Category Archives: Geographic Information Systems

The New Urban Geography

.. the nation’s urban population increased by 6.4% between 2010 and 2020 based on 2020 Census data and a change in the way urban areas are defined. As a result of these changes, 1,140 areas containing approximately 4.2 million people, classified as urban in 2010 are now rural. See more about the 2020 urban/rural geography/population. See more about the urban population.

Patterns of the New Urban Geography

click graphic for larger view

As of 2020, there are 2,613 Urban Areas in the U.S. with a combined Census 2020 population of 265,149,027 (80%). The remaining area is defined as rural with Census 2020 population of 66,300,254 (20%).
  • Use this interactive table to view, sort urban areas.
  • Use this interactive table to view, sort states by 2010/2020 urban/rural.

These Federal designated urban areas are comprised of densely settled core of census blocks that meet minimum housing unit density and/or population density requirements. This includes adjacent territory containing non-residential urban land uses. To qualify as an urban area, the territory identified according to criteria must encompass at least 2,000 housing units or a population of at least 5,000. Rural encompasses all population, housing, and territory not included within urban areas.

Importance of Urban/Rural Designations
Data users and researchers interested in analyzing data for urban and rural population and housing use urban area geostatistical data routinely updated by statistical agencies. Analysts use urban area data to study patterns of urbanization, suburban growth and development, and urban/rural land area change.

Larger Urban Areas form the nucleus of Core-Based Statistical Areas (metros). Many metro areas (one or more contiguous counties) contain large rural areas even though some consider metros as large cities. Importantly, they are not the same.

Various federal and state agencies use urban and rural definitions as the basis for their own urban and rural definitions and settlement classifications for use in tabulating and presenting statistical data. The National Center for Education Statistics uses the urban area definitions in its locale codes classification. The U.S. Department of Agriculture uses the urban area classification as the basis for various urban and rural classifications used to analyze and report on demographic and economic patterns in rural areas.

Other government agencies use Urban Area designations to determine program eligibility and in their funding formulas. The Federal Highways Administration uses urban areas of 50,000 or more population to establish Metropolitan Planning Organizations. For rural health programs, a clinic qualifies as a rural health clinic if it is located outside the boundaries of any urban area.

GeoSpatial Analysis of New Urban Geography
Use the VDA Web GIS to examine urban/rural area geographic, demographic and economic make-up and in context of other geography and subject matter.

Urban Areas in the Houston, TX Region

click graphic for larger view

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.

Naturally Occurring Retirement Communities in Path of Hurricane Ian

.. 25.8 million U.S. households had a head of household age 65 years or over in 2010; 22.1% of total households. 3.1 million households with head of household 65 years or over were located in 10,201 “naturally occurring retirement communities” (NORCs) — areas where the percent of head of household age 65 or over is 40 percent or more. Has the number of NORCs tripled by now? Where and how much .. a next blog.

Here, we review Naturally Occurring Retirement Communities in the Path of Hurricane Ian by block group (BGs) in Lee County, FL … using VDA Web GIS. The same process can be applied to any area.

The following view shows a map view of the BGs meeting the criteria. A partial list of the BGs are shown in the table below the map. In the graphic, BGs meeting the criteria show with blue cross-hatch. Zoom in, label, get a profile if viewing real-time. In the graphic, for example, BG 120710019151 (state 12, county 171, tract 001951, BG code 1) has a total Census 2020 population of 2,061.

vda_lee_norc_bgs

Step-by-Step Guide
See this VDA Web GIS tutorial showing how to develop a similar view for areas of interest.

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.

Examining Majority-Minority Population by Census Tract

.. a geographic area, such as a census tract or county, has a majority-minority (MM) population when the percent of the population less White, NonHispanic population is more than 50-percent or more of the total population. This section examines patterns of MM by 2020 census tract in the Houston, TX area using the VDA Web GIS (VDA). You can use VDA to examine patterns of MM by tract for areas of interest. All you need is a Web browser and Internet.

