to the data. For example, as
we discussed last year, after adjusting the
pre-2017 estimates for the impact of the CPS
ASEC survey redesign and processing changes,
07:58
median household income in 2018 was not higher
than in 2007, 2000 or 1999. However, this year,
even with these adjustments, median household
income in 2019 was the highest since 1967.
These adjustments are not made in
the table packages we released or
the rest of this presentation because
they require the assumption that the
impact of the data improvements would
have been identical in all years.
For more details on this adjustment
mechanism, see today's America Counts story.
Now, looking at income by race and Hispanic
origin, the 2019 real median income of each
group shown increased from the 2018 medians. These
increases amounted to changes of 7.9% for Blacks;
7.1% for Hispanics; 5.7% for non-Hispanic
Whites; and 10.6% for Asians.
The 2019 median household income
estimates were higher than 2018
for all age groups both native-born and
foreign-born households each region and
09:08
households within Metropolitan Statistical Areas
or MSAs both inside and outside principal cities.
The change in median income for households
outside MSAs was not statistically significant.
In addition to looking at changes at the
median, it's interesting to look at how
income is distributed across the population.
A quintile is one of five equal groups
ranked by income from lowest to highest so
that 20% of all households are in each group.
This is shown by the bar
on the left of this slide.
The bar on the right shows the share
of aggregate income by quintile.
In 2019, households in the lowest quintile
received 3.1% of aggregate household income
while households in the highest quintile received
51.9%. In fact, the highest quintile received
more income than the other four lower quintiles
combined. Looking closer at the highest quintile,
we can see that the top 5% of households
received 23% of aggregate household income.
Using the information about the distribution of
household income, we can produce a Gini Index,
10:19
a statistical measure of income and
inequality ranging from zero to one.
It measures the amount that any incomes differ
on average relative to mean income. It is a
natural indicator of how far apart or spread
out incomes are from one another. A value of
zero represents perfect equality and a
value of one indicates total inequality.
The money income Gini Index was 0.484 in
2019, not statistically different from 2018.
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 if all workers
and full time year-round
workers from 1960 to 2019.
Earnings are the sum of wages,
salary and self-employment income.
In 2019, about 77% of aggregate
income came from earnings.
Between 2018 and 2019, the median earnings of
men increased 2.5% while the median earnings of
women increased 7.8%. For those who work full
time year-round, the median earnings of men,
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$57,500 increased by 2.1% while the median
earnings of women, $47,300 increased 3%.
Here, we see the female-to-male
earnings ratio historically.
The female-to-male earnings ratio compares
the median earnings of women working full
time year-round to the median earnings
of men working full time year-round.
The 2019 female to male earnings ratio was 82.3%,
not statistically different from the 2018 ratio.
Year to year changes in this
ratio are not common. However,
the female to male earnings ratio has increased
5.8% from 77.8% in 2007 to 82.3% in 2019.
This slide shows the number of workers
historically by work experience and sex.
Between 2018 and 2019, the total number of
people with earnings increased by 2.2 million.
The number of women with earnings
increased by 1.3 million while the
number of men increased approximately
900,000. The number of females who were
12:42
full time year-round workers increased by
about 1.2 million between 2018 and 2019
while the change for their male counterparts
was not statistically significant.
As we noted before, these statistics
reflect earnings and employment in 2019.
You can find more information on how these
have changed during the pandemic in BLS reports
on the Employment Situation
and Usual Weekly Earnings.
To evaluate changes in median earnings across the
span of the most recent economic business cycle
is useful to compare 2019 medians with medians
from 2007, the year before the last recession.
Median earnings for men working full time
year-round were up 3% over this period while
the median for women working full time year-round
was up 9%. Between 2007 and 2019, the number of
men working full time year-round increased by
approximately 4.1 million or 6.6% while the
number of women working full time year-round
increased by about 6.4 million or 14.1%.
13:52
Now, let's turn our attention to poverty.
Here are the highlights from the report.
The official poverty rate in 2019 was 10.5%,
down 1.3 percentage points from 11.8% in 2018.
This was the fifth consecutive annual
decline in poverty. The number of
people in poverty in 2019 was 34 million,
approximately 4.2 million fewer than 2018.
Following the Office of Management and
Budget's, OMB, Statistical Policy Directive 14,
the Census Bureau uses a set of income
thresholds that vary by family size and
composition to determine who is in poverty.
In 2019, a family with two adults and two
children was categorized as in poverty
if their income was less than $25,926.
This slide shows the official poverty rate and the
number of people in poverty going back to 1959,
the first year for which we have
estimates. As you can see from this chart,
the 2019 poverty rate of 10.5% was
the lowest observed since 1959.
15:03
Here, we demonstrate differences in poverty trends
for people across race and Hispanic origin groups.
Between 2018 and 2019, each of the race and
Hispanic origin groups experience the decline
in their poverty rates. The poverty rate for
non-Hispanic Whites fell by 0.8 percentage points.
The poverty for Asians fell 2.8 percentage
points. And the poverty rate for Hispanics
declined by 1.8 percentage points. For Blacks,
the poverty rate declined by 2 percentage points.
Here, we show how the population and poverty
compares to the total population distribution
across race and origin groups. We show you ratio
of the population share of the demographic group
in the poverty population divided by the
share of that group in the total population.
Values higher than one indicate a group is
over represented among the population in
poverty and while values less than
one indicate under representation.
In 2019, Blacks and Hispanics were over
represented in the poverty population
while non-Hispanic Whites were under represented.
These differences are particularly pronounced
16:16
among the population aged 65 and older. The
shares of Blacks and Hispanics aged 65 and
older in poverty were approximately twice
their shares in the overall population.
This slide returns to the total
population and looks at how these
same ratios have evolved overtime
by race and Hispanic origin groups.
