Category Archives: Trends

Urban Area Demographic Trends 2010-15

.. tools and analytics to examine all urban areas with particular focus on Urbanized Areas and demographic change between 2010 and 2015 .. examining urban areas in context of metropolitan areas .. the four fastest growing Urbanized Areas (UAs) from 2010 to 2015 were in Texas. McKinney, TX UA led the nation with an increase of 27.5% in total population. View, rank, compare 2010 and 2015 demographic characteristics for UAs using the interactive table in this related section. Urban areas (Urbanized Areas and Urban Clusters) are important for many reasons. More than metros and cities, urban area geography better reflects how the urban and rural population is changing. Both metros and cities can change geographic boundary over the years. Urban areas are based on Census 2010 and unchanging between 2010 and 2020. Annual demographic updates are available from the American Community Survey (ACS 2015).

This section is focused on tools and analytics to examine all urban areas with particular focus on Urbanized Areas and demographic change between 2010 and 2015. Use the interactive table >in the related section to view, rank, query urban areas and demographic change for larger urban areas. Use the related GIS tools and data to develop related thematic and relationship maps. Perform geospatial analysis of geographic and demographic-economic characteristics using the resources we have developed. Gain insights into patterns that might affect you. Use these resources to collaborate on how, where, what, when and why of change.

McKinney TX Urbanized Area in Context of City
The McKinney, TX UA (bold orange pattern) is shown in context of McKinney city (cross-hatched area) and other urban areas (lighter orange pattern). It is easy to see that some parts of the city are rural and that the UA extends beyond the city in many areas. See more about the McKinney UA and in comparison to other urban areas using the interactive table.


– view created using CVGIS software and related GIS project.

Most Urbanized Areas (UAs, 435 of 487) have population 65,000 population or more resulting in the availability of annual demographic-economic estimates. Data are fresher than available for smaller urban areas (ACS 5-year estimates for areas under 65,000). This means more current data to assess more recent characteristics. As annual data are available UAs enabling analysis of change over time. The “2010s” marks the first time these refreshed, time series-like data have been available for urban areas. Businesses and those examining change performing market analysis benefit from the ability to examine characteristics or urban areas in combination with counties and metros.

Houston Urbanized Area in Context of Houston Metro
The Houston metro has a bold brown boundary. It is easy to see how the Houston UA (darker orange fill pattern) geographically relates to the metro. Other urban areas (all) are shown with a lighter orange fill pattern. It is easy to see the urban/pattern character of the general region. While the Houston UA is the largest, there are four UAs that intersect with Houston metro. Use the interactive table below to view their names and characteristics.


– view created using CVGIS software and related GIS project.

Urbanized Areas tend to be associated with metropolitan areas having a similar name. But very often there are multiple UAs within a metro; sometimes one is not dominant. Often there are several UAs in a metro having similar size. Use the interactive table below to view the relationship of UAs and metros (CBSAs).

Using Interactive Table
Use the interactive table to view, rank, compare, query urban areas based on a selection of demographic measures. The following graphic illustrates how the table can be used. Click graphic for larger view.

The graphic shows the urbanized areas ranked in descending order based on 2010-2015 population. The rightmost column shows the area percent change in population over the period.

Fastest Growing Urbanized Areas, 2010-15

Try it yourself. Use the table to examine urban area patterns and characteristics based on your selected criteria.

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.

State Population & Components of Change: 2010-2016

.. data and tools to examine how state demographics are changing 2010-2016 … using the new 2016 population and components of changes estimates. The U.S. population changed from 308,758,105 (2010) to 323,127,513 (2016), a change of 14,369,408 (4.7%). Only three states lost population. See the growth rates for DC and the remaining states in this table. Highest growth rates were in D.C., North Dakota, Texas, Utah and Colorado.

Patterns of Population Change, 2010-2016, by State
The following graphic shows the percent population change by state with labels showing the rank among all states based on the percent change in population, 2010-16.

