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.

America’s Cities: Situation & Outlook

.. the path forward .. planning for the future .. in April 2019, the employment in Houston, TX was 1,111,283 with an unemployment rate of 3.2%. In April 2020, the employment in Houston, TX was 927,105 with an unemployment rate of 14.9%. What will the 2020 annual look like? 2021? There are many paths to get to 2021 and beyond. What policy and action measures might work best? What about your cities of interest? See the related Web section for more details.

Houston characteristics: Demographic .. Social .. Economic .. Housing
Get for any city/area .. e-mail your request

The pandemic impacts on America’s cities in different ways .. some experiencing little change, others with massive change. When, where and how will these disparate patterns change in cities and communities of interest? How might this change impact you and your community? A comprehensive plan needs to be developed and set in motion to achieve best outcomes. This section provides access to tools and data that stakeholders can use to examine America’s cities demographic-economic characteristics and trends. Examine cities of interest. Use ProximityOne data, tools, methods and advisory services to achieve improved results.

Of the nation’s 327.2 million people, an estimated 206.0 million (62.9%) live within an incorporated place. Of approximately 19,500 incorporated places, about 76 percent had fewer than 5,000 people and nearly 50 percent had fewer than 1,000 people. Examine characteristics of individual city population trends and compare cities in states, regions and peer groups using the interactive table below.

Patterns of Economic Prosperity; Cities 50,000 Population or More
The following view shows cities with 2019 population of 50,000 or more as markers .. mainly principal cities of metropolitan statistical areas (MSAs). Nationally, there are 69 cities with 2019 population of 5,000 or more (determine using interactive table below). The marker color shows the median household income; see inset legend. Click graphic for larger view; expand window to full screen.

– View developed using the ProximityOne CV XE GIS software.

Patterns of Economic Prosperity; Cities 5,000 Population or More
– zoom-in to Dallas Metro
The following view shows cities with 2019 population of 5,000 or more as polygons/city boundary-area in the Dallas metro area. There are 201 cities that intersect with the Dallas metro (code 19100); 96 of these cities have a population greater than 5,000 (determine using interactive table below). The color patterns show the median household income range; see inset legend. Click graphic for larger view; expand window to full screen.

Patterns of Economic Prosperity by Neighborhood & Adjacent Areas
The following view shows patterns of median household income by block group (sub-neighborhoods) within city (bold black boundary) in the Dallas County, TX area. In examining the situation & outlook for a city it is important to examine characteristics of drill-down geography and adjacent cities/areas. Inset legend shows median household income color intervals. Click graphic for larger view; expand window to full screen. In the larger view, a cross-hatch pattern is applied to Dallas city. It is easier to see how Dallas city is comprised of a core area as well as outlying areas and extends into adjacent counties.

Interactive Analysis of Cities: Demographic-Economic Patterns & Trends
Use the interactive table to view, rank, compare cities based on demographic-economic trends and characteristics. The following static graphics provide two examples.

 

Largest 15 U.S. Cities Ranked on 2019 Population

California Cities Ranked on Educational Attainment

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

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

116th Congressional Districts & Patterns of Economic Prosperity

.. Congressional District Analysis and Insights .. tools to examine patterns of median household income .. median household income is one measure of economic prosperity. This section reviews patterns of median household income (MHI) by 116th Congressional Districts based on the 2018 American Community Survey 1-year estimates (ACS 2018). View, rank, compare the MHI by congressional district, among related demographic attributes using the interactive table on the main Congressional Districts page.

116th Congressional District Analysis & Insights
.. patterns of household income & economic prosperity:
Based on the ACS 2018 median household income (MHI):
• the MHI among all districts was $60,291
• the U.S. overall MHI was $61,937
As of November 2019:
• the 19 districts with highest MHI have Democrat incumbents
• the 10 districts with the highest Gini Index have Democrat incumbents
• there are 69 Republican incumbent districts above the all districts MHI
• there are 149 Democrat incumbent districts above the all districts MHI
• the MHI of the 236 Democrat incumbent districts is $66,829
• the MHI of the 199 Republican incumbent districts is $56,505
Median household income is only one measure of economic prosperity.
See more at http://proximityone.com/cd.htm.

Patterns of Economic Prosperity 116th Congressional District
The following graphic shows patterns of 2018 median household income by 116th Congressional District. Use GIS tools/data to generate similar views for any state and/or drill-down. Click graphic for larger view with more detail. Expand browser window for best quality view.

