Category Archives: Decision-Making Information

Census 2020 – First Results

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

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

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

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

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

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

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

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

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

U.S. Demographic-Economic Insights

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

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

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

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

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

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

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

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

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

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

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

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

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

Housing Value Appreciation

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

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

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

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

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

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

Patterns of Median Housing Value by State

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

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

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

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

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.

Examining How Metro GDP is Changing

.. which metros had the largest 2018 real GDP? How did they change since 2010? How to they compare on a per capita basis? What about metros of interest to you? Read on …

As an investor, business or stakeholder in a metro, it is important to know how and where the economy is changing … and how one or selected metros relate to the U.S. and other metros. Is metro X changing in a different direction than metro Y? By how much, why and is there a pattern? What does the healthcare sector, for example, contribute to a metro’s gross domestic product (GDP)? How does it compare to peer metros? How is the healthcare industry trending? Metro GDP data can provide insights and answers to these important questions.  See related main Web page.

In 2018, per capita real gross domestic product (GDP) in MSAs ranged from $19,299 (The Villages, FL MSA) to $196,277 (Midland, TX MSA). The percent change in per capita real GDP by metro, 2010 to 2018 ranged from -24% (New Orleans-Metairie, LA MSA) to 126.6% (Midland, TX MSA). Use the interactive table to view these and related data.

Change in Per Capita Real GDP by Metro; 2010-2018
The following graphic shows patterns of change in per capita real GDP by metro (MSA) from 2010 to 2018. Label shows 2018 rank of the metro among all 384 MSAs based on 2018 per capita real GDP. Click graphic for larger view. Expand browser to full window for best quality view.

— view created using ProximityOne CV XE GIS and associated GIS project

Top 25 Metros (MSAs) based on 2018 per capita real GDP
The following graphic shows the top 25 metros (MSAs) based on 2018 per capita real GDP labeled with rank. Click graphic for larger view. Expand browser to full window for best quality view.

— view created using ProximityOne CV XE GIS and associated GIS project
 
Using the Interactive Table – 10 largest metros based on 2018 real GDP
— insights into comparative analytics and trends.
— view, rank, compare districts based on your criteria.
— example, which metros have the largest 2018 real GDP?
Use the interactive table to examine GDP characteristics and trends of metros. The following view illustrates use of the table. This view shows use a query to show the ten metros ranked on 2018 real GDP. Click graphic for larger view.

Try using the interactive table to examine metros 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.

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.

Insights into County/Metro Business Establishment Patterns

.. new data, released this past week, enable us to better assess county and metro business establishment patterns .. these data help businesses understand how sales of their products and services align with markets .. what counties might be underserved? .. where should marketing and sales operations be ramped up or reduced in scope/reallocated? .. what do these tell us us about organization of market territories? how are these characteristics trending by county? Use the this interactive table to examine business establishments characteristics by county and metro by type of business. See more detail in the related Web section about topics covered in this post. 

• U.S. establishments rose 1.2% from 7,663,938 in 2015 to 7,759,807 in 2016.
• First quarter employment was up 2.1% from 124,085,947 to 126,752,238
• Annual payroll was up 2.9% from $6.3 trillion in 2015 to $6.4 trillion in 2016.

Based on the 2016 data (new April 2018), there are 7.3 million establishments in Metropolitan Statistical Areas (MSAs). In these MSAs ..
• 5.3 million establishments have fewer than 10 employees.
• 6,522 of these establishments have 1,000 or more employees.
• 374 of these establishments have 5,000 or more employees.

MSAs by Number of Establishments with 1,000 or more Employees
The following graphic shows Metropolitan Statistical Areas (MSAs) by number of establishments with 1,000 or more employees. Click graphic for larger view view showing metros labeled with number of these establishments. Expand brower to full window for best quality view.
.. View developed with CV XE GIS software and related GIS project.

Business Establishment Characteristics Updated in Metro Reports
Examine 2014, 2015, 2016 mini trend profiles for establishments by 2-digit sector in Metro Situation & Outlook Reports Choose any MSA by clicking column 3 in this table .. then view section 6.3. Examples:
New York .. Los Angeles .. Miami .. Chicago .. Dallas .. Houston .. Denver .. Seattle

Gaining Insights
Gain insights into these types of patterns by county by detailed type of business (NAICS). Use the interactive table below to examine business establishment characteristics for counties and metros of interest. Data reviewed in this section are based on the Census-sourced County Business Patterns released in April 2018. We have integrated current population estimates with the establishment data in the interactive table.

