Category Archives: APIGateway

API Gateway

Using GIS & GeoDemographics

.. join us in the GIS & GeoDemographics self-paced, online course.

Visual representation, maps, of demographic data by geographic area can be exciting and rewarding. Using Geographic Information Systems (GIS) can bring maps alive. Creativity is boundless. The banner at the top of the corresponding Web section presents a static view of a map rendered using GIS. This map shows the Los Angeles area by census tract. For the analyst or stakeholder, it shows something more — the percent Asian citizen voting age population by tract, overlayed with Congressional District boundaries and codes. It shows relationships, patterns. Using the power of GIS, the zoom level, colors, legend, and labeling can all be changed immediately. You, the GIS user, are at once analyst, artist and storyteller. In control of your medium, canvas, you further your benefits from use these software and data by making dynamic presentations in collaborations. Make compelling arguments. Capture your views and blend them with words and charts into documents. Welcome to the world of GIS and geodemographics.

Mapping census block demographics
The graphic shown below illustrates use of GIS software with the TIGER digital map database census block shapefile to show census blocks for two Ohio counties in context of 2018 CBSAs/Metros. Clicking on a census block (see pointer) shows a mini profile for that block.

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

Using GIS & GeoDemographics .. about the course
Examining geographic-demographic-economic characteristics, patterns and trends … researchers, policymakers, journalists, administrators, students among others. How can you most benefit from using the TIGER geographic data to meet your objectives? These data are available at no cost. Join us in the Using GIS Tools & GeoDemographics online, self-paced course. Learn all aspects of using the Census Bureau TIGER files and related Census-sourced and other Federal statistical data. Augment your professional skills; participants receive all required data, methods and tools. Your personal session is developed and coordinated by Warren Glimpse. You receive the GIS course certificate upon completion. The course may be started at any time and includes requisite Windows-based CV XE GIS software. The course assumes the participant has basic familiarity with a Windows computer, Internet and spreadsheet operations. No GIS related experience is required. Experienced GIS professionals also benefit by learning about the use and nuances of Census-sourced data and integrating these with other data. The structure includes four segments that typically require 2.5 hours each. It is feasible to complete the course in a day or two though we suggest two weeks.

Use Geographic Information Systems (GIS) with TIGER … integrate/analyze data from American Community Survey (ACS) or the decennial census (Census 2010) (Census 2020) into TIGER files to make thematic maps. Merge data from other statistical programs. Geocode your address-based data and add the geocoded data to a GIS project/map view; examine patterns. View your market/service areas and assess competitive position, unmet opportunities. Learn about procedures and strategies to develop GIS projects that meet your needs. Acquire the tools and data to perform these tasks without spending more — provided as a part of our course.

The course is not just about TIGER and demographic-economic data. It provides a well-rounded framework for how to use GIS. While TIGER is a focus, we review procedures to access and use thousands of public use shapefiles and GIS files that may be useful to you. It provides a well-rounded framework for how to use GIS.

Enroll today …
Click the enrollment button/link (opens new page) to enroll now ($395). We will contact you and provide next step information.   Questions? Call us at (800)364-7656.

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.

Block Group Demographic Data Analytics

.. use tools described here to access block group data from ACS 2016 (or ACS2017 in December 2018) using a no cost, menu driven tool accessing the data via API. Select from any of the summary statistic data. Save results as an Excel file or shapefile. Add the shapefile to a GIS project and create unlimited thematic pattern views. Add your own data. Join us in a Data Analytics Web session where use of the tool with the ACS 2017 data is reviewed.

See related Web section for more details.
– examine neighborhoods, market areas and sales territories.
– assess demographics of health service areas.
– create maps for visual/geospatial analysis of locations & demographics.

Illustration of Block Group Thematic Pattern Map – make for any area

– click graphic to view larger view
– pointer (top right) shows location of Amazon HQ2

Topics in this how-to guide (links open new sections/pages)
• 01 Objective Thematic Pattern Map View
• 02 Install the CV XE GIS software
• 03 Access/Download the Block Group Demographic-Economic Data
• 04 Download the State by Block Group Shapefile
• 05 Merge Extracted Data (from 03) into Shapefile (04)
• 06 Add Shapefile to the GIS Project; Set Intervals
• 07 Viewing Profile for Selected Block Group
• 08 BG Demographics Spreadsheet
• 09 Block Group Demographics GIS Project
• 10 Why Block Group Demographics are Important

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

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

API Integrated Data Profiles

Getting an integrated view of up-to-date decision-making information … many key demographic-economic measures are developed by different agencies and organizations. It can be challenging to assemble these data for a holistic, more comprehensive view. Differently sourced data are developed for varying time periods and frequency of update; it can be problematic in bringing together monthly, quarterly and annual data — and have the most up-to-date view possible.