View created with CVGIS and related GIS project. Click graphic for larger view.

Resources to Analyze these Data
Use our tools to view and analyze annual population estimates, 2010 to 2016, rankings and components of change for the U.S., regions and states. Use the interactive table below in this section to view, rank, compare these data. Use the GIS tools and ready-to use project described below in this section to create maps for states and regions of interest. Create thematic maps for any of the fields/measures shown in the interactive table. Change color patterns and labels. Integrate your own data.

Using Interactive Table
Use the interactive table to view, rank, compare, query states based on a selection of demographic measures. The following graphic illustrates how the table can be used. Click graphic for larger view.

The graphic shows the largest 10 states ranked in descending order based on 2016 population. The column “PopChg Rank 10b16” (second from right) shows the rank of this state, among all states, based on the population change from 2010 to 2016. The rightmost column shows the state’s rank for the period based on percent change in population over the period.

Largest 10 States based on 2016 Population

Try it yourself. Use the table to examine state patterns and characteristics based on your selected criteria.

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.

School District Demographic Trends: 2010-2015

.. data and tools to examine how school districts of interest are changing … based on total population, the largest 10 school districts in 2015, all experienced an increase in total population over the period 2010-2015. Five of these districts had a decrease in school age population (ages 5-17 years). Four of these districts had a decrease in the number of related children in families ages 5-17 years. See characteristics of districts in this interactive table. See the related Web section for more details.

School Districts with 2015 Population 100,000 or More
More than 600 of the total 13,245 school districts have a total 2015 population of 100,000 or more (red markers).

– view developed with CVGIS software and related GIS project.

Using New 2015 Estimates Released December 2016
– for use in 2017 ESEA Title I Allocations
Analyze annual demographic data for each U.S. school district for the period 2010 through 2015. These data include the Federal official 2015 estimates available for all districts. Developed for use as inputs for the ESEA Title I allocation formula, the data have broader uses of interest to school district demographics stakeholders. Use the interactive table in this section to view, rank, compare, query demographic characteristics of districts of interest.

The annual estimates for each school district include:
• total population
• number of children ages 5 to 17
• number of related children ages 5 to 17 in families in poverty

Using Interactive Data Tools
Use the interactive table to view, rank, compare, query ZIP codes based on a selection of demographic measures. The following graphics illustrate how the table can be used. Click graphic for larger view.

Total Population — 10 districts with largest change 2010-15
– ranked descending on rightmost column

– click graphic for larger view.

School Age Population — 10 districts with largest change 2010-15
– ranked descending on rightmost column

– click graphic for larger view.

Related Children Ages 5-17 in Poverty
– 10 districts with largest change 2010-15
– ranked descending on rightmost column

– click graphic for larger view.

Try it yourself. Use the table to examine a set of districts 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.

Census 2020 LUCA Program and You

.. what would be the financial impact of a one-percent understatement in the Census 2020 population count? Many political districts are drawn based upon population change and shifts, and allocations of government funding and services are made based upon official population data. Consider this one specific example. For each one-percent of the Atlanta MSA population missed in Census 2020, potentially due to less than fully accurate address and location data, the financial impact could be on the order of $414 million per year. How and why? At margin, each person not counted in the decennial census results in a per capita disposable income loss for the area in the magnitude of $5,494 in 2000, and $6,770 per person in 2020. 61,100 people undercounted times $6,770 yields $414 million.

This section is about the Censue 2020 Local Update of Census Addresses (LUCA) program and how it might impact the reduction in undercount .. and make the data more accurate for wide-ranging needs and uses. Read on for details about the LUCA program.

Atlanta-Sandy Springs-Roswell, GA MSA
The Atlanta metro shown with black bold boundary. More about this metro.

– View developed with CV XE GIS software.
– Click graphic to view patterns of neighborhood economic prosperity.

