Tag Archives: Texas

Metro Population & Components of Change Trends 2010-2016

.. tools and data to examine how the U.S. by metro population is changing. Is the population moving away or into metros of interest? What are the trends; what is causing the change? What are the characteristics of the population moving in and out? How might this impact your living environment and business?

This section provides information on how and why the population is changing by metro from 2010 to 2016 in terms of components of change: births, deaths and migration. It provides a summary of tools, interactive table and GIS project, to analyze population change by metro using latest Census Bureau estimates through 2016. These data are used by ProximityOne to develop/update annual demographic-economic projections.  See related Web page to access full interactive table and more detail.

Patterns of Population Change by Metro, 2010-2016
The following graphic shows how metros (MSAs – Metropolitan Statisticsl Areas) changed from 2010 to 2016 based on percent population change. Click graphic for larger view; expand browser window for best quality view.

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

Narrative Analysis of Metro Demographic Change in Context
A narrative summary and analysis of metro demographic characteristics and change, contextually with other data and geography, is provided for each metro in the Situation & Outlook Reports. See more about the wide-ranging subject matter that are knitted together in the schedule of updates. Examine metro dynamics in context of the U.S. overall and related states and counties.

The nation’s 382 Metropolitan Statistical Areas (MSAs) had a population of 277.1 million in 2016 (86% of the total population). MSAs increased by 2.3 million people from 2015. The nation’s 551 Micropolitan Statistical Areas (MISAs) had a population of 27.7 million in 2016 (9% of the total population). MISAs increased by 16,000 people from 2015. See more highlights below

MSAs and MISAs together, or metro areas, comprised the set of Core-Based Statistical Areas (CBSAs). Each metro/CBSA is defined as a set of one or more contiguous counties.

Related Sections
• Metros Main
• Situation & Outlook Reports
• City/Place Population Trends
• County Population Trends
• County Population Projections to 2060
• ProximityOne Data Service

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.

See more about these topics below:
• Natural Increase/Change; birth & deaths
• Migration; net international, net domestic, net migration

Using the Interactive Table – Peer Group Analysis
Use the full interactive table to examine U.S. national scope metros by population and components of change. Consider an application where you want to study metros having a 2016 population between 250,000 and 300,000. Use the tools below the interactive table to select these metros as illustrated in the graphic shown below. The graphic shows these metros ranked on the overall U.S. metro rank (percent population change 2010-2016). As shown in the graphic, the Greeley, CO metro was ranked 11th among all metros and the fastest growing metro in this group. Use the tools/buttons below the table to create custom views.

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.

TractWatch — Examining Small Area Change

Understanding the demographic-economic landscape for small area geography and how it is changing is vital for many stakeholders. Businesses and other organizations need to know how their market/service areas are changing … getting answers to questions like knowing about recent trends, where we are now and the how/where/how much things might change in the future.

Examining Tract Change
The following view shows census tracts (black boundary) located in the northeast Houston, TX area. Tracts are labeled with 2017 population estimates and percent population change from 2010 to 2017. Tract geography and characteristics are shown in context of three cities/places — Houston (orange cross-hatch), Humble (blue) and Atascocita CDP (green). It is easy to see what census tracts intersect with what cities and where. The pointer/hand is located in census tract 48-201-240902, partly intersecting with Humble city. The tract 2017 population of 12,984 reflects an increase of 10.4% since 2010. The dark brown bold boundary at the top of this tract is the Harris County, TX boundary.

.. view developed with ProximityOne CV XE GIS and related GIS project.
.. create views like this for any area in the U.S.; add your own data.

TractWatch tells us which tracts in a region of interest changed during the past year based on quarterly observable data with only a one quarter lag.

Census Tracts & TractWatch
TractWatch is a new tool/service focused on examining recent demographic-business change for each census tract. These approximate 74,000 geographic areas cover the U.S. wall-to-wall and averaged 4,000 population as of Census 2010. Tracts have a generally stable geography between decennial censuses and are coterminous with county boundaries. Tracts cover the U.S. with more than a 2-to-1 ratio compared to ZIP code areas (see tract-ZIP relationship table).

Integrated with Situation & Outlook
TractWatch insights are developed through the use of the ProximityOne Situation & Outlook (S&O) database and information system — a part of S&O demographic-economic estimates and projections developed and updated annually. The 2017 vintage tract estimates and projections (annual data) cover the period 2010 through 2022 (5-year projection).

TractWatch – Monitoring Change
As a part of the S&O annual estimates and projections development, a range of measures are updated quarterly at the census tract level. Quarterly data are developed that include population, housing units, vacant units, households and business establishments.

There is only a one-quarter lag in the availability of observable census tract data. For example, observable 2017Q1 data can be added to the S&O database in July 2017. Data are analyzed and converted into a TractWatch national dataset.

Situation & Outlook Reports
The Situation & Outlook Reports (S&O Reports) are updated weekly, for the U.S. and each county, metro and state. TractWatch is a part of the “Recent Change and Outlook” S&O Report section and updated quarterly. See schedule of updates the shows when TractWatch is updated.

