Category Archives: economic indicator

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.

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.

Analyzing Patterns of COVID-19

.. as COVID-19 impacts our demographics, economy and way of life, we look for answers about where we are and what lies ahead.  Here we review data on COVID-19 incidence and tools to analyze those data. In the coming days, weeks, we plan to augment these tools and data. See more below.  See related Web section for more detail.

Use new resources to examine/analyze patterns of COVID-19 incidence in context of related demographic-economic characteristics. Resources include the narrative/interpretative portion, interactive table and GIS tools and project/files. Data and tools are updated daily. There is no fee to use any of these resources.

COVID-19 Incidence by County in the Atlanta Metro Area
The following graphic shows patterns of COVID-19 incidence (number of cases per 1,000 population) by county. See color patterns in the inset legend. This view shows counties labeled with name and number of confirmed COVID-19 cases. Use the GIS project described below to create variations of this view and develop similar views for any metro.

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

The GIS resources and interactive table below makes use of the COVID-19 confirmed cases data updated daily by the New York Times. See more about the New York Times U.S. tracking page.

COVID-19 Incidence — U.S. by County
Similar to the above view, the following graphic shows patterns of COVID-19 incidence (number of cases per 1,000 population) by county for the U.S. See color patterns in the inset legend. This view shows counties labeled with name and number of confirmed COVID-19 cases. Use the GIS project described below to create variations of this view and develop similar views for any metro. Click graphic for larger, more detailed view. Expand browser window for best quality view.

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

Using GIS Tools & Resources
Use the Geographic Information System (GIS) CV XE GIS software and GIS project to view maps and geospatially analyze patterns COVID-19 cases in context of related demographic-economic data. The GIS project automatically opens with the following view:

.. see details about using the mapping/GIS resources.
.. create map views for your areas of interest.

COVID-19 Confirmed Cases by County Interactive Table
Use the interactive table to view, rank, query compare patterns of COVID-19 cases. See related demographic-economic interactive tables.

The following static graphic illustrates use of the table to view daily patterns of COVID-19 cases in Cobb County, GA.

Use the interactive table to examine counties 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.

Neighborhood Median Family Income: Measuring Economic Well-Being

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

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

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

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

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

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

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

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

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

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

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

Personal Consumption Expenditures by Type & State

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

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

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

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

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

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

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

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

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

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

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

U.S. & State Real Median Household Income Trends

.. during the past two years, 2017 and 2018, the real median household income increased by $1,627. Some states experienced a decline in real median household income in the past two years. During the previous two years, 2015 and 2016, the real median household income increased by $3,329. See details in interactive table (opens new page).

Real median household income in the U.S. increased 0.8 percent between the 2017 ACS and 2018 ACS based on the American Community Survey (ACS 2018). The U.S. MHI, based on ACS 2018 (released September 2019), was $61,937. The national MHI has been increasing since 2013. The increase from 2017 is smaller than the prior 3 years, during which MHI increased between 1.8 percent and 3.3 percent annually. This was the second consecutive year that U.S. MHI was higher than 2007.

Household income as used here is the combined gross income of all members of a household, defined as a group of people living together, who are 15 years or older. The median household income is used to examine the economic health of an area or to compare living conditions between geographic regions.

Use the interactive table and related Geographic Information System (GIS) resources to examine income trends and geographic patterns. See details on using GIS project.

Patterns of Real Median Household Income Change; 2016-2018
— change during two calendar years labeled with 2018 real MHI
— click link for larger view; expand browser window for best quality view.

– view developed using ProximityOne CV XE GIS and related GIS project.
– geospatial analyze income characteristics integrated with your data to examine patterns; gain insights.

Median Household Income in the United States: 2005–2018

U.S. & State Median Household Income: Annually 2005–2018 — Interactive Table
The following static graphic illustrates use of the U.S. & State MHI interactive table. This view shows the 10 states/areas ranked on the 2018 real median household income. See pointer, note that D.C. had the highest real 2018 MHI.  

Try it yourself. Use the table to examine different patterns … like which states experienced a decline in a selected year or over a selected period.

Alternative Measures of MHI
There are other ways to measure/estimate MHI. Possibly the most notable alternative is the Census/BLS Current Population Survey (CPS). This topic will be covered in an upcoming blog .. and how ACS and CPS MHI estimates differ. While the CPS can be used to develop state and higher level geography estimates, ACS might be preferred as MHI estimates can also be developed for counties, cities, census tracts and block groups .. and many other political/statistical areas not possible using CPS.

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.

State of the States: 2019

.. the State of the States reports and information service provide insights into demographic, economic & business characteristics.  Unique in their composition,  updated daily/weekly, the reports summarize what’s changing where & when and assessing what’s ahead. It organizes disparate Federal statistical data and presents those data in an organized, consumable manner. A resource to help determine how change might affect you, it is an indispensable resource for investors, leaders, policymakers, researchers and decision-makers. See State of the States main section for more information.  Your briefing notes, organized by state.

Some details .. the U.S. economy is slowing, dragged down by trade tensions and weak growth overseas. But there are few signs that the decade-long expansion is on the verge of stalling out. Real Gross Domestic Product (RGDP), the broadest measure of goods and services produced in the economy, rose at a 2.1 percent annual rate in 2019Q2, down from 3.1 percent in 2019Q1, according to preliminary data released by the Bureau of Economic Analysis on 7/26/19.

But what about the states, and what about related measures? In Texas, the 2019Q1 change from 2018Q4 was 5.1 percent annual rate. Texas ranked 2nd among all states. The 2019Q2 state GDP will be posted in section 6.5 on Nov. 7, 2019 (see in scheduled updates). How does Texas compare to other states and the U.S.  Answers are organized in the reports.  Create insights. Share with others.

