Category Archives: Core-Based Statistical Areas

Metropolitan Area New Residential Construction in 2017

.. understanding the housing situation; examining housing supply and demand market conditions; assessing trends for metropolitan areas … and how metros of interest are changing .. tools and data to examine patterns and change.

During 2017, cities and counties in permit issuing places authorized the construction of 1,281,977 new privately owned housing units with a total valuation of $258.5 billion. This was 1.4 percent above the annual estimate of 1,264,051 housing units and is a 6.2 percent increase from the 2016 total of 1,206,642.

Patterns of New Residential Construction by Metropolitan Area
The following graphic shows the 20 largest metropolitan statistical areas (MSAs) based on the number of new residential housing units authorized in 2017. Click graphic for larger view showing MSAs labeled with rank and name.

View created with CV XE GIS. Click graphic for larger view.

Residential Construction Data Analytics — Using Tools & Data
Visit the related Web section to access interactive table and GIS/GeoSpatial analytical tools and data.

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.
 

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.

 

 

Metro 2016 Demographic-Economic Data Analytics: Social Characteristics

.. part one of four parts focused Metro 2016 Demographic-Economic Data Analytics.  This post is on Social Characteristics; ahead: general demographics, economic characteristics and housing characteristics. See related Web section.

Patterns of Educational Attainment by Metro
The following graphic shows patterns of educational attainment (percent college graduate) by Metropolitan Statistical Area (MSA). Legend shows color patterns associated with percent college graduate values.

– View developed using CV XE GIS software and associated GIS project.
– use these resources to develop similar views for any area.
– modify subjects, zoom, colors, labels, add your data.

A Selected Social Characteristic & How Metros Vary
In 2016, the U.S. percent college graduates was 31.3 percent (of the population ages 25 and over) while Metropolitan Statistical Areas (MSAs) ranged from 11.3% (Lake Havasu City-Kingman, AZ MSA) to 60.6% (Boulder, CO MSA). See item/column S067 in the interactive table to view, rank, compare, analyze metros based on this measure for 2016 … in context of related social characteristics. These data uniquely provide insights into many of the most important social characteristics.

Social Characteristics – Subject Matter Covered
– Households by Type
– Relationship
– Marital Status
– Fertility
– Grandparents
– School Enrollment
– Educational Attainment
– Veteran Status
– Disability Status
– Mobility; Residence 1 Year Ago
– Place of Birth
– Citizenship Status
– Year of Entry
– Region of Birth
– Language Spoken at Home
– Ancestry
– Computers & Internet Use

Metro Data Analytics
Use tools, resources and methods to access, integrate and analyze social characteristics for metropolitan areas or Core-Based Statistical Areas (CBSAs). The table includes data for 382 Metropolitan Statistical Areas (MSAs) and 129 Micropolitan Statistical Areas (MISAs). These data will update in September 2018.

Approximately 600 subject matter items from the American Community Survey ACS 2016 database (released September 2017) are included in these four pages/tables:
• General Demographics
• Social Characteristics — reviewed here
• Economic Characteristics
• Housing Characteristics
See related Metro Areas Population & Components of Change time series data.

Focusing on Specific Metros & Integrated Multi-sourced Data
While these data provide a good cross section of data on social characteristics, this access structure is a) for one time period and b) data sourced from one statistical program. Also, there is a lot going on in metros; these are typically large areas with many important and diverse smaller geographies such as cities, counties and neighborhoods among other others.

Use the Metropolitan Situation & Outlook (S&O) reports to develop extended insights. See this example of the Washington, DC MSA S&O Report. Examine trends and projections to 2030. Inegrate your own data.

Using the Interactive Table
The following example illustrates use of the metro social characteristics interactive table … try using it on areas of interest. This view, showing metros partly or entirely in Arizona, was first developed by using the state selection tool below the table Next the selected columns button the table is used to examine educational attainment columns/items. The final step was to click the header cell on the “S067” item to sort metros on percent college graduates. It is easy to determine that the Flagstaff metro has the highest percent college graduates (home to Northern Arizona University).

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 10 Largest Urban Areas

.. why it matters .. among other reasons, these 10 areas have 24% of the total U.S. population. Three have increased by more than 20% in the past 5 years.

More than 80-percent of America’s population is urban, but far more than 80-percent of America’s geography is rural. Census 2010 shows that America’s urban population increased by 12.1 percent from 2000 to 2010, compared to the national overall growth rate of 9.7 percent. Urban areas now account for 80.7 percent of the U.S. population, compared to 79.0 percent in 2000.