Tools You Can Use
• create maps and geospatially analyze business establishments at 6-digit industry detail with ready-to-use GIS project/tools .. see related section for details.
• Use the APIGateway tools to build custom business establishment datasets.
• Use the interactive table to query/view sort business establishment characteristics by county and metro.

Data Analytics Web Sessions
Join me in a Data Analytics Web Session, every Tuesday, where we review access to and use of data, tools and methods relating to GeoStatistical Data Analytics Learning. We review current topical issues and data — and how you can access/use tools/data to meet your needs/interests.

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.

Housing Price Index Updates & Trends

.. this past week we have updated Housing Price Index data and tools to examine patterns and trends for the U.S., states, metros and counties .. the Housing Price Index (HPI) is one of many measures useful to gain insights into the housing market. The HPI provides information on how housing value appreciation is changing for areas of interest. Use the interactive table to view, compare, sort metros/CBSAs based on annual HPI 2010-2017 and housing value appreciation during the period. These annual data, with a 2000 base index value of 100, provide insights into longer term patterns.  The HPI is alos updated quarterly for U.S./state/metro areas quarterly for analyses requiring more recent data.  These data are new as of February 2018.

Visual Analysis of Housing Price Appreciation
The following graphic shows housing value appreciation as of 2017 based on the HPI with 2000 base of 100 by county in the Charlotte, NC-SC metro area. See more about by HPI by county for the Charlotte metro.

– view developed using CV XE GIS and related GIS project.
– Click graphic for larger view and details.

See similar HPI 2017 patterns view for the Houston, TX metro.

Housing Price Appreciation 2010-2017 — Largest 10 Metros
This table, derived from the  interactive table, shows the largest 10 metros based on total population. the HPI 2010, HPI 2017, housing price appreciation 2010-2017 and total population are presented in the table. Click the CBSA code link to view HPI by county component for the metro and an extended series.

 Metro CBSA HPI2010 HPI2017 HPA1017 Pop2016
 New York   35620 159.53 172.76 8.29 20,153,634
 Los Angeles   31080 169.83 242.78 42.95 13,310,447
 Chicago   16980 117.48 124.58 6.04 9,512,999
 Dallas   19100 120.89 175.35 45.05 7,233,323
 Houston   26420 134.02 183.52 36.93 6,772,470
 Washington   47900 166.82 198.74 19.13 6,131,977
 PhiladelphiaA   37980 157.26 162.91 3.59 6,070,500
 Miami   33100 140.43 213.91 52.33 6,066,387
 Atlanta   12060 103.95 129.24 24.33 5,789,700
 Boston   14460 134.33 165.27 23.03 4,794,447

– Metro names abbreviated; use table to view full name and code.

Using the HPI Annual 2010-2017 Interactive Table
The following graphic illustrates use of the HPI Annual 2010-2017 interactive table. Click graphic for larger view. This view shows metros in the 250,000-300,000 population peer group. Set your own criteria using tools below the table. There are 23 metros in this group. The table has been sorted on housing price appreciation (HPA) from 2010-2017 (second column from right). It shows that the Merced, CA metro had the highest HPA — 82.13% di=uring this period.

Use the interactive table and examine areas of interest.

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.

 

 

Examining Health Care Infrastructure by ZIP Code

.. small area data providing information on sub-county and sub-city/place geographies are challenging to locate and use — particularly in context of demand for healthcare services and demographic attributes of associated neighborhoods. Develop insights into the healthcare infrastructure by ZIP code using the two related resources reviewed here — 1) individual ZIP code demographic-economic profiles and 2) ZIP code demographic-economic interactive tables. One way to examine the healthcare infrastructure for an area is to view/analyze the number and attributes (employment, earnings) of healthcare establishments by types of business/industry (such as physicians office or hospitals). Data and tools reviewed here provide insights into characteristics and patterns of national scope ZIP code areas — examine your ZIP codes of interest.