More information on this topic can be found in the
associated America Counts story released today.
This slide looks at poverty rates by age. Between
2018 and 2019, poverty rates fell for all three
major age groups. For individuals under age 18,
14.4% were in poverty. Poverty decreased 9.4%
for people aged 18 to 64 while people aged
65 and older had a poverty rate of 8.9%.
In this slide, we look at poverty rates
for all families from 1959 to 2019.
In 2019, the poverty rate for families was 7.8%.
This was the lowest rate ever for all families.
We now add the poverty rates for the
Census Bureau's three major family
17:28
classifications - married-couple families;
male-householder no spouse present families;
and female-householder no spouse present families.
In 2019, poverty declined for two of the three
family types - married-couple families and
female-householder families. The poverty rate for
married-couple families was 4%. The poverty rate
for female-householder families in 2019 was 22.2%.
Poverty rates for female-householder families
have declined in four of the last five years.
The gap in poverty rates between married-couple
families and female -householder families
has decreased from 26.9 percentage points
in 1973 to 18.2 percentage points in 2019.
Between 2018 and 2019, poverty rates declined for
most major demographic groups. No groups saw an
increase in poverty rates. Poverty rates
declined for men and women, native-born
and foreign-born individuals, all regions and
inside and outside metropolitan statistical areas.
18:42
For more information on income and poverty
statistics in the United States in 2019, please
visit our Web site where you can find detailed and
historical income and poverty tables as well as
poverty thresholds for 2019 by family composition.
Additionally, please see the America Counts and
Research Matters stories released today providing
additional insights on income and poverty in 2019.
Next, Liana Fox will summarize the findings
for the Supplemental Poverty Measure. Liana?
[Liana Fox] Thank you, Trudi.
The Supplemental Poverty Measure or SPM report is
based on data from the CPS ASEC. The SPM extends
the official poverty measure by taking into
account many of the government programs designed
to assist low income families and individuals
that are not included in the official 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 does not replace
the official poverty measure and is not used to
determine eligibility for government programs.
19:47
Let me begin by summarizing the main findings
from this report. The SPM rate in 2019 was 11.7%.
This was 1 percentage point lower than 2018
and the lowest rate since estimates
were initially published for 2009.
The SPM rate for 2019 was 1.3 percentage points
higher than the official poverty rate of 10.5%.
There were 16 states plus the District of
Columbia for which SPM rates were higher
than official poverty rate,
25 states with lower rates,
and nine states for which the differences
were not statistically significant.
The SPM uses thresholds produced by the
Bureau of Labor Statistics from consumer
expenditure survey data. Separate thresholds are
created for renters, homeowners with a mortgage
and those who own their homes free and clear.
While the official poverty threshold is constant
throughout the United States, the SPM adjust
for geographic differences and housing cost.
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 2019
with 2018 for all people and be age group. The
20:59
2019 SPM rate for the entire population was
11.7%. SPM rates were down for all major age
categories in 2019 compared to 2018. In 2019,
children under age 18 had an SPM rate of 12.5%.
Adults aged 18 to 64 had a rate of 11.2% and
adults aged 65 and older had a rate of 12.8%.
This slide compares the SPM estimates for 2019
with the official poverty estimates for all
people and by age group. The 2019 SPM rate for the
entire population was 1.3 percentage points higher
than the 2019 official poverty rate.
Looking at specific age categories,
the SPM 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.
Census Bureau estimates for the SPM are
available back to 2009. . Since the SPM's initial
production, the SPM rate has been higher than
the official poverty rate ranging from 0.6 to 1.6
percentage points higher than the official measure
over this period. SPM rates in 2019 were at their
22:09
lowest levels since 2009 even after adjusting for
survey redesign and processing system changes.
This slide shows SPM rates over time for
individuals categorized by race and Hispanic
origin groups. Between 2018 and 2019, all major
groups - all major groups shown in this figure
experienced a decline in poverty. SPM rates in
2019 were also at their lowest level since 2009
for all groups shown. In 2019, the SPM
rate for Hispanics was 18.9%; 18.3%
for Blacks; 11.7% for Asians;
and 8.2% for non-Hispanic Whites.
While the SPM national poverty rate was higher
than official, that difference varies by
geographic area. This figure shows the United
States divided into three categories by state.
There were 16 states plus the District of Columbia
where SPM rates were higher than official,
these are shaded blue. There were 25 states
where the SPM was lower than official,
these are shaded orange. And,
finally, there were nine states
whether the differences in the rates were not
statistically significant, these are gray.
23:16
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 2019 SPM rate
of the additional 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 or SNAP and refundable tax credits
are included only in the SPM resource measure.
Using this chart, we can see that 26.5 million
people were taken out of poverty by social
security benefits. This figure also shows the
breakdown by age with the majority of individuals
taken out of poverty by social security aged 65
and older; 7.5 million people were taken out of
poverty by refundable tax credits; 2.5 million
people were taken out of poverty by SNAP benefits.
However, subtracting medical expenses from income
increase the number of people in poverty by 7.7
24:20
million using the SPM. For more information on
the Supplemental Poverty Measure, please see the
report as well as additional tables and working
papers available online. Also, please note that an
interagency technical working group is reviewing
potential changes to the SPM to implement in 2021.
Next, Sharon Stern will summarize
the findings for health insurance.
[Sharon Stern] Thank you so much, Liana.
Health insurance coverage is an important measure
of our nation's overall well-being. Whether it's
for illness, injury or preventative needs, health
insurance provides greater access to medical care,
protection from high unexpected
costs and more economic stability.
Each year, the Census Bureau provides
data on health insurance coverage.
