Category Archives: Atlanta demographic economic characteristics

State of the States: Demographic Economic Update

.. tools and resources to examine the demographic-economic state of the states .. in 2016, the U.S. median housing value was $205,000 while states ranged from $113,900 (Mississippi) to $592,000 (Hawaii). See item/column H089 in the interactive table to view, rank, compare, analyze state based on this measure … in context of related housing characteristics. These data uniquely provide insights into many of the most important housing characteristics.

Use new tools, data and methods to access, integrate and analyze demographic-economic conditions for the U.S. and states. 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
• Economic Characteristics
• Housing Characteristics

GIS, Data Integration & Visual Data Analysis
Use data extracted from these tables in a ready-to-use GIS project. These ACS sourced data (from the four tables listed above) have been integrated with population estimates trend data, components of change and personal income quarterly trend data. See details in this section.

Examining Characteristics & Trends
Below are four thematic pattern maps extracted from the main sections listed above. Click a map graphic for a larger view. Use the GIS project to create variations of these views.

Patterns of Median Age by State
Yellow label shows the state USPS abbreviation; white label shows median age. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column D017 in the interactive table to view, rank, compare, analyze state based on median age.

Patterns of Educational Attainment by State
Yellow label shows the state USPS abbreviation; white label shows % college graduates. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column S067 in the interactive table to view, rank, compare, analyze state based on percent college graduates.

Patterns of Economic Prosperity by State
Yellow label shows the state USPS abbreviation; white label shows $MHI. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column E062 in the interactive table to view, rank, compare, analyze state based on median household income.

Patterns of Median Housing Value by State
Yellow label shows the state USPS abbreviation; white label shows $MHV. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column H089 in the interactive table to view, rank, compare, analyze state based on median housing value.

Examining Characteristics & Trends; Using 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 LinkedIn.

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.

Low & Moderate Income Census Tracts; 2017 Update

..  data and tools to analyze characteristics and patterns of census tract geography with a focus on low and moderate income.   See related Web page for more detail.

Of the total 75,883 census tracts for which low and moderate income data were tabulated in the HMDA 2017 data, 6,023 (8.7%) were low income, 16,873 (24.5%) were moderate income, 32,509 (47.1%) were middle income and 19,159 (27.8%) were upper income. See more about these classifications. Find out about your tracts/neighborhoods of interest and how they compare to others using data and tools provided in this section.

Analysis of the low, moderate, middle, and upper income of the population and households by small area geography is important to housing market stakeholders, lenders, investors, cities/neighborhoods and others. Low and moderate income data by block group and census tract are used for compliance, eligibility determination and program performance in many Federal programs and agencies.

• Use the interactive table below to view, query, compare, sort census tracts.
• Use tract estimates & projections to examine changing characteristics.
– extended demographic-economic measures, annual 2010-2022

Low & Moderate Income by Census Tract
The following view shows census tracts designated as low and moderate income (orange fill pattern) in the the Houston, TX MSA (bold brown boundary) area. These are tracts having income level with codes 1 and 2 in the interactive table. A wide range of market insights can be created zoom-in views for counties, cities and neighborhoods and linking these with other data. Make variations of this view using ProximityOne data and tools described in this section.

– View developed using CV XE GIS and related GIS project.

View similar maps for these areas:
.. Atlanta metro
.. Chicago, IL metro
.. Dallas, TX metro
.. Knoxville, TN metro
.. with drill-down views for Knoxville city
.. Los Angeles, CA metro
.. San Francisco, CA metro

Using the Interactive Table
  – Examining LMI Tracts in Your Metro

Use the interactive table to view, query, sort compare tracts based on various demographic and LMI characteristitcs. The following graphic illustrates how the table can be used to view low and moderate income tracts for the Charlotte, NC-SC metro.
– click ShowAll button below table.
– enter a CBSA code in the edit box at right of Find CBSA LMI>.
– click the Find CBSA LMI button.
Resulting display of Charlotte metro LMI tracts only.

– click graphic for larger view.

