Measuring & Analyzing Households by Social Class by PUMA

.. a social class is a population or household group typically referred to as a lower, middle and upper class. The size of the population or households in a social class is often determined in relationship to an interval related to the median household income of an area — from two-thirds of median household income to twice the median household income (MHI). Subsequent blog posts will address a broader definition for class determination. By better understanding composition and determinants of social class for an area, we might better understand and improve on income inequality and create new opportunities. This is a multi-part blog post on social class analytics. Click Follow at right to receive updates.

Percent Population in Households by Social Class by PUMA
.. Los Angeles area .. click for larger view.

Los Angeles metro area by social class .. PUMAs shown with black boundaries; pointer at Los Angeles-Orange County line

Percent of Households by Social Class by PUMA
.. Los Angeles area .. click for larger view.

Los Angeles metro area by social class .. PUMAs shown with black boundaries; pointer at Los Angeles-Orange County line

Using American Community Survey Microdata
We use of the American Community Survey microdata or “public use microdata samples” (PUMS) http://proximityone.com/pums.htm to develop estimates of population and households by middle class, lower class and upper class by “public use microdata area” (PUMA) http://proximityone.com/puma.htm. Microdata files are comprised of anonymized individual respondent data within PUMAs. The approximate 2,800 PUMAs cover the U.S. wall-to-wall and must have 100,000 population or more. 2010 and 2020 vintages PUMAs may be examined and compared with other geography using the VDA Web GIS http://proximityone.com/vda.htm with the MetroDynamics Project.

Social Class Participation by PUMA
Using custom software, the PUMA (ACS 2021 1 year data in this case), individual housing records are summarized for each PUMA. An estimate is developed for the lower, middle and upper class based on an algorithm.

Examine patterns of social class stratification using VDA Web GIS anywhere in U.S.
The estimates are then integrated into a PUMA shapefile. The PUMA shapefile is added to a Geographic Information System (GIS). Access this shapefile/layers using VDA Web GIS to examine patterns of social class, such as the graphics shown above, or in combination with other geography and subject matter.

About VDA GIS
VDA Web GIS is a decision-making information resource designed to help stakeholders create and apply insight. Use VDA Web GIS with only a Web browser; nothing to install; GIS experience not required. VDA Web GIS has been developed and is maintained by Warren Glimpse, ProximityOne (Alexandria, VA) and Takashi Hamilton, Tsukasa Consulting (Osaka, Japan).

Data Analytics Web Sessions
Join us in the every Tuesday, Thursday Data Analytics Web Sessions. See how you can use VDA Web GIS and access different subject matter for related geography. Get your geographic, demographic, data access & use questions answered. Discuss applications with others.

About the Author
Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Join Warren on LinkedIn.

Examining Ukraine and Region using VDA

Ukraine is a country that is now on many people’s minds. It is easy to examine the geography of Ukraine in context of the region using VDA Web GIS.

The Visual Data Analytics (VDA) Web GIS supports worldwide applications. Explore characteristics of Ukraine and the surrounding area with only a browser. There is no cost. Follow the steps described below to get started.

• Start VDA Web GIS using a browser .. link to start VDA Web GIS.
– you will need to sign-up, then you can easily revisit.
• Open the Situation & Outlook Project.
– next you will see a form asking you to select a project.
– select the Situation & Outlook project.
– the opening view is the U.S. by county.
– note that for the VDA Level 1 free version, the session closes in 10 minutes.
– just start over … you are now more familiar with operations.
– if you are new to VDA, please review getting started.
• Check on “OpenStreetMaps” in Legend Panel; left of Map Window toward bottom:

• Navigate to Kyiv, Ukraine
– Key in the name Kyiv in Find Address edit box and click Find Address button
– the view refreshes; a marker (for Kyiv location) shows in the Map Window:

• In the legend panel, click on the “Country Projections to 2050” layer
• Zoom-out to Ukraine country view
– click zoom-out button below map window 6 times (or use zoom window).
– navigate in the map window to obtain this view of the region:

