Category Archives: Patterns

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.

Examine Neighborhood Demographics for any City

.. examine neighborhood demographics for any city (or county, school district ..) using the no fee, no registration new beta version of the Visual Data Analytics (VDA2) Web GIS. Nothing to install, access with any Web browser. Use this unique and powerful resource to make custom maps similar to the one shown below.

Patterns of Economic Prosperity by Neighborhood in Tampa, FL Area
Examine patterns of economic prosperity by neighborhood in context of a selected county, city or other geography. The following view shows patterns of median household income by census tract in Tampa, FL area. The bold black border shows the city boundary for Tampa; the thematic pattern shows colors associated with intervals of median household income ($MHI). The $MHI layer is set with a see through transparency enabling a view of the underlying topology. Create a view similar to this for any of the 19,500 cities in the U.S. See detailed steps to develop this view in the notes below the graphic.

Map Your Own Map View
Follow these stpe to create your own neighborhood by city map view.  Use other features of VDA2 to access demographic-economic data in a tabular or visual form.

More About VDA2 Web GIS
New in VDA2, not available in VDA1, are the table/query operations. View/analyze data for any layer in a spreadsheet/grid form.  Sort and perform queries on subject matter of interest. Click a button in the data grid to zoom to that geographic area in the map window.  The following graphic shows the VDA2 start-up view after clicking the Query/Table On/Off button. This button (shown below map window at right by pointer) toggles the table view on/off.

.. click graphic for larger view.

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.

Tip of the Day – Examining Median Housing Value – 2020 Update

.. tip of the day .. a continuing weekly or more frequent tip on developing, integrating, accessing and using geographic, demographic, economic and statistical data. Join in .. tip of the day posts are added to the Data Analytics Blog on an irregular basis, normally weekly. Follow the blog to receive updates as they occur.

.. in this era of uncertainly, we ponder the risk and opportunity associated with changing housing value.  Median housing value by ZIP Code area is one metric of great interest to examine levels and change.  While only one measure useful to examine housing characteristics, it is part of a broader set of demographic-economic data that enable analysis of the housing infrastructure and change in a more wholistic manner. How is housing value trending at the neighborhood level in 2020 and beyond? See more about the Situation & Outlook.

.. 5 ways to access/analyze the most recent estimates of median housing value and other subject matter by ZIP Code area .. based on the American Community Survey (ACS) 5-year estimates. See related Web section.

Option 1. View the data as a thematic pattern map
Option 1 is presented as Option 1A (using CV XE GIS) and Option 1B (using Visual Data Analytics VDA Mapserver). See more about GIS.

Option 1A. View $MHV as a thematic pattern map; using CV XE GIS:
— Median Housing Value by ZIP Code Area; Los Angeles Area
Click graphic for larger view with more detail.

Click graphic for larger view.
Use the Mapping ZIP Code Demographics resources to develop similar views anywhere in U.S.

Option 1B. View $MHV (ACS 2018) as a thematic pattern map; using VDA Mapserver:
— Median Housing Value by ZIP Code Area; Phoenix/Scottsdale, AZ area
Click graphic for larger view with more detail.

Click graphic for larger view. Expand window to full screen for best quality view. View features:
– profile of ZIP 85258 (blue crosshatch highlight) shown in Attributes panel at left
– values-colors shown in Legend panel at left
– transparency setting allows “see through” to view ground topology below.
Use VDA Mapserver: to develop similar views anywhere in U.S. using only a browser. Nothing to install.

Option 2. Use the interactive table:
– go to http://proximityone.com/zip18dp4.htm (5-year estimates)
– median housing value is item H089; see item list above interactive table.
– scroll left on the table until H089 appears in the header column.
– that column shows the 2018 ACS H089 estimate for for all ZIP codes.
– click column header to sort; click again to sort other direction.
– see usage notes below table.