We look at who is and isn't covered, where
they live and what type of insurance they
have. The health insurance estimates released
today come from two surveys. The CPS ASEC asks
people about their health insurance coverage
at any time in the previous calendar year.
The American Community Survey or
ACS is conducted throughout the year
25:26
and asks people about their coverage at the time
they are interviewed. In the health insurance
report, the CPS ASEC provides calendar year
coverage estimates at the national level.
The ACS presents changes in coverage over
time and for states and smaller populations.
Let me begin by summarizing the main funding from
the CPS ASEC this year. An estimated 92% of the
population had health insurance coverage for some
or all of 2019; 8% or about 26.1 million did not
have health insurance at any time in 2019; 68% of
people were covered by private health insurance at
some point during the year. The percentage
of people with public coverage was 34.1%.
This chart shows the percentage of
people covered by specific types
of health insurance using the CPS ASEC
data. As noted in the previous slide,
most people had health insurance coverage
at some point during the calendar year,
with more people having private health insurance
than public coverage. Looking more closely at
26:32
private coverage, employer-based insurance was
the most common subtype of coverage overall
covering 56.4% of the population while 10.2%
of people purchased their coverage directly.
Turning to people who had public
coverage for some or all of 2019,
Medicare covered 18.1% of the population. Medicaid
covered 17.2% and VA and CHAMPVA covered 1%.
The largest sample size of the American Community
Survey allows us to observe characteristics for
smaller populations, including the state level.
In this and the following slides, I'll
present results that show changes in
insurance coverage using the ACS at the state and
national level and by selected characteristics.
This map shows the uninsured rate by state in
2019. Lighter colors represent lower uninsured
rates. Darker colors represent higher uninsured
rates. Five states and the District of Columbia
are in the lightest shade of blue with less than
5% of people uninsured at the time of interview.
Seven states in the darkest shade have
an uninsured rate of 12% or higher.
27:46
This map presents the change in uninsured rates
by state between 2018 and 2019. Overall, for the
United States, the uninsured rate increased by
0.3 percentage points between 2018 and 2019.
However, as you can see on the map,
there are differences by state.
Between 2018 and '19, the percentage of
people without health insurance coverage
increased in 19 states. These
states are shaded in orange.
The State of Virginia, which expanded Medicaid
eligibility under the ACA effective January 1st,
2019 is the only state that had
a decrease in its uninsured rate
by 0.9 percentage points and is shaded in blue.
Looking back at the national level. As noted a
moment ago between 2018 and 2019, the percentage
of people without health insurance at the time
of the interview increased by 0.3 percentage
points. There was not a statistical difference
in private coverage between 2018 and 2019.
The increase in employment-based
coverage at the time of interview
28:54
0.2 percentage points was offset by a decrease in
direct purchase coverage, 0.3 percentage points.
The percentage of public coverage was
down, its two main components - Medicare
and Medicaid - within opposite directions.
Medicare coverage increased, in part due to
the growth in the number of people aged 65 and
older. Medicaid decreased between 2018 and 2019.
Over time, changes in the rate of health insurance
- pardon me - may reflect economic trends, shift
in the demographic composition of the population
and policy changes that affect access to coverage.
This chart shows the time series of the
uninsured rate by race and Hispanic origin.
There were no dramatic
changes between 2009 and 2010,
following the previous recession. Between 2010 and
2013, uninsured rates stayed steady or decreased.
The most notable change in the uninsured rate
for all groups occurred between 2013 and 2014
30:02
when many provisions of the patient protection
and Affordable Care Act or ACA were implemented.
The uninsured rate continued to show modest
declines through 2016. More recently, between 2018
and 2019, Hispanics, Asian and non-Hispanic Whites
all experienced an increase in the uninsured rate.
Age is strongly associated with the
likelihood that a person has health insurance.
Those aged 19 to 64 consistently
have the highest uninsured rate
while adults 65 and over have the lowest
uninsured rate. Between 2018 and 2019,
the uninsured rate for children under age 19
increased by 0.4 percentage points to 5.7%.
The uninsured rate for those aged 19 to
64 also increased by 0.4 percentage points
to 12.9%. The uninsured rates for
people aged 65 and older remained
the lowest of all age groups and did not
statistically change between 2018 and 2019.
31:11
This chart shows the percentage of people under
65 without health insurance by income to poverty
ratio. For adults aged 19 to 64 in all poverty
classifications shown in the figure on the left,
the percentage without health insurance coverage
was significantly higher in 2019 than in 2018.
The uninsured rate for children under 19 followed
the same pattern. The increase in uninsured rate
increased across all poverty classifications.
However, the change was not uniform across groups.
As an example, for children and families with
income at or above 400% of poverty, far-right
on this chart, the uninsured rate increased
by 0.3 percentage points to 2.6%, whereas
for children living in poverty, the uninsured
rate increased, 0.7 percentage points to 7.4%.
As shown earlier, there were increases in
uninsured rates across race and Hispanic origin
groups. This chart focuses on the 2018 and 2019
uninsured rates for those same groups separated
32:21
into adults 19 to 64 on the left and children
under age 19 on the right. Between 2018 and 2019,
Hispanic adults aged 19 to 64 experienced
an increase in their uninsured rate 0.7
percentage points to 25.9%. An increase
was also seen for Hispanic children
who experienced a one percentage point
increase in their uninsured rates to 9.2%.
While there is no significant change in
uninsured for Black working age adults,
Black children experienced a 0.3 percentage
point increase in the uninsured rate. Finally,
the uninsured rate for non-Hispanic White children
and adults both increased between 2018 and 2019.
Additional information is available online.
Now, I will turn it back to David Waddington.
[David Waddington]
All right. Great. Thanks. And that concludes our
presentations and a slight disruption there. So to
recap the highlights, real median household income
increased 6.8% to $68,700 between 2018 and 2019.