• To get the above view, with Ukraine the selected country, proceed as follows:
– select “Country Projections to 2050” in the “Select Layer” dropdown (upper left)
– click anywhere in map window on Ukraine
– the crosshatching appears; a profile of Ukraine appears in lower left Profile Panel.
– click the HTML button (lower left) to view this profile in HTML format.
– browser must be enabled to show popups.
– in the HTML profile, see that the 2022 Ukraine population is 43.5 million.
• Examining Ukraine provinces — Luhansk Oblast (eastern Ukraine):
– select “Country by State” in the “Select Layer” dropdown (upper left)
– navigate to eastern Ukraine
– click anywhere on Luhansk Oblast map and the following view appears:

– the crosshatching appears showing this Oblast.
– a profile of Luhansk Oblast appears in lower left Profile Panel.
– click the HTML button (lower left) to view this profile in HTML format.
– in the HTML profile, see the Oblast VDA computed area is 26,310,276,552 sqmt
… or 10,158 square miles (26310276552/2589988).

About VDA Web GIS
VDA Web GIS is a decision-making information resource designed to help stakeholders create and apply insight. VDA Web GIS has been developed and is maintained by Warren Glimpse, ProximityOne (Alexandria, VA) and Takashi Hamilton, Tsukasa Consulting (Osaka, Japan).

About the Author
Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Join Warren on LinkedIn.

Arizona’s Shifting Demographics

.. part of a state-by-state series .. these periodic posts examine how and why the state and its counties changed bwteen 2010 and 2020. Later posts will provide more of a drill-down look at change. Click the Follow link at right to receive new and updated information.

Census 2020 Arizona Demographics
The Arizona July 1, 2020 Census model-based population estimate of 7,421,401 compares to the Census 2020 population count of 7,151,502 people. The difference of -269,899 between the 2020 estimate and the 2020 count can be explained by several factors. First, the estimate is for a point in time that is three months later that the Census. There will be a tendency of the Census Bureau to adjust the Joly 1, 2020 population estimate to conform to the Census 2020 value. The July 1, 2020 estimate will likely be adjusted to reflect this change when the July 1, 2021 estimates are released April/May of 2022.

The 2020 population estimate is determined using a component method. The 2020 population estimate is the sum of the 2019 population estimate (7,291,843 for Arizona) and each of the following for the period July 1, 2019 through June 30, 2020 …
plus births (AZ 81,451)
less deaths (AZ 66,385)
plus international migration (AZ 9,272)
plus domestic migration (AZ 105,435)
plus an estimation residual (AZ -214)

Any one or a combination of these 6 estimate based values could be wrong, or the Census 2020 value could be wrong. It is likely a combination of all of these factors.

The remainder of this section is based on Census Bureau model-based estimates, released April 26, 2021. See more about these data for all U.S. counties in the Demographics 2060 section where Arizona demographic projections can be examined.

Visualizing Arizona Demographic Change
The following graphic illustrates how Arizona county demographics have changed from 2010 to 2020. The labels show the actual percent change; the color patterns, as shown in the legend, provide a visual thematic pattern view.

Examining the How and Why of Demographic Change
The following table shows a row for the state and each county, providing more detail as to the where, what/how much, how and why demographic change has occurred from 2010 to 2020.

Click graphic for larger view.

Looking Ahead
More geographically detailed data (counties for example) based Census 2020 (August 2021) will reveal much starker percentage differences between the 2020 estimates versus Census results. The ProximityOne annual estimates and projections to 2060 are developed using two basic series (and variation among those (low, base, high): Census 2020 based series and 2020 estimates series. See http://proximityone.com/demographics2060 for details.

Learn more — Join me in the Data Analytics Web Sessions
Join me in a Accessing & Using GeoDemographics Web Session where we discuss topics relating to measuring and interpreting the where, what, when, how and how much demographic-economic change is occurring and it’s impact.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Census 2020 – First Results

.. the first results of Census 2020, the apportionment data, were released on April 26, 2021.  Based on the decennial census, the United States total resident population increased from 308,745,538 (2010) to 331,449,281 (2020), a change of 22,703,743 (7.3%). For now, these data should be trusted and assumed accurate.  The apportionment data provide only total population counts at the state level.  More will be revealed about the accuracy of these data when the redistricting data are released in August 2021.