America’s 10 Largest Urbanized Areas
The following table shows the largest 10 Urbanized Areas (UAs) based on the American Community Survey 2011 and 2016 1-year estimates (ACS2016) and change over the period. UAs are sorted in descending order based on the 2016 population estimate. Note that Atlanta, Dallas and Houston moved up in rank.

Geodemographic relationships vary widely between the urbanized areas (UAs). Some, such as Miami, comprise most or all of the urban area within the corresponding metropolitan statistical area. Others, such as Philadelphia, are nested within a mix of adjacent urban areas interspersed with rural areas. Among other things, these different geodemographic structures reflect how planning, needs assessment and market development vary widely from associated metro-to-metro. These data show the importance and need to consider the urban/rural population distribution even in the largest metros.

Visual Analysis — Dallas Urbanized Area
The urbanized area (UA) of the corresponding metropolitan statistical area (MSA) generally occupies less than half of the MSA.
See the Dallas-Fort Worth-Arlington, TX MSA Situation and Outlook Report

… View developed using CV XE GIS.

Map Views for Each of the Largest 10 Urbanized Areas
Maps for each of the 10 largest UAs are shown at
http://proximityone.com/urbanareas_2016.htm.

Each graphic shows the designated urbanized area in a darker salmon color fill pattern, associated metropolitan statistical area with bold brown boundary, and other urban areas with a lighter shade of salmon fill color, counties black boundaries and yellow labels. The ACS 2016 UA population is shown as a white label under the UA name. The ACS 2016 estimates are the most recent data available and will update with 2017 estimates in late 2018.

More About Analyzing Urban/Rural Patterns and Characteristics
See the related section on America’s urban/rural population and geography:
http://proximityone.com/urbanpopulation.htm.

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 L

Creating Custom Demographic Datasets with API Tools

.. develop national scale spreadsheet files with virtually no learning time .. easy-to-use API operations to create national scope demographic-economic datasets based on American Community Survey 2016 1-year estimates .. custom subject matter selections. See more detail in related web sections ACS2016 and ACS2016_API.

Benefits and utility … how to acquire a spreadsheet showing the population of all cities with population estimates based on the ACS 2016 1-year data? … or, housing units, median household income, median housing value, etc.? Variations of this need frequently arise — what is the list of largest California counties sorted on total population: What are the 25 metros having the highest median household income? Which 10 congressional districts have the highest poverty incidence? Which urban areas have the highest educational attainment?

Use simple API calls described below to get answers to these types of questions — and more.  Create files that can be used for recurring applications. An example …

Urban Areas with 2016 Population 65,000+ Population
… results from using the API downloaded data … the following graphic shows urban areas with 65,000 or more 2016 population; zoom-in to Texas. The full national scope GIS project is available as described below; examine U.S. or any region. The file used to develop this view was created using the results of the API call reviewed below (requires integration of those data into the urban areas shapefile). Click graphic for larger view; expand browser window. Larger view shows urban areas labeled with name and mini profile for Dallas UA showing all subject matter items downloaded (via API) as described below.

… View developed using CV XE GIS.
… See more about Urban Population & Urban Areas.

Access ACS 2016 1-Year Data Using API Tools
Here are the API links … use these API calls to access/download selected items for selected geographies. See more about using API tools. Click a link and receive a return page with CSV-like structured data. See usage notes below. As these are ACS 2016 1 year estimates; geographies are only available for areas 65,000+ population.
Click a link:
• All U.S. cities/places
• All U.S. counties
• All U.S. CBSAs
• All U.S. Urban Areas
• All 115th Congressional Districts
• All U.S. states
• U.S. only

The following data retrieval operations are by state. These are examples using Arizona (FIPS state code 04).
• All [within state] Elementary School Districts
• All [within state] Secondary School Districts
• All [within state] Unified School Districts

API Call Returned Data Usage Notes
Clicking the All U.S. cities/places link above generates a new page with content very much like a CSV file. Try it .. click an above link.

See the related ACS2016_API web section for more details.