This section is focused on the “APIGateway Integrated Data Profile” (IDP). The IDP is a report providing monthly, quarterly, annual and decennial data by county — any county in the U.S. See the current Mecklenburg, NC IDP. See more general information.

Mecklenburg County, NC (Charlotte NC-SC metro)

View illustrative IDPs:
Maricopa County, AZ (Phoenix metro)
Santa Clara County, CA (San Jose metro)
Johnson County, KS (Kansas City metro)
Harris County, TX (Houston metro)

Create Your Own IDPs Now
Freshly updated IDPs can be generated for counties of interest using the no-fee, no-cost APIGateway. Follow these simple steps (How to Run Reports) to install the application on your Windows computer; create profiles of interest.

API Technology
Using API (Application Programming Interface) technologies, the APIGateway fetches data from multi-sourced servers where updated data are stored. There are no large database downloads; no custom application development steps.

The IDP reports are generated in HTML structure and can be easily viewed with a Web browser. The data, and thus the reports, update monthly. Optionally update an IDP in March/monthly, getting new/updated workforce data … establishments, employment, wages by industry sectors and employment/unemployment.

Longitudinal Data
An interesting feature of the report is that it shows the annual demographic-economic data for Census 2000 and Census 2010 as well as the annual American Community Survey data and Census Bureau annual model-based estimates in a side-by-side manner. This longitudinal data view using multiple data sources creates an easy-to-consume, powerful and unique way to gauge patterns and trends. Monthly workforce data provide a valuable, more recent, update.

Related County Demographic-Economic Data Resources
  • See CountyTrends Web section

IDP Updates
The IDP structure is new and continues to evolve. Please send feedback and suggestions that might improve usefulness.

Road Corridor Demographics

There are more than 50 million road segments in the U.S. While it is most common to view/analyze small area demographics for geographic areas such as census blocks, block groups or census tracts, the focus of this section is on providing demographic attributes for the left and right side of individual road segments. 

Road corridor demographics are demographics attached to the right- and left-sides of a road/street segment. These are demographics (e.g., population, housing, median income, etc.) for the census block or block group that the road segment faces or passes through. A road/street segment is the section of a road/street between two intersections.

Using road corridor demographics, the characteristics of chained/linked road segments, a pathway or a corridor, can be analyzed. Road segments have left- and right-side address ranges and road corridor demographics can be developed through the aggregation of address-oriented data located on the road of interest. Address data can be geocoded and attached to road segement. Examples include customers, housing sales, or patient data on a particular road segment.

See more details about developing and using road corridor demographics at road corridor demographics. The tools and methods described there are in production use. They may be applied to any county or higher-level geographic area in the whole U.S. This one-step batch application requires TIGER/Line edges, feature names and faces shapefiles. The CV XE API acquires the demographic data via Internet and codes these demographics into the road corridor shapefile, which is created as the primary output of the process.

The application demonstrated at road corridor demographics is focused on Alexandria, Virginia. The yellow highlighted road segment in the map graphic below is W. Braddock Road but could be any other set of roads.

Using these Resources
The CV XE GIS software available to members of the ProximityOne User Group (join now, no fee) can create the basic corridor demographics shapefile for any county in the U.S. The resulting shapefile may be used with CV XE GIS to perform analyses and/or used with other GIS software.

Small Area Disability Demographics

Goto ProximityOne   People with disabilities bring unique sets of skills to the workplace, enhancing the strength and diversity of the U.S. labor market. They make up a significant market of consumers, representing more than $200 billion in discretionary spending and creating technological innovation and entrepreneurship. People with disabilities also often rely on various government interventions to maintain their participation in the community. Demographic data about people with disabilities help stakeholders better understand needs and make more informed decisions relating to a wide range of topics concerning people with disabilities.

