Census Tract Demographic-Economic Characteristics & Trends

..  Census tract demographics are used in wide-ranging public and private sector applications to examine patterns and characteristics of sub-county areas. Tract level data from Census 2000, Census 2010 and the American Community Survey (ACS) can be used to analyze trade/market areas, neighborhoods and other small area study areas. But what about more current data and trends since 2010? What about business establishment data and other subject matter not included in either the census or ACS data?

There are no current demographic-economic census tract data available from the Census Bureau or other Federal statistical programs. Annually released ACS 5-year estimates are available by census tract but are for 5-year periods and dated. The most recent census tract level ACS data are based on the ACS 2017 5-year estimates (ACS 1317). Those data are not for the year 2017 but estimates for ACS survey respondents for the 5 year period 2013-2017; centric to mid-2015.

Patterns of Median Household Income %Change by Census Tract
The graphic below shows patterns of economic prosperity change based on median household income percent change ACS 2012 to ACS 2017 by tract in the Dallas metro area.

– view developed using ProximityOne CV XE GIS and related GIS project.

Using the Interactive Table
Use the interactive table .. click this link .. to view, query, rank, compare selected characteristics of the population, housing, educational attainment and income for census tracts based on ACS 2012 5-year, and ACS 2017 5-year data. Hundreds of additional items are available. See about related census tract data resources and applications.

Try it yourself ..
Tracts with ACS 2017 population 3,500-4,500 ranked on change in $MHI:
Replicate the following graphic using the interactive table. This view was produced by clicking the Pop17 button below the table to select only tracts with a ACS 2017 population between 3,500 and 4,500. Then the $MHI columns button was clicked to view only selected columns. Finally the qualifying tracts were sorted in descending order by clicking the $MHI Change column header cell.

Based on these estimates, tract 04013105004 in Maricopa County, AZ is top ranked, where the $MHI increased by $97,723 from the ACS 2012 5-year period to the ACS 2017 5-year period.

Corresponding API calls to access the $MHI for this tract (click links to access data):
ACS 2012 $MHI … ACS 2017 $MHI
Join us in an upcoming Data Analytics Web Session (see below) to learn more about using APIs to access these data and similar data.

Access more detailed ACS 2017 tract interactive tables:
  General demographics .. Social .. Economic .. Housing

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

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

Mapping Block Group Data

.. demographic-economic patterns and characteristics can often be “masked” when using larger geographic areas such as counties and metros. Using data for small area geography such as census tracts and block groups can help identify clusters and areas of interest. Now, demographic-economic data for block groups (217,000 areas averaging 1,200 population covering the U.S. wall-to-wall) are tabulated annually from the American Community Survey (ACS). There are hundreds of subject matter items updated annually. Without specialized tools, it is very difficult to navigate through the maze of small area data that are available and make effective use of these data for analysis and decision-making.

Use the combination of API tools and GIS tools described in this Web section to visually and geospatially analyze demographic-economic characteristics of block groups. Covering the U.S. wall-to-wall and averaging 1,200 population, block groups are the smallest geographic tabulation area for data from the American Community Survey (ACS 5-year estimates). Block group (BG) data are also available from Census 2010 Summary File 1 (SF1) for the same block group area geography.

Patterns of Median Household Income
— San Francisco, CA by Block Group
Create map views similar to the one shown here for your areas of interest.

… Click graphic for larger view. View developed using CV XE GIS.

Install Tools
There are two software tools involved to create maps such as the one above for any county in the U.S. using block group level data for multiple years, flexibly choosing among more than a thousand subject matter items. Steps to use two tools are described in this Web section. You can perform these operations for any area in the U.S. and use the resulting maps and data in any manner.
• Demographic-Economic Data Extraction (DEDE) API tool
• CV XE GIS software
See the corresponding Web sections above to install the Windows-based software. There is no fee to use these tools to perform operations described here. There are no block group subject matter datasets to download. The steps to use these tools are summarized here.

Get Help Using these Resources
The flexibility and breadth of data selection options afforded by access to thousands of subject matter items from multiple statistical programs requires several steps to use the data in GIS applications. Join us in a Data Analytics Lab session for additional assistance. We can go through/discuss any aspect of steps summarized here. There is no fee for the Data Analytics sessions.

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.