Part of a multi-dimensional information resource, the state of the states report has been derived from the Situation & Outlook (S&O) database, updated daily. ProximityOne uses the historical S&O database to develop current demographic-economic estimate and projections.

View the U.S. or a State Report .. click a link
.. illustrative reports .. see more about report structure & options in report.
United States
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
District of Columbia
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin

Demographic 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.

County Housing Patterns & Trends

.. at a time when “housing costs are going through the roof” and “affordable housing” are topics widely in play, current housing data at the county level are essential for business and public policy planning. In this section, new Census Bureau U.S. by county 2018 housing unit estimates are viewed .. and tools to access and use these data.

Patterns of Housing Unit Percent Change by County: 2010-2018
The graphic below shows patterns of county housing unit percent change from 2010 to 2018. Click graphic for larger view showing more detail.

– view developed using CV XE GIS software and associated GIS project.
– create similar maps for counties/areas using CV XE GIS & associated GIS project.

This section reviews the new 2018 county housing unit estimates (released May 2019) and tools and applications to analyze them. See more about topics covered here in this related Web section.

The U.S. housing stock grew by more than 1.15 million from 2017 to 2018, reaching over 138.5 million units. The growth rate of 0.8 percent from 2017 to 2018. The national housing stock increased by 6.7 million units (5.1 percent) between 7/1/2010 and 7/1/2018. But housing stock change was far from even as shown in the graphic presented above.

Total housing units are the “tip of the iceberg” to examine housing market characteristics. Yet, there are no other Federal statistical data for any other housing attribute for every county more recent than circa mid-2015. Those data are from the American Community Survey 5-year estimates for the period 2013-2017 — data going on 4 years old. For example, there are no Federal statistical data for all counties for the 2018 number of households or vacant units … let alone measures that would enable computing the size and location of affordable housing, one of many important housing market attributes. Use related 2018 and projected housing market data developed by ProximityOne available as part of the Situation & Outlook demographic-economic estimates and projections. Examine these data in context with other geographic and market characteristics in the metro Situation & Outlook reports.

Using the Interactive Table
Use the interactive table to view, rank, compare states and counties based on number of units annually 2010 to 2018 and related measures. Compare counties among metros or states .. or peer groups based on size. Here are two examples of using the table.

Largest Counties based on 2018 Housing Units
.. ranked on 2018 housing units .. click for larger view

Counties with 10,000 or more 2018 Housing Units
.. ranked on percent change 2010-2018 .. click for larger view

Data Analytics Web Sessions
See these applications live/demoed. Run the applications on your own computer.
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.

Examining County Gross Domestic Product

.. what is the annual per capita real-valued output of counties of interest? How is this measure trending? Why is this important? This section reviews tools and data to examine county-level Gross Domestic Product (GDP) trends and patterns. The first ever county-level GDP estimates to be developed as a part of the official U.S. national scope GDP estimates were released in December 2018. The county GDP estimates join the county-level personal income by major source, both now part of the Regional Economic Information System (REIS). See more detail about topics reviewed in this post in the related County GDP web section.

Patterns of Real Per Capita GDP by County
The graphic below shows patterns of per capita real GDP, 2015, by county.

– View developed using CV XE GIS and related GIS project.
– create custom views; add your own data, using the GIS project.

Gross Domestic Product (GDP) by county is a measure of the value of production that occurs within the geographic boundaries of a county. It can be computed as the sum of the value added originating from each of the industries in a county.

Example … use this interactive table to see that 2015 Los Angeles County, CA total real GDP of $656 billion was just slightly larger that than of New York County, NY (Manhattan) at $630 billion. Yet, the total 2015 population of Los Angeles County of 10.1 million is 6 times larger than that of New York County of 1.6 million — see about steps. GDP provides very different size measures, and economic insights, compared to population.

In 2015, real (inflation adjusted) Gross Domestic Product (GDP) increased in 1,931 counties, decreased in 1,159, and was unchanged in 23. Real GDP ranged from $4.6 million in Loving County, TX to $656.0 billion in Los Angeles County, CA.

This post is focused on U.S. national scope county level estimates of Gross Domestic Product (GDP) annually 2012 through 2015. This marks the first time county level GDP estimates have been developed, a part of the Regional Economic Information System (REIS). Use the interactive table to rank, compare, query counties based on per capita GDP, current GDP, real GDP by type of industry. Use the related GIS project to develop thematic map views such as the one shown below. See more about these data.

Current Annual Estimates & Projections
ProximityOne uses these and related data to develop and analyze annual Situation & Outlook demographic-economic estimates and projections. GDP items included in the table below are included in the “annual 5-year” projections as shown in the schedule of release dates; next release April 18, 2019 and quarterly.

Examining County GDP Using GIS Tools
Use the County REIS GIS project. Make your own maps; select different item to map; modify colors, labels. Zoom in views of selected states shown below. Graphics open in a new page; expand browser window for best view. Patterns: see highlighted layer in legend to left of map; MSAs bold brown boundaries with white shortname label
counties labeled with name and 2015 per capita real GDP
.. Arizona .. Alabama .. California .. Colorado .. Iowa .. Georgia .. Kansas .. Missouri
.. New York .. Nevada .. North Carolina .. South Carolina .. Nevada .. Texas .. Utah .. Vermont

Using the County GDP Interactive Table
The graphic below illustrates use of the interactive table. Tools below the table have been used to view only per capita real GDP for all sectors (total sources) and for county with total population between 50,000 and 60,000. Counties were then ranked on 2015 per capita real GDP (rightmost column).

– click graphic for larger view.

Using County GDP: Data Analytics Web Sessions
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.