Financial Impact Details … the 2015 per capita current transfer payments (PCTP) in the Atlanta-Sandy Springs-Marietta MSA were $6,132, up from $5,494 in 2010. The PCTP figure in 2020 may be $6,770. For each one-percent of the Atlanta MSA population (61,100 people) missed in Census 2020, potentially due to less than fully accurate address and location data, the financial impact could be in the order of $414 million (61,100 x $6,770) per year as of Census 2020.  $414 million per year based on the 2020 population and PCTP.

Financial Impact in Your Areas of Interest
Estimate the financial impact in your areas of interest. Get the 2010 and 2015 population and PCTP data from the REIS Interactive Table for any county or state.  Compute the 2020 population and PCTP values, potential undercount to determine the financial impact on an area of interest

Census 2020 LUCA Overview
The Census 2020 LUCA program is an initiative of the Census Bureau, partnering with thousands of state and local governments across the U.S. At the core of this program, Census provides address list data to communities; those communities compare those data with their own data and provide address/geographic updates back to the Census Bureau.  The updated address and geographic data are integrated into the TIGER/Line files  — geographic backbone for collecting and tabulating the Census results. This important MAF/TIGER address-plus update program will help insure improved accuracy for Census 2020. LUCA is a geographic data development program engaging local communities across the U.S.

ProximityOne works with local areas to improve the TIGER/Line files leading up to Census 2020. Using the CV XE GIS software and specialized expertise, we helped hundreds of governmental units, including all of the State of Georgia, improve the coverage and content of the TIGER/Line files and thus the accuracy and completeness of Census 2010.

The Census 2020 LUCA program is starting now in 2016.  See the full schedule and related details in the LUCA Web section.

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.

Regional Economic Information System: Annual Updates

.. which counties are experiencing the fastest economic growth? by what economic component? what does this look like on a per capita level?

.. access & analyze economic characteristics and patterns by county and state .. annual time series 1969 through 2015 with projections.  Personal income is the income available to persons for consumption expenditures, taxes, interest payments, transfer payments to governments and the rest of the world, or for saving. Use the interactive table to examine characteristics of counties and regions of interest. The table provides access to 31 personal income related summary measures. These data are a selection of a broader set of annual time series data from the Regional Economic Information System (REIS). REIS is a part of the ProximityOne State & Regional Income & Product Accounts (SRIPA) and Situation & Outlook (S&O) featuring current (2016) estimates and demographic-economic projections. Go to table.

Visual Analysis of Per Capita Personal Income Patterns
The following map shows the Houston metro (view profile) with bold brown boundary. Counties are labeled with county name and 2014 per capita personal income.

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

Per Capita Personal Income Change 2008-2014 by County
.. relative to U.S 2008-2014 change

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

Interactive Analysis – County or State Profiles
The following graphic illustrate use of the interactive table to view an economic profile for Harris County, TX. Use the table to examine characteristics of any county or state. Click graphic for larger view.

Interactive Analysis
– comparing per capita personal income across counties
The next graphics illustrates use of the interactive table to rank/compare per capita personal income across counties. Rank/compare states. Choose any of the economic profile items. 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.

Personal Consumption Expenditures by State: Updates & Pattern Analysis

.. data and tools to develop insights into personal consumption patterns by state .. growth in state personal consumption expenditures (PCE) – the measure of goods and services purchased by or on behalf of households – decelerated to 3.6 percent on average in 2015 from 4.4 percent in 2014. In 2015, PCE growth ranged from 1.5 percent in Wyoming to 5.0 percent in Florida. PCE by state data for 16 expenditure categories are shown for the U.S. and by state in the interactive table. See related Web section for more detail.

Per Capita Personal Consumption Expenditures
  — Patterns & Characteristics by State

The following graphic shows patterns of percent change in total PCE 2010-2015 by state labeled with 2015 per capita total PCE. Use CVGIS project to examine PCE by types and different years. Integrate additional subject matter and types of geography. Click graphic for larger view with details.

– views developed with CVGIS and related GIS project & datasets.