Financial Institutions & Neighborhood Characteristics

Examining patterns of financial institutions, neighborhoods and geographic-demographic-economic relationships … this section is one of several related sections focused on data and resources useful to analyze America’s banks and savings institutions. This section is focused on use of Geographic Information System (GIS) tools to examine the nation’s 96,000 FDIC-insured institutions/branch offices in context of neighborhoods and economic prosperity. This is not intended as a study to draw conclusions, but rather to illustrate how these data and tools can be used to perform more detailed analyses for any metro, county or city in the U.S. See related more detailed Web section.

This section illustrates use of FDIC Deposit Market Share (DMS) data by institution. Subsequent sections will integrate other related data into the GIS applications including the FFIEC “Census 2014/2015” dataset (data by state, metro, county and census tract).

Deposit Market Share
The Deposit Market Share (DMS) is the percentage of deposits an FDIC-insuredinstitution has within a defined geographic market. We use these data in GIS applications reviewed below. See the example of the DMS Report in the related Web section. These data are based on the annual Summary of Deposits survey of FDIC-insured institutions. The DMS data provide information for each/all FDIC-insured institutions by address and a range of related attributes. Market presence and growth rate analyses can be examined annually by institution or bank holding company.

The 2014 annual DMS address-based data were geocoded and converted into a shapefile for GIS analysis. The DMS shapefile was integrated into a GIS project. The GIS project also includes a U.S. national scope census tracts shapefile with demographic-economic data from the 2013 American Community Survey 5-year estimates (ACS2013). GIS tools can be used to examine a single institution, institutions within a geographic area or aggregated within a geographic area. Optionally examine these institutional locations in context with patterns of neighborhood or regional economic prosperity (or choose many other types of subject matter).

Branch Locations by Size; Houston, Texas
The map presented below shows banks as markers in the Houston, TX area. Harris County appears with bold blank boundary. Bank markers shown by 2014 deposit size class. See size class/color patterns in legend at left of map.

Click graphic for larger view; view developed with CV XE GIS.
Map view developed using Banks2015 GIS Project.

Branch Locations in Context of Neighborhood Economic Prosperity
Similar to the map above, the map below shows banks as markers in the Houston, TX area. Patterns of economic prosperity (based on median household income – MHI) are shown by census tract/neighborhood. See MHI intervals/color patterns in legend at left of map. It is easy to see where concentrations of banks in more affluent neighborhoods.

Click graphic for larger view; view developed with CV XE GIS.

Selecting Specific Institutions — using site analysis tool
The map presented below shows financial institution locations as markers with a zoom-in to neighborhood level. The site analysis tool is used to select a set of institution locations within a census tract (red boundary, yellow label) — tract code 4115.01 or 411501, located in Harris County, TX. See more about census tracts. Eight locations are selected (hatched markers) using the circle selection method (any location intersecting with circle is selected). Alternatively select only one institution, visually cherry-pick certain institutions or apply a select-from-list query. One variable is summarized, sum of deposits 2014 ($2.2 billion for sum of these 8 locations).

Click graphic for larger view; view developed with CV XE GIS.

Tabular View of Selected Institutions
The view presented below shows the data grid populated with attributes of the eight selected locations (see above). This view is displayed by using the View File button — see at right of map view in above graphic. The table/grid shows the institution/branch name, sum of deposits for that location, and other attributes. Optionally save this selection of locations an a dbase/CSV/Excel/text file for further analysis.

Click graphic for larger view; view developed with CV XE GIS.

Deposit Market Share Report
The view presented below shows the Deposit Market Share Report for ZIP code 77027. This report is for the ZIP code area that includes the selected locations shown above. See the full interactive DMS report.

Click graphic for larger view.

Top 50 Commercial Banks & Savings Institutions Interactive Table
The following graphic shows the largest Commercial Banks & Savings Institutions among all FDIC-Insured Institutions based domestic deposits as of June 30, 2014. See full interactive table.

Click graphic for larger view.

Upcoming Blog Posts on Related Topics
Upcoming blog topics will include using the following data resources integrated into the GIS and related applications focused on financial institution and market research and analysis.
  • FFIEC tract level estimates (2010, 2013, 2014)
  • FFIEC 2015 tract estimates (not yet released)
  • ProximityOne tract demographic-economic estimates (2015) and projections (2020).
  • FFIEC “Census2014” dataset, containing 1,200+ subject matter items
  • Quarterly CEW county time series data on financial services sector establishments.
  • Other FDIC institutional characteristics by address/location.

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 is developer of the CV XE GIS software used to develop the GIS project and views shown in this section. 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.