SIPP Webinar Series: Assets, Income, and Poverty

SIPP Webinar Series: Assets, Income, and Poverty


Coordinator: Thank you for standing by. I’d like to inform all participants that your
lines are on a listen-only mode until the question-and-answer session of today’s call. Today’s call is also being recorded. If there are any objections, you may disconnect
at this time. I will now turn the call over to Ms. Deborah
Rivera. Ma’am, you may begin. Deborah Rivera: Thank you so much Christy. Good afternoon everybody. Welcome to this SIPP webinar series, Webinar
Number 4. As Christy stated my name is Deborah Rivera. I am a training specialist for the Census
Bureau. And today we have a webinar on Assets, Income
and Poverty where our speaker will be discussing the basics of the assets, income and poverty
content in Waves 1 and 2 of the 2014 Survey of Income and Program Participation. The SIPP webinar series will continue throughout
the month of June. The next webinar will take place this Thursday,
June 20 at 2:00 p.m. Eastern Time. And it will be on Programs, Adult Well-Being
and Food Security. So a few housekeeping items before we get
started. As always we are recording this webinar and
along with the training materials associated with it, we will be posting it to our Census
Academy site as a free learning resource. Previous sessions of the SIPP webinar series
are already available and those include all of the handouts, the exercises and a few other
items. So if you’d like to find those, we will be
sharing a link with you on the screen and we’ll be sure to send it through the chat
as well. So we will wait for questions to the end or
until the end of the presentation, but we also have the chat feature as I mentioned. So if you wanted to submit your questions
in written form, we do have subject matter experts available to field your questions. I would now like to introduce our presenter,
Shelley Irving. Shelley Irving is a survey statistician in
the SIPP coordination and outreach staff. And she has been at the Census Bureau since
2009 and has worked on the SIPP that entire time on a variety of capacities. Shelley has a Ph.D. in sociology and demography
from Penn State. Thank you so much, Shelley. Shelley Irving: All right, thank you, Deb,
for that introduction. As Deb mentioned, this is part of the SIPP
webinar series. This is Webinar Number 4 and we will be discussing
assets, income and poverty. My name is Shelley Irving. I’m from the SIPP Coordination and Outreach
staff here at the US Census Bureau. Also on the line we have Mathew Marlay and
Holly Fee who are also from the SIPP Coordination and Outreach staff. So as Deb mentioned, we’re doing a bunch of
SIPP webinars on various topics throughout the month of June. We’re mostly focusing on Waves 1 and 2 of
the public use data. However, I will mention that we recently released
Wave 3. We do have supplemental materials including
exercises and handouts for most to the topics. And the webinars will be recoded and posted
for later reference. If you want to learn more about this webinar
or others in the series, check out that Web site. On the right-hand side of your screen, you’ll
see the list of topics as well as the session dates. Before I begin, I want to mention that if
you haven’t already done so, I would suggest that you listen to the overview session that
took place two weeks ago. This covers a lot of general background about
the SIPP but includes a lot of good information on definitions and concepts that are new to
the 2014 SIPP. And will be important for your understanding
of the material them about the present. Today’s webinar we will be looking at assets,
income recodes, and poverty and then I will follow that up with a brief discussion of
some resources for data users. We’ll start with our asset content. So the 2014 SIPP provide data on assets, liabilities
and additional assets-related content. The asset content is divided into the category
of retirement accounts, interest earnings, asset, other income generating asset and the
other assets. Liabilities include those that are secured
by asset and those that are not secured by asset. The additional topics include information
on rent or mortgage payments and the payment of utilities. There are several items that are new to the
2014 SIPP panel. This includes annuities, trusts, educational
savings accounts, such as 539s, and Coverdell accounts, businesses owned by an investment
only and debt from student loans or educational-related expenses. Some variables are person-level while others
are household level. Regardless, there is no monthly variation
in the assets data. So you’ll remember that the SIPP the 2014
SIPP panel or, you know, data files come out as a person month file. So there are 12 monthly records per person. So you’re going to see the same asset values
for all 12 monthly records for a person to the person level variables and the same value
for all 12 monthly records for all members of the household for household level variables. So when you’re doing an analysis is important
to know first if this is a person variable or household variable. But then also you want to just use one monthly
value. We recommend using month code equals 12 which
refers to December of the reference year. For many of the person level assets there
are separate variables for assets owned jointly with a spouse. Those held jointly with someone other than
a spouse. And in those that the respondent holds in
their name only. You will know this in the variable name. So if you see the EJS in the variable name
