Tag Archives: Maps

Business Establishment Characteristics by County

.. what are the number and types of businesses underlying county economies of interest? What is the employment size by type of business establishment? What scope of wages, earnings do they contribute? Learn more here.

The pandemic impact on businesses remains in flux .. this post tools and data that can be used to examine pre-pandemic business establishments and employment pattern characteristics by county. By examining pre-pandemic conditions, we can better assess the impact of how and why business, demographic and economic change and impact as we move forward. The magnitude and duration of the impact on businesses will vary by community/area and become more measurable in the months ahead. The “How & Where of Business Establishment/Employment Change” will be updated later in 2020. See related, more detailed web section. See related section focused business establishments by ZIP code.

Where Things are Made by County
The following graphic shows patterns of the number of manufacturing establishments (NAICS 31) by county for the U.S. 48 contiguous states. Inset legend in map view shows number of establishments by interval/color. View/examine all U.S. states and areas using the related GIS project. Create custom maps similar to this view for your regions of interest depicting establishments, employment or payroll for your type of business selection(s). Click graphic for larger view with more detail; expand browser window for best quality view.

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

The above view shows patterns for only one type of business. Data are tabulated more than 2,000 NAICS/type of business codes. These data may be examined by county using the interactive table. Use the GIS tools and related GIS project to develop variations of the views shown here.

Using the Interactive Table
The 10 largest counties based on the number of manufacturing establishments are shown in the static graphic below. Click for larger view.

Use the interactive table to dynamically create similar rankings on employment size or payroll. Set a query for a county, metro or state of interest.

Updates
These data update in June 2020. Follow the blog (click button at upper right) to receive updates.

Learn more — Join us 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 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.

How & Why County Demographics are Changing

.. the pandemic impact on population change remains in flux. For many counties it will impact each component of population change: births, deaths and migration. The magnitude and duration of the impact on each component will vary by county and become more measurable in the months ahead. The “How & Why County Demographics are Changing” will be updated later in 2020.

Here we look at population and components of change by county for the period 2010 to 2019 .. tools and data to examine how the U.S. by county population is changing. These latest 2019 estimates were released this spring. See more in the related web section.

Top 25 Counties with Largest Population Change 2010-2019
Create a table similar to the one shown below using the interactive table. Sort on selected criteria and within a selected state or metro.

Patterns of Population Change by County, 2010-2019
The following graphic shows how counties have gained population (blue and green) and lost population (orange and red) during the period 2010 to 2019. Click graphic for larger view; expand browser window for best quality view.

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

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. The above graphic shows these relationships.

County Population & Components of Change 2010-2019 – Interactive Table
View/analyze county population and components of change characteristics and trends in a tabular manner using the interactive table. The following static graphic shows net migration 2010-2019 by year for Houston, TX metro component counties. Rows have been ranked in descending order based on 2010 population. It is easy to see how the net migration in Harris County has been decreasing annually since 2015.

Try it yourself. Use the interactive table to examine counties/areas of interest.

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 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.

Patterns of Income in America’s Largest Cities

The retreat in personal and household income resulting from the pandemic will be historic and substantial. How long term? Which cities of what size and location will be affected the most? We start to study patterns and trends as new data become available in the next several weeks.

America’s largest 629 cities accounted for a group population of 121,228,560, or 37.1%, of the total U.S. population (327,167,434) in 2018. All of these cities are in Metropolitan Statistical Areas (MSAs). With contiguous cities and places, these urban areas account for more than 80% of the U.S. population. These cities, each with 65,000 population or more, are shown as markers in the thematic pattern view below. See more about cities/places and city/place 2010-2018 demographic trends.

Patterns of Economic Prosperity: America’s Largest Cities
– cities with 2018 population 65,000+ shown as markers
– markers show level of 2018 median household income
– data used to develop this veiw were extracted using GeoFinder.
– click map for larger view; expand browser to full screen for best quality view.

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

Top 25 Largest Cities based on Median Household Income

About America’s Largest Cities & Economic Characteristics
The set of the 629 America’s largest cities is based on data from the 2018 American Community Survey 1-year estimates (ACS 2018). ACS 2018 1-year estimates, by design, provide data only for areas 65,000 population or more. The ACS 2018 data are the only source of income and related economic data for national scope each/all cities/places (29,853) on an annual and more recent basis. These data will update with 2019 estimates in September 2020. ACS-based data reflecting the impact of the pandemic will not be available until September 2021.

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 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.

Analyzing Patterns of COVID-19

.. as COVID-19 impacts our demographics, economy and way of life, we look for answers about where we are and what lies ahead.  Here we review data on COVID-19 incidence and tools to analyze those data. In the coming days, weeks, we plan to augment these tools and data. See more below.  See related Web section for more detail.

Use new resources to examine/analyze patterns of COVID-19 incidence in context of related demographic-economic characteristics. Resources include the narrative/interpretative portion, interactive table and GIS tools and project/files. Data and tools are updated daily. There is no fee to use any of these resources.

COVID-19 Incidence by County in the Atlanta Metro Area
The following graphic shows patterns of COVID-19 incidence (number of cases per 1,000 population) by county. See color patterns in the inset legend. This view shows counties labeled with name and number of confirmed COVID-19 cases. Use the GIS project described below to create variations of this view and develop similar views for any metro.

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

The GIS resources and interactive table below makes use of the COVID-19 confirmed cases data updated daily by the New York Times. See more about the New York Times U.S. tracking page.