33:34
The official poverty rate between - in 2019 was
10.5%, down 1.3 percentage points from 2018.
The SPM in 2019 was 11.7%. This was
1 percentage point lower than 2018.
And percentage of people with health
insurance coverage for the entire
calendar year - without health insurance
coverage for the entire calendar year was 8%.
More information is available
in our reports and online.
We have a number of detailed and
historic tables on our Web site
as well as additional analysis available in
our America Counts and Research Matters blog.
Again, estimates released today cover calendar
year 2019, the last year of the economic
expansion. They do not reflect the impacts of
COVID-19 pandemic or the current recession.
Data users looking for more current information
relating to measurement of the economic,
social or health impacts of COVID-19
are encouraged to look at findings
from our Household Pulse or
Small Business Pulse Surveys.
Both Pulse surveys are releasing
data on a regular basis.
More information about those surveys can be
found on our experimental estimates Web site.
34:45
And now, I'll turn it back over to Michael
who lead our question and answer session.
[Michael Cook] Thank you, Dave. We'd like
to go ahead and start taking questions now.
To fit everyone in, we'll allow everyone one
question and one follow up. I'll turn it over
to the operator now to give us instruction
on how to submit your questions. Operator?
[Coordinator] Yes. Thank you.
Today's question and answer session
is reserved for accredited members of the media
only. If you would like to ask a question,
please dial “star,” “1”, unmute your phone
and record your name clearly. If you need
to withdraw your question, please dial
“star,” “2”. Again, to ask a question,
please press “star,” “1”. It will take just a few
moments for the first question to come through.
[Michael Cook] Thank you. While we wait
for the first question to queue up, a quick
reminder. To check out our press kit online,
it contains today's slide presentations and
will also have - or has our news release that
we put out. The full list of reports are there
on the topics we've covered
today. And we'll eventually have
35:49
this actual online news
conference archived later today.
Operator, by chance, do we have our first caller?
[Coordinator] Yes. Our first caller is
Tami Luhby. Tami, your line is open.
[Tami Luhby] Hi. Thank you so much for
holding this. Can you tell in the data
what drove the huge increase in median income and
also can you tell me the 6.8%, is that the largest
one year, year-over-year increase on record? And
relatedly, what drove the top year rate down?
[Michael Cook] Okay. Great.
Thanks for that question, Tami.
I want to turn that over to Trudi to address
your questions about income and poverty. Trudi?
[Trudi Renwick] Thanks, Tami. Good questions.
I'll start with the year-to-year increase,
the 6.8%. It is not the highest on record.
It is not statistically different from the
increase that we saw in 2015. But it is certainly
among the highest that we have seen on record.
36:55
As for the increases in income and decreases in
poverty, those are consistent with the economic
conditions in 2019. We had low unemployment rates.
We had an increase in the number of workers. We
had increases in median earnings for both full
time, year-round workers and part-time workers.
So, it's not surprising to see median
household income up as well as poverty down.
[Michael Cook] Great. Thanks for that,
Trudi. Operator, do we have another caller?
[Coordinator] Yes. Our next question comes from
Susanna Lottie. Susanna, your line is open.
[Susanna Lottie] Thank you. I just have a
question on the health insurance portion
on the direct purchase. Is that ACA plans as
well as short-term plans health care sharing
ministries, is that kind of across the board of
all insurance? And did you focus just on ACA?
37:57
[Michael Cook] Thanks for that question on
health insurance. I'm going to turn
that over to Sharon Stern. Sharon?
[Susanna Lottie] Hi.
[Sharon Stern] Hi. Thank you for that question.
When we ask in the survey about direct purchase,
it includes any type of direct purchase. So,
however, I wasn't sure - I wasn't following
all the plans you listed, specifically. We
only include comprehensive insurance. So,
let's say, a dental plan would not
be included. But all comprehensive,
whether they're purchased on a marketplace or
elsewise are included in that statistic together.
[Susanna Lottie] So, it could be a
short-term limited duration as long
as it's health and not just dental, for example.
[Sharon Stern] As long as
comprehensive health insurance,
we don't ask them about the duration of the plan.
[Susanna Lottie] Okay. Thanks.
[Sharon Stern] You're welcome.
[Michael Cook] Thanks for that question.
Operator, do we have our next caller?
[Coordinator] Yes. Our next caller is
Mary Ellen McIntire from CQ Roll Call.
39:00
Mary Ellen, your line is open.
[Mary Ellen McIntire] Hi. Thanks for doing
this. I wanted to ask also about the health
insurance numbers. Did you guys find that the
changes in the implementation and enforcement
of the individual mandate had any sort of
significant change on the numbers for last year?
[Michael Cook] Thanks for that health insurance
question. So, I'll turn it over to Sharon Stern.
[Sharon Stern] Since the passage of the ACA, as
you know, several of its provisions have gone
into or out of effect at different times. We
can't speculate as to what cause is, but it's
clear that over time changes in coverage
are influenced by policy shift as well
as demographic composition of the population and
other aspects of the health insurance environment.
So, we provide the data but
don't necessarily point to
the underlying reasons or try to infer a
cause and effect. Thank you for your question.
40:04
[Michael Cook] Thank you. Operator,
do we have our next caller?
[Coordinator] Yes. Our next caller is Scott
Horsley from NPR. Scott, your line is open.
[Scott Horsley] Thanks very much, can you unpack
a little bit about why the Supplemental Poverty
Measure is higher than official in some states
and lower than official in others. I guess,
is it sort of a tug-of-war between the extra
transfer benefits that are included and the
adjustment that you make in the thresholds, which
I think you said take into account housing cost?
[Michael Cook] Thanks for that
question on the Supplementary
Poverty Measure. I'll turn it over to Liana.