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 Population & Components of Change Trends 2010-2016

.. tools and data to examine how the U.S. by metro population is changing. Is the population moving away or into metros of interest? What are the trends; what is causing the change? What are the characteristics of the population moving in and out? How might this impact your living environment and business?

This section provides information on how and why the population is changing by metro from 2010 to 2016 in terms of components of change: births, deaths and migration. It provides a summary of tools, interactive table and GIS project, to analyze population change by metro using latest Census Bureau estimates through 2016. These data are used by ProximityOne to develop/update annual demographic-economic projections.  See related Web page to access full interactive table and more detail.

Patterns of Population Change by Metro, 2010-2016
The following graphic shows how metros (MSAs – Metropolitan Statisticsl Areas) changed from 2010 to 2016 based on percent population change. Click graphic for larger view; expand browser window for best quality view.

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

Narrative Analysis of Metro Demographic Change in Context
A narrative summary and analysis of metro demographic characteristics and change, contextually with other data and geography, is provided for each metro in the Situation & Outlook Reports. See more about the wide-ranging subject matter that are knitted together in the schedule of updates. Examine metro dynamics in context of the U.S. overall and related states and counties.

The nation’s 382 Metropolitan Statistical Areas (MSAs) had a population of 277.1 million in 2016 (86% of the total population). MSAs increased by 2.3 million people from 2015. The nation’s 551 Micropolitan Statistical Areas (MISAs) had a population of 27.7 million in 2016 (9% of the total population). MISAs increased by 16,000 people from 2015. See more highlights below

MSAs and MISAs together, or metro areas, comprised the set of Core-Based Statistical Areas (CBSAs). Each metro/CBSA is defined as a set of one or more contiguous counties.

Related Sections
• Metros Main
• Situation & Outlook Reports
• City/Place Population Trends
• County Population Trends
• County Population Projections to 2060
• ProximityOne Data Service

Examining Population Components of Change
Population change can be examined in terms of components of change. There are three components of change: births, deaths, and migration. The change in the population from births and deaths is often combined and referred to as natural increase or natural change. Populations grow or shrink depending on if they gain people faster than they lose them. Examining a county’s unique combination of natural change and migration provides insights into why its population is changing and how quickly the change is occurring.

See more about these topics below:
• Natural Increase/Change; birth & deaths
• Migration; net international, net domestic, net migration

Using the Interactive Table – Peer Group Analysis
Use the full interactive table to examine U.S. national scope metros by population and components of change. Consider an application where you want to study metros having a 2016 population between 250,000 and 300,000. Use the tools below the interactive table to select these metros as illustrated in the graphic shown below. The graphic shows these metros ranked on the overall U.S. metro rank (percent population change 2010-2016). As shown in the graphic, the Greeley, CO metro was ranked 11th among all metros and the fastest growing metro in this group. Use the tools/buttons below the table to create custom views.

Click graphic for larger view.

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.

TractWatch — Examining Small Area Change

Understanding the demographic-economic landscape for small area geography and how it is changing is vital for many stakeholders. Businesses and other organizations need to know how their market/service areas are changing … getting answers to questions like knowing about recent trends, where we are now and the how/where/how much things might change in the future.

Examining Tract Change
The following view shows census tracts (black boundary) located in the northeast Houston, TX area. Tracts are labeled with 2017 population estimates and percent population change from 2010 to 2017. Tract geography and characteristics are shown in context of three cities/places — Houston (orange cross-hatch), Humble (blue) and Atascocita CDP (green). It is easy to see what census tracts intersect with what cities and where. The pointer/hand is located in census tract 48-201-240902, partly intersecting with Humble city. The tract 2017 population of 12,984 reflects an increase of 10.4% since 2010. The dark brown bold boundary at the top of this tract is the Harris County, TX boundary.

.. view developed with ProximityOne CV XE GIS and related GIS project.
.. create views like this for any area in the U.S.; add your own data.

TractWatch tells us which tracts in a region of interest changed during the past year based on quarterly observable data with only a one quarter lag.