New Disability Demographics
Disability demographics from the American Community Survey (ACS) have been available for cities, counties and larger areas with population over 65,000 for a few years. New as of December 2013, are ACS 2012 5-year (ACS0812) disability demographics available for all cities, school districts, counties and geographies down to the census tract level — and ZIP code area. Disability demographics are often “masked” when analyzed for larger population areas. Masked, not in the sense of suppressed data, but that concentrations that might be identified at the census tract level may become less prominent when viewed in the aggregate of county or higher level geographies. This section reviews disability-related ACS0812 data available for these small area geographies and how they can be used to facilitate decision-making.

Disability Concepts
Subject matter categories about people with disabilities from ACS generally involve limitations with vision, hearing, cognitive, ambulatory, self-care or independent living difficulty.

• Vision — blindness or serious difficulty seeing even when wearing glasses
• Hearing — deafness or serious difficulty hearing
• Cognitive — difficulty concentrating, remembering or making decisions
• Ambulatory — serious difficulty walking or climbing stairs
• Self-care — difficulty bathing or dressing
• Independent living — difficulty going outside to shop or visit a doctor’s office

Visual Analysis of Disability Patterns by Census Tract
The following view shows the population ages 5-17 years with disabilities (ACS0812 estimates) by census tract for Harris County, Texas (Houston area). The inset legend shows color patterns associated with data from Table B18101 (see below).
The above view was developed using the CV XE GIS software with a GIS project. The GIS project includes a county by census tract layer with Table B18101 (see below) integrated subject matter. This particular view shows patterns of the sum of items B18101007 (males age 5-17 years with disability) and B18101026 (females age 5-17 years with disability). View all items in this table by opening excel file B18101 in the section below. Members of the ProximityOne User Group may download and use this project to develop similar views on their computer. Add other geographies to the view such as school districts or cities. Add your own data from any source. Join the User Group now, no fee.

Disability Subject Matter Data/Tables
View the scope of ACS 2012 5-year estimates subject matter using the interactive table at Sort on the rightmost column and scroll to Disabilities. These same tables are listed below. Click a link on the table number to view a sample of the data (an excel file will open). All data tables are provided for Houston ISD (HISD), Texas school district. The same scope of data are available for any school district.

Table B18101 shows that there are more than 9,000 K-12 school age children with disabilities in Houston ISD (3,493 females, 6,133 males). Using the additional Table B18101 iterations, the distribution of this population can be examined by race and origin. Of course, school age children without disabilities can be impacted by other household members that do have disabilities. Demographics provided in these tables show characteristics for the total population and many age groups. Tables B18102 through B18107 provide insights into the number of persons by age and gender by type of disability. Table B18135 provides data on health insurance coverage. Employment status and workforce data are provided by Tables C18120 and C18121. Earnings and poverty characteristics data are provided by Tables B18140, C18130 and C18131.

ACS 2012 Disability Tables
B18101 — Sex by Age by Disability Status
B18101A — Age by Disability Status:  White alone
B18101B — Age by Disability Status:  Black or African American alone
B18101C — Age by Disability Status: American Indian and Alaska Native alone
B18101D — Age by Disability Status: Asian alone
B18101E — Age by Disability Status: Native Hawaiian and other Pacific Islander
B18101F — Age by Disability Status: Some other race alone
B18101G — Age by Disability Status: Two or more races
B18101H — Age by Disability Status: White alone, not Hispanic or Latino
B18101I — Age by Disability Status: Hispanic or Latino
B18102 — Sex by Age by  Hearing Difficulty
B18103 — Sex by Age by Vision Difficulty
B18104 — Sex by Age by Cognitive Difficulty
B18105 — Sex by Age by Ambulatory Difficulty
B18106 — Sex by Age by Self-Care Difficulty
B18107 — Sex by Age by Independent Living Difficulty
B18135 — Age by Disability Status by Health Insurance Coverage
B18140 — Median Earnings in the Past 12 Months
C18108 — Age by Number of Disabilities
C18120 — Employment by Disability Status
C18121 — Work Experience by Disability Status
C18130 — Age by Disability Status by Poverty Status
C18131 — Ratio of Income to Poverty Level Past 12 Months by Disability

Accessing & Using the Data
Access the above tables using the CV APIGateway. Integrate the disability-related data with other demographic-economic data from ACS 2012 and other data sources. Save data for multi-geography such as all census tracts for a county. Merge these data into a county by tract shapefile and use the CV XE GIS software to visually examine small area patterns of the population with disabilities.

