Tag Archives: Trends

Examining HMDA/CRA Census Tract Demographics

.. the ability to effectively analyze low, moderate, middle, and upper income 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. See the main Web page for more detail.

This section reviews the scope and use of the FFIEC 2019 HMDA/CRA census tract data (released September 2019). Use the interactive table to view, rank, compare selected items from these updated data for any/all tracts. Use GIS tools with these data to map and geospatially analyze these data as illustrated and further described as illustrated here. See more about banking, CRA and LMI tracts and more about these data.

Visual Analysis of Banks in Context Census Tract Demographics
Click graphic for larger view; expand browser window for best quality view.

– view developed using CV XE GIS and related GIS project.
– install this GIS tool and related GIS project on your computer to examines patterns, market share and more.

Low & Moderate Income Population by Census Tract
Low, moderate, middle, upper income classification by census tract is based on the median family income of a specific census tract relative to the metropolitan statistical area (MSA) or non-MSA area in which the tract is located. The FFIEC data include a “low and moderate income indicator”:
1 – Low — MFI is less than 50% of the MSA/parent area MFI
2 – Moderate — MFI is from 50% to 80% of the MSA/parent area MFI
3 – Middle — MFI is from 80% to 120% of the MSA/parent area MFI
4 – Upper — MFI is 120% or more of the MSA/parent area MFI
0 – NA — MFI is 0 or not available
where MFI is the Median Family Income

Low and moderate income designation is closely associated with implementation of the Home Mortgage Disclosure Act (HMDA) and the Community Reinvestment Act (CRA) and is a widely used in many other applications as a measure of economic prosperity.

Using the Interactive Table
Use the interactive table to examine individual tracts or sets of tracts as to their low and moderate income status and related demographics. The following view illustrates use of the table. Clicking buttons below table, this sequence of steps was used to obtain this view:
– click ShowAll
– click “Find CBSA; Low & Mod Tracts”
  >this selects tract in CBSA 26420 (Houston) that are low or mod
– click “Status Cols”
The table refreshes to show 470 tracts that are low/mod in this metro.
Finally, click the column header “Tract MFI %Region” to sort in descending order.

View your areas of interest. Start the steps over and use your CBSA code for a metro of interest.

Bankers Analytics Tools Web Sessions
Join me in a Bankers Analytic Tools Lab session (every Wednesday 3:00 pm ET) 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.
Topics:
• mapping and geospatially analyzing your data with FFIEC data
• tract demographic vintages and trends
• issues regarding MSA/MD vintage, change; about the 2018 vintage CBSAs
• defining and using assessment area geography
• examining the community & neighborhoods in context of assessment areas
• using the FDIC bank location/deposits data with FFIEC/ACS demographics
• using the FFIEC/ACS interactive table below
• alternative methods of accessing census tract ACS data

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 2000Census 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 $MHIACS 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.

Examining County Gross Domestic Product

.. what is the annual per capita real-valued output of counties of interest? How is this measure trending? Why is this important? This section reviews tools and data to examine county-level Gross Domestic Product (GDP) trends and patterns. The first ever county-level GDP estimates to be developed as a part of the official U.S. national scope GDP estimates were released in December 2018. The county GDP estimates join the county-level personal income by major source, both now part of the Regional Economic Information System (REIS). See more detail about topics reviewed in this post in the related County GDP web section.

Patterns of Real Per Capita GDP by County
The graphic below shows patterns of per capita real GDP, 2015, by county.

– View developed using CV XE GIS and related GIS project.
– create custom views; add your own data, using the GIS project.

Gross Domestic Product (GDP) by county is a measure of the value of production that occurs within the geographic boundaries of a county. It can be computed as the sum of the value added originating from each of the industries in a county.

Example … use this interactive table to see that 2015 Los Angeles County, CA total real GDP of $656 billion was just slightly larger that than of New York County, NY (Manhattan) at $630 billion. Yet, the total 2015 population of Los Angeles County of 10.1 million is 6 times larger than that of New York County of 1.6 million — see about steps. GDP provides very different size measures, and economic insights, compared to population.

In 2015, real (inflation adjusted) Gross Domestic Product (GDP) increased in 1,931 counties, decreased in 1,159, and was unchanged in 23. Real GDP ranged from $4.6 million in Loving County, TX to $656.0 billion in Los Angeles County, CA.

This post is focused on U.S. national scope county level estimates of Gross Domestic Product (GDP) annually 2012 through 2015. This marks the first time county level GDP estimates have been developed, a part of the Regional Economic Information System (REIS). Use the interactive table to rank, compare, query counties based on per capita GDP, current GDP, real GDP by type of industry. Use the related GIS project to develop thematic map views such as the one shown below. See more about these data.

Current Annual Estimates & Projections
ProximityOne uses these and related data to develop and analyze annual Situation & Outlook demographic-economic estimates and projections. GDP items included in the table below are included in the “annual 5-year” projections as shown in the schedule of release dates; next release April 18, 2019 and quarterly.

Examining County GDP Using GIS Tools
Use the County REIS GIS project. Make your own maps; select different item to map; modify colors, labels. Zoom in views of selected states shown below. Graphics open in a new page; expand browser window for best view. Patterns: see highlighted layer in legend to left of map; MSAs bold brown boundaries with white shortname label
counties labeled with name and 2015 per capita real GDP
.. Arizona .. Alabama .. California .. Colorado .. Iowa .. Georgia .. Kansas .. Missouri
.. New York .. Nevada .. North Carolina .. South Carolina .. Nevada .. Texas .. Utah .. Vermont

Using the County GDP Interactive Table
The graphic below illustrates use of the interactive table. Tools below the table have been used to view only per capita real GDP for all sectors (total sources) and for county with total population between 50,000 and 60,000. Counties were then ranked on 2015 per capita real GDP (rightmost column).

– click graphic for larger view.

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

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