Option 3. Use the API operation:
– develop file containing $MHV for all ZIP code areas in U.S.
– load into Excel, other software; link with other data.
– median housing value ($MHV) is item B25077_001E.
click this link to get B25077_001E ($MHV) using the API tool.
– this API call retrieves U.S. national scope data.
– a new page displays showing a line/row for each ZIP code.
– median housing value appears on the left, then ZIP code.
– optionally save this file and import the data into a preferred program.
– more about API tools.
Extending option 3 … accessing race, origin and $MHV for each ZIP code …
click on these example APIs to access data for all ZIP codes
.. get extended subject matter for all ZIP codes
.. get extended subject matter for two selected ZIP codes (64112 and 65201)

Items used in these API calls:
.. B01003_001E – Total population
Age
.. B01001_011E — Male: 25 to 29 years (illustrating age cohort access)
.. B01001_035E — Female: 25 to 29 years (illustrating age cohort access)
Race/Origin
.. B02001_002E – White alone
.. B02001_003E – Black or African American alone
.. B02001_004E – American Indian and Alaska Native alone
.. B02001_005E – Asian alone
.. B02001_006E – Native Hawaiian and Other Pacific Islander alone
.. B02001_007E – Some other race alone
.. B02001_008E – Two or more races
.. B03001_003E – Hispanic (of any race)
Income
.. B19013_001E – Median household income ($)
.. B19113_001E – Median family income ($)
Housing & Households
.. B25001_001E – Total housing units
.. B25002_002E – Occupied housing units (households)
.. B19001_017E — Households with household income $200,000 or more
.. B25003_002E — Owner Occupied housing units
.. B25075_023E — Housing units value $500,000 to $749,999
.. B25075_024E — Housing units with value $750,000 to $999,999
.. B25075_025E — Housing units with value $1,000,000 or more
.. B25002_003E – Vacant housing units
.. B25077_001E – Median housing value ($) – owner occupied units
.. B25064_001E – Median gross rent ($) – renter occupied units

View additional subject matter options.

Option 4. View the $MHV in context of other attributes for a ZIP code.
Using – ACS demographic-economic profiles. Example for ZIP 85258:
General Demographics ACS 2018 .. ACS 2017
Social Characteristics ACS 2018 .. ACS 2017
Economic Characteristics ACS 2018 .. ACS 2017
Housing Characteristics ACS 2018 .. ACS 2017 .. $MHV shown in this profile.

Option 5. View 5- and 10-mile circular area profile from ZIP center.
– profile for ZIP 80204 dynamically made using SiteReport tool.
– with SiteReport running, enter the ZIP code, radii and click Run.
– comparative analysis report is generated in HTML and Excel structure.
Click this link to view resulting profile.
– from the profile, site 2 is 1.9 times the population of site 1.
– Site 1 $MHV is $296,998 compared to Site 2 $MHV $269,734.
– GIS view with integrated radius shown below.

This section is focused on median housing value and ZIP code areas. Many other subject matter items will be apparent when these methods are used. Optionally adjust above details to view different subject matter for ZIP codes.

Join me in a Data 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.

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.

Relating ZIP Codes and Census Tracts

.. what census tracts intersect with a ZIP code of interest? There are many reasons for the underlying the need to convert/equivalence ZIP codes to/from census tracts. Some organizations have to provide census tract codes for addresses/ZIP codes of clients to be in compliance with a law or regulation. Some organizations have addresses/ZIP codes of clients/locations for which they would like to determine the corresponding census tract codes to analyze census tract demographics. This post reviews tools and options for these operations. See related Web section to access interactive table and learn more about mapping and geospatially relating these two geographies.

Phoenix/Scottsdale, AZ ZIP Code-Census Tract Relationship
The following graphic illustrates the relationship between ZIP code area 85258 (orange fill pattern) with census tracts (green boundaries and geocode labels).
(StCtyTract=04013216813).
.. view created with ProximityOne CV XE GIS software and related GIS project.