Apportionment of the U.S. House of Representatives
Congressional apportionment is the process of dividing the 435 members, or seats, in the House of Representatives among the 50 states based on the population data from the decennial census. See more about congressional districts and demographic-economic characteristics. See this related web section for detailed information on apportionment. Use the interactive table to view/analyze the Census 2010 and Census 2020 apportionment data. The following view shows patterns of congressional seats based on the decennial census. Labels show the number of seats based on the 2020 Census. Color patterns show the change in seats, 2010 to 2020.

Census 2020: the Process & Challenges
Counting the total population and selected population attributes in a pandemic is not only challenging but not possible.  During 2020, as the data were collected, it seemed good news that more than two-thirds of the potential respondents had completed the questionnaire.  But then the questions set in.  Bureau public announcements frequently made reference to the number or housing units and the number of households (occupied housing units) “accounted for” reaching 90 percent and progressively more.  By observation, using administrative record data, and other methods, housing units can be much more easily counted than the population and population attributes.  Likewise, determining the number households is  easier than determining the population count and characteristics.

The fact that the state population counts were unexpectedly different from the Bureau’s model based estimates is troubling.  We seek more assurance that the count of  population and population characteristics — by location — are as represented by the apportionment data.

Census Bureau 2020 Model-Based Estimates
New Census Bureau sourced U.S. by county model-based population estimates by age/gender/race-origin as of July 1, 2020 will be released by the Bureau in May 2021.  These estimates are independent of Census 2020 and make use of methods used annually throughout the 2010-2020 period.  An upcoming blog will report on ProximityOne’s analysis of these estimates in comparison with the Census 2020 data.

ProximityOne Estimates & Projections to 2060
ProximityOne annual demographic estimates and projections 2010-2060 by county will begin a new update cycle in May 2021.  The schedule is shown here.  

Starting with the May updates, two base projection series will be developed and progressively updated: one controlled to the Census 2020 data and one based on continued use of 2020 model-based estimates. As more information is released from Census 2020. Follow this blog for more information on evolving developments.

Learn more — Join me in the Data Analytics Web Sessions
Join me in a Accessing & Using GeoDemographics Web Session where we discuss topics relating to measuring and interpreting the where, what, when, how and how much demographic-economic change is occurring and it’s impact.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

U.S. Demographic-Economic Insights

The results of the Census 2020 will not provide us with a good picture of the United States demographic-economic situation, mainly as a result of limited scope subject matter. While the Census 2020 data are important due to their more accurate and up-to-date small area demographics, and data tabulated by census block, only a small number of demographic subject matter items are available from Census 2020. The scope of subject matter is limited by items tabulated based on the questionnaire.

In comparison, the annual American Community Survey (ACS) data provide a much broader range of subject matter. Based largely on the 2019 ACS (the most up-to-date with data for small area geography .. released in December 2020), ProximityOne has developed tools/data to develop demographic-economic insights for the most widely used types of geography.

Demographic-Economic Insights Role & Scope
ACS and related data and ProximityOne tools have been used to develop the U.S. demographic-economic insights report, reviewed here, illustrating the scope and organization of the data and how it can be used. You can develop similar comparative analysis reports for your areas of interest. See more about the role and scope of the Demographic-Economic Insights.

U.S. National Scope Demographic-Economic Insights
View the U.S. National Scope Demographic-Economic Insights report develop using the ProximityOne Insights tool. This report is organized into two subject matter description columns, four statistical data columns and four subject matter groups. The first two statistical data columns present data based on the ACS 2019 1-year estimates. The second set of statistical data columns show data based on the 2019 ACS 5-year estimates (values centric to mid 2017). This report is a useful resource to compare/contrast data values based on the 1-year estimates side-by-side with the 5-year values. The four subject matter groups are reviewed below.

General Demographics
Graphic shows partial list of “D” items .. click graphic for larger view.
.. view this section in the U.S. Insights report.

Social Characteristics
Graphic shows partial list of “S” items .. click graphic for larger view.
.. view this section in the U.S. Insights report.

Economic Characteristics
Graphic shows partial list of “E” items .. click graphic for larger view.
.. view this section in the U.S. Insights report.

Housing Characteristics
Graphic shows partial list of “H” items .. click graphic for larger view.
.. view this section in the U.S. Insights report.