[Liana Fox] Hi, Scott. Thanks for your
question. And you're absolutely right,
I think you've kind of answered your own question.
Why we see differences across states? It's a
combination of different thresholds that we
have in different states, so different
- reflecting different housing costs.
There could also be a different mix
of housing tenure, owners, renters,
owners without a mortgage or without - with
or without. There are also differences in
41:10
demographics and then also differences
in generosity of non-cash benefits. So,
all of those come into account when we look
at differences in SPM rates across the state.
[Michael Cook] Thanks for that.
Operator, do we have our next caller?
[Coordinator] Yes. Our next
caller is Rebecca Carballo
from the Houston Chronicle.
Rebecca, your line is open.
[Rebecca Carballo] Hi. I actually was going to ask
you the same question about SPM rate. But have we
seen the states that tend to have - those
darker states on the map, do we notice are
they trending that way? Are those states that
tend to have higher SPMs, have they historically
had higher SPMs? Or is there any state that
had - have gone in a different direction?
[Michael Cook] We'll go ahead and
just stick with Liana then. Liana?
[Liana Fox] Hi, Rebecca. I don't have the time
trends for the states right in front of me. But
42:11
historically, the states that have higher SPM
rates have consistently had higher SPM rates,
but I don't have all of those right in front
of me. If you want to follow up afterwards,
we can absolutely talk. Thank you.
[Rebecca Carballo] Okay. It sounds good.
[Michael Cook] Awesome. Operator,
do we have our next caller?
[Coordinator] Yes. Our next caller is
Reade Pickert (from Bloomberg News.)
Reade , your line is open.
[Reade Pickert] Thanks for taking my
call. I have a quick question about
the differences between the two health
insurance surveys, the fact that kind of
one is for 2019 and then one is
for the when the survey was taken.
Could you put a little light on kind of which
one we should be looking at in terms of trends
and how we should be comparing those over time?
[Michael Cook] Great. Thanks for that
line of questions on health insurance.
I'll go ahead and turn that over to Sharon Stern.
[Sharon Stern] Hi. Thank you for the question.
You had a couple of different questions,
the difference between them, when to use. So,
let me take a quick step back and say that
43:15
the current population survey -
annual, social and economic supplement
is our most widely used health insurance
statistics from our household surveys.
And what we do is we ask a retrospective
(pass to your question). So, they do reflect
2019 in a similar way as ACS but they were
collected this year just like the income
and poverty data shown today in February -
excuse me - yes, February, March and April.
The ACS data, they're interviewed throughout 2019,
so all of these data are pre-pandemic. They were
collected last year. And people are only asked
about their coverage at the time of the interview.
So, we always - pardon me
- for the past few years,
we've included Pulse surveys as
they complement each other. They
have slightly different measures and
they are collected in different ways.
This year, due to the influence of the pandemic
on our data collection, in ASEC, we are
recommending that people use the ACS to compare
year-to-year as its methodology is consistent
44:22
and provides a measure that you can even use
as we did in our report to go back to 2010.
So from 2008, when we introduced the question
to 2019, that is a consistent question
asked in a consistent way about coverage at the
time and it sort of then represents an average
of current coverage. So that's, kind
of, a 2019 average current coverage.
So this year, we are recommending that
people make that comparison using the ACS
again due to the adaptations s of the CPS ASEC.
We know we have a consistent measure in ACS
this year. I hope that answers your question.
[Lee Pickert] Yes. (Because just confirming ) that
would be the best one to use for year-over-year
comparison, so it'd be the 9.2% of people
were uninsured at the time of the interview.
[Sharon Stern] Yes, correct.
[Lee Pickert] Okay. Wonderful, thank you.
[Sharon Stern] Thank you.
[Michael Cook] And that brings
us to our next caller. Operator?
[Coordinator] Yes. Just as a reminder, if
you are an accredited member of the media,
45:30
please dial “star,” “1” to ask a question,
unmute your phone and record your name clearly.
If you need to withdraw your question, please
dial “star,” “2”. Our next question comes
from Jessica Goodheart from Capital
& Main. Jessica, your line is open.
[Jessica Goodheart] Thank you so much, thanks
for this conference. I see online that you have
a report in income and poverty
and health insurance and I'm wondering if do you
have the tables available to download as well?
[Michael Cook]
Yes. This is, Michael. We do have on that
electronic press kit - let me kick this over
to Dave Waddington. I think I'm actually - I was
going online as you're asking that question, so…
[Jessica Goodheart] Yes. I'm looking at
- yes, I'm looking at the table (A3),
for example, the health insurance table and
I see it - I don't see an (interact) - I
mean, one that I can download is Excel.
46:35
[Sharon Stern] Hello. This is Sharon Stern
speaking. Indeed, we do have those tables online,
so that you can download them. And if
you're having difficulties finding them
after the call, I'm sure PIO can arrange
for us to get you the exact location.
[Jessica Goodheart] Okay. Thank you so much.
[Sharon Stern] You're welcome.
[David Waddington] Thanks, Sharon. And
that's, of course, for all the tables
and all the different topic areas on - both
for supplemental poverty measure and then lots
of historical tables on income and poverty
as well as health insurance. So, thank you.
[Michael Cook] Thank you, everyone. Operator,
I think we are waiting for our next caller.
[Coordinator] Yes, our next caller is Karen
Ho from Quartz. Karen, your line is open.
[Michael Cook] Hi, Karen.
[Karen Ho] Hi. Thank you so much for
taking my call. I really appreciate it.
In the figure 8 in regards to the impact of
medical expenses in regards to how much they
contribute to the number of people in poverty
after each element there is a breakdown by age,
47:38
but I would really like to hear more in regards
to how much medical expenses are contributed
to people in poverty based on gender
and also racial categories as well.