it indicate that it is the asset that is held jointly with a spouse. EJO in the variable name indicates an asset
that is held jointly with someone other than a spouse in the household. And EO are assets that are held individually. Married couple household or married couples
have the same data for assets that they hold jointly. So for the amount variable the total amount
is divided by two and put on each person’s record. So for example, you’ll have the variable EJSOWNCHK
which indicates that you own a regular checking account with your spouse. And then a TJSCHKVAL is the value of that
checking account. And I will show you an example of this in
a little bit, but the reported value is divided by two and put on each spouse’s record. So there is no double counting of assets. We use some across people in the household. So the information that is being shown on
these next couple of slides is also available as a handout on the webinar Web site. So if you’re interested in doing the different
topics that we have in the assets content, and some of the information about it. Please do check out that handout. So the abbreviation column shows the letter
sequence for each asset type that you will see in the variable name. And as I mention on the previous slide, some
of the variables are available at the person level while others are at the household level. And it will tell you on these slides where,
what level these variables are for. A check in the income column indicates that
there is a variable indicating the annual income amount and a check in the type of the
ownership column indicates that you can determine whether the asset is owned individually with
a spouse or with another household member. At the top of your screen or at the top of
the table you will see that the retirement accounts are divided into one IRA and Q accounts
and two 401K, 403B, 405B and thrift saving plan accounts. Next you’ll see the complete listing of interest-earning
assets that are available in SIPP. This includes items such as interest-earning
checking accounts, money market accounts and certificates of deposit. Here is our list of other income generating
assets which comes in the form of stocks, mutual funds, rental property, annuities and
trusts. This slide shows our other assets topics that
are included in SIPP. This includes things such as regular checking
account, primary residences, cars and others financial investments. Other financial investments may include things
such as coins, collectibles, jewelry, artwork, mortgages paid to the respondent, other loans
owned to the – owed to the respondent and royalties. Here’s a listing of the different liabilities
topics. So you also see the abbreviation which is
the sequence of letters that you’ll see in the variable name. Some of the liabilities are household level. Some are person-level just as with assets. And for several of these variables, you can
identify whether it was owned individually, jointly with spouse or jointly with some other
household member. So at the top, you see our list of debts that
are secured by assets. This includes items such as primary residence
debt, vehicle debt, and debt on a business owned as a job. On the bottom, there are three types of debt
not secured by assets. These include debt from credit cards or store
bills, student loans and other educational related expenses, and a catch-all other debt
category. In addition to the information about specific
asset and liability topics, our subject matter experts have created some very easy to use
recodes for the asset section. We suggest trying to use these when possible
since they are easier to work with and more intuitive than the original variables. And these are all so variables listed here
are all household recodes that go on the record of every person in the household. You’ll see that all of these variables start
with a T. So these are recodes, but they have been top-coded. So they get that T prefix. So we have TH Net Worth which is total household
net worth. THVAL underscore Bank, a recode for the balance
of all bank accounts for accounts at financial institutions with the household. THVAL underscore R-E-T which is retirement
account balance recode. THEQ underscore home, home equity, THVAL underscore
AST, total household assets and THDEBT underscore AST, is total household debt. So now let’s go ahead and look at some example
data so that you sort of get a feel for what to expect when you start working with the
data. So this example shows one month of data for
the people living in three households. I’m just showing month code equals 12 which
refers to the December of the reference year because as I already said there is no variation
in the values across the reference year. So they’re going to have the same value in
Month Code 1 as they have in Month Code 12. So you just want to look at one month. We are looking at the value of checking accounts. So individually, with a spouse and with someone
other than a spouse. In addition to total person level debt, total
household debt and total household net worth. TOCHKVAL is the value of individually owned
regular checking account. You’ll see that that the adults in the first
household each have an individually owned checking account. So Person 101 has his or her own checking
account and it is valued at $2,000. And then the Person 102 in this household
has his or her own checking account and it is valued
at $525. TJSCKHVAL is the value of a join tly owned
