Tag Archives: demographic trends

Climate Change & the Demographic-Economic Outlook

.. it is startling that many do not accept the reality that climate change is upon us. Climate change is, right now, affecting the demographic-economic outlook … how things will change in the next fifty years and how this change might impact each of us. A challenge is to determine how to best integrate the right set of data, variables, into our cause and effect predictive models. By doing so, we improve the quality and accuracy of projections. We can better examine what-if scenarios. Business decision-making and policy-making implications are enormous.

BlackRock, the world’s largest asset manager, has recently taken the position that climate change has become a defining factor in companies’ long-term prospects.

Climate Risk Is Investment Risk
Investment strategies mean exiting/avoiding some investments that present a high sustainability-related risk, such as coal producers and new/expanded investment products that screen fossil fuels. Many others.

The impact of these types of investment risks are already appearing. While the stock market continues an unprecedented rally, energy sector companies are not performing as well. This impacts the metros/areas where they operate affecting the economic base and impacting the population/housing growth and composition.

Climate Risk Affects Personal/Family Decision-Making
As Larry Fink/Blackrock notes, what will happen to the 30-year mortgage – a key building block of finance – if lenders can’t estimate the impact of climate risk over such a long timeline? What if there is no viable market for flood or fire insurance in impacted areas? Happening now. What happens to inflation, and in turn interest rates, if the cost of food climbs from drought and flooding? Risks to human health and and migration due to climate change are already being experienced.

The Situation & Outlook — Improving Model Specification
This is our challenge — modeling economic change where emerging markets see their productivity impacted due to extreme heat and other climate impacts .. modeling migration of people and businesses being impacted by climate change .. modeling the housing infrastructure being implemented by climate change .. determining how and where climate change might impact personal income and GDP by county. In many cases, because of the way and what data are collected, it is difficult to sort out what part of migration, business change and other key measures are due in what part to climate change.

Quantification of climate change, and new model-based cause and effect specifications, will be reflected in the 2020 ProximityOne Situation & Outlook demographic-economic projections to 2060. For the first time, and on a continuing basis, we and our clients will be able to examine the quantified impact of climate change down to the county level of geography. This is now a topic included in the weekly Situation & Outlook web sessions.

Situation & Outlook Weekly Web Sessions
Join me in a Situation & Outlook web session to discuss more details about demographic-economic estimates and projections.

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.

U.S. & World Population, 2020

.. changing demographics .. the U.S. population stands 330,222,422 on January 1, 2020 .. an increase of 1,991,085, 0.61%, from a year ago. The April 1, 2010 Census population was 308,758,105.


 
In January 2020, the United States experiences one birth every eight seconds and one death every 11 seconds.

.. the net international migration adds one person to the U.S. population every 34 seconds. The combination of births, deaths and net international migration will increase the U.S. population by one person every 19 seconds.

The projected world population on January 1, 2020, is 7,621,018,958, an increase of 77,684,873, or 1.03%, from a year earlier. During January 2020, 4.3 births and 1.9 deaths are expected worldwide every second.

Kickoff of Census-Sourced Vintage 2019 Population Estimates Program
Starting in December of each year, the Census Bureau develops official population estimates for July of that year. In 2020, the Bureau will progressively release population estimates with greater subject matter detail for more detailed subnational geography. These model-based estimates will be completed in June 2020 for incorporated places.

The July 2019 estimates for the U.S. and states were just released in December 2019. These estimates reflect that the natural Increase dropped below 1 million for the first time in decades due to fewer births and more deaths.

The July 1, 2019, U.S. population estimate is 328,239,523, growing by 0.5% between 2018 and 2019, or 1,552,022 people. Annual growth peaked at 0.73% this decade in the period between 2014 and 2015. The growth between 2018 and 2019 is a continuation of a multiyear slowdown since that period. More detail on U.S. and state trends will be reviewed in a subsequent post.

Population Projections & Subnational Demographics
ProximityOne uses these Census-sourced historical annal data to develop current estimates and projections to 2060. See about projections and more geographic detail in the Demographics 2060 section.

Demographic-Economic 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.