COVID-19 Incidence — U.S. by County
Similar to the above view, the following graphic shows patterns of COVID-19 incidence (number of cases per 1,000 population) by county for the U.S. See color patterns in the inset legend. This view shows counties labeled with name and number of confirmed COVID-19 cases. Use the GIS project described below to create variations of this view and develop similar views for any metro. Click graphic for larger, more detailed view. Expand browser window for best quality view.

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

Using GIS Tools & Resources
Use the Geographic Information System (GIS) CV XE GIS software and GIS project to view maps and geospatially analyze patterns COVID-19 cases in context of related demographic-economic data. The GIS project automatically opens with the following view:

.. see details about using the mapping/GIS resources.
.. create map views for your areas of interest.

COVID-19 Confirmed Cases by County Interactive Table
Use the interactive table to view, rank, query compare patterns of COVID-19 cases. See related demographic-economic interactive tables.

The following static graphic illustrates use of the table to view daily patterns of COVID-19 cases in Cobb County, GA.

Use the interactive table to examine counties of interest.

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 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 2020 Residential Address Counts by Block

.. using Census 2020 residential address count data to examine change since 2010 .. the Census Bureau has released preliminary Census 2020 residential address counts by Census 2010 census block. These data, count of residential addresses and group quarters addresses, reflect updates as of October 2019 and do not represent final Census 2020 counts. The data will continue to be updated to support Census 2020. See related Web section with more detail and updates.

Importance and Use
These data are of immediate value in determining and analyzing how the number of housing units have changed, 2010 to 2019. Since the data are at the census block level, they may be aggregated to any other Census-defined summary level/type of geographic area such as block group, tract, ZIP code, city, county, school district, etc. These data are also important as they give us a “year in advance look” at how small area demographics are changing since 2010. Before this, the most recent census block data were from Census 2010. A lot has happened in many areas. These data provide insights into that change. The Census 2020 block level data will be released in early 2021 for Census 2020 census block geography. So, another important feature of these data is that they are summarized for Census 2010 census block boundaries. Census 2010 and 2020 block boundaries may differ, particularly in areas experiencing larger demographic growth/change. An important limitation is that they are counts, subject to change as the Census data are collected/tabulated.

Comparing Census 2010 Housing Units with Census 2020 Address Counts
The following graphic shows patterns of Census 2010 housing counts with the Census 2020 (late 2019 vintage) residential address counts by census block. This view is focused on census tract 3608100700 (tract 000700) in Queens County, NY (code shown near center of graphic). Individual blocks are labeled with block code (4 digits) with the Census 2010 housing units (yellow label) and Census 2020 residential address count (green label) shown below the block code. As an example, the block located at the pointer has block code 3006 (or full national scope unique block code 36-081-00700-3006) with a Census 2010 count 44 housing units and a Census 2020 (late 2019 count) of 232 residential addresses. Click graphic for larger view. Expand browser window to full screen for best quality view.

.. view created with ProximityOne CV XE GIS software and related GIS project.

More About Using these Data
We have summarized these data at the census tract level and are evaluating their use, in combination with other data, to develop current estimates and projections to 2025.

Data 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 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.

Examining Economic Well-Being by Metro

.. examining the state of economic well-being: 2008-2017 .. expanding insights through data analytics .. tools and data to examine how and where the U.S. by metropolitan area real personal income is changing.  Real per capita personal income (RPCPI) is the best single measure of personal economic-well being. By examining RPCPI trends over a period, stakeholders can better determine if the area in improving, stable or declining. Still, RPCPI is but one important measure among many others, such as the Regional Price Parities (RPP). Use the interactive table, and related GIS tools, to examine these and other real personal income measures for the Nation’s 383 Metropolitan Statistical Areas (MSAs). See related Web section for more detail.

Based on data released by the Bureau of Economic Analysis in May 2019, see about in statistical release dates, real state personal income grew 2.6 percent in 2017, after increasing 1.5 percent in 2016. Real state personal income is a state’s current-dollar personal income adjusted by the state’s regional price parity and the national personal consumption expenditures price index. Across metropolitan areas, the percent change ranged from 14.8 percent in Midland, MI to -5.9 percent in Enid, OK

Visually Examining Patterns of Economic Well-Being
Geographic Information Systems (GIS) tools provide a powerful to explore these data. The following graphic shows a view of real per capita personal income (RPCPI), 2017, for Texas MSAs. Color patterns for levels of RPCPI are shown in the inset legend. MSAs are labeled with the 2017 RPCPI rank among all U.S. MSAs. Click graphic for larger view; expand browser window for best quality view. The larger view shows MSAs labeled with short name and a mini-profile for Harris County (pointer).

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

Using the Interactive table
The interactive table (click link to view/use) includes a row for the U.S., U.S. nonmetro area and each Metropolitan Statistical Area (383). Each row provides a 2008-17 annual time series for four items (and derived items): real per capita personal income, regional prices parities-all items, total real personal income, implicit regional price deflator.

The following graphic shows these areas ranked on RPCPI in 2017. See rightmost column rank. Click graphic for larger view. Midland, TX MSA has the 4th highest 2017 RPCPI (shown in blue; also shown in blue in the map graphic above). But … that metro experienced a decrease of 12.1 percent over the period 2010-2017 .. and down from a high RPCPI of $115,069 in 2014. The dynamics of the oil industry!

Data Analytics Web Sessions
See these applications live/demoed. Run the applications on your own computer.
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.