The S&O Reports (metro and county) Recent Change and Outlook section includes a list of census tracts which have shown significant change over the past year for that geography. A table of typically 10-to-25 key tracts are listed in a table with selected demographic-business change attributes.

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.

115th Congressional Districts: Analysis and Insights

.. interpretative data analytics; tools, data & methods ..  this section is focused on 115th Congressional District geographic, demographic and economic patterns and characteristics. Use tools and data reviewed here to examine/analyze characteristics of one congressional district (CD) or a group of CDs based on state, party or other attribute. Use the GIS resources described here for general CD reference/pattern/analytical views, to examine current demographics and demographic change and for redistricting applications. See this related Web section for more details.

Examining the 115th Congressional Districts
• the 115th Congress runs from January 2017 through December 2018.
• FL, MN, NC, VA have redistricted since the 114th CD vintage;
  .. some 115th CDs have new boundaries compared the 114th CDs.
• view, rank, compare CDs using the interactive table.
  .. table uses ACS 2015 data for 115th CDs & include incumbent attributes.
  .. examine districts by party affiliation.
• use these more detailed 114th CD interactive tables
  .. data based on 2015 American Community Survey – ACS 2015.
  .. corresponding data for the 115th CDs from ACS 2016 available Sept 2017.
• use the new GIS project including 114th & 115th CDs described below.
  .. create CD thematic and reference maps;
  .. examine CDs in context of other geography & subject matter.
• join us in the April 25 Data Analytics Lab session

Visual Analysis of Congressional Districts
The following views 1) provide insights into patterns among the 115th CDs and 2) illustrate how 114th to 115th geographic change can be examined. Use CV XE GIS software with the GIS project to create and examine alternative views.

Patterns of Household Income by 115th Congressional District
The following graphic shows the patterns of the median household income by 115th Congressional District based on the American Community Survey 2015 1-year estimates (ACS2015). The legend in the lower left shows data intervals and color/pattern assignment

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

Charlotte NC-SC Metro Area
  – with 114th/115th Congressional District 12

The following graphic shows North Carolina CD 12 with 114th boundary (blue) and 115th boundary (pale yellow) and Charlotte metro bold brown boundary. Click graphic for larger view with more detail. Expand browser window for best view.

.. view developed using the CVGIS software.

• View zoom-in to Charlotte city & Mecklenburg County.

115th Congressional District Interactive Table
Use the interactive table to examine characteristics of one congressional district (CD) or a group of CDs. The following graphic illustrates use of the interactive table. First, the party type was selected, Democratic incumbents in this example. Next, the income and educational attainment columns were selected. Third, the set of districts were sorted on median household income. It is quick and easy to determine that CA18 has the highest median household income and that the MHI is $1,139,900. Try using the table to examine districts 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.

County 5-Year Trends: Income & Income Inequality

.. tools and data to examine how the U.S. by county household income and income inequality are changing … how is household income changing in counties of interest? What are the trends; what is causing the change? What are the characteristics of income inequality and how is it changing? How might this change impact your living environment and business?

This section provides access to tools and data to examine U.S. by county measures of household income and income inequality between two 5-year periods (2006-10 and 2011-2015). These data can provide insights into how household income and income inequality are changing for one county, a group of counties and the U.S. overall. Use the interactive table to view median household income and measures income inequality for all counties. See more detail about these topics here. Measures of income inequality can be estimates/examined using the Gini Index.

The Gini Index & Measuring Income Inequality
The Gini Index is a dimensionless statistic that can be used as a measure of income inequality. The Gini index varies from 0 to 1, with a 0 indicating perfect equality, where there is a proportional distribution of income. A Gini index of 1 indicates perfect inequality, where one household has all the income and all others have no income.

At the national level, the 2015 Gini index for U.S. was 0.482 (based on 2015 ACS 1-year estimates) was significantly higher than in the 2014 ACS Index of 0.480 (based on 2014 ACS 1-year estimates). This increase suggests that income inequality increased across the country.

Examining Household Income & Income Inequality Patterns & Change
The following two graphics show patterns of the GIni Index by county. The first view is based on the American Community Survey (ACS) 2010 5-year estimates and the second is based on the ACS 2015 5-year estimates. The ACS 2010 estimates are based on survey respondents during the period 2006 through 2010. The ACS 2015 estimates are based on survey respondents during the period 2011 through 2015. One view compared with the other show how patterns of income inequality has changed at the county/regional level between these two 5-year periods.

Following these Income Inequality views are two corresponding views of median household income; using data from ACS 2010 and ACS 2015. Use CV XE GIS software with the GIS project to create and examine alternative views.