with spouse regular checking account. You’ll see that the couples in the second
and third households have checking accounts owned jointly with their spouses. Remember that the total value is divided by
two and put on each person’s record. In the case of the second household, Persons
101 and 102 each have $50 on their record telling us that the total amount in that checking
account is $100. Looking at the third household we see that
Persons 101 and 102 each have values of $575 which means that there is a total of $1,150
in this joint account. Where that third household do note that the
amount is only on the record of the very couple, not on anybody else including children in
that household. TJOCHKVAL is the value of a jointly owned
with someone other than the spouse regular checking account. Person 102 in that first household has a checking
account that is jointly owned with someone other than a spouse. When an account is jointly owned with someone
other than a spouse, the respondents are asked to share the account that belongs to them. So we get – we rely on accurate reports by
respondents for this information. TDEBT_AST is total person level
debt. You’ll see that the universe for this variable
is people aged 15 plus remembering that this the definition of an adult in terms of SIPP
respondents. And then anybody who is less than 15 is non-universe
and has a missing value. In this example, the values of person-level
debt range from zero dollars to $20,000. THNETWORTH is total household level net
worth. As you see in the second household in this
example, total household net worth can be negative depending on the value of debt within
a household. As this is a household level variable, it
is on the record of every person in the household. So every person in the household will have
the same value. And again, this shows – this example shows
data for month code equals 12. You would see the same values present from
month code values of 1 through 11. So you just want to focus on one month so
that you don’t end up multiplying assets and debt amounts by 12. And as I just mentioned respondents who are
less than 15 years old are not asked the questions about assets and debt. They’re not in universe, instead, they’re missing. They do, however, get values on the household
recodes. Here’s another example. This is an example of vehicle ownership data
and it incorporates data from Wave 1 and Wave 2. We have 24 monthly records for a single respondent. I’m not showing all of the months here because
there simply is just not enough room on the screen. However, since these data do not vary within
a way, you’re not missing any information. This is a long file. So we have the Wave 1 data at the top in that
light blue color. And are identified with a month code value
of 1 through 12. So Wave 2 data are at the bottom in gray and
have month code values of 13 through 24. Remember that each SIPP wave contains month
code values of 1 through 12. So what we did when we stacked this data is
that we added 12 to the month code values in the Wave 2 cases so that we would get the
month code values of 13 through 24 and it would be easily distinguished from Wave 1
data. Notice that there is the same value across
all person months within a wave for a person. And in this example in Wave 1, TE – TVEH underscore
NUM is the number of cars the household owns. In this case, they have two cars. In Wave 2, the household owned three cars. In Wave 1, the household owned two cars. So the year of these two cars are listed under
TVEH1 or 2 underscore Year. The value of TVEH1 underscore Year should
be the newest car. In this case that is a Model Year 2014. The second car is listed under TVEH1 underscore
year and is a Model Year 2010. As you’ll see, you really can’t compare cars
across waves. You’ll see here that this household acquired
a third car between the Waves 1 and 2 interviews. In this case, the new car they acquired was
a Model Year 2015. If you look at TVEH2 underscore year, however,
you’ll see that there’s a value of 2015. Due to the top-coding procedures for TVEH2
underscore year, any car that has – is a Model Year 2013, 2014 or 2015 is collapsed into
a single category that is just given the value of 2015. So it may or may not be the Model Year 2014
car that was reported in Wave 1. And then you’ll see the 2010 car listed under
TVEH3 underscore year. These variables do have the T prefix. They are top-coded. So if you are interested in using this or
any other top-coded variable, make sure you check our data dictionary or metadata from
– make sure that you’re not misinterpreting some of the values that you’re seeing in the
data. So I’m going to wrap up the assets with a
– just a few notes about the data. The match between steps and the survey of
consumer finance is estimates is closer in the 2014 panel than it was in the 2008 panel. So for median net worth this is no statistically
significant difference between the SIPP and SCF estimates. However, the difference between the SIPP and
SCF estimates for the 25th percentile of net worth is large. It’s about 3,700 for SIPP compared to 8,700
for SCF. Many of our asset amounts do have high imputation
rates. However, the rates are lower in the 2014 panel
compared to the 2008 SIPP panel. Part of this was due to the fact that the
implemented range follow up questions to help us provide better imputed amounts. So for example, if someone said I have a retirement
account, but they couldn’t tell us the amount that was in that account. We asked well how much was in that retirement