[Michael Cook]
Thanks for that question. I’m going to turn
that over to Trudi to shed some light and if
it takes too long to unpack it, we can definitely
talk about this offline after the call. Trudi?
[Trudi Renwick] Well, I’m
going to pass it to Liana.
[Liana Fox] Hi, Karen. Thank you for that
question. This is Liana Fox. In the report
we show breakdowns by overall and we show it by
major age categories but we do not have breakdowns
by gender or race or Hispanic origin
groups. That’s something I’m happy to
talk with you offline but we don’t have
those estimates in the report. Thank you.
[Michael Cook] And again, anyone who needs to
follow up with the Public Information Office after
the call you (can incidentally) call 301-763-3030 ;
301-763-3030. Or if it’s easier to email, just email
48:41
your request to pio@census.gov, that’s P-I-O at
C-E-N-S-U-S dot G-O-V, and we’ll make sure that we
hook you up and have you sit down and get on
the call with our SMEs today so that you can
go ahead and write your stories and get as much
details and background information as you need.
Operator, I think we are
ready for our next caller?
[Coordinator] Yes. Our next caller is Aimee Picchi
from CBS MoneyWatch. Aimee, your line is open.
[Aimee Picchi] Yes. Hi.
[Michael Cook] Hi.
[Aimee Picchi] Thanks for the call. Hi. Yes
I had a question about the response rate.
Heidi Shierholz at EPI tweeted this
morning about the response rate that
was lower because of COVID and that it
could be making a non-response rate.
The higher non-response rate could make
the picture look rosier than reality.
I wonder if you could address that or talk
about that if there’s any issue of the data
scaling towards like people with higher incomes
responding more than lower, if there’s any
concern about whether that might make the income
look higher than it could be in reality? Thanks.
49:47
[Michael Cook] Thanks. Thank you. Thanks
for that question. I think I'll start by
tossing this over to Dave, to have him shed
some light. And if any other people want to
shed some light or give some (sound)
on that they can as well. Dave?
[David Waddington] Yes, sure, thanks.
That’s a good question. I mean
we can’t tell you the exact impacts
of different things. We can tell
you and they report it on our site and
elsewhere what the response rates were.
And as you pointed out we do this
between February and April, and
in-person interviews are a very important
aspect of our data collection and this year
with the extraordinary challenges in the pandemic
we actually stopped our in-person interviews to
protect the health and safety of our employees as
well as the respondents. And that certainly had
an impact on the response rates for the basic CPS
and where the response rate were approximately 10
points lower than they normally are and have been
in recent months, as well the response rate for
our supplement, the annual social and
economic supplement were lower as well.
However, we do have analysis that we do. Whenever
we have response rates that are below 80%,
50:55
we do an non-response bias analysis and begin
to assess the potential impacts of that. We have
actually started some of that work already and as
quickly as we can to turn things around and two of
the working papers that we are posting today,
address some of those - some of those topics.
So, I encourage you to look at both the working
papers that are up there today as well as the
Research Matters blog that discusses some
of the changes in the sample composition
and actually provides some alternative
approximation for potential impact.
[Michael Cook] Thanks for that, Dave.
Operator, can we have our next caller?
[Coordinator] Yes. Our next caller is Tami
Luhby from CNN. Tami, your line is open.
[Michael Cook] Hello again, Tami.
[Tami Luhby] Hi. Thank you. I’m
sneaking in another question.
Trudi, would you be able to please
tell us just break down a little,
was this by race particularly where poverty and
the median income highest on record for all races,
51:59
for certain races and ethnicities, can you
discuss that for poverty and median income?
[Michael Cook] Trudi?
[Trudi Renwick] Hi. This is Trudi Renwick.
I have the numbers right in front of me for
race and it was the lowest ever for Hispanics
since we started collecting data for Hispanics,
and I believe in 1973 and
it is the lowest for Blacks
even after we make the adjustments for the
changes to the survey. I do not have - I can
get you the median income by race after this
call but don’t have those in front of me.
[Tami Luhby] Okay. That would be great.
[Trudi Renwick] Taking into account
those adjustments. Thank you.
[Tami Luhby] Thank you.
[Michael Cook] Yes, Tami, if you could just
call PIO and we’ll set something up. Thanks.
[Tami Luhby] Okay. Should I call or email?
[Michael Cook] Whichever is easiest
for you. We are looking everywhere so…
[Tami Luhby] All right. Thank you.
[Michael Cook] All right, Tami.
Operator, do we have another caller?
[Coordinator] Yes. Our next caller is Josh Ortega
from Cronkite News. Josh, your line is open.
53:04
[Josh Ortega] Hi, thank you for having
me. Could you just break down a little
more aggregate income and what exactly are the
characteristics that go into that highest quintile
and how you went about, how those
have compared to previous years?
[Michael Cook] Thanks for that question on income.
Trudi, it looks like he’s looking
for information on quintiles?
[Trudi Renwick] Hi. I want to start
with the easy question first. So the
shares going to the different
quintiles did not change
between 2018 and 2019. The changes were not
statistically significant between 2018 and 2019,
so we did not see a shift. I’m not sure
what do you mean by the characteristics.
[Josh Ortega] Hello?
[Trudi Renwick] Hello?
[Josh Ortega] Oh, I’m sorry.
Yes. I was just looking at the
just sort of median income level and could you
just explain more what aggregate income is?
[Trudi Renwick] So aggregate income is the sum
of all income, earnings, wages, Social Security,
54:20
public assistance, unemployment
benefits, it’s all cash income,
so that would be totaling it
up for the entire population.
