Category Archives: Statistical Programs

Population Living Alone & Age 65 Years and Over

.. how many people are living alone in your community, neighborhood? How does this population impact the community? What are their special needs? How does this population vary by area and population group? There were 37.9 million one-person households, 29% of all U.S. households in 2022. In 1960, single-person households represented only 13% of all households. These estimates are based on the 2022 Current Population Survey (CPS). Moving forward, the number of one-person households, people living alone, will increase at the rate of one million or more per year. People in households exclude people living in group quarters. This post examines patterns of people living alone with focus on people living alone age 65 year and over and distribution by small area geography.

While the CPS data provide a current snapshot of the number of people living alone, we have to use data from the American Community Survey to obtain data for smaller area geography like counties and census tracts.

Population Living Alone by Census Tract –Visual Data Analytics
The four graphics below show patterns of the population living alone by census tract. These views have been developed using the Visual Data Analytics (VDA GIS) tools with integrated demographics. Develop variations on these views using the VDA Web GIS using only a web browser.

Patterns of Population Living Alone by Tract

.. click graphic for larger view.

Patterns of Population 65 and Over Living Alone by Tract

.. click graphic for larger view.

Patterns of Population Living Alone by Tract — Houston Metro Area

Patterns of Population 65 and Over Living Alone by Tract — Houston Metro Area

Examine the Data in More Detail
As noted in this related New York Times story, nearly 26 million Americans 50 or older now live alone, up from 15 million in 2000. Older people have always been more likely than others to live by themselves makes up a bigger share of the population than at any time in the nation’s history. The trend has also been driven by deep changes in attitudes surrounding gender and marriage. People 50-plus today are more likely than earlier generations to be divorced, separated or never married. Similar ACS data as used to develop the graphics shown above are available by race/origin. These data are based on the ACS 2020 data; the same scope of data will be available from ACS 2021 to be released in December 2022.

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).

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.

Personal Economic Well-Being

.. examining characteristics, patterns and change in personal economic well-being; learning about what per capita personal income by county tells us. Per capita personal income (PCPI) is the best single measure of personal economic well-being. PCPI differs American Community Survey (ACS) measure of per capita income, median household income and similar income measures as PCPI includes non-monetary income .. PCPI provides a more comprehensive measure. This post provides an update focused on new data released November 2022, county level personal income time series data starting in 1969.

Patterns of 2021 Per Capita Personal Income by County

.. click graphic for larger view
.. use VDA Web GIS for Web-based interactive viewing/analytics.
.. see this more detailed analytical framework for analytics using VDA Desktop.

Importance of these Data
How is the regional economy doing? How is it trending? What policies might be changed to improve personal economic well-being? Answers to these and similar questions are why knowing about personal income and its derivation, components is important — to residents, businesses and governments. While median household income is often considered the best measure of buying power for an area, it is not the best measure of personal or household economic well-being. PCPI and the Regional Economic Information System provides insights and answers to these questions.

U.S. Change in PCPI
In U.S. metropolitan areas, PCPI increased 7.3 percent in 2021, up from 6.0 percent in 2020. In U.S. nonmetropolitan areas, PCPI increased 7.5 percent, down from 7.9 percent.

Regional Economic Information System
PCPI is a small part of the broader Regional Economic Information System (REIS). The following links show examples of detailed tables for Harris County, TX comparing 2019 and 2021 developed using the ProximityOne REIS package. Develop these profiles for any county for your selected year 1970 through 2021.
  • Personal Income by Major Source
  • Earnings by Source & Sector
  • Employment by Type & Sector
  • Transfer Payments
  • Economic Profile
  • Farm Income & Expenditures

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).

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.

Real Quarterly GDP Trends: State of the States

.. real gross domestic product (RGDP) decreased in 46 states and DC in 2022Q1, as real GDP for the nation decreased at an annual rate of 1.6 percent. The percent change in real GDP in 2022Q1 ranged from 1.2 percent in New Hampshire to 9.7 percent in Wyoming. Updated quarterly GDP estimates have only a 3-month lag from the reference date (e.g., 2022Q1) to access date (e.g. June 2022). Used as a time series, these data provide insights into recent economic change and prospective future change. The RGDP estimates are developed by sector, enabling an assessment of which and how sectors are contributing to change. While we look at all states in this post, California is used as an example. Examine your state(s) of interest using the tools and data described here.

