Tag Archives: demographic trends

Examining Houston Metro Demographic-Economic Characteristics

.. tools & data to examine metro demographic-economic characteristics .. this Houston, TX metro focused section is one of several similar metro sections that will be covered in weeks ahead.  Each metro-focused section provides a summary of tools and data that can be used to view, rank, compare, analyze conditions and trends within the metro and this metro relative to other metros, regions and the Nation.  The ready-to-use GIS project/datasets provide the basis for extended data/geographic views and analysis immediately.  See more detail about topics covered in this related Web section.

Relating your data to demographic-economic characteristics and trends in a region involves more than information provided by a report or set of statistical tables. It is important to use your data to be able to identify areas of missed opportunity and competitive position. It is important to have a “10,000 foot” view as well as understanding individual neighborhoods and market/service areas. Geographic Information System (GIS) tools, with the right set of geographic, demographic and economic data can facilitate decision-making through the use of visual and tabular data analytics.

This section provides information on installing and using the Houston Metro Demographic-Economic GIS software and project/datasets. This same scope of data, tools and operation is available for any metro, state or combination.

10,000 Foot View
The following graphic shows patterns of median household income by census tract for the Houston metro area. This is the start-up view when using the GIS tools and data described below. The color patterns/intervals are shown in the highlighted layer in legend at left of map window. Use the GIS tools described below to develop thematic pattern maps for a range of data and criteria.

.. view developed using the CVGIS software.

See more about census tracts; see tracts main page.

Several additional views follow, developed using this same GIS project. These views illustrate different levels of geographic granularity and patterns of different subject matter.

Median Household Value by Block Group
See more about block groups; see block groups main page.

.. view developed using the CVGIS software.

Population/Housing Unit by Block
See more about census blocks; see census block main page.

.. view developed using the CVGIS software.

Zoom-in to Sugarland/Fort Bend County
See more about cities/places; see cities/places main page.
Access data for any city using interactive table.

.. view developed using the CVGIS software.

Further Zoom-in Showing Street/Road Detail
See more about streets.

.. view developed using the CVGIS software.

Additional Information
See the related Houston metro Situation & Outlook Report.

Using the GIS Software and Project/Datasets
(requires Windows computer with Internet connection)
1. Install the ProximityOne CV XE GIS
… run the CV XE GIS installer
… requires UserID; take all defaults during installation
2. Download the Houston Metro GIS project fileset
… requires UserID; unzip Houston Metro GIS project files to local new folder c:\p1data
3. Open the c:\p1data\us1_metros_houston.gis project
… after completing the above steps, click File>Open>Dialog
… open the file named c:\p1data\us1_metros_houston.gis
4. Done. The start-up view is shown above.

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.

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.

New ACS 2015 1-Year Demographic-Economic Data

.. essential data to assess where we are, how things have changed and how things might change in the future down to the sub-neighborhood level. The American Community Survey (ACS) is a nationwide survey designed to provide annually updated demographic-economic data for national and sub-national geography. ACS provides a wide range of important data about people and housing for every community across the nation. The results are used by everyone from planners to retailers to homebuilders and issue stakeholders like you. ACS is a primary source of local data for most of the 40 topics it covers, such as income, education, occupation, language and housing. ProximityOne uses ACS to develop current estimates on these topics and 5-year projections. This section is focused on ACS 2015 data access, integration and use and is progressively updated.

New ACS 2015 1-year estimates are available as of September 15, 2016.

Importance of ACS: Assessing Demographic-Economic Change
Oil prices plummeted in late 2014. How has this affected people and households in areas hardest hit? Find out for wide-ranging geographies using the ACS 2015 1-year estimates. Compare to ACS 2014 1-year estimates. Use the ACS 2016 1-year estimates (September 2017) to see how the impact has continued. Demographic-economic conditions change for many reasons; oil price changes are just one.

Keep informed about ACS developments and related tools and applications:
• Updates are sent to ProximityOne User Group members (join here).
… access special extract files and GIS projects available to members.
• ACS updates and applications are covered in the Data Analytics Blog.
• ACS data access, integration & use … join us in a Data Analytics Lab session.

In the weeks ahead, the following ProximityOne information resources will be updated with new ACS 2015 1-year data:
U.S.-State-Metro Interactive Tables
• Demographic component section of Metro Situation & Outlook Reports .. example for Dallas metro
• Housing characteristics component section of Metro Situation & Outlook Reports .. example for Dallas metro
Demographic-Economic Trend Profiles
• Special study 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.

Future of Indonesia: Demographic Trends

Indonesia, the world’s fourth most populous country … the population of Indonesia is projected to change from 243.4 million in 2010 to 300.2 million in 2050. How will Indonesia age-cohort patterns in 2010 compare to those projected for 2050? How do these patterns compare with those of the United States?

This section illustrates use of population pyramids to examine age by gender demographic patterns for Indonesia as of 2010 and 2050. See related Web section. Similar population pyramids can be developed for any country. Population pyramids help us visualize and more easily understand age-gender structure — and how it is changing over time.

Indonesia — red hatch pattern
Indonesia
Click graphic for larger view; view developed with CV XE GIS.
Map view developed using World GIS Project.

Additional Views:
Jakarta region zoom-in showing provinces
Jakarta city zoom-in with urban area

Indonesia Demographic Dynamics
The age and gender structure of a population is one of its most important and formative features, because nearly all demographic characteristics and processes vary by age and gender. Age and gender composition is also revealing in that it reflects those demographic characteristics and processes. Population pyramid chart graphics can help us visualize and more easily understand age-gender structure — and how it is changing over time.

Population pyramids for 2010 and 2050 are shown below for Indonesia with associated popualtion by age-gender tabular data. Click graphic for larger view of supplemental Web page.

A top-heavy pyramid suggests negative population growth that might be due to many factors, including high death rates, low birthrates and increased emigration. A bottom-heavy pyramid suggests high birthrates, falling or stable death rates and potential for rapid population growth.

The population pyramid shows a male population bar chart (left side of pyramid, blue) symmetrically with a female population bar chart (right side of pyramid, light red). Each bar shows the population by 5-year age group, 0-4 years to 80-84 years and 85 years and over.

Indonesia, Total Population, 2010

Click graphic for larger view.

Indonesia, Total Population, 2050

Click graphic for larger view.

More About Indonesia Demographics; Examining Other Countries
Use the ChartGraphics tools to get answers to these types of questions and gain insights world by country age-cohort patterns over time … into the future. Population pyramids developed using ChartGraphics provide an easy-to-develop and consume visual analysis of these patterns.

ChartGraphics is available at no fee to ProximityOne User Group members. Join now, there is no fee.

About the Author
— Warren Glimpse, developer of the CV XE GIS and ChartGraphics software, is former senior Census Bureau statistician responsible for innovative data access and use operations. He is developer of the Columbia, MO GBF/DIME used as the prototype for the Census Bureau TIGER/Line system, the digital map database underlying wide-ranging Web-based mapping applications. 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.