Create your own maps of areas relating ZIP codes and census tract, in context of other geography. Use the CV XE GIS with shapefiles.

Using the Interactive Table
Use the ZIP code to census tract interactive table (opens new page) to answer questions such as:
• Which census tracts intersect with a ZIP code of interest?
• Which ZIP code(s) intersect with census tract(s) of interest?
• What is the Census 2010 population for a census tract and ZIP code combination?

The interactive equivalence/look-up table shows a row for each unique combination of a Census 2010 ZIP code area and Census 2010 census tract. The start-up view is sorted on the State-County-Tract column (StCtyTract). View ZIP codes in one state using the State selection button. To locate a ZIP code of interest, either use the Find ZIP query or sort on the ZIP code column and then scroll down the table until the ZIP of interest is located.

Example. Click Find ZIP button using the interactive table (opens new page) to view only the tracts intersecting with ZIP code 85258 (as shown in map view above). The Location 1 marker (see pointer in map) is located in the area intersecting ZIP code 85258 and census tract 2168.13. The refreshed table view is shown by the graphic below. There are nine tracts intersecting with this ZIP code; see the tract codes in the table.

Try this for a ZIP of interest:
• View the interactive table (opens new page).
• Click the Showall button below table.
• Key in your 5-digit ZIP code in edit box where 85258 now shows.
• Click Find ZIP button.
• Table refreshes showing only tracts intersecting with this ZIP code.

Scope of Tracts and ZIPs in Table
There are 150,806 rows in the table, each showing a unique combination of a census tract (73,057 Census 2010 tracts) and ZIP code area (33,120 Census 2010 ZCTAs). Each row represents an intersection of the specified census tract and ZIP code area and corresponds to a geographic area of one census block or more. The total population and housing units values have been derived by summing component census block values. The sum of the population column is 308,745,538, the United States Census 2010 total population.

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.

116th Congressional Districts & Patterns of Economic Prosperity

.. Congressional District Analysis and Insights .. tools to examine patterns of median household income .. median household income is one measure of economic prosperity. This section reviews patterns of median household income (MHI) by 116th Congressional Districts based on the 2018 American Community Survey 1-year estimates (ACS 2018). View, rank, compare the MHI by congressional district, among related demographic attributes using the interactive table on the main Congressional Districts page.

116th Congressional District Analysis & Insights
.. patterns of household income & economic prosperity:
Based on the ACS 2018 median household income (MHI):
• the MHI among all districts was $60,291
• the U.S. overall MHI was $61,937
As of November 2019:
• the 19 districts with highest MHI have Democrat incumbents
• the 10 districts with the highest Gini Index have Democrat incumbents
• there are 69 Republican incumbent districts above the all districts MHI
• there are 149 Democrat incumbent districts above the all districts MHI
• the MHI of the 236 Democrat incumbent districts is $66,829
• the MHI of the 199 Republican incumbent districts is $56,505
Median household income is only one measure of economic prosperity.
See more at http://proximityone.com/cd.htm.

Patterns of Economic Prosperity 116th Congressional District
The following graphic shows patterns of 2018 median household income by 116th Congressional District. Use GIS tools/data to generate similar views for any state and/or drill-down. Click graphic for larger view with more detail. Expand browser window for best quality view.

– view developed using ProximityOne CV XE GIS and related GIS project.

Using the Interactive Table
— view, rank, compare districts based on your criteria.
— example,which districts have the highest median household income?
Use the interactive table to examine incumbency and and demographic characteristics of the 116th Congressional Districts (CDs). The following view illustrates use of the table. This view shows use a query to show the ten CDs having highest 2018 median household income.

Try using the interactive table to existing districts and categories of interest.

Congressional District/State Legislative District Group
Join in .. be a part of the Congressional Districts/State Legislative District (CDSLD) group. Access analytical tools and data. Learn about CDSLD analytics, patterns and trends. Share insights with like-minded stakeholders.

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.

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.