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.

Monthly Local Area Employment Situation: 2017

.. tools & data to examine the local area employment situation .. this update on the monthly and over-the-year (Jan 2016-Jan 2017) change in the local area employment situation shows general improvement. Yet many areas continue to face challenges due to both oil prices, the energy situation and other factors.  This section provides access to interactive data and GIS/mapping tools that enable viewing and analysis of the monthly labor market characteristics and trends by county and metro for the U.S. See the related Web section for more detail. The civilian labor force, employment, unemployment and unemployment rate are estimated monthly with only a two month lag between the reference date and the data access date (e.g., March 2017 data are available in May 2017).

Use our new tools to develop your own LAES U.S. by county time series datasets. Link your data with LAES data. Run the application monthly extending/updating your datasets. Optionally use our 6-month ahead employment situation projection feature. See details

Unemployment Rate by County – January 2017
The following graphic shows the unemployment rate for each county.

— view created using CV XE GIS and associated LAES GIS Project
— click graphic for larger showing legend details.

New with this post are the monthly 2016 monthly data on the labor force, employment, unemployment and unemployment rate. Use the interactive table to view/analyze these data; compare annual over the year change, January 2016 to January 2017.

View Labor Market Characteristics section in the Metropolitan Area Situation & Outlook Reports, providing the same scope of data as in the table below integrated with other data. See example for the Dallas, TX MSA.

The LAES data and this section are updated monthly. The LAES data, and their their extension, are part of the ProximityOne Situation & Outlook database and information system. ProximityOne extends the LAES data in several ways including monthly update projections of the employment situation.

Interactive Analysis
The following graphic shows an illustrative view of the interactive LAES table. In January 2017, 149 counties experienced an unemployment rate of 10% or more. The graphic shows counties experienced highest unemployment rates. Use the table to examine characteristics of counties and metros in regions of interest. Click graphic for larger view.

Metro by County; Integrating Total Population
The following graphic shows an illustrative view of the interactive LAES table focused on the Chicago MSA. By using the query tools, view characteristics of metro component counties for any metro. This view shows Chicago metro counties ranked on January 2017 unemployment rate (only 10 of the 14 metro counties shown in this view). Click graphic for larger view.

The above view shows the total population (latest official estimates) as well as employment characteristics.

More About Population Patterns & Trends
U.S. by county population interactive tables & datasets:
  • Population & Components of Change 2010-2016 – new March 2017.
  • Population Projections to 2060 2010-2060 – updated March 2017.

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

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

Regional Economic Information System: Annual Updates

.. which counties are experiencing the fastest economic growth? by what economic component? what does this look like on a per capita level?

.. access & analyze economic characteristics and patterns by county and state .. annual time series 1969 through 2015 with projections.  Personal income is the income available to persons for consumption expenditures, taxes, interest payments, transfer payments to governments and the rest of the world, or for saving. Use the interactive table to examine characteristics of counties and regions of interest. The table provides access to 31 personal income related summary measures. These data are a selection of a broader set of annual time series data from the Regional Economic Information System (REIS). REIS is a part of the ProximityOne State & Regional Income & Product Accounts (SRIPA) and Situation & Outlook (S&O) featuring current (2016) estimates and demographic-economic projections. Go to table.

Visual Analysis of Per Capita Personal Income Patterns
The following map shows the Houston metro (view profile) with bold brown boundary. Counties are labeled with county name and 2014 per capita personal income.

Click graphic for larger view. View developed with CV XE GIS software.

Per Capita Personal Income Change 2008-2014 by County
.. relative to U.S 2008-2014 change

Click graphic for larger view. View developed with CV XE GIS software.

Interactive Analysis – County or State Profiles
The following graphic illustrate use of the interactive table to view an economic profile for Harris County, TX. Use the table to examine characteristics of any county or state. Click graphic for larger view.

Interactive Analysis
– comparing per capita personal income across counties
The next graphics illustrates use of the interactive table to rank/compare per capita personal income across counties. Rank/compare states. Choose any of the economic profile items. Click graphic for larger view.

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

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

Using ACS County Data

… we are always seeking the most current data for areas of interest. This section provides an update on accessing unpublished ACS 1-year data for many counties.  Learn about how you can access ACS 1-year estimates for 85 counties for which Census released only as 5-year estimates … and why it matters. See the corresponding full Web section.

Data are tabulated from the Census Bureau American Community Survey (ACS) as 1-year estimates (for areas with population 65,000 and over) and as 5-year estimates (for areas under 65,000 population). See more about ACS 1-year versus 5-year estimates in this section.

ACS 2014 1-year tabulation areas, as released by the Census Bureau included 817 of 3142 counties and 508 of 917 metros/CBSAs. There are 85 counties for which ACS 2914 1-year estimates were not released by Census but are derivable by subtracting the aggregate county components from metro totals in selected metros.