Combined Statistical Area Demographic Trends

.. a Combined Statistical Area (CSA) is a group of two or more adjacent metropolitan areas; they include contiguous metro counties that have demographic-economic affinity. These 172 areas (September 2018 vintage) are important in wide-ranging geographic and demographic analysis. Based on the 2018 population estimate, these areas include 256.2 million population of the total U.S. population of 327.2 million (78.3 percent). CSAs are at least two adjacent metropolitan areas — reflecting a larger and broader market/service/impact assessment area. Due to their size (of many), it is often possible to develop more detailed custom demographic-economic estimates and projections than at the county or metropolitan area level. See more about CSAs in this related Web section.

Patterns of 2018 Population by 2018 CSA
The following graphic shows the September 2018 vintage CSAs based on the 2018 official population estimates. The intervals/colors are depicted in legend panel at left of map window. Create custom maps similar to this view for your regions of interest. Use the GIS project/datasets to examine alternative patterns such as percent change for different time periods. Set queries to include CSAs by peer group. Click graphic for larger view with more detail; expand browser window for best quality view. Larger view shows CSAs labeled with percent population chnage 2010-2018.

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

Use the GISproject and datasets to examine CSAs in a mapping and geospatial analysis context. The database includes all CSAs and the subject matter described below.

Using the Interactive Table
Use the interactive table (opens new page) to examine patterns and relationships among CSAs of interest. The following static graphic illustrates how the table can be used to rank or query CSAs and display selected columns. Selecting population change columns and ranking in descending order on population change 2010-2018, shows that the Dallas CSA had the largest population … it also shows this CSA was the 7th largest CSA based on 2018 population and 9th on percent population change 2010-2018 … use the table to determine which CSA ranked first on percent population change 2010-2018.

– click graphic for larger view.

Data Analytics Web Sessions
See these applications live/demoed. Run the applications on your own computer.
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.

U.S. House of Representatives 2020 Apportionment

.. Congressional Apportionment by State .. 2010 & projected 2020 state by state congressional seats.

What will the results of Census 2020 tell us us about how the House of Representatives will be reapportioned, state by state? This section examines scenarios which might occur based on state population projections. See related Web section http://proximityone.com/apportionment.htm for more detail and interactive table.

Use the GIS tools and project to make your own map views … see details
.. use in classroom .. research .. reference .. collaboration.

This section has been developed using
– 2020 apportionment population projections
.. part of the ProximityOne Situation & Outlook (S&O)
– the reapportionment/redistricting feature of the CV XE GIS software
The 2020 population projections reflect anticipated change under one scenario. Those values are then used in the CV XE GIS reapportionment operation to compute the number of House seats shown in the related table.

Apportionment of the U.S. House of Representatives
— based on the 2010 Census

– view created with CV XE GIS. Click graphic for larger view with more detail.

Apportionment of the U.S. House of Representatives
— based on ProximityOne 2020 Population Projections

– view created with CV XE GIS. Click graphic for larger view with more detail.

Congressional apportionment is the process of dividing the 435 memberships, or seats, in the House of Representatives among the 50 states based on the population figures collected during the decennial census. The number of seats in the House has grown with the country. Congress sets the number in law and increased the number to 435 in 1913. The Constitution set the number of representatives at 65 from 1787 until the first Census of 1790, when it was increased to 105 members. More about apportionment.

Initial Census 2020 demographic data, the apportionment data, will be released by December 31, 2020. See related Census 2010 Apportionments.

Apportionment totals were calculated by a congressionally defined formula, in accordance with Title 2 of the U.S. Code, to divide among the states the 435 seats in the U.S. House of Representatives. The apportionment population consists of the resident population of the 50 states, plus the overseas military and federal civilian employees and their dependents living with them who could be allocated to a state. Each member of the House represents, on average, about 710,767 people for Census 2010.

Using the Interactive table
The following graphic illustrates use of the 2010 & 2020 apportionment by state and historical apportionment 1910 to 2010. Sort on any column; compare apportionment patterns over time. Click graphic for larger view.
Use the interactive table at http://proximityone.com/apportionment.htm#table.