In 2015, the fastest growing categories of expenditures across all states were food services and accommodations, health care and other nondurable goods. These categories along with housing and utilities were also the largest contributors to growth in total PCE by state.

Per capita PCE by state measures average PCE spending per person in a state. Across all states, per capita total PCE was $38,196. Per capita PCE by state ranged from a high of $49,717 in Massachusetts to a low of $29,330 in Mississippi.

Personal Consumption Expenditure by Category
PCE by state is the state counterpart of the Nation’s personal consumption expenditures (PCE). PCE by state measures the goods and services purchased by or on behalf of households and the net expenditures of nonprofit institutions serving households (NPISHs) by state of residence for all states and DC. PCE by state reflects spending on activities that are attributable to the residents of a state, even when those activities take place outside of the state. Per capita PCE by state measures average PCE spending per person in a state.

Interactive Analysis
The following two graphics illustrate use of the interactive PCE table. View 1 shows Texas by PCE type ranked in ascending order on percent change from 2010 to 2015 (ranked on far right column). View 2 shows Texas by PCE type ranked in descending order on percent change from 2010 to 2015 (ranked on far right column). Use the table to examine characteristics of states of interest. Click graphic for larger view.

Texas by PCE Type; Ranked Ascending on PCPCE Change 2010-15

Texas by PCE Type; Ranked Descending on PCPCE Change 2010-15

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.

Metropolitan Area Gross Domestic Product: Trends & Updates

… data and analytical tools to examine Metro GDP patterns and trends.  As a policy-maker, investor, business, advisor or stakeholder, it is important to know how and where the metro economy is changing … and how one or selected metros relate to the U.S. and other metros. Is metro X changing in a different direction than metro Y? By how much, why and is there a pattern? What does the healthcare sector, for example, contribute to a metro’s gross domestic product (GDP)? How does it compare to peer metros? How is the healthcare industry trending? Metro GDP data can provide insights and answers to these important questions. Developing insights using metro GDP data — an example. See related Web section for more detail.

Change in Per Capita Real GDP by Metro, 2010-2015
The following graphic shows patterns of change in per capita real GDP by metro from 2010 to 2015. The orange and red fill patterns show metros experiencing a decrease in per capita real GDP over the period. Click graphic for larger view that shows the 2015 rank of the metro among all 382 MSAs based on 2015 per capita real GDP.

— view created using CV XE GIS and associated MetroGDP GIS Project

282 metropolitan statistical areas, of the total 382, experienced an increase in real Gross Domestic Product (GDP) between 2010 and 2015. Growth was led by growth in professional and business services; wholesale and retail trade; and finance, insurance, real estate, rental and leasing, Collectively, real GDP for U. S. metropolitan areas increased 2.5 percent in 2015 after increasing 2.3 percent in 2014. Use the interactive table and GIS project/datasets described in this section to view/analyze patterns and characteristics in metros of interest.

Illustrative GDP by Sector Trend Profiles
Real GDP by sector profiles are available for the U.S. and each state and MSA. The Metro GDP data are part of the State & Regional Income & Product Accounts (SRIPA). The following profiles illustrate these data for metros, states and the U.S.

Atlanta, GA MSA
Charlotte, NC-SC MSA
Chicago, IL MSA
Columbia, MO MSA
Houston, TX MSA
Phoenix, AZ MSA
United States
Missouri
Texas

Metro Situation & Outlook Reports
View Metro GDP 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. GDP tells an important but small part of the broader metro demographic-economic characteristics. Most metros have sub-county areas experiencing growth or activity sometimes masked when looking at the entire metro. Click a metro (metro GDP estimated for MSAs only) link in the table at upper right to view the GDP estimate in context of related subject matter.

Interactive Analysis
The following graphic shows an illustrative view of the interactive MetroGDP table. This view shows California MSAs ranked in descending order on percent change in per capita real GDP from 2010 to 2015 (ranked on far right column). Use the table to examine characteristics of metros in regions 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.