Census Tracts & TractWatch
TractWatch is a new tool/service focused on examining recent demographic-business change for each census tract. These approximate 74,000 geographic areas cover the U.S. wall-to-wall and averaged 4,000 population as of Census 2010. Tracts have a generally stable geography between decennial censuses and are coterminous with county boundaries. Tracts cover the U.S. with more than a 2-to-1 ratio compared to ZIP code areas (see tract-ZIP relationship table).

Integrated with Situation & Outlook
TractWatch insights are developed through the use of the ProximityOne Situation & Outlook (S&O) database and information system — a part of S&O demographic-economic estimates and projections developed and updated annually. The 2017 vintage tract estimates and projections (annual data) cover the period 2010 through 2022 (5-year projection).

TractWatch – Monitoring Change
As a part of the S&O annual estimates and projections development, a range of measures are updated quarterly at the census tract level. Quarterly data are developed that include population, housing units, vacant units, households and business establishments.

There is only a one-quarter lag in the availability of observable census tract data. For example, observable 2017Q1 data can be added to the S&O database in July 2017. Data are analyzed and converted into a TractWatch national dataset.

Situation & Outlook Reports
The Situation & Outlook Reports (S&O Reports) are updated weekly, for the U.S. and each county, metro and state. TractWatch is a part of the “Recent Change and Outlook” S&O Report section and updated quarterly. See schedule of updates the shows when TractWatch is updated.

The S&O Reports (metro and county) Recent Change and Outlook section includes a list of census tracts which have shown significant change over the past year for that geography. A table of typically 10-to-25 key tracts are listed in a table with selected demographic-business change attributes.

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.

U.S. State Capital City Demographic-Economic Characteristics

.. tools and data to examine demographic-economic characteristics of each U.S. State capital city. The profiles are part of the America’s Communities Program. The profiles help stakeholders know “where we are”, how things are changing where and by how much, and how things might change in the future. See related web section for more detail.

State Capital Cities
The following graphic shows state capital city locations as markers. This view was developed using GIS tools enabling creation of similar views in context of other geography and subject matter. Orange markers are cities with less than 65,000 population; blue markers are cities with more than 65,000 population. based on percent population change. Click graphic for larger view. Larger view shows city names and urban areas. Expand browser window for best quality view.

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

State Capital City Demographic-Economic Profiles
State capital cities are listed below organized by state. Click the link within the brackets to view a demographic-economic profile for that city. The 2016 total population is shown in parentheses.