County & Metro ACS 2014 1-year Estimates
The following graphic shows Texas and adjacent areas:
• ACS 2014 1-year estimates metros with bold brown boundaries
• Counties for which ACS 2014 1-year data were tabulated and released (green).
• Counties for which ACS 2014 1-year data are derivable but not released as tabulation areas (blue).

… view developed using the CV XE GIS software.
… click map for larger view and details.

The next view shows a zoom-in to the Austin, TX metro. The four green shaded counties had ACS 2014 1-year estimates tabulated and released. The fifth Austin metro county, Caldwell shaded blue, was not tabulated but the ACS 1-year data are derivable by subtracting the sum of the four counties from the metro totals. Tabulated data for Caldwell was released only as ACS 2014 5-year estimates. A similar situation exists in many metros across the country.

Why this Matters
There are 85 counties for which ACS 2014 1 year data are available but not released/made available by Census as separately tabulated areas. This is important due to these considerations:
• these are true annual estimates (as opposed to the other 5-year estimated counties)
• they are more recent that 5-year estimates
• they reflect conditions centric to one year
• they enable time series/trend analysis
• [as it turns out] they enable access to 1 year estimates for all counties (instead of some) in some metros

Using API Tools to Examine these Data
Create CSV-like files by clicking these links. When a link is clicked a new page will show the ACS 2014 1-year estimates tabulations areas. The area name, code and ACS 2014 1-year total population estimate is shown.
• Click to retrieve county data
• Click to retrieve metro data

Items used in these API calls:
.. B01001_001E – Total population
.. B19013_001E – Median household income ($)
.. B19113_001E – Median family income ($)
.. B19301_001E – Per capita income

Create/derive these data on your own; learn about which counties are derivable …

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.

 

Comparing Census Tract Demographics Over Time

.. it’s about more than census tracts .. this section is about comparing American Community Survey ACS 5-year estimates: 2005-2009 with 2010-2014 … something new and powerful happening this week.

To make good business decisions we need hard data, recent data, trend data … to assess patterns and change and develop reliable, superior plans. Read about the past and then how things have changed for the better.

Imagine that it is 2005. Data from Census 2000 are now 5 years old. There will not be another update for richer demographics for all counties and cities in the foreseeable further. There will not be any update for small area geography such as census tracts or block groups until Census 2010. Businesses are forced to use out-of-date data to assess markets … where and how are opportunities changing? City and neighborhood planners can only make educated guesses to respond to growing needs of various population groups. Federal and state government programs that base funding allocations on demographics are challenged. Changes in the rental vacancy rates for most cities, counties and metros will remain unknown for the foreseeable future.

Fast forward to 2015 and present day reality. The situation is now radically different. First, we can now compare 5-year estimates from the 2009 American Community Survey ACS to those from the 2014 ACS 5 year estimates. Second, we will be able to do that again in 2016 — compare 5-year estimates from ACS 2010 to those from ACS 2015. Health planners can now assess the size and change in special needs population and how that matches up to resources that respond to those needs — rather than guessing. Schools and school districts can better understand how school age population trending and plan for enrollment change. Education agencies are better able to assess how changing demographics among school systems compare to one-another. Businesses can now determine the size of potential markets and how they are trending based on hard data. It is possible to compare changing patterns in rental vacancy rates and rental housing market conditions for all levels of geography down to block group.

The American Community Survey ACS provides a wide range of important statistics about people and housing for every community in the nation. These data are the only source of local estimates for most of the approximately 40 topics it covers for even the smallest communities. It produces statistics for ancestry, language, education, commuting, employment, mortgage status and rent, as well as income, poverty and health insurance. The ACS estimates are tabulated annually as 1-year estimates (e.g., the ACS 2014 1-year estimates) and 5-year estimates (e.g., the ACS 2014 5-year estimates. See a comparison below in this section about scope, advantages/disadvantages, and other usage attributes for the 1-year versus 5-year estimates.

See ACS 2014 5-year main page for additional data access & use details.

Data from the 5-year estimates are available for all geographies down to the block group level regardless of population size. Starting with the ACS 2014 5-year estimates, for the first time, users will be able to compare two non-overlapping five-year periods 2005-09 and 2010-14. Looking ahead, data from the 2006-10 and 2011-15 (available December 2016) will be comparable … and so on. Over several years, a time-series of 5-year estimates, non-overlapping five-year periods, will evolve.

Comparing Geography Between 2005-09 & 2010-14 ACS 5-Year Data
The following graphic summarizes geographic tabulation areas for 2005-09 and 2010-14 ACS 5-year data. Use the corresponding Web table as a reference guide for comparing data over time. Links provided in the table enable you to navigate to selected data access tables. This Web-page table updates with new links; bookmark the page for re-visits.

Updates
Posts later this month will provide updates on this topics; new data and new data analytics tools. Join me in a Data Analytics Lab session to discuss use of these data using analytical tools and methods applied to your situation.

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.