account? Would you say it’s less than $5,000, between
$5,000 and $25,000, $25,000 and $50,000 or $50,000 or more? And then if they were able to give us answers
in some of those ranges then we would impute an amount in that range rather than from a
whole spectrum of responses. And finally the 2014 SIPP panel provides better
estimates on the value of vehicles and life insurance plans compared to previous SIPP
panels. So here’s an example of something you could
do with the assets data. Just a few things I want to mention. These published values use non-top-coded values. So as you know the public use data are top-coded. And also there were certain universe restrictions
mostly having to do with group quarters that were made when making this table that you
can’t do with the public use data. Nonetheless, you could certainly come up with
something very similar if you were so inclined. So it shows the percentage of households that
held an asset type and the median value. This next example is just an extension of
that previous slide, so they added the Wave 2 data and they also added unsecured liabilities. So you have the percent and an median value
for 2013 and 2014. That wraps up our asset section. We’ll move into income recodes now. Our income recode content includes earnings,
property income, means tested transfer payments, income from social insurance programs, income
from other sources and total income. All of our income notes are top-coded. This is done primarily for disclosure reasons. However, it does also handle concerns of outlaying
cases. So all of the components – all of our separate
individual income components are top-coded. For that we identified a top three percentage
– 3% of cases. We find the mean of those cases and then each
of those cases is given that mean value. And then the individual income data are top-coded. Those top-coded values are used in creating
our income recodes. Earnings, TPEARN is the sum of gross earnings,
wages and salary and/or the amount of monthly income positive or negative from self-employment
for each job and/or business. Property income TPPRPINC is the sum of dividend
income, interest income and property or rental income. Note that the property rental income is an
annual amount. It is divided by 12 to get a monthly amount. Means tested transfer payment, TPTRNINC is
the sum of payments from supplemental security income or SSI, temporary assistance to needy
families or TANF, passthrough child support and general assistance or GA. Income from social insurance programs, TPSCININC
is a sum of income received from VA benefits except for VA pensions, workers’ compensation,
unemployment compensation and social security. And then we have income from other sources,
TPOTHINC. It is a sum of income received from other
income sources such as survivor benefits, retirement benefits, disability benefits,
foster childcare payments, child support payments, alimony payments, lumpsum payments, deferred
payments from a prior job, life insurance payment and miscellaneous income sources. Several of those that are listed, again, are
annual amounts. They’re divided by 12 to get a monthly amount. And then where you see the numbers in parentheses
it just means that number of possible sources. So for disability benefits there are ten possible
ways you can get disability. And that will be discussed in more detail
on Thursday’s webinar, I believe. And before I forget, I want to mention that
the 2014 SIPP panel is the first to differentiate social insurance income from other income
sources. And then we have total monthly income. It is the sum of earning, property income,
means tested transfer payment, income from social insurance programs and other income. I will show you an example of how this works
momentarily. I will mention that total monthly income is
available at the person, family and household level. And it is available with and without Type
2 people. If there are no Type 2 people present in the
household in a given month, then the value with and without Type 2 people is the same. For those of us who need a reminder, Type
2 people are people who lived with a sample respondent during the reference year but not
at the time of interview. Type 2 people are not in a sample household
at the time of interview, so they don’t have a person record in the data. But we do have some information about them,
and we do have information on income and poverty status both with and without Type 2 people. Here’s an example data. We’re looking at one month of data for four
separate households. Keep in mind that the income data, the income
recode data may vary month to month. And what I’m showing you here are the personal
level income sources. So we have earnings income, property income,
means tested transfer payments, other income sources and income from social insurance programs
and then at the end we have total person income. If you sum the five income sources which are
in yellow for this top respondent, you will get the total person level income in fuchsia
for a given month. For total person income TPTOTINC, respondent
less than 15 are given values of 0. There is one exception and that was being
respondents less than 15 who receive SSI. They would have a value on TPTRNINC which
is the mean tested transfer payments. I will discuss more about this on Thursday
when we discuss programs. But as a general rule, those under 15 are
going to have a value of 0. Here we’re looking at the same household as
in the previous slide. This example is to show you how total person
