Category Archives: Trends

Housing Value Appreciation by 3-Digit ZIP Code: 2015Q3-2016Q3

.. tools, data and methods to examine housing value appreciation from 2015Q3 to 2016Q3 by 3-digit ZIP code based on the Housing Price Index (HPI).  How is the housing value changing in areas of interest?  How does housing value appreciation compare among a set of ZIP codes? Which ZIP code areas have the highest and lowest housing value appreciation in a state, region custom defined areas of interest? The HPI is calculated in part using home sales price information from Fannie Mae- and Freddie Mac-acquired mortgages. The U.S. all transactions HPI rose 5.6 percent from the 3rd quarter of 2015 to the 3rd quarter of 2016. Rank, compare, evaluate quarterly or annual housing value change for the approximate 900 3-digit ZIP code areas using the interactive table.

3-Digit ZIP Codes with Highest Housing Value Appreciation
Derived from the interactive table below this table shows the ten 3-digit ZIP codes having the highest housing value appreciation over the year 2015Q3-2016Q3. The areas are ranked on percent HPI change (rightmost column).

Gaining Insights in Housing Prices, Conditions & Markets
.. data, tools and methods to assess characteristics, patterns & trends
.. weekly Housing Data Analytics Lab sessions

Patterns of Housing Value Change by 3-Digit ZIP Code
The following graphic shows housing value appreciation 2015Q3-2016Q3 by 3-digit ZIP code based on the HPI. Use related GIS tools to zoom-in, assign labels, show in context with other geography.

– view developed using CVGIS and related GIS project.
– Click graphic for larger view and details;

Examining Housing Appreciation by 3-Digit ZIP Code
Use the interactive table below to view/rank/compare the non-seasonally adjusted “all transactions” HPI for the most recent 5 quarters for all 3-digit ZIP codes. The ranking table shows the latest quarterly HPI data and preceding quarters for one year earlier. This table will be updated on February 24, 2017, with 4th quarter 2016 data and related prior quarterly estimates and re-computed quarterly change values (last column).

Using the Interactive Table
The following graphic illustrates use of the HPI by 3-digit ZIP code interactive table. HPI data are shown for the quarterly period 2015Q3 through 2016Q3. The state selection below the table has been used to select only California ZIP codes. The Group1 button below the table has been used to select ZIP codes with a 2016Q3 HPI value of 175 ore more. The table is then sorted on the rightmost column. The resulting view shows that among all California 3-digit ZIPs having an HPI of 175 or more in 2016Q3, ZIP code 948/Richmond CA had the highest housing value appreciation — a 10.6% increase over the year.

Use the interactive table to examine states or ZIP code groups 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.

National Children & Education Statistics Program Updates

.. NCES Program updates .. tools, data & methodology to examine national scope children & education .. school, school district & extended geographic-statistical data with drill-down to school and intersection level. See more about the NCES Program below.

New this Week
ACS 2015 school district demographic-economic interactive tables
– view, compare, analyze selected/all U.S. school districts
– more focused blog updates coming soon.

School Districts with Highest Median Household Income
Use the interactive table to examine economic characteristics of school districts. Below is a list of the 10 school districts having the highest median household income developed using the Economic Characteristics interactive table. Develop similar views for metros and states of interest.

– ranked on item E062 — median household income.
– click graphic for larger view.

Use GIS tools to develop thematic pattern maps such as the one shown below with NCES GIS projects. Select from hundreds of statistical measures. Create your own regional;/district views. Integrate other data.

Patterns of Economic Prosperity by School District
– median household income (item E062 in table)

– view developed with CVGIS software & related GIS project and data.
– click graphic for larger view.

See the School Districts Economic Characteristics Interactive Table.

About the National Children & Education Statistics Program
The National Children & Education Statistics (NCES) Program provides access to tools, data & methodology to examine national scope children’s demographics & education-related characteristics. These resources enable stakeholders to view and analyze detailed geographic and statistical data at the school, neighborhood, community, attendance zone, school district and higher level geography. Integrate these data with drill-down demographic-economic data to the census block and intersection levels. Examine characteristics of schools, school districts and education data with related and higher level geography including urban/rural, cities, counties, metros, state and the U.S.

See NCES Main Section.

Contents: Summary of NCES Program Resources
Click a link to view more detail on a selected topic.
Updates: New Resources, Events & Related Topics
Analytics, Blogs, Studies
Using Software Tools & Datasets
01 Mapping & Visual Analysis Tools
02 School District Annual Demographic-Economic Data Resources
03 Children’s Demographics & Living Environment by School District
04 School District Enrollment & Operational Characteristics
05 School District Finances: Sources & Uses of Funds
06 School District Geographic Size & Characteristics
07 School District-ZIP Code Area Relationship Table
08 K-12 Public Schools
09 K-12 Private Schools
10 K-12 Public School Attendance Zones
11 K-12 Public Schools by Urban/Rural Status
12 Census Tract Demographic-Economic Characteristics
13 Metropolitan Area Situation & Outlook Reports

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.

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.