Linguistic Isolation Patterns

Goto ProximityOne  Size and distribution data on speakers of languages other than English and on their English speaking ability are important for many reasons. These data help us understand where populations with special needs exist and how they are changing. The data are used in a wide-ranging legislative, policy, and research applications. Many legal, financial and marketing decisions involving language-based issues make use of data on language use and English-speaking ability.

This post reviews data useful to analyze “household linguistic isolation” based on American Community Survey (ACS) 5-year estimates at the block group geographic level. The same scope of subject matter is available for higher level geography.  The following graphic shows patterns of linguistic isolation in Queens County, NY.  Block groups colored in red have more than 50-percent of households where no household member age 14 years and over speaks English “very well”.

Patterns of Linguistic Isolation; Queens County, NYli_queens

One definition of a “linguistically isolated household” is a household in which all adults have substantial limitation in communicating English. In the ACS data, a household is classified as “linguistically isolated” if 1) no household member age 14 years and over spoke only English, and 2) no household member age 14 years and over who spoke another language spoke English “very well”.

Like many demographic measures, linguistic isolation tends to be “masked” when analyzing data for larger geographic areas, even census tracts, are used. Block group geography provides an ability to locate linguistic isolation in sub-neighborhood areas.

Census Block Groups sit in a “mid-range” geography between census blocks and census tracts. All cover the U.S. wall-to-wall and nest together, census blocks being the lowest common denominator for each. Block Groups (BGs) are the smallest geographic area for which annually updated American Community Survey (BG) data are tabulated.

Advantages of using BG geodemographics include the maximum degree of geographic drill-down (using ACS data) … enabling the most micro-perspective of demographics for a neighborhood or part of study area. A disadvantages of using BG estimates is that typically the smaller area estimates have a relatively higher error of estimate.

Language Spoken by Households
The table presented below shows data from ACS Table B16002 Households by Linguistic Isolation for block group 1 in census tract 046300 in Queens County (081) New York (36); geoid=360810463001. This block group is shown in the above map at the pointer. Data for this block group are shown in the rightmost column of the table below. 62.8 percent of households (610) are linguistically isolated (232+60+91).

Table B16002. Household Language by Households
Item Code Item Description Households
B16002001 Total 610
B16002002   English only 12
B16002003   Spanish language 321
B16002004     No one 14 and over speaks English only or speaks English “very well” 232
B16002005     At least one person 14 and over speaks English only or speaks English “very well” 89
B16002006   Other Indo-European languages: 60
B16002007     No one 14 and over speaks English only or speaks English “very well” 60
B16002008     At least one person 14 and over speaks English only or speaks English “very well” 0
B16002009   Asian & Pacific Island languages: 217
B16002010     No one 14 and over speaks English only or speaks English “very well” 91
B16002011     At least one person 14 and over speaks English only or speaks English “very well” 126
B16002012   Other languages: 0
B16002013     No one 14 and over speaks English only or speaks English “very well” 0
B16002014     At least one person 14 and over speaks English only or speaks English “very well” 0

“Language Spoken” categories are based on four major language groups.

Next Steps
Use the CV APIGateway to access Table B16002 and related data for block groups in cities or counties of interest.  Join us in the upcoming December 17, 2013 one hour web session where we talk about using the ACS 2012 5-year demographics for small area analysis.  Those new data are scheduled to be released that day.

ACS 2012 BlockGroup Data

Goto ProximityOne  There are several things to like about the new American Community Survey 2012 (ACS2012) 5-year demographic-economic data (available 12/17/13). These data are one year more recent data than released in December 2012 (the ACS 2011 5-year data).  As a result, they provide an updated and more current picture. Two, this is a third year sequel to having Census 2010 vintage census tract and block group data available.  This de facto three year mini-time series enables a start to examine trends. Three, these estimates are centric to mid-2010 and thus roughly comparable to what would have been “richer demographics” from Census 2010 (had the long-form not been eliminated).  This enables a rough comparison between 2000 and 2010 (it will be the best opportunity ever).  These data provide unique and powerful measures that facilitate development of decision-making information.  The ACS 5-year block group estimates are the smallest geographic areas for which the Census Bureau develops richer demographic-economic data such as income, educational attainment, employment, housing value among a wide range of related items.