income is used to create family and household income. Looking at our top household, if you look
at RFAMNUM, you’ll see that there are two separate families in this household. Persons 101, 102 and 103 are in a family. So their total person income is summed to
create total family income. Persons 104 and 105 are a separate family
in that household and their total person income is summed to a total family income. Total person income is summed across all the
people living in the same household to create total household income. To identify who is living in a single household
in a given month, you need to identify the people with the same value of SSUID and e-residence
ID in a given month. We know that they all live together when they
were interviewed, but they don’t necessarily have to had lived together throughout every
month of the referenced year. Looking at our second household, you’ll notice
that in this month, which is January, month code equals one, Person 101 lives at a different
address from Persons 102 and 103. So they have separate household income and
in each case family income equals household income. Our third household is a one-person household,
so person income equals family income equals household income. And then our final household there are two
separate families. Persons 101 and 103 are family. So their person income is summed to get family
income and Person 102 is not part of that family. So their person income equals family income. And the income is summed across all three
people in this household to get total household income. What you’re looking at here is an example
for one respondent combining Wave 1 and Wave 2. This is a wide file. I have the Wave 1 variables on the left. They have the underscore W1 suffix. And the Wave 2 variables are on the right
with the underscore W2 suffix. Here we’re just looking at total person level
income, TPTOTINC, earning income TPEARN and income from social insurance programs, TPSCININC. These respondents all had 0 dollars in reported
income from other income sources; property, means tested and income from other sources. So they’re just not shown here. On your left, as I said you have the Wave
1 data. On your right, you have the Wave 2 data. Looking at January of 2013, month code equals
1 for Wave 1. We see that total income TPTOTINC is the sum
of all the income sources. So you just had TPEARN and TPSCINIC. Remember that the other three income sources
are equal to 0. And the same thing goes for every month across
Waves 1 and 2. You just sum all of those individual income
recodes to get the total person income. And you’ll notice that income amounts may
and often do change month-to-month. That wraps up our overview of the income recodes
data and now we will turn our attention to poverty data. The poverty data includes monthly poverty
thresholds, monthly income to poverty ratios, and annual income to poverty ratios. The data allow data users to track individual’s
poverty status from month-to-month. With these data, you can create monthly poverty
statistics, do spell-base poverty analysis, and examine poverty transitions such as identifying
trigger events, excuse me, events that trigger changes in poverty status. As you may be aware already, poverty status
is a function of family size, the number of children in the household or family and age. Here is our poverty threshold table for 2014. And these are the thresholds that are used
for the official poverty measurement. So if total income is below the threshold,
you’re considered in poverty. If you are at or above the threshold, you
are considered not poor. These are annual measures. To create the monthly measures that you’ll
see in the data, we divided the annual thresholds by 12 and I will mention that the thresholds
are adjusted for this consumer price index monthly. In SIPP, family and household composition
are dynamic. That means it can change month-to-month. So if there is a change in the family or household
composition across months, you will see a corresponding change to the poverty threshold. The poverty threshold are not adjusted for
the number of days per week or days or weeks in the month. Whereas income is. So this causes income in short months such
as February to be lower relative to the poverty threshold. Thus increasing the likelihood of falling
into poverty in that month. We do have plans to correct this for the 2018
SIPP panel, but we do know if you’re working with the 2014 SIPP panel that you do this
little bump in poverty in February. Finally unlike the ACS and SIPP, excuse me,
the ACS and SCF, with SIPP we observed monthly changes in family dynamics in corresponding
changes in income and poverty status. And poverty measures in SIPP are available
with and without Type 2 people. And the presence of Type 2 people generally
increases household income and results in lower poverty estimates. Here we have the poverty variables that are
available in the 2014 SIPP. So as we mentioned in the income recode section,
we have total monthly income. Additionally, we have the poverty threshold
value. And then the monthly income to poverty ratio
and an income, annual income to poverty ratio. All of these measures are available at the
household level and the family level both with and without Type 2 people. And so you’ll see the variable name that they
are depending on which type you are interested in looking at. So let’s turn our attention to some example
data. Here we are looking at Month Code 1, January