Creating Insights and Talking Points
The four subject matter groups provide a dense array of tabular statistical data that can be overwhelming to consume. Yet, not every topic can be distilled to just a few numbers. The scope of key data depends on the objective presentation, audience and desired talking points.

For example, a briefing or synopsis might include only 10-15 subject matter items such as … this report tells us that in 2019 (based on 2019 1-year estimates), the total resident population was estimated to be 328,239,523. The median age was 38.5 years. The percent high school graduates was 88.6%. The number of housing units was 139,686,209. The percent owner occupied housing units was 64.1%. These measures are roughly the same today, at the end of 2020, even with the pandemic impact. Some other measures in the report as not as reflective “as of today”.

While data shown here do not fully summarize the state of the Nation, there provide many insights. The same can said for any of the geographic areas covered. To obtain a better picture of the state of the Nation, we need supplementary subject matter, more up-to-date data and trending data that give clues into what’s happening.

Learn more — Join me in the Situation & Outlook Web Sessions
Join me in a Situation & Outlook Web Session where we discuss topics relating to measuring and interpreting the where, what, when, how and how much demographic-economic change is occurring and it’s impact.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Housing Value Appreciation

.. U.S. housing prices rose nationwide in August, up 1.5% from the previous month, based on the FHFA Housing Price Index (HPI). Housing prices rose 8.0% from August 2019 to August 2020.

If you purchased a housing unit in 2019Q2 at $260,200 (the ACS 2019 median housing value), the value of the unit in 2020Q2 would be $271,000, an increase of 4.2%. A good deal in this era of low interest rates.

U.S. housing prices posted a strong increase in August .. the 1.5% increase is the largest one-month price increase observed since the start of the HPI measurement in 1991. This large month-over-month gain contributes to an already strong increase in prices over the summer. These price gains can be attributed to the historically low interest rates, rebounding housing demand and continued supply constraints.

The HPI has various limitations as a measure to assess the housing market. One important limitation is that it a measure in isolation; other related demographic-economic measures are not included. This is unlike the American Community Survey (ACS) estimates of the median housing value ($MHV), used as an annual, year-over-year measure of housing value appreciation.

Median Housing Value
The U.S. ACS 1-year estimate of median housing value ($MHV) increased from $229,700 in 2018 to $240,500 in 2019. The ACS 2020 estimate, which will be impacted by the pandemic, will not be available until September 2021. The ProximityOne 2020 estimate of $MHV is $270,500.

Click this API link to view a CSV-like file showing the 2019 median household income and median housing value by state. Join me in a Data Analytics Web Session (see below) to integrate these data into a map view like shown below. Add other data.

Patterns of Median Housing Value by State

– view developed using ProximityOne CV XE GIS
– click graphic for larger view

An advantage of using the ACS or ACS-like $MHV data is that this measure is synchronized with other related measures, like total population, total housing units, housing units by tenure and age built and so on. Though a popular measure to assess geographically comparable housing values, the $MHV has many limitations. A key limitation is that few survey responders really know the value of their home. Other limitations have to do with the definition itself and how the data are collected/developed. ACS $MHV measures value of only occupied housing units and excludes houses on 10 or more acres and housing units in multi-unit structures. See more. While there are other Federal sources of $MHV, it remains that the usabilty aspects of the ACS or ACS-like measures are second to none.

Learn more — Join me in the Situation & Outlook Web Sessions
Join me in a Situation & Outlook Web Session where we discuss topics relating to measuring and interpreting the where, what, when, how and how much demographic-economic change is occurring and it’s impact.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

How & Why County Demographics are Changing

.. the pandemic impact on population change remains in flux. For many counties it will impact each component of population change: births, deaths and migration. The magnitude and duration of the impact on each component will vary by county and become more measurable in the months ahead. The “How & Why County Demographics are Changing” will be updated later in 2020.

Here we look at population and components of change by county for the period 2010 to 2019 .. tools and data to examine how the U.S. by county population is changing. These latest 2019 estimates were released this spring. See more in the related web section.

Top 25 Counties with Largest Population Change 2010-2019
Create a table similar to the one shown below using the interactive table. Sort on selected criteria and within a selected state or metro.

Patterns of Population Change by County, 2010-2019
The following graphic shows how counties have gained population (blue and green) and lost population (orange and red) during the period 2010 to 2019. Click graphic for larger view; expand browser window for best quality view.