[Josh Ortega] Okay. And so, how much
of the highest quintile, so that’s 20%
of all households are taken in the highest
amount of aggregate income, correct? Am I…?
[Trudi Renwick] To the highest, the richest
20% of households received 51.9% of all income.
[Josh Ortega] Okay.
[Trudi Renwick] And the lowest 20% received 3.1%.
[Josh Ortega] Okay. Thank you.
[Trudi Renwick] And if you go to our report it
would give you the cut-off for each of those
quintiles, how much income you needed
to have to be in each quintile.
[Josh Ortega] Okay. That's what I was
looking for there. Okay. Thank you.
[Trudi Renwick] It’s in the report. I
think it’s on page seven of the report.
55:33
[Josh Ortega] Okay.
[Trudi Renwick] Here I’ve got it right now, all
right? The lowest income quintile are incomes
below $28,000 and the highest income
quintile had incomes above $142,502.
That very top 5% were incomes over $270,000.
That’s all on page seven in our report.
[Josh Ortega] Okay. Thank you.
[Michael Cook] Thank you, Trudi. Thank you, Trudi.
Thank you, caller. Operator,
do we have our next question?
[Coordinator] Yes. Our next question
comes from Steph Solis from MassLive.
Steph, your line is open.
[Steph Solis] Hi. Thank you so much for holding
this. I was just wondering with the uninsured
rate by state is on the flip side there is a
state by state breakdown of insured rates and
the type of insurance people reported or
responded - reported having at a state level.
[Michael Cook] Thanks for that question
on health insurance, Steph. Let me go
ahead and turn that over to Sharon Stern.
56:38
[Sharon Stern] Hi. Thank you for that
question. Those data I do not believe
are in the report but they are available in our
detailed tables which will either be released
today or with the ACS data on Thursday.
I would need to check which for you.
[Steph Solis] Okay.
[Sharon Stern] But if you follow
up with me, I can certainly have a
very specific answer to that question.
[Steph Solis] Thank you. And I’m sorry, I
don’t know if I wrote down the URL wrong,
but are the reports supposed to be available
to us later today or are we supposed to be
able to access that link now at end of the
report, the links for the various reports.
I got an error message when I clicked on
it, but it’s possible I wrote it down wrong.
[Sharon Stern] Well, certainly if you get
back with us just after this press conference,
we can get you the exact correct links
if there’s any problem with that,
if that’s what’s happening there.
[Steph Solis] Okay. Thank you.
[David Waddington] But they
should be available right now.
They should be posted on our site now,
so it might just be a link that’s not,
57:43
either not functioning right or maybe it was
written wrong but they should be posted right now.
[Steph Solis] Thank you very much.
[Michael Cook] Thanks for that line of
question. And we’ll go ahead and double
check those links while we are on to make sure
that everything is working smoothly for everyone.
Operator, do we have our next caller?
[Coordinator] Yes. Our next caller is Melissa
Jenco from AAP News. Melissa, your line is open.
[Melissa Jenco] Thank you. Can you hear me okay?
[Michael Cook] Loud and clear.
[Melissa Jenco] Okay. I just wanted to know
if you could shed some light on why the
rate of children who are uninsured has been going
up while the poverty rate has been going down?
[Michael Cook] Let me see if
Sharon Stern has any information
that she can shed on that, light
she can shed on that. Sharon?
[Sharon Stern] Hi. Thank you for the question.
Health insurance for children is
related not only to income and poverty,
it’s related to things like employment
status, the location where the person lives,
58:50
there are a variety of external factors to adjust
income, but that’s really only a partial answer.
There’s another part of the answer which is that
this year we are using a different survey to show
that change from year to year so we are using
the ACS last year as for point in time coverage,
collected last year. So, what was presented today
by income and poverty is the different survey,
so sometimes there’s inconsistencies in that way.
It’s difficult to make certain kinds
of comparisons. I’m sure the income
and poverty specialists can address that in
more detail, but it’s certainly consistent.
Thank you for the question.
[Michael Cook] Thanks for that, Sharon.
Operator, do we have our next caller?
[Coordinator]
Yes. Our next caller is Janet Adamy from Wall
Street Journal. Janet, your line is open.
[Jane Adamy] Hi. Just a follow-up question
for Trudi. Can you put a little bit more
01:00:00
color around the income increase? You said
at the beginning that it was driven by low
unemployment rates and an increase
in the number of workers. Is there
anything else that you can tell us
about why it was so sharp this year?
[Michael Cook] Thanks for that
question. I'll turn that over to Trudi.
[Trudi Renwick] Hi. This is Trudi Renwick. Well
other than we - I can just talk about what we have
seen in the data, right? I really can’t give you
any definitive answers of why something happened
or why something didn’t happen. But we do see in
the data that we have an increase in employment,
that we have an increase in earnings, and those
would all tend to push median household income up.
[Michael Cook] Thanks for that, Trudi.
And I know just for your reference, caller, if
you call PIO we have the ability at times to
01:01:08
direct you to stakeholders across
the country that work on census data
so you can always reach out to us for that.
And then also I just wanted to flag that
we double checked the links from the
reports and they all look to be working
on our end, so if anybody is running into
technical issues with accessing today’s data,
please I encourage you to reach out to us at
PIO so we can assist and make sure that you are
headed in the right direction and looking at
the right links to get access to today’s data.
Operator, do we have our next caller?
Operator?
[Coordinator] Yes. I am so sorry. Our next
caller is Catherine Rampell from the
Washington Post. Catherine, your line is open.
[Catherine Rampell] Thanks so much for doing
this call. I really appreciate it. I have another
question about the uninsured rates for children
and how comparable they are from year to year.
So, for example, in this year’s report it shows
that the biggest increase in uninsured rates
01:02:18
among children was - of any race by one
percentage point. If I recall it correctly
last year’s report also showed a similar
pattern that there was an increase in
uninsured rates that was especially
prevalent amongst Hispanic children.