for three different households. What you see here is total family income,
the poverty threshold and the monthly ratio both with and without Type 2 people. So within a month, you have TFTOTINC, total
family income in orange. You divide that by RFPOV, which is the poverty
threshold, and you get TFINCPOV. Which is the monthly income to poverty ratio. And then you do the same thing with the variables
that include the Type 2 people. You take the income variable with Type 2 people
divided by the thresholds, including Type 2 people and then you get the monthly income
to poverty ratio including Type 2 people. In the first and third households, you will
notice the presence of Type 2 people as indicated by the different values on income, the threshold
and the ratio with – versus without Type 2 people. So even without having to look at the Type
2 data, we know that there are Type 2 people present in these two households for the month
of January. In the second household, we see different
family units. So each family has their own total family
income, poverty threshold and ratio. Preparing Wave or without Type 2 people to
with Type 1 people we see that they’re the same value. So there are no Type 2 people in this household
in this month. So now let’s combine data from Waves 1 and
2 for a single respondent. This is Wide File. We have total household income, monthly household
threshold values, the monthly income to poverty ratio, and the annual income to poverty ratio. On the left in blue is data from Wave 1. It has the underscore wave, W1 suffix on the
right in orange. Data from Wave 1, it has the underscore W2
suffix. So within a given month, if you were to divide
THTOTINC, divided by RHPOV, you get THINCPOV which is the monthly income to poverty ratio. And you will see that this changes, can change
month-to-month as income changes or the threshold changes. We also include annual measures on the data
file. So if you were to sum all of the monthly total
household income in yellow, you would get their annual income. Similarly, if you were to sum RHPOV, you would
get the sum of – you would get the annual ratio, excuse me, the annual threshold. And then if you divided that total annual
income by the total annual threshold, you would get the annual poverty ratio which you
see in red. This is an annual measure. So it’s going to have the same value for a
all months of the reference year. And in this case for the 2014 SIPP panel,
a reference year is the same as the calendar year. And you would do the same for Wave 2. Sum the total household income. Sum the total household thresholds and then
you would get the total annual income to poverty ratio for Wave 2. I will briefly discuss our supplemental poverty
measure. So since the creation of the official poverty
measure in 1964, several changes to the social safety net and taxes have occurred. These include a vast expansion of a supplemental
nutrition assistance program, SNAP or food stamps for under $1 million in relief in 1964
to over $40 million today. The introduction of Meda, Medicare and Medicaid
programs in 1965 and 1966 respectively, the creation of the earned income tax credit in
1975 and large changes to the tax code. In November of 2011, the Census Bureau released
its first supplemental poverty measure of SPM report. The SPM follows the official poverty measure
in using the current population ASAK and includes broader measurement units of families revised
poverty thresholds including a larger share of consumption than food consumption used
in the official poverty measure, geographic adjustments, medical out of pocket expenses,
transfer income and tax adjustments. This slide nicely summarizes the difference
between the official poverty measure and the supplemental poverty measure. For the official poverty measure, the measurement
unit are families who are people related by blood, marriage or adoption. For SPM, the measurement unit are resource
units which is the official family definition plus any co-resident unrelated children, foster
children, unmarried partners, and their relatives. The poverty threshold for the official poverty
measure is three times the cost of a minimum food diet in 1963. This special varies by family size, composition,
and age of householder. And it has been updated annually based on
the consumer price index. In contrast, the SPM’s poverty threshold is
based on expenditures of food, clothing, shelter and utilities. This threshold varies by family size and composition. Additionally there are geographic adjustments
for differences in housing cost by tenure and it is updated annually using a five-year
moving average of expenditures on food, clothing, shelter and utilities. For the official poverty measure, resources
are measured as grossed, pre-taxed, cash income. For the SPM, resources are measured as the
sum of cash income, plus noncash benefits that resource units can use to meet their
food, clothing, shelter and utility needs minus taxes, work expenses, medical expenses
and child support paid to another household. The 2014 SIPP has many useful features for
implementing the supplemental poverty measure. We have detailed questions about earnings,
program participation and benefit amount. Medical expenses, work and childcare expenses
and child support paid. Additionally the household relationship matrix
variables which are RREL1 through RREL30 and the correspondent RREL_PNUM 1 through 30 as
was discussed in our demographics webinar a couple weeks ago. And we have the inclusion of Type 2 individuals