See this companion video illustrating some aspects of using VDA Web GIS with the state quarterly GDP.

Analyzing Real Quarterly GDP by State Using VDA MetroDynamics
Percent Change in Real GDP, 2021Q1 to 2022Q1, U.S. by State

.. create variations of this view using VDA Web GIS .. nothing to install.
.. about MetroDynamics GIS Project
.. click here to start VDA Web GIS

Examine Real Quarterly GDP by State by Sector
GDP is estimated quarterly for 21 sectors. the following graphic shows quarterly RGDP by sector for California. Use VDA to examine these data for state(s) of interest. Step-by-step how-to details below.

View the above data as an Excel file (save to file and open with Excel).

Using VDA Web GIS to Examine GDP by State – Mapping Patterns
Follow these steps:
Start VDA Web GIS
– Select MetroDynamics Project in next form.
.. VDA user interface appears
– select States in upper left dropdown
– in legend panel, uncheck “Metros Base ..”
– in legend panel, check the top 4 States layers on
– in legend panel, check “+” by “St RGDP%Ch 21q1-22q1” layer name
.. view now shows similar to view presented above.

– click a state to view a profile of the demographic-economic attributes.
.. the profile appears in lower left panel.
.. click the HTML button, lower left, to view the attributes in HTML format.

Using VDA Web GIS to Examine GDP by State — Table/Query
Complete the above steps, then click Query/Table button (below map at right)
– a table/grid now shows below the map window
.. the table has a row for each state; columns show subject matter items
– use Select Field button to select only a few items:
  .. state name
  .. RGDP2021Q1
  .. RGDP2022Q1
  .. RGDP2021Q1-2022Q1 change
  .. RGDP2021Q1-2022Q1 % change
.. table refreshes with view shown below (sorted on RGDP2021Q1-2022Q1 % change).

Looking Ahead; Updates
New quarterly GDP by state estimates for 2022Q2 and revised annual GDP by state estimates for 2017 to 2021 and will be released on September 30, 2022.

About GDP and Measurement
State GDP estimates are updated quarterly by the U.S. Bureau of Economic Analysis (BEA). The following terminology may be a useful reference.
Gross domestic product (GDP) by state is the market value of goods and services produced by the labor and property located in a state. GDP by state is the state counterpart of the nation’s gross domestic product, the most comprehensive measure of U.S. economic activity.
Current-dollar statistics are valued in the prices of the period when the transactions occurred—that is, at “market value.” Also referred to as “nominal GDP” or “current-price GDP.”
Real GDP values are inflation-adjusted statistics, these values exclude the effects of price changes.
State GDP is the lowest geographic level for which quarterly estimates of GDP are produced by BEA.
Seasonal adjustment and annual rates. Quarterly values are expressed at seasonally adjusted annual rates.
Quantities and prices. Quantities, or “real” measures, are expressed as index numbers with a specified reference year equal to 100 (currently 2012). Quantity indexes are calculated using a Fisher-chained weighted formula that incorporates weights from two adjacent periods (quarters for quarterly data and annuals for annual data). “Real” dollar series are calculated by multiplying the quantity index by the current dollar value in the reference year and then dividing by 100. Percent changes calculated from chained-dollar levels and quantity indexes are conceptually the same. Chained-dollar values are not additive, because the relative weights for a given period differ from those of the reference year.
Chained-dollar values of GDP by state are derived by applying national chain-type price indexes to the current dollar values of GDP by state for the 21 North American Industry Classification System-based industry sectors. The chain-type index formula that is used in the national accounts is then used to calculate the values of total real GDP by state and real GDP by state at more aggregated industry levels. Real GDP by state may reflect a substantial volume of output that is sold to other states and countries. To the extent that a state’s output is produced and sold in national markets at relatively uniform prices (or sold locally at national prices), real GDP by state captures the differences across states that reflect the relative differences in the mix of goods and services that the states produce. However, real GDP by state does not capture geographic differences in the prices of goods and services that are produced and sold locally.

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.

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.

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.