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

Using the Interactive Table –
— view, rank, compare districts based on your criteria.
— example,which districts have the highest median household income?
Use the interactive table to examine incumbency and and demographic characteristics of the 116th Congressional Districts (CDs). The following view illustrates use of the table. This view shows use a query to show the ten CDs having highest 2018 median household income.

Try using the interactive table to existing districts and categories of interest.

Congressional District/State Legislative District Group
Join in .. be a part of the Congressional Districts/State Legislative District (CDSLD) group. Access analytical tools and data. Learn about CDSLD analytics, patterns and trends. Share insights with like-minded stakeholders.

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

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

U.S. & State Real Median Household Income Trends

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

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

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

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

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

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

Median Household Income in the United States: 2005–2018

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

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

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

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

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

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.

Monthly Local Area Employment Situation: 2017

.. tools & data to examine the local area employment situation .. this update on the monthly and over-the-year (Jan 2016-Jan 2017) change in the local area employment situation shows general improvement. Yet many areas continue to face challenges due to both oil prices, the energy situation and other factors.  This section provides access to interactive data and GIS/mapping tools that enable viewing and analysis of the monthly labor market characteristics and trends by county and metro for the U.S. See the related Web section for more detail. The civilian labor force, employment, unemployment and unemployment rate are estimated monthly with only a two month lag between the reference date and the data access date (e.g., March 2017 data are available in May 2017).

Use our new tools to develop your own LAES U.S. by county time series datasets. Link your data with LAES data. Run the application monthly extending/updating your datasets. Optionally use our 6-month ahead employment situation projection feature. See details

Unemployment Rate by County – January 2017
The following graphic shows the unemployment rate for each county.

— view created using CV XE GIS and associated LAES GIS Project
— click graphic for larger showing legend details.

New with this post are the monthly 2016 monthly data on the labor force, employment, unemployment and unemployment rate. Use the interactive table to view/analyze these data; compare annual over the year change, January 2016 to January 2017.

View Labor Market Characteristics section in the Metropolitan Area Situation & Outlook Reports, providing the same scope of data as in the table below integrated with other data. See example for the Dallas, TX MSA.

The LAES data and this section are updated monthly. The LAES data, and their their extension, are part of the ProximityOne Situation & Outlook database and information system. ProximityOne extends the LAES data in several ways including monthly update projections of the employment situation.

Interactive Analysis
The following graphic shows an illustrative view of the interactive LAES table. In January 2017, 149 counties experienced an unemployment rate of 10% or more. The graphic shows counties experienced highest unemployment rates. Use the table to examine characteristics of counties and metros in regions of interest. Click graphic for larger view.

Metro by County; Integrating Total Population
The following graphic shows an illustrative view of the interactive LAES table focused on the Chicago MSA. By using the query tools, view characteristics of metro component counties for any metro. This view shows Chicago metro counties ranked on January 2017 unemployment rate (only 10 of the 14 metro counties shown in this view). Click graphic for larger view.

The above view shows the total population (latest official estimates) as well as employment characteristics.

More About Population Patterns & Trends
U.S. by county population interactive tables & datasets:
  • Population & Components of Change 2010-2016 – new March 2017.
  • Population Projections to 2060 2010-2060 – updated March 2017.

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.

ZIP Codes with Highest & Lowest Economic Prosperity

.. the latest data for ZIP Code Areas show that eleven had a median household income of $250,000 or more during the period 2011-15. More than 20 ZIP code areas had a median housing value of $2,000,000 or more. Contrast these ZIP code areas with higher economic prosperity with the more than 150 ZIP codes that had a median housing value of less than $30,000.  Use the interactive table in this related Web section to see which ZIPs meet these and other criteria.

ZIP Codes with MHI $100,000 or More; Dallas, TX Metro
Analyzing economic prosperity patterns using combined types of small area geography … the following graphic shows ZIP code areas a red markers with the median household income or $100,000 or more in context of median household income by census tract thematic pattern. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view for your areas of interest. .

– view developed with CV XE GIS software.

This section reviews measures of economic prosperity for all ZIP code areas. These data were released in December 2016. This section updates with new data December 2017. See the list of all ZIP ccdes showing population, housing and economic characteristics in the interactive table shown below. Use the interactive table to view, rank, compare and query ZIP code attributes.

Examining demographic-economic characteristics by ZIP code is important for several reasons. We are familiar with our own ZIP codes as a geographic location. We tend to be interested in our area compared to other areas. ZIP codes provide an easy way to do that. Also, many secondary data resources are tabulated by ZIP code area; some important data are only available by ZIP code. See more about ZIP Code areas.