Items Retrieved in the API Calls
The sample header record above shows the subject matter item listed at the left in the following set of items. Modify API call and use other subject matter items. See full array of subject matter – xlsx file.
.. 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_025E — Housing units value $1,000,000 to $1,499,999
.. B25075_026E — Housing units with value $1,500,000 to $1,999,999
.. B25075_027E — Housing units with value $2,000,000 or more
.. B25002_003E – Vacant housing units
.. B25077_001E – Median housing value ($) – owner occupied units
.. B25064_001E – Median gross rent ($) – renter occupied units

The rightmost fields/columns in the rows/records contain the area name and geographic codes.

Using API Tools for Data Analytics
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 L

Important Upcoming Data Releases: September 2017

.. monthly updates on recent & upcoming data analytics tools & resources .. this section provides a monthly update on important new data developments and applications/developments to further their use in data analytics. A focus of this section is on new or revised geographic, demographic and economic data. Most of these data are used to develop and update ProximityOne census tract-level up demographic-economic projections to 2022 and county-level up population by single year of age projections to 2060. See about September projection updates below on this page. This section is organized into recent past data updates and upcoming (month ahead) data releases and may be updated to reflect new or extended details. See related news and updates:
• What’s New daily updates
• Situation & Outlook Calendar

See related Web section.

Recent Past Data Releases/Access

U.S. by Census Tract 2017 HMDA Low & Moderate Income (FFIEC)
• Release date — 8/17; next update — mid 2018
• 2017 annual HMDA data — covers all income levels not only LMI
• New 2017 HMDA data
• See more information – access data.

U.S. by County Population by Single Year of Age (NCHS)
• Release date — 8/22/17; next update — mid 2018
• 2010 through 2016 annual population by single year of age
• New 2016 data extending annual series 2010 forward
• See more information – access updates.

Housing Price Index (FHFA)
• Release date — 8/22/17; next update — 11/28/17
• Quarterly HPI
• New 2017Q2 data extending quarterly time series.
• See more information – access updates.

Quarterly Gross Domestic Product by State (BEA)
• Release date — 9/20/17; next update — 11/21/17
• Quarterly GDP by Industry
• New 2017Q1 data extending quarterly time series.
• See more information – access data.

Upcoming Data Releases/Access 

2017 TIGER Digital Map Database (Census)
• Expected ~ 9/7/17
• Topologically Integrated Geographic Encoding & Referencing (TIGER) data.
• Geographic data; predominately shapefiles.
.. intersection to intersection road segment geography and attributes.
• New 2017 GIS/mapping shapefiles for use with wide-ranging data
.. including with Census 2010, ACS 2016 & other subject matter.
• See more information – updates to access summarized in that section.

Census of Employment and Wages (BLS/CEW)
• Release date — 9/6/17; next update — 12/5/17
• AKA ES-202 data — establishments, employment & wages by NAICS code/type of business
• U.S. by county.
• New 2017Q1 data extending quarterly time series.
• See more information.

2016 American Community Survey 1-year estimates (Census/ACS)
• Release date — 9/14/17
• Wide-ranging demographic-economic data for areas having population 65,000+
.. all states, CDs, PUMAs, MSAs and larger cities/CBSAs/school districts/counties (817 of 3142)
• New 2016 estimates.
• See more information – updates to access summarized in that section.

SY 2015-16 Annual School & School District Characteristics (NCES)
• Expected ~ 9/14/17
• National school school & school district characteristics.
• New 2015-16 school year administratively reported data.
• Schools … see more information – access updates.
• School District … see more information – access updates.

2016 Annual Gross Domestic Product by Metro (BEA)
• Release date — 9/20/17
• GDP by Industry by Metro
• New 2016 data extending time series
• See more information – access updates.

Census Tract Estimates and Projections to 2022 — ProximityOne
• Release data ~ 9/27/17
• National census tract and higher level geography demographic-economic updates
• Annual estimates & projections; 2010 through 2022
• Updated to reflect/integrate data released through 9/2017 as summarized above   • See more information.

County Population by Single Year of Age Projections to 2060 — ProximityOne
• Release data ~ 9/27/17
• National county and higher level geography demographic updates
• Annual estimates & projections; 2010 through 2060
• Updated to reflect/integrate data released through 9/2017 as summarized above.   • See more information.

Notes [goto top]
– BEA – Bureau of Economic Analysis
– BLS – Bureau of Labor Statistics
– Census – Census Bureau
– FFIEC – Federal Financial Institutions Examination Council
– FHFA – Federal Housing Finance Agency
– NCES – National Center for Education Statistics
– NCHS – National Center for Health Statistics

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.