The focus of this post is on block group level data … demographic-economic data tabulated for approximately 220,000 areas averaging 1,200 population covering the U.S. wall-to-wall.  Block groups are one of many geographic levels/areas for which ACS 5-year estimates are tabulated.  While it might seem easy to determine what subject matter data are available at the block group level, it is not easy.  Block group data cannot be accessed via the Census Bureau FactFinder online data access tool, so that presents the first challenge.  Fortunately, the ACS block group data can be accessed using the ProximityOne CV APIGateway tool.

Washington DC Area; Median Household Income by Block Group

Is unemployment data tabulated by block group?  Language spoken at home?  If so, what are the corresponding table numbers? Only selected tables are available at the block group level — a situation unique to the block group level geography.  Presently, the only way to determine availability of a subject matter item or data table is to view Appendix E of the technical documentation.  In that section, listing all tables, there is a column with an indicator showing whether or not the table is available at the block group level.

Struggling with this situation in years past, we have developed this Web page that contains an interactive table to facilitate determining subject matter availability by block group.  The interactive table contains a row for each data table for which ACS 2012 5-year data are tabulated.  In the interactive table, there is a column with an indicator showing whether or not that data table is available at the block group level.  This way all of the data tables can be browsed as well as those only available at the block group level.

Below the interactive table a few tool buttons are available.  Now you can do a keyword search on all tables for specific subject matter words, like “Language Spoken.”  Or, show the whole table and click the block group button to view only those tables available at the block group level.

ACS 2012 Public Use Microdata Sample (PUMS) Data
Soon there be related post focused on the ACS 2012 Public Use Microdata Sample (PUMS) data.  That post will also provide improved data navigation and locator tools.

County Monthly Workforce Trends

Goto ProximityOne  Keep up-to-date with current county monthly workforce patterns and trends using the CV APIGateway. Automatically updated with multi-sourced demographic-economic data, the APIGateway Integrated Profile (IP) provides monthly workforce updates from the Bureau of Labor Statistics (BLS) Census of Employment and Wages (place of work data) and Local Area Unemployment Statistics (LAU – place of residence data). This section is focused on data and analytical tools to examine county workforce trends and patterns using the Local Area Unemployment Statistics data.

A unique and important property of the LAU data is that they are the only source of semi-official data available on a national scale for each/all counties and larger places providing current and monthly data on unemployment and the unemployment rate. The next runner-up to these estimates are the ACS 5 year estimates that are a) for a five year period and b) at least 3 years old (to the mid-point of the estimate period) when they become available. These highly perishable and time-sensitive economic measures are important to understanding the relative and absolute strength or weakness of workforce conditions and the employment sector on a local and regional basis.

The table presented below is a section taken from the APIGateway IP for Santa Clara County, CA (San Jose-Cupertino metro). The monthly/annual LAU data shown in the table are available for each/all counties. The APIGateway IP shows these four workforce series from 2011 forward. It auto-updates monthly with only a two-month lag to the reference time period. View a series as a chart: click graphic; on new page click a link shown in the table. Optionally set a wider time interval.
Santa Clara County, CA Monthly Labor Force Characteristics

Using GIS Resources for Visual Pattern Analysis
Separate from the APIGateway IP, the 2008-2012 annual time series data have been integrated into a U.S. by county shapefile. The graphic shown below illustrates how these tools can be used to examine the change in employment conditions by county since the recession started. This view shows the change in the unemployment rate from 2008 to 2012. Counties with red coloring experienced/are experiencing/ a 3-percent or more increase in the unemployment rate in 2012 compared to 2008. Using this measure alone, it is easy to see the extent to which the economy in many areas is still struggling to compensate for the recession impact and exactly which county/regional areas are impacted and how much. While one county might be prospering, many adjacent or nearby counties are not. View zoom-in to Santa Clara county area.

Interactive Table
Click the graphic shown below to use this interactive table to examine this same set of annual workforce data 2008-2012. Viewing the interactive table, click ShowAll button below table and then FindInName with default value “Santa Clara” to view the 5-year series for the same scope of subject matter as shown above in monthly form. The interactive table provides a convenient structure to view, rank, compare counties using these measures.