MM Tracts in the Houston Area
The following graphic shows patterns of the MM by tract in the Houston metro developed with VDA. The map shows tracts having more than 50% MM population with a red/salmon color. Tracts having 50% or less MM population are shown in blue/green/yellow. Harris County, TX has 1,115 2020 census tracts; 854 of these tracts have a MM population. See the partial list of those tracts by tract code and %MM in the table below the map. A query was used to determine the number of tracts meeting a criteria and sorted in descending order by %MM.

See this VDA Guide section for a step-by-step description
of how you can develop this or a similar view/analysis.

Percent Majority-Minority is a demographic attribute/measure for a geographic area. Like population density or percent population of a certain age, %MM can provide insights for stakeholders or analysts.

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.

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.

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.

Majority-Minority Population by Census Tract

.. based on the Census Bureau’s assessment of Census 2020 results, the most prevalent racial or ethnic group for the United States was the White alone non-Hispanic population at 57.8%. This decreased from 63.7% in 2010. This trend will continue into the future. Over time, interest has grown in majority-minority areas ranging from congressional districts to neighborhoods. Of the 85,190 Census 2020 census tracts, 28,317 tracts were majority-minority based on Census 2020 demographics. Decision-making information using VDA Web GIS .. examining lending institution assessment areas .. see below.
.. of the 1,113 Census 2020 census tracts in Harris County, TX (Houston), 549 tracts are majority-minority tracts based on Census 2020 data. Minority-majority areas are those areas where the resident population is less than 50% non-Hispanic whites. Use tools and methods described in this section to analyze the majority-minority patterns in your census tracts, neigborhoods, areas of interest.
Patterns of Majority-Minority Population in Harris County, TX
The following view shows patterns of Census 2020 percent majority-minority population by Census 2020 census tract in the Houston area.
This view was developed using the VDA Web GIS. You can create a similar for areas of interest. Only a Web browser is needed. In this view, the tracts layer is selected as the “active layer” and a census tract is clicked in the map window. The tract highlights with a blue hatch pattern and a profile is shown in the lower left panel. See that this tract has a Census 2020 total population of 5,380 (TotPop) and White alone, non-Hispanic population (White1NH) of 131. Use the VDA Table/Query feature to examine tracts in a spreadsheet/grid.
Majority-Minority Population by Tract Interactive Table
The following view illustrates use of the VDA Table/Query feature to examine and query the majority-minority population by tract.

This SQL statement is used to select, compute and show the data in a tabular form by tract.
select uid, geoid, totpop, white1nh, 100*(totpop-white1nh)/totpop where totpop>0 and geoid like ‘48201%’
The percent majority-minority is computed “on the fly”.
The table is ranked by on this sort instruction:
100*(totpop-white1nh)/totpop desc
The resulting table shows tracts as rows with the highest percent majort-minority at the top. A larger population tract is selected by clicking on it in the grid. The tract 48-201-331700 is selected in the table; that tract is zoomed-to in the map, and the demographics are shown in the profile (TotPop 4,045, White1NH 29).
Examining Majority-Minority Tract Patterns in Context of Lending/Mortgages
Majority-minority census tracts relates to banks/lenders and the Community Reinvestment Act (CRA). The following graphic developed using VDA Web GIS, shows locations of a California bank in context of patterns of percent majority-minority tracts. It is easy to see how bank locations relate to patterns of majority-minority tracts. Lenders and stakeholders are enabled to analyze patterns and gain insights. See more about adding/using the national FDIC bank locations data to VDA Web GIS to perform more in-depth analysis.

Using VDA GeoSelect Tool to Examine Assessment/Service Areas
The following graphic illustrates use of the VDA GeoSelect tool to select tracts around a bank location to evaluate demographic characteristics of an area .. an assessment area or service area. As tracts are selected they are shown with a hatch pattern. The Profile panel, lower left, is dynamically updated to show aggregated demographics for the set of tracts selected including total population and race/origin details.

Using the Visual Data Analytics (VDA) Web GIS
Learn more about VDA.
Sign-in to to VDA using browser, nothing to install.
Select the “Base — Majority-Minority Tracts” GIS Project.
The opening view shows majority-minority tract patterns, similar to the above graphic/view.

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. Warren Glimpse/ProximityOne/Alexandria, VA USA and Takashi Hamilton/Tsukasa/Osaka, Japan are co-developers of VDA. 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.

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.