that helps to identify SIPP household relationships. We also have questions regarding whether household
filed a tax return, their filing independents status and whether the received the earned
income tax credit which is helpful in calculating taxes paid and tax credits received. For more information, check out this website. That’s all about the supplemental poverty
measure. That wraps up our content portion of today’s
webinar. Now I will just point you to some handy resources. So up on the website, you will find exercises. We have a handout with information about the
exercise as well as SAS and data solution code. We have an assets, a couple of asset exercises,
some for income recodes and some for poverty. As I mentioned, we do have the assets handout
available on the website. And you can access all of those materials
at this website. For general data resources when it comes to
SIPP, you have our SIPP website. There’s also the SIPP FTP site where you can
just kind of directly access data or data dictionaries. And the NBER has a great SIPP webpage. I think it is particularly useful if you’re
not SAFF savvy. They also have the data available in a data
and SPSS. Although for the 2014 SIPP panel, we did release
the data in SAS and Stata for the first time. The SIPP website is probably your best overall
resource. There we have our users guide, our metadata,
our release notes, user notes, codebook, and a crosswalk; so 2008 to 2014 and 2014 to 2008. If you are interested in the topics that we’ve
talked about today. Here are a couple of publication available
on the SIPP website that are related to the data that we talked about. We have the network of households, improvements
to measuring the network of households and the monthly and average monthly poverty rates
by selective demographic characteristics and there are other SIPP publications on other
topics here as well. So the next webinar in this series is scheduled
for June 20 which is Thursday. We will cove programs, adult well-being and
food security. If you’re interested in the Census webinar,
there’s the Web site again and then again on the right is the topic and their dates. Those that we already have done are or will
be available on the Web site if you missed and you want to catch up. So with that, I want to thank you all for
joining us today. Here is the SIPP email address an our phone
number. Please feel free to give us a call or send
us an email if you have any questions as you – regarding this data. And I think at this point, we will open up
the lines for questions. Coordinator: Thank you. To ask a question, please press Star followed
by the 1. Record your name clearly when prompted. To withdraw your question, please press Star
2. Again, if you would like to ask a question,
please press Star 1. One moment please. Our first question comes from (Jonah). Your line is open. (Jonah): Hi there, thank you. It’s pretty clear that this particular dataset
release is geared towards, you know, super researchers that are really going to crunch
numbers. I’m just wondering for those of us that don’t
want to dig that deep, do you publish summary tables by topic and geography like the ACS
would do or does Mathew Marlay: So the – SIPP is mostly at
the national and state level. (Jonah): I understand that. Mathew Marlay: Okay, so right. So we don’t have all of the substrate geographies
like ACS does. The different subject matter branches publish
different kinds of reports. I think Shelley’s slides showed a few of the
reports that we publish, and the poverty branch has put out things, research about poverty
using the SIPP numbers. If you have some specific questions that you’re
interested in, if you want to send us that in the chat, we can forward your questions
to the subject matter experts and they ought to be able to point you to anything they produced. ‘ (Jonah): So on a selective basis, they’ll
publish those types of reports. Do they understand that it’s primary national
state, will they aggregate data? Like for example, home equity averages at
the county level or is that too detailed in the geography to be statistically? Mathew Marlay: Yes, that chops our sample
too finely to be able to provide really meaningful answers. (Jonah): Okay, so you really don’t go too
much further down from the state level. Mathew Marlay: Right, not below the state
level. (Jonah): Okay, got it. Okay, thank you so much. Mathew Marlay: You’re welcome. Coordinator: Thank you. Our next questions comes from (Mary Gray). Your line is open. (Mary Gray): Yes, my names is (Mary Gray). I’m very interested in this particular webinar
that you’ve presented. I’m retired from banking and anyway, I’ve
lost a lot of assets and everything over the last 10 years due to different situations. And I want to make sure that I will get a
copy of this webinar in your registered, you know, the website. Will there be a copy sent so I can go through
this again? Shelley Irving: The slides should be available
on the website now. If you wanted to download them. (Mary Gray): Okay. Shelley Irving: The recorded portion of it
will be added in a couple of days as well as the transcript if you needed that information
as well. Deborah Rivera: We’re now sending them through
the chat. (Mary Gray): Yes, I would like to have that
information because I live in an area where poverty has become extremely relevant to this. And so I would like to – Shelley Irving: I believe Deb is sending the