Congressional District/State Legislative District Group
Join the CDSLD Group (http://proximityone.com/cdsld.htm), a forum intended for individuals interested in accessing and using geodemographic data and analytical tools relating to voting districts, congressional districts & state legislative districts and related geography with drill-down to intersection/street segment and census block level. Receive updates on topics like that of this section.

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.

How & Why State Demographics Are Changing

.. to examine how and why state demographics are changing, we look at the state as the sum of its parts — counties. Here we review tools and data to examine how and why state/county population is changing … is the population moving away or into your areas 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? See related Web section for more detail on topics covered here and access interactive table.

Patterns of Population Change by County, 2010-2017
The following graphic shows how counties have gained population (blue and green) and lost population (orange and red) during the period 2010 to 2017. Click graphic for larger view; expand browser window for best quality view.

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

The above graphic provides a visual summary of how and why demographics are changing from 2010 to 2017 in terms of components of change: births, deaths and migration. See the underlying data in this interactive table.

Change in the population from births and deaths is often combined and referred to as natural increase/change. The other way an area population changes is through migration (net international, net domestic, net migration). Examining an area’s unique combination of natural change and migration provides insights into why its population is changing and how quickly the change is occurring.

Examine States of Interest
Click a state link to view details about specific states …
Alabama .. Alaska .. Arizona .. Arkansas .. California .. Colorado .. Connecticut .. Delaware .. Florida .. Georgia .. Hawaii .. Idaho .. Illinois .. Indiana .. Iowa .. Kansas .. Kentucky .. Louisiana .. Maine .. Maryland .. Massachusetts .. Michigan .. Minnesota .. Mississippi .. Missouri .. Montana .. Nebraska .. Nevada .. New Hampshire .. New Jersey .. New Mexico .. New York .. North Carolina .. North Dakota .. Ohio .. Oklahoma .. Oregon .. Pennsylvania .. Rhode Island .. South Carolina .. South Dakota .. Tennessee .. Texas .. Utah .. Vermont .. Virginia .. Washington .. West Virginia .. Wisconsin .. Wyoming

Situation & Outlook Briefing Sessions
Join me in a Situation & Outlook Briefing Session, every Tuesday, where we review the where, what, how, and when of demographic-economic-business change – and how change might impact you.  We review current topical issues and data — and how you can access/use tools/data to meet your needs/interests.

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.

 

Life Expectancy Change by County, 1980-2014

.. data and tools to examine changing life expectancy by county. Use the interactive table to examine life expectancy characteristics and related demographics for counties and regions of interest. Use the related GIS project and datasets to examine life expectancy contextually with other geography & subject matter. See details below. These data and tools are part of the ProximityOne health data analytics resources.

Life expectancy is rising overall in the United States, but in some areas, death rates are going in the other direction. These geographic disparities are widening.

Life Expectancy Change by County, 1980-2014
The following graphic shows patterns of the change in life expectancy change from 1980 to 2014. Click graphic for larger view. Expand browser window for best quality view.

– View developed using CV XE GIS and related GIS project.
– see below in this section about using this GIS project.

Life expectancy is greatest in the high country of central Colorado, but in many pockets of the U.S., life expectancy is more than 20 years lower. These data are based on research and analysis by the University of Washington Institute for Health Metrics and Evaluation.

Examining life expectancy by county allows for tracking geographic disparities over time and assessing factors related to these disparities. This information is potentially useful for policymakers, clinicians, and researchers seeking to reduce disparities and increase longevity.

Life Expectancy Change by County, 1980-2014 — drill-down view
— South Central Region
The following graphic shows patterns of the change in life expectancy change from 1980 to 2014. Click graphic for larger view. Expand browser window for best quality view. The larger graphic shows counties labeled with change in life expectancy from 1980-2014.

– View developed using CV XE GIS and related GIS project.
– see below in this section about using this GIS project.

Additional Views — use the GIS project to create your own views
.. click link to view
Alaska
Hawaii
Minneapolis metro

Using the Interactive Table
Use the interactive table to view, rank, compare life expectancy characteristics. This graphic shows California counties ranked on life expectancy change 1980-2014 in descending order. Select states or metros of interest. Click graphic for larger view.

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

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

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.