Alabama
• Montgomery, AL [0151000] (200,022)
Alaska
• Juneau, AK [0236400] (32,468)
Arizona
• Phoenix, AZ [0455000] (1,615,017)
Arkansas
• Little Rock, AR [0541000] (198,541)
California
• Sacramento, CA [0664000] (495,234)
Colorado
• Denver, CO [0820000] (693,060)
Connecticut
• Hartford, CT [0937000] (123,243)
Delaware
• Dover, DE [1021200] (37,786)
District of Columbia
• Washington, DC [1150000] (681,170)
Florida
• Tallahassee, FL [1270600] (190,894)
Georgia
• Atlanta, GA [1304000] (472,522)
Hawaii
• Honolulu, HI [1571550] (351,792)
Idaho
• Boise City, ID [1608830] (223,154)
Illinois
• Springfield, IL [1772000] (115,715)
Indiana
• Indianapolis, IN [1836003] (855,164)
Iowa
• Des Moines, IA [1921000] (215,472)
Kansas
• Topeka, KS [2071000] (126,808)
Kentucky
• Frankfort, KY [2128900] (27,885)
Louisiana
• Baton Rouge, LA [2205000] (227,715)
Maine
• Augusta, ME [2302100] (18,494)
Maryland
• Annapolis, MD [2401600] (39,418)
Massachusetts
• Boston, MA [2507000] (673,184)
Michigan
• Lansing, MI [2646000] (116,020)
Minnesota
• St. Paul, MN [2758000] (302,398)
Mississippi
• Jackson, MS [2836000] (169,148)
Missouri
• Jefferson City, MO [2937000] (43,013)
Montana
• Helena, MT [3035600] (31,169)
Nebraska
• Lincoln, NE [3128000] (280,364)
Nevada
• Carson City, NV [3209700] (54,742)
New Hampshire
• Concord, NH [3314200] (42,904)
New Jersey
• Trenton, NJ [3474000] (84,056)
New Mexico
• Santa Fe, NM [3570500] (83,875)
New York
• Albany, NY [3601000] (98,111)
North Carolina
• Raleigh, NC [3755000] (458,880)
North Dakota
• Bismarck, ND [3807200] (72,417)
Ohio
• Columbus, OH [3918000] (860,090)
Oklahoma
• Oklahoma City, OK [4055000] (638,367)
Oregon
• Salem, OR [4164900] (167,419)
Pennsylvania
• Harrisburg, PA [4232800] (48,904)
Rhode Island
• Providence, RI [4459000] (179,219)
South Carolina
• Columbia, SC [4516000] (134,309)
South Dakota
• Pierre, SD [4649600] (14,008)
Tennessee
• Nashville, TN [4752006] (660,388)
Texas
• Austin, TX [4805000] (947,890)
Utah
• Salt Lake City, UT [4967000] (193,744)
Vermont
• Montpelier, VT [5046000] (7,535)
Virginia
• Richmond, VA [5167000] (223,170)
Washington
• Olympia, WA [5351300] (51,202)
West Virginia
• Charleston, WV [5414600] (49,138)
Wisconsin
• Madison, WI [5548000] (252,551)
Wyoming
• Cheyenne, WY [5613900] (64,019)

Related Demographic-Economic Interactive Tables
Use the national scope demographic-economic interactive tables to view, rank, compare selected or all cities/places (approximately 29,500 places) using an extended set of data as used in the community profiles. The data are based the American Community Survey 2015 5-year estimates and organized into four subject matter groups:
General Demographics
Social Characteristics
Economic Characteristics
Housing Characteristics

See the related city population trends 2010-2016 interactive table to view, query, rank compare each cities are changing over time.

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.

Life Expectancy Change by County, 1980-2014

.. data and tools to examine changing life expectancy by county. Use the interactive table to examine life expectancy characteristics and related demographics for counties and regions of interest. Use the related GIS project and datasets to examine life expectancy contextually with other geography & subject matter. See details below. These data and tools are part of the ProximityOne health data analytics resources.

Life expectancy is rising overall in the United States, but in some areas, death rates are going in the other direction. These geographic disparities are widening.

Life Expectancy Change by County, 1980-2014
The following graphic shows patterns of the change in life expectancy change from 1980 to 2014. Click graphic for larger view. Expand browser window for best quality view.

– View developed using CV XE GIS and related GIS project.
– see below in this section about using this GIS project.

Life expectancy is greatest in the high country of central Colorado, but in many pockets of the U.S., life expectancy is more than 20 years lower. These data are based on research and analysis by the University of Washington Institute for Health Metrics and Evaluation.

Examining life expectancy by county allows for tracking geographic disparities over time and assessing factors related to these disparities. This information is potentially useful for policymakers, clinicians, and researchers seeking to reduce disparities and increase longevity.

Life Expectancy Change by County, 1980-2014 — drill-down view
— South Central Region
The following graphic shows patterns of the change in life expectancy change from 1980 to 2014. Click graphic for larger view. Expand browser window for best quality view. The larger graphic shows counties labeled with change in life expectancy from 1980-2014.

– View developed using CV XE GIS and related GIS project.
– see below in this section about using this GIS project.

Additional Views — use the GIS project to create your own views
.. click link to view
Alaska
Hawaii
Minneapolis metro

Using the Interactive Table
Use the interactive table to view, rank, compare life expectancy characteristics. This graphic shows California counties ranked on life expectancy change 1980-2014 in descending order. Select states or metros of interest. Click graphic for larger view.

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.