.. view developed with ProximityOne CV XE GIS and related GIS project.

Examining Population Components of Change
Population change can be examined in terms of components of change. There are three components of change: births, deaths, and migration. The change in the population from births and deaths is often combined and referred to as natural increase or natural change. Populations grow or shrink depending on if they gain people faster than they lose them. Examining a county’s unique combination of natural change and migration provides insights into why its population is changing and how quickly the change is occurring. The above graphic shows these relationships.

County Population & Components of Change 2010-2019 – Interactive Table
View/analyze county population and components of change characteristics and trends in a tabular manner using the interactive table. The following static graphic shows net migration 2010-2019 by year for Houston, TX metro component counties. Rows have been ranked in descending order based on 2010 population. It is easy to see how the net migration in Harris County has been decreasing annually since 2015.

Try it yourself. Use the interactive table to examine counties/areas of interest.

Situation & Outlook Web Sessions
Join me in a Situation & Outlook Web Session where we discuss topics relating to measuring and interpreting the where, what, when, how and how much demographic-economic change is occurring and it’s impact.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Financing America’s Schools

.. as we look to restarting America’s economy, the nation’s public school systems face many questions and logistical issues.  Among these issues are a wide range of financial challenges.  Financing America’s public K-12 schools is supported by a mix of Federal, state and local funding.  In FY 2017, 13,311 regular public school districts reported total revenues of $679,925 billion derived from $51,212 billion federal (7.5%), $317,434 billion state (46.7%) and $311,278 billion local (45.8%) sources. These data are based on the school district finances (F-33) program data released by the Census Bureau in May 2019. States and individual school districts vary widely on the make-up/distribution of these federal, state and local sources.  See more about this topic and related K-12 schools topics in the ProximityOne K-12 schools main Web section.

Use tools and data reviewed here to examine K-12 school district finances — sources and uses of funds for FY 2017. View, sort, query, compare school district sources and uses of funds using the interactive table below in this section. Create/view profiles for district(s) of interest.

Data and resources reviewed here update in early May 2020 with new FY 2018 sources and uses of funds data and related school/school district financial data. We examine the implications of COVID-19 for school systems as we look to Restarting the Economy. Join the User Group to receive updates.

Percent Federal Revenue by School District, FY 2017
The following graphic shows patterns of percent Federal revenue by school district (unified and secondary), FY 2017. Click graphic for larger view. Expand browser to full window for best quality view.

– view developed using ProximityOne CV XE GIS software and related GIS project.
– use these tools on your computer to examine these data & related data.

Percent State Revenue by School District, FY 2017
The following graphic shows patterns of percent State revenue by school district (unified and secondary), FY 2017. Click graphic for larger view. Expand browser to full window for best quality view.

– view developed using ProximityOne CV XE GIS software and related GIS project.
– use these tools on your computer to examine these data & related data.

Interactive Table
The following static graphic shows the 10 Texas school districts having the largest Federal revenue. Sources of Federal revenue by program are also shown. Create views like this for any of the sources and uses of funds items for your selection of school districts. Use the interactive table (separate page) for dynamic analysis of individual school districts in context of U.S. overall, states or metros. Select by state or metro and rank based on any of several selected revenue by source and per student expenditure by category.

– click graphic for larger view

Situation & Outlook Web Sessions
Join me in a Situation & Outlook Web Session where we discuss topics relating to measuring and interpreting the where, what, when, how and how much demographic-economic change is occurring and it’s impact.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Neighborhood Median Family Income: Measuring Economic Well-Being

.. Median Family Income ($MFI) and Median Household Income ($MHI) are two measures of economic well-being. Based on the 2018 American Community Survey 1-year (ACS) data, the U.S. 2018 $MFI was estimated to be $76,401 while the $MHI was estimated to be $61,937 .. both in 2018/current dollars. Create insights into patterns of well-being by neighborhood using geospatial analysis. $MFI patterns are illustrated by the following thematic pattern map.

Patterns of Economic Prosperity by Neighborhood/Census Tract
The following view shows patterns of $MFI by census tract for the inner beltway area of Houston/Harris County, TX. Income interval color patterns are shown in the inset legend. Tracts are labeled with $MFI. Click graphic for larger view. Expand browser window for best quality view. Larger view shows tracts labeled with tract code. It is easy to see how west Houston and east Houston areas differ.