Patterns of Income Inequality by County; ACS 2010
The following graphic shows the patterns of the Gini Index by county based on the American Community Survey 2010 5-year estimates (ACS1115). The legend in the lower left shows data intervals and color/pattern assignment

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

Patterns of Income Inequality by County; ACS 2015
The following graphic shows the patterns of the Gini Index by county based on the American Community Survey 2015 5-year estimates (ACS1115). The legend in the lower left shows data intervals and color/pattern assignment

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

Patterns of Economic Prosperity by County; ACS 2010
The following graphic shows the patterns of median household income ($MHI) by county based on the American Community Survey 2010 5-year estimates (ACS1115). The legend in the lower left shows data intervals and color/pattern assignment

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

Patterns of Economic Prosperity by County; ACS 2015
The following graphic shows the patterns of median household income ($MHI) by county based on the American Community Survey 2015 5-year estimates (ACS1115). The legend in the lower left shows data intervals and color/pattern assignment

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

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.

Creating Custom School District Maps

…tools & data to map & geospatially analyze school districts. Ready-to-use state-by-state GIS projects may be downloaded enabling you to view and create custom maps almost instantly. Benefit from the power of using GIS software to perform tasks not available on Web-based mapping options. Use the latest school district and related shapefiles. See more information about using these resources in this related Web section.

Federal Revenue per Student by School District
Create views similar to the one shown below. Optionally combine layers as illstrated here by showing four Texas metros.

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

Extending Reference and Analytical Possibilities

Texas by School District
Examine reference maps at the state, regional or local level. Optionally combine with roads/streets and other layers.

Patterns of Economic Prosperity by School District
Select from many ready-to-use demographic-economic subject matter items to create custom pattern views.

Drill-down — Houston Metro Area by School District
Zoom-in to a school district of interest. Set attributes of district as shown here.

County/School District
Visually examine the boundaries or school districts and counties. This view shows Harris County, TX area; select a county of interest.

Drill-down to Street Level
Add road/street and other layers. Drill-down within Fort Bend ISD, Houston metro, showing general earth surface features with streets layers. Mouse used to click on street (see pointer) and display mini-profile of street segment attributes.

Use for Analysis, Reference or in the Classroom
Schools and teachers: consider using these resources for classroom use. Familiarize students about how GIS resources can be used with a minimum of learning time and no cost. Enable students to use their own geography and adapt that learning to more general geography. See related Mapping Statistical Data ready-to-use GIS projects.

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.

Examining County Migration: 2010-2016

.. tools and data to examine U.S. by county migration 2010 to 2016 … is the population moving away or into your counties of interest? What are the trends; what is causing the change? What are the characteristics of the population moving in and out? How might this impact your living environment and business?

The total net international migration among all counties 7/1/2010 – 7/1/2016 was 5,641,260, an annual average of 940,432. The sum of net domestic migration among counties is zero by definition, but domestic migration among counties varies radically by size and direction. This section is focused on U.S. by county migration from 2010 to 2016. Migration is one component of change used to develop population estimates. See more about county population estimates and components of change in this related Web section.

Largest 10 Counties Based on 2016 Population
This table shows how domestic migration varies widely among the most populated counties. Use this interactive table to develop your own custom views for counties of interest.

Patterns of Population Change by County, 2010-2016
– the role and impact of migration
The following graphic shows how counties have gained population (blue and green) and lost population (orange and red) during the period 2010 to 2016. 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
– net migration and natural 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.

Using the Interactive Table
– examining migration by county
Use the interactive table to examine characters of counties by states, metro or peer group. The following graphic illustrates use of the interactive table to view net migration for the Houston metro by county. The net migration button was used to select only the net migration columns, FindCBSA button used to show only counties in this metro and the final step was to sort the resulting table on 2016 population. 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.

Tools to Analyze County Demographic-Economic Characteristics

.. demographic-economic characteristics of counties are essential for business development, market analysis, planning, economic development, program management and general awareness of patterns and trends. This section provides access to data and tools to examine these data for all counties in the U.S. This annual update includes geographic area characteristics based on ACS 2015 data.  The tools/data are organized into four related sections summarized below.

1. General Demographics
View interactive table at http://proximityone.com/us155dp1.htm
Patterns of School Age Population by County
Use GIS tools to visually examine county general demographics as illustrated below. The following view shows patterns of percent population ages 5 to 17 years of age by county — item D001-D004-D018 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

2. Social Characteristics
View interactive table at http://proximityone.com/us155dp2.htm 
Patterns of Educational Attainment by County
– percent college graduate
Use GIS tools to visually examine county social characteristics as illustrated below. The following view shows patterns of percent college graduate by county — item S067 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

3. Economic Characteristics
View interactive table at http://proximityone.com/us155dp3.htm 
Patterns of Median Household Income by County
Use GIS tools to visually examine county economic characteristics as illustrated below. The following view shows patterns median household income by county — item E062 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

4. Housing Characteristics
View interactive table at http://proximityone.com/us155dp4.htm 
Patterns of Median Housing Value by County
Use GIS tools to visually examine county housing characteristics as illustrated below. The following view shows patterns median housing value by county — item E062 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

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.