Next Steps
The U.S. by county shapefile with workforce data shown in the table and used to develop maps shown in this section are available to ProximityOne User Group members. (join now, no cost). Use these resources to develop wide-ranging variations of this view and analyze tabular data on your own computer; integrate your own data; add other types of geography; zoom-in to specific metros/regions. Visit the CountyTrends Web section for more information on county demographic-economic data and analytics.

2013 Metros: Houston, TX

Goto ProximityOne  94% of the U.S. population live in metropolitan areas.  Metropolitan areas are comprised of one or more contiguous counties having a high degree of economic and social integration. This section is one in a continuing series of posts focused on a specific metropolitan area — this one on the Houston-The Woodlands-Sugar Land, TX MSA.   This section illustrates how relevant Decision-Making Information (DMI) resources can be brought together to examine patterns and change and develop insights.  The data, tools and methods can be applied to any metro. About metros.

Focus on Houston-The Woodlands-Sugar Land, TX MSA
A thumbnail … in 2012, the Houston-The Woodlands-Sugar Land, TX MSA had a per capita personal income (PCPI) of $51,004. This PCPI ranked 23rd in the United States and was 117 percent of the national average, $43,735. The 2012 PCPI reflected an increase of 4.5 percent from 2011. The 2011-2012 national change was 3.4 percent. In 2002 the PCPI of the Houston MSA was $34,696 and ranked 37th in the United States. The 2002-2012 compound annual growth rate of PCPI was 3.9 percent. The compound annual growth rate for the nation was 3.2 percent.  These data are based in part on the Regional Economic Information System (REIS).  More detail from REIS for the Houston metro at the end of this section.

Geography of the Houston MSA
The geography of the Houston-The Woodlands-Sugar Land, TX MSA is shown in the graphic below.  The green boundary shows the 2013 vintage metro, black boundary/hatch pattern shows the 2010 vintage boundary, counties labeled. San Jacinto County is no longer a part of the metro.


Changing Metro Structures Reflect Demographic Dynamics
Click here
to view a profile for the 2013 vintage Houston metro. Use this interactive table to view demographic attributes of these counties and rank/compare with other counties.

The Census 2010 population of the 2013 vintage metro is 5,920,416 (6th largest MSA) compared to the 2012 estimate of 6,177,035 (5th largest MSA). See interactive table to examine other metros in a similar manner.

Demographic-Economic Characteristics
View selected ACS 2012 demographic-economic characteristics for the Houston metro (2010 vintage) in this interactive table.  Examine this metro in context of peer metros; e.g., similarly sized metros.  In 2012, the Houston metro had a median household income of $55,910, percent high school graduates 81.1%, percent college graduates 29.6% and 16.4% in poverty.

Houston Demographic-Economic Profiles
Use the APIGateway to access detailed ACS 2012 demographic-economic profiles.  A partial view of the Houston 2010 metro DE-3 economic characteristics profile is shown below.  Install the no fee CV XE tools on your PC to view extended profiles for Houston or any metro. See U.S. ACS 2012 demographic-economic profiles.  Viewing graphic with gesture/zoom enabled device suggested.  

Houston 2010 vintage MSA Economic Characteristics

Houston Metro Gross Domestic Product
View selected Houston 2013 vintage metro Gross Domestic Product (GDP) patterns in this interactive table.  The Houston metro 2012 real per capita GDP is estimated to be $62,438 ($385,683M real GDP/6,177,035 population).

Examining Longer-Term Demographic Historical Change
— Use this interactive table to view, rank, compare Census 2000 and Census 2010 population for Census 2010 vintage metros (all metros).
— Use this interactive table to view, rank, compare 2013 vintage metros (all metros) — Census 2000, Census 2010, 2012 estimates population and related data.

Houston Metro by County Population Projections to 2060
The graphic presented below shows county population projections to 2060 for the 2013 vintage metro.  Use this interactive table to view similar projections for all counties.  The metro population is projected to increase to 2.8 million by 2030 and to 3.4 million by 2060 based based on current trends and model assumptions. Viewing graphic with gesture/zoom enabled device suggested.