– view developed with ProximityOne CV XE GIS software and related GIS project.
– these $MFI data are based on the 2018 ACS 5-year estimates.

This section focuses on $MFI but could just as well focus on $MHI and yet other related income measures. $MFI will almost always be greater that $MHI, generally by a large margin. See the U.S. 2018 $MFI and $MHI in context of related demographic-economic measure here. See more about the distinctions/definitions of families and and households below.

The ACS data are a unique source of income and related data at the neighborhood or sub-county level. View more about accessing and using the 2018 ACS 5-year estimates.

Family Definition
A family is a group of two people or more (one of whom is the householder) related by birth, marriage, or adoption and residing together; all such people (including related subfamily members) are considered as members of one family. The number of families is equal to the number of family households. However, the count of family members differs from the count of family household members because family household members include any non-relatives living in the household.

Related … an unmarried partner, also known as a domestic partner, is specifically defined as a person who shares a close personal relationship with the reference person. … Same-sex unmarried-partner families or households – reference person and unmarried partner are both male or female.

Household Definition
A household consists of all the people who occupy a housing unit. A house, an apartment or other group of rooms, or a single room, is regarded as a housing unit when it is occupied or intended for occupancy as separate living quarters; that is, when the occupants do not live with any other persons in the structure and there is direct access from the outside or through a common hall.

A household includes the related family members and all the unrelated people, if any, such as lodgers, foster children, wards, or employees who share the housing unit. A person living alone in a housing unit, or a group of unrelated people sharing a housing unit such as partners or roomers, is also counted as a household. The count of households excludes group quarters. There are two major categories of households, “family” and “nonfamily”.

Situation & Outlook Weekly Web Sessions
Join me in a Situation & Outlook web session to discuss more details about demographic-economic estimates and projections.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Personal Consumption Expenditures by Type & State

.. using Personal Consumption Expenditures (PCE) measures to monitor/examine the strength of a regional economy and consumer buying trends in that region and compare among regions … PCE estimates released in October 2019, show that state personal consumption expenditures increased 5.1 percent in 2018, an acceleration from the 4.4 percent increase in 2017. The percent change in PCE across all states ranged from 7.3 percent in Utah to 3.6 percent in West Virginia.

In 2018, across all states and D.C., per capita PCE was $42,757. Per capita PCE by state ranged from a high of $55,095 (MA) to a low of $31,083 (MS). Per capita PCE in D.C. $63,151. Use the interactive table to example per capita and total PCE by state for 24 categories annually 2010 to 2018.

Per Capita Personal Consumption Expenditures by Category; U.S. 2018
— how does your situation and areas of interest compare to U.S. overall?
— view, sort, query by state and year in the interactive table

Goods and services purchased by people are personal consumption expenditures (PCE). These data provide insights into the strength of a state economy and consumer buying trends. As a major component of GDP, PCE growth has recently accounted for much of the GDP growth. The data reviewed in this section are developed by the Bureau of Economic Analysis (BEA, released each October). ProximityOne develops regional PCE estimates by metro and county. More about PCE.

See related sections:
• State Real Median Household Income
• State Annual Gross Domestic Product by Industry

Per Capita Consumption Expenditures by State, 2018
The following graphic shows patterns of 2018 per capita personal income expenditures (PCE). Intervals show distribution in quintiles, equal number of states per interval. The 2018 U.S. per capita PCE was $42,757. Use CV XE GIS project to examine PCE by types, per cpaita vs total, different years and change. Integrate additional subject matter and types of geography. Click graphic for larger view with details. Expand browser window for bets quality view.

– view developed with ProximityOne CV XE GIS and related GIS project & datasets.

Using the Interactive Table
— which areas have the highest health care expenditures?
Use the interactive table to examine personal consumption expenditures by type and state annually for the period 2010-2018. The following view illustrates use of the table. This view shows use a query to examine only health care expenditures. The table was then sorted in descending order to show the areas with the highest per capita health care expenditures in 2018.

Try using the interactive table to existing states or categories of interest.

Demographic-Economic Analytics Web Sessions
Join me in a Demographics Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.