I’m wondering given some of the methodological
issues that you talked about if it is okay
to compare the change last year to the change this
year. And if there are any longer term historical
data that are available that would provide
an apples to apples comparison in terms of
what’s happening to insurance rates for
children of different races and ethnicities.
[Michael Cook] Thanks for that. I
will pass that off to Sharon …Stern.
[Sharon Stern] Yes. Thank you.
This is Sharon Stern. That is a
very specific technical and important question
that you’ve just asked. As a matter of fact,
we do recommend staying within a single survey.
01:03:22
So, I wouldn’t want to directly compare
the change that we are reporting this year
between ’18 and ’19 that uses the ACS
directly to the change reported last year
from ’17 to ’18. We can help you though
after this conference find a consistent time
series because we have not done that
test, ACS to ACS change to change but
would be required for what you're asking, but we
may be able to look that up for you. So if you are
really interested, we can absolutely handle
this after the conference if you contact PIO,
we can try to find you the most
comparable. I hope that’s helpful.
[Catherine Rampell] Great, thanks. Yes,
thank you. That’s exactly what I was
trying to figure out, if there is a time period
that exists, that would be closer to you.
[Sharon Stern] Yes. Thank you.
[David Waddington] So, let me just add in a
little bit more to that. I mean, again, we do have
the two surveys that we have been conducting for
many years, and as Sharon has pointed that the
American Community Survey has been
consistently asked and we’ve have had not any
01:04:32
changes in the questionnaire or impact
from the data collection this past year.
But, again, I think it’s important for you as
well as anybody else to look at those survey data,
look at any potential implications from how
things were processed or done and that’s a
decision we can give you some guidance on and you
can then make the best decision for which estimate
is most appropriate for your use and provides
the level of precision that you need for yours.
[Michael Cook] Thanks for that, Dave,
and thanks, Sharon. Operator, I believe
we are top of the hour. I think
we have one more caller left?
[Coordinator] Yes. Our last
caller is Isaiah Thompson. Isaiah,
your line is open. Isaiah is from WGBH News.
[Michael Cook] Hi, Isaiah.
[Isaiah Thompson] Yes. Hi, everyone. Hello.
Thank you for putting this on and you guys
are always great and super helpful. I really
apologize if this was covered earlier. I’m
having a little trouble of my own getting on.
I heard about, it could have been a
separate census product but does this
01:05:41
data at all touch on homelessness or
housing characteristics as it relates to
income and poverty specifically, or is
that a completely separate set of surveys?
[Michael Cook] Thanks for that question.
I think I will turn that over to Dave and…
[David Waddington] Yes. Thank you. Yes. We are
not reporting anything today regarding the CPS,
ASEC or ACS regarding homelessness. This is
pretty much exclusively about the income,
poverty and health insurance estimates
and then associated characteristics.
We do have some other surveys that are ongoing.
I'm not sure which one might be looking at
homelessness if we have one on that topic but
we weren’t discussing that earlier today, sorry.
[Isaiah Thompson] No, it’s all right.
And I see the same is true for something
like another thing related to poverty which would
be like food, hunger or food access, that’s not
part of this survey either. These are just income
and health insurance characteristics, healthcare.
01:06:48
[David Waddington] Yes, that’s correct. Yes.
We do have a few other ongoing surveys that
I mentioned that are being focused on our
experimental estimates Web site. We have
a Small Business Pulse Survey and Household Pulse
Survey and it might be that you’ve seen something
related to that and there’s probably about
40 plus tables that we've been putting out
on our experimental estimates page and we
have a bi-weekly release going on that.
And the Household Pulse Survey does ask questions
about people’s expected ability to pay their
rent or mortgage as well as some mental health
and food security questions. So, you might be
thinking about a release that
came out relative to that.
In fact, we had a release last week of our second
phase of that survey and then next Wednesday,
I think it’s next Wednesday, I believe, will
be our release of the second set of data on a
revised questionnaire that we began asking
about four weeks ago. So, we can happily
give you and point you to more information about
the Household and Business Pulse surveys as well.
01:07:49
[Isaiah Thompson] Thank you so much.
[Michael Cook] Thanks for that question.
And, again, if you weren’t able to ask
your question today during the conference,
please reach out to us. But before we wrap,
I’d like to direct your attention to several
key products scheduled for release, the
results for the 2019 American Community
Survey. The American Community Survey are now
available, (embargo) began about an hour ago. So,
this will be publicly released
on September 17th, this Thursday.
And if you have additional questions about
specifically today’s news conference or
you’d like to arrange an interview, please call,
again, the Public Information Office at 3017633030
or email us at pio@census.gov. And
a reminder to visit America Counts,
that’s our stories behind the numbers on
census.gov or the news stories on the latest
income, poverty and health insurance
findings that we’ve discussed today.
01:08:53
I’d like to thank the survey respondents.
The Census Bureau conducts a 100 surveys
each year, more than a 100 survey each year,
including the American Community Survey
and the Current Population Survey.
We're also grateful to the Census Bureau field
representatives and telephone interviewers
who collected this data. Conducting interviews
during the COVID-19 pandemic made this task much
more challenging. Without their dedication, the
preparation of this report would not be possible.
Finally, I’d like to thank our presenters,
David Waddington, Trudi Renwick, Sharon Stern
and Liana Fox. I’m Michael Cook and I'd like
to thank you all who joined us. Have a great
rest of your day. This concludes today’s
news conference. Thanks, everyone.
[Coordinator] That concludes today’s conference.
Thank you for participating. You may disconnect
at this time. Speakers, allow a moment of
silence and stand by for your post conference.