Houston Metro Population Projections by County to 2060

Thematic Maps & Visual Analysis
The graphic below shows the 2013 vintage metro (bold boundary) counties labeled with county name and county per capita personal income (PCPI).  The legend shows the change in PCPI from 2008 to 2012.

The above graphic illustrates the power of using visual analysis tools (CV XE GIS).  These data are from the  Regional Economic Information System (REIS) introduced earlier in this section.  Use the links shown below to examine much more detail from REIS at the metro and county level.  A thematic pattern map could be developed for any one of these items.  The REIS data are annual time series starting in 1970 and continue to 2012.  Click a link to view a sample profile spreadsheet for Harris County, TX and the Houston MSA for 2011 and 2012.
• Personal income, per capita personal income, and population (CA1-3)
• Personal income summary (CA04)
• Personal income and earnings by industry (CA05, CA05N)
• Compensation of employees by industry (CA06, CA06N)
• Economic profiles (CA30)
• Gross flow of earnings (CA91)

Join us in an Upcoming Decision-Making Information Webinar
We will review topics and data used in this section in the upcoming webinar “Metropolitan Area Geographic-Demographic-Economic Characteristics & Trends” on January 9, 2014.  This is one of many topics covered in the DMI Webinars (see more).  Register here (one hour, no fee).

About Metropolitan Areas
By definition, metropolitan areas are comprised of one or more contiguous counties. Metropolitan areas are not single cities and typically include many cities. Metropolitan areas contain urban and rural areas and often have large expanses of rural territory. A business and demographic-economic synergy exists within each metro; metros often interact with adjacent metros. The demographic-economic makeup of metros vary widely and change often.

2013 vintage metropolitan areas include approximately 94 percent of the U.S. population — 85 percent in metropolitan statistical areas (MSAs) and 9 percent in micropolitan statistical areas (MISAs). Of 3,143 counties in the United States, 1,167 are in the 381 MSAs in the U.S. and 641 counties are in the 536 MISAs (1,335 counties are in non-metro areas).

Homeownership Patterns by Census Block

The homeownership rate peaked in America in 2004 at approximately 69.2 percent.  Homeownership is defined as the percent of occupied housing units (households) that are owner-occupied.  The homeownership rate in 2013 is roughly the same as in 1995. The gradual decline continues.

        Homeownership Rate 1970Q1-2013Q3 not seasonally adjusted; based on CPS/HVS

The focus of this section is on creating thematic pattern map views depicting homeownership by census block for the Washington, DC area.  This section builds on the previous post Mapping Demographic Patterns: Census Blocks.

The starting place is where Mapping Demographic Patterns: Census Blocks left off — the required software and GIS project are installed on the computer.  The next step is to start the CV XE GIS software, open the DC GIS project and set the intervals for the thematic pattern views.

To compute homeownership, the minimum required data items/fields are the number of owner-occupied housing units and the number of housing units. By examining the Census 2010 SF1 table shells (xls), these items are found in Table H4. Tenure — owner/renter occupancy of occupied units (line 9259 in the xls file).  Looking at the  SF1 technical documentation (pdf) matrix section (sequential page 483, numbered page 6-321), it is determined that the items field needed are (H0040002 + H0040003) — owner occupied housing units and H0040001 (occupied housing units).  These items are already loaded into the DC block shapefile dbf.

Intervals are defined for the map view with queries that set blue to blocks with homeownership rate of 65% or more, orange to blocks with rate 50%-65% and red to population blocks with a rate below 50%.  Zero population blocks are set to gray.  The initial view shown below tells the visual story that more of Washington, DC has a homeownership rate below the national average than above the national average — and how these homeownership rate patterns are distributed by block.

Homeownership Rate by Census Block — Washington, DC

Zoom-in to area east of U.S. Capitol complex
— transparency set to 60% enabling “see through” of color patterns
— mini profile of blue block at pointer
— h0040001: 79 occupied housing units and 54 owner occupied housing units (h0040002+h0040003)


Similar thematic maps showing patterns of homeownership rate by census block may be created for any area in the U.S.  Procedures to access and use these no cost resources for Census 2010 Summary File 1 census block applications are summarized in the the APIGateway Guide.

In a future post, homeownership rates will be reviewed for all states and metros, 2008 through 2012, using annual American Community Survey (ACS) data.