Resources & Methods to Examine Small Area Demographics
• See related ZIP Code Demographic-Economic Interactive Tables
  .. extended subject matter
• See related Census Tract Code Demographic-Economic Interactive Tables
• Examine ZIP Code Urban/Rural Characteristics
• Examine ZIP Code Business Establishment patterns
• Examine ZIP Code Housing Price Index patterns
• Join us in the weekly Data Analytics Lab Sessions
  .. reviewing applications using these and related data.

ZIP Code Areas with $MHI $100,000 or More
The following graphic shows ZIP code areas as red markers having median household income or $100,000 or more. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view; integrate other data; select alternative ACS 2015 subject matter.

– view developed with CV XE GIS software. Click graphic for larger view.

ZIP Code Areas with $MHV Less than $30,000
The following graphic shows ZIP code areas as orange markers having median housing value of less than $30,000. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view; integrate other data; select alternative ACS 2015 subject matter.

– view developed with CV XE GIS software. Click graphic for larger view.

ZIP Code Areas: Population & Economic Prosperity
  — Interactive Table –
Use the interactive table to view, rank, compare, query ZIP codes based on a selection of demographic-economic measures. The following graphic illustrates how the table can be used to examine patterns of the three digit ZIP code area (San Diego) by 5-digit ZIP code. Table operations are used to select ZIP codes in the 921 3-digit area (containing 39 5-digit ZIP codes). These 39 ZIP code are then ranked in descending order on median household income. See results in the table shown below. ZIP code 92145 has the highest $MHI in this group with $228.036.

– click graphic for larger view.

Try it yourself. Use the table to examine a set of ZIP codes on your selected criteria in for a state/area of interest.

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.

Demographic-Economic Patterns: Composite & Related Geography

.. we often need data for study areas that do not conform to conventional political/statistical geography. The geography for a market, sales territory, impact zone or other type of study area often do not align with political or statistical geographic areas for which relevant demographic-economic data are available. While the interest might be in demographic-economic characteristics for a particular county, patterns and trends within a county cab vary widely for sub-county geography such as ZIP code areas, census tracts, cities, school districts and other types of geography. It is important to be able to examine the composite, or drill-down, geography for a larger area. Related geography are equally important. Even though primary interest might be in three ZIP code areas, knowing about patterns in related, contiguous ZIP codes is also important. This section illustrates how to examine semi-comprehensive demographic-economic characteristics and trends using organized profiles for alternative geography.

Patterns of Economic Prosperity by Neighborhood
ZIP Code Area 60565 in Naperville, IL area — bold black boundary

– note this ZIP code area intersects with many census tracts;
    … in many cases tract boundaries are not coterminous with ZIP code.
– colors show patterns of median household income by census tract
– view developed with CV XE GIS … view full profile

More information — get for your areas anywhere in U.S.

Illustrative set of different types of geography; Naperville, IL; Chicago metro.
Click links to view full profile.
– ZIP Code Area 60565 — Naperville, IL area — see graphic above
– Census Tract 17197880119 — Naperville, IL area — see graphic below
– Naperville city, IL — see graphic below
– Naperville School District, IL — see graphic below
– DuPage County, IL — see graphic below

Patterns of Economic Prosperity by Neighborhood
Census tract 17197880119 in Naperville, IL area — bold black boundary

– ZIP code 60565 shown with red boundary.
– colors show patterns of median household income by census tract
– view developed with CV XE GIS … view full profile

Patterns of Economic Prosperity by Neighborhood
Naperville, IL city — cross-hatched pattern, bold black boundary

– colors show patterns of median household income by census tract
– view developed with CV XE GIS … view full profile

Patterns of Economic Prosperity by Neighborhood
Naperville School District, IL — cross-hatched pattern, bold black boundary

– Naperville city shown with semi-transparent cross-hatch pattern.
– colors show patterns of median household income by census tract
– view developed with CV XE GIS … view full profile

Patterns of Economic Prosperity by Neighborhood
DuPage County, IL — cross-hatched pattern, bold black boundary

– Naperville city shown with semi-transparent cross-hatch pattern.
– colors show patterns of median household income by census tract
– view developed with CV XE GIS … view full profile

There are many other ways to use composite and related geography in data analytics. GIS tools enable wide-ranging geospatial analysis not covered in detail here. See more about this topic in the data analytics program.

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.