link to that information right now. (Mary Gray): Okay, thank you so much. I appreciate it. Shelley Irving: Thank you for joining us. Coordinator: Thank you. Our next question comes from (Jonah) again. Your line is open. (Jonah): Sorry, I’m good. Thank you. Coordinator: Thank you. Again if you would like to ask a question
please press Star followed by 1. One moment. At this time, I’m showing no further questions. We do have one new question from (Anthony
Edwards). Sir, your line is open. (Anthony Edwards): Yes, I was just wondering
if there are any recommendations on maybe substate measures of poverty in some way,
shape or form, even if it’s not through Census if there are other sources that you are aware
of. Shelley Irving: Yes, you’re not going to be
able to get them from SIPP. I would, ASC and CPS would be your best bet
for getting any geography smaller than the state level. But again, you know, they don’t have the monthly
information that we have. So it’s a tradeoff on what information that
you want. Does that address your question? (Anthony Edwards): Yes, ma’am. Thank you. Mathew Marlay: Certainly if you’re looking
for very fine geographical measurements, the American Community Survey has a very, you
know, they’re very geographically specific. So that ought to give you what you’re looking
for. (Antony Edwards): Is there anything on a quarterly
basis? Mathew Marlay: Not that I know of. ACS is always in the field, but they only
release data once a year. And I’m not sure how frequently CPS releases
data. (Anthony Edwards): Okay, thank you. I was just – I know BLS does some quarterly
stuff. And I didn’t know if there was anything in
there that might be applicable. Mathew Marlay: So if you – this is Mathew
Marlay. If you want to send me a note including your
email address in the chat, I can forward your question to our poverty statistics branch. And they ought to be able provide you with
some specific information. (Anthony Edwards): Awesome, thank you. Mathew Marlay: You’re welcome. Coordinator: Thank you. At this time, I’m showing no further questions. Mathew Marlay: Shelley, there was a question
that just came in the chat. Do you want to answer that? Shelley Irving: Yes, I’m trying to find it
right now. Which data point do we update monthly versus
yearly? I think it’s just the monthly poverty ratios
that are adjusted month to month based on the CPI. Otherwise I think the income measures are
all just divided by 12 and it’s just that threshold, some of the threshold that’s adjusted
month-to-month. So you won’t – like if there were no changes
in family dynamics month-to-month, you would not see it. You might see a slight change in the threshold. And that’s just based on the adjustment based
on the CPI. If that does not address your question, feel
free to send us an email. Coordinator: We do have a question from (Tina
Phillips). Ma’am, your line is open. (Tina Phillips): Hi, good afternoon. I’m, thank you. I have a quick question in regards to s i p p, is it SIPP? Shelley Irving: Yes. (Tina Phillips): Yes, thank you. The – I was not able to see the webinar and
the slides. But does the data collected include the education
of the members in the household? Shelley Irving: Yes. (Tina Phillips): And the educational – does
it include the educational facilities that they’re participating in? Shelley Irving: If they are enrolled during
the reference year, we would have information, I think, about whether it was a public or
private institution. But we don’t really set anything beyond that. And it’s only if they are enrolled during
the year. For just educational attainment, we don’t have
any additional information. (Tina Philips): That’s fine. And you also give information about if a family
member is of the school age or postgraduate, excuse me, higher education status, but they’re
not participating, do you give that information as well? Shelley Irving: Are you saying just like,
are you asking about educational attainment? We have for everybody in the household, we
have what is their highest educational attainment? (Tina Phillips): Wonderful, oaky. Thank you so much. Coordinator: At this time, I have no further
questions. Deborah Rivera: Okay, thank you (Christy). This is Deborah Rivera again. Once again we’d like to thank everybody for
joining us and taking time out of their day to listen in on the webinar for income, poverty,
and – Shelley Irving: Assets. Deborah Rivera: – assets. That’s what I was missing. Thank you, Shelley. So we’re just going to hang around a few more
minutes before we conclude today’s session in case we do have some last minute questions
coming in. But in the meantime, I just wanted to let
everybody know that once you log off from the WebEx session if you were able to join
us, you were going to have a popup link and that is for an evaluation survey. We would appreciate it if you could just take
a few minutes out of your time to give us your feedback, any comments or if you have
additional suggestions on other topics that you’d like to see us cover in the future,
so yes, we’d appreciate it if you could take just a few minutes and fill that out. Don’t forget to join us for the next webinar
for the SIPP webinar series that I taking place on Thursday, June 20. It begins at 2:00 p.m. Eastern Time. And that webinar will be on programs, adult
well-being and food security. So if there are no more questions, we’ll go
ahead and conclude today’s session. Thank you again. Coordinator: Thank you. This does conclude today’s conference. Thank you all for participating. You may disconnect at this time.

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