Option 1 — ZIP Code Profiles
.. examining the healthcare infrastructure in context of the related demographic-economic situation … the following graphic shows ZIP code 10514 (Westchester County, NY) with a bold red boundary.  Census tracts are shown with black boundaries with tract codes as white labels. See more about ZIP-Tract relationships. Cities/places are shown with blue cross-hatch pattern.

– view created with CV XE GIS software and related GIS project.

The above map graphic is part of a ZIP Code 10514 profile (click link to view complete profile). Section 3.1. of the profile shows the number healthcare establishments in the ZIP Code as partly shown in this graphic:

The portion of the table shows the NAICS/type of business code at left, followed by type of business description and the number of establishments at the right.

Examine other characteristics of this ZIP code profile and in context of others via this related Web section. These profiles update in May 2018.

Option 2 — ZIP Code Health Care Sector comparative analysis
.. examining the healthcare infrastructure for a set of ZIP codes in a state, metro, county or peer group … use the interactive table located here to view/rank/compare health care business establishments by type of business for a selected set of ZIP codes. This table shows a query placed on the table to show the total number of offices of physicians for ZIP codes in the vicinity of ZIP 10514. It shows that there are 14 offices of physicians establishments and 13 have 1-4 employees.

About These and Related ZIP Code Data
Data used to develop the tools/resources described above are based in part on the Census Bureau County Business Patterns program. These establishment data update annually.

ZIP code demographic-economic interactive tables
Use the following tables to examine a wide range of ZIP code demographic-economic conditions:
  • General Demographics
  • Social Characteristics
  • Economic Chacteristics
  • Housing CHaracteristics

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.

Examining America’s Cities: Demographic-Economic Updates

.. of the approximate 29,500 U.S. cities and places — geographic areas of population concentration — 301 had an ACS 2016 5-year estimated population of 100,000 or more. The median household income among these places, one measure of economic prosperity, ranged from $26,249 (Detroit, MI) to $117,642 (Frisco, TX).

What are the demographic-economic characteristics of your cities/places of interest? How do these compare to peer groups or a metro/state of interest. Learn more using the new city/place demographic interactive tables. Its about more than economic prosperity — using these data provide otherwise unknowable attributes about the demographic, social, economic and housing characteristics of individual cities/places.

Visual Analysis of City/Place Population Dynamics
The following view shows patterns of population percent change by city in the Charlotte, NC/SC metro area.

… view developed using the CV XE GIS software.
… more about above view in City/Place Economic Characteristics section.

Patterns of Economic Prosperity ($MHI) by City/Place
— Northern Virginia, DC, Maryland; part of the Washington, DC metro.

… view developed using the CV XE GIS software.
… click graphic for larger view with places labeled by name and $MHI.

Interactive Tables — new January 2018
Use these interactive tables to get answers, build insights:
• General Demographics
• Social Characteristics
• Economic Characteristics — used to develop data at top of section
• Housing Characteristics
Related:
• City/Place GeoDemographics Main Section
• Annual City/Place Population Estimates & Trends
• Similar ACS tables: Census Tracts | ZIP Codes | State, Metro & County

More About City/Place GeoStatistical Data and Data Analytics
The term “places” as used here refers to incorporated places and Census Designated Places (CDPs). Incorporated places are political areas having certain governmental powers designated by the corresponding state. Unincorporated places, or Census Designated Places (CDPs), are statistical areas having no official standing and no governmental powers but are recognized as being areas of population concentration. Wide-ranging demographic-economic estimates are developed annually for the approximate 29,500 incorporated cities and CDPs based on the American Community Survey 5-year estimates. See more about the ACS 2016 5-year estimates.

Many cities have planning and data development operations that develop important local data including tax parcel data, building permit data, transportation and infrastructure data … bit generally not the data reviewed in this section. Many cities have no planning department to develop, organize and analyze geographic, demographic, economic data … making these data even more essential.

Increasingly in core sections of metropolitan areas, as shown in the above graphics, a large number of cities/places are contiguous. Many retain their own character evolving over many years. Having the detailed ACS demographic-economic data makes it possible to compare places side by side. Use the same data for related drill down geography such as census tracts and block groups to examine neighborhoods and market areas.

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.