VDA Mapserver: Comparing Census Tracts & ZIP Codes

.. for small area demographic-economic analysis, census tracts and ZIP code areas both have their advantages and disadvantages.  While the same scope of subject matter data are available from the American Community Survey (ACS) and ProximityOne current estimates and projections for these geographies, it can be difficult to view how the geographic areas visually relate or intersect in a map.  A flexible solution, accessible by any Web browser, is the Virtual Data Analytics (VDA) Mapserver.  See details.  You can start using VDA immediately with nothing to install.

Visual Data Analytics Mapserver
The VDA Mapserver is a learning resource, a tool that you can use for interactive mapping and geospatial analysis using only Internet and a browser. The VDA Mapserver is set apart from related tools due to the scope and style of accessing data for wide-ranging geography and frequently updated demographic-economic subject matter data. Use the unique combination of Federal statistical data with proprietary current estimates and projections.

Other geographies and subject matter will be reviewed in subject posts.

An Illustration: ZIP Code Area 85258, Scottsdale, AZ

– click for larger view.

The above shows a zoom-in to ZIP code area 85258 in Scottsdale, AZ. A step-by-by description of how to develop this view is shown in this section of the VDA guide.

As shown in the graphic, ZIP Code area 85258 intersects with 8 census tracts. ZIP code areas and tracts are not coterminous. On average there are approximately 2.5 tracts per ZIP code area. But there are more than 150,000 intersecting combinations of ZIP Code areas and tracts. See intersecting areas and interactive table.

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.

America’s Cities: Situation & Outlook

.. the path forward .. planning for the future .. in April 2019, the employment in Houston, TX was 1,111,283 with an unemployment rate of 3.2%. In April 2020, the employment in Houston, TX was 927,105 with an unemployment rate of 14.9%. What will the 2020 annual look like? 2021? There are many paths to get to 2021 and beyond. What policy and action measures might work best? What about your cities of interest? See the related Web section for more details.

Houston characteristics: Demographic .. Social .. Economic .. Housing
Get for any city/area .. e-mail your request

The pandemic impacts on America’s cities in different ways .. some experiencing little change, others with massive change. When, where and how will these disparate patterns change in cities and communities of interest? How might this change impact you and your community? A comprehensive plan needs to be developed and set in motion to achieve best outcomes. This section provides access to tools and data that stakeholders can use to examine America’s cities demographic-economic characteristics and trends. Examine cities of interest. Use ProximityOne data, tools, methods and advisory services to achieve improved results.

Of the nation’s 327.2 million people, an estimated 206.0 million (62.9%) live within an incorporated place. Of approximately 19,500 incorporated places, about 76 percent had fewer than 5,000 people and nearly 50 percent had fewer than 1,000 people. Examine characteristics of individual city population trends and compare cities in states, regions and peer groups using the interactive table below.

Patterns of Economic Prosperity; Cities 50,000 Population or More
The following view shows cities with 2019 population of 50,000 or more as markers .. mainly principal cities of metropolitan statistical areas (MSAs). Nationally, there are 69 cities with 2019 population of 5,000 or more (determine using interactive table below). The marker color shows the median household income; see inset legend. Click graphic for larger view; expand window to full screen.

– View developed using the ProximityOne CV XE GIS software.

Patterns of Economic Prosperity; Cities 5,000 Population or More
– zoom-in to Dallas Metro
The following view shows cities with 2019 population of 5,000 or more as polygons/city boundary-area in the Dallas metro area. There are 201 cities that intersect with the Dallas metro (code 19100); 96 of these cities have a population greater than 5,000 (determine using interactive table below). The color patterns show the median household income range; see inset legend. Click graphic for larger view; expand window to full screen.

Patterns of Economic Prosperity by Neighborhood & Adjacent Areas
The following view shows patterns of median household income by block group (sub-neighborhoods) within city (bold black boundary) in the Dallas County, TX area. In examining the situation & outlook for a city it is important to examine characteristics of drill-down geography and adjacent cities/areas. Inset legend shows median household income color intervals. Click graphic for larger view; expand window to full screen. In the larger view, a cross-hatch pattern is applied to Dallas city. It is easier to see how Dallas city is comprised of a core area as well as outlying areas and extends into adjacent counties.

Interactive Analysis of Cities: Demographic-Economic Patterns & Trends
Use the interactive table to view, rank, compare cities based on demographic-economic trends and characteristics. The following static graphics provide two examples.

 

Largest 15 U.S. Cities Ranked on 2019 Population

California Cities Ranked on Educational Attainment

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.