Category Archives: Situation & Outlook

The Local Area Monthly Employment Situation

.. in June 2019, the local area unemployment rate ranged from 1.3% (Lyon County, IA) to 19.6% (Yuma County, AZ) among the lower 48 states. 133 counties had an unemployment rate of 7% or more during June 2018 through June 2019. Over the past year, as shown in the this interactive table, the unemployment rate has generally decreased among all counties. We track the local area employment situation historically and develop alternative scenario projections. See the related Web page for more information.

Patterns of Unemployment Rate by County
The following graphic shows patterns of the estimated June 2019 unemployment rate by county. Use the GIS tools and data to develop variations of this view optionally integrated with other data. Click graphic for larger view. Expand browser window for best quality view.

— view created using the ProximityOne CV XE GIS and associated GIS Project

Examine Areas of Interest
This graphic illustrates the monthly over the year employment situation for the Houston, TX metro using the interactive table.

Click graphic for larger view.

Create a similar table for any metro:
Open the interactive table (green and white table midway down).
Click ShowAll button below table.
Key in a 5-character metro code in edit box at right of FindCBSACode.
    … get from scroll list at upper right of table.
    … e.g., 19100 for Dallas, TX metro.
Click FindCBSACode; table refreshes showing only counties in this metro.
Click Current Situation button below table; table refreshes with selected columns.
Click the Pop2018 column header cell twice to rank-order the columns.
Done .. try these steps for an area of interest.

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.

Census 2020 P.L. 94-171 Redistricting Data Updates

.. we are just two years away from the first census block level data from Census 2020.  The initial block level data will be the P.L. 94-171 redistricting data.  But before that, the initial Census 2020 TIGER/Line shapefiles/GIS files, the geography, will become available in November 2020, maybe earlier.  Stakeholders will be able to see how block and tract codes and geography have changed in many areas since 2010.  The prototype P.L. 94-171 data (see final file layout and subject matter items) are expected in the last week of March 2019 and will cover the Providence County, RI area. This post shows illustrative views and related details about the area. The Census 2020 P.L. 94-171 program and plans are reviewed in this Federal Register notice.

The applications/views shown below have been developed using the ProximityOne CV XE GIS software and related GIS project.

Census 2020 Data Access and Use Program
ProximityOne operates a comprehensive Census 2020 Data Access and Use Program providing tools to integrate and analyze these data with other data for redistricting, planning, evaluation, management, general analysis and policy-related applications. Contact us for more information; mention Census 2020 Data Access and Use Program in text section.

Providence, RI Census 2020 P.L. 94-171 Prototype
The Census 2020 P.L. 94-171 prototype covers Providence County, RI, part of the Providence-Warwick, RI-MA MSA (39300) — see Situation& Outlook report. Providence County is shown with cross-hatch pattern in the following graphic.

The next graphic shows a zoom-in to the county with cities/places shown with green fill pattern.

The next graphic shows patterns of economic prosperity for the county based on ACS 2017 median household income by census tract — blue, higher and red, lower.

The next graphic shows Census 2010 blocks for the county. Demographics described in the P.L. 94-171 file described about will be provided at the census block level.

Census block boundaries are primarily defined by roads. Providence County roads are shown in the next view.

The next view shows a zoom-in to the downtown Providence city area. Census blocks are shown with red boundaries and labeled with the 15-character U.S. national scope unique census block code. The pointer is located in census block 440070012001001, or 44-007-001200-1001, expressed as SS-CCC_TTTTTT-BBBB. Access these Census 2010 data (an example) using the Census FactFinder tool via this link. This is the “P1 RACE” table. The Census 2010 population of the block was 598. This census block is one of 13,597 Census 2010 census blocks comprising Providence County.

Rhode Island 116th Congressional Districts 01 and 02 (labeled) split Providence city (cross-hatch pattern) as shown in the graphic below. Pointer shows CD boundary.

Similar to above, the graphic below shows census blocks in context of Providence city (bold green boundary) and CDs 01 and 02.

Next Steps
This section provides a geographic orientation the Census 2020 P.L. 94-171 prototype area. A subsequent post (March 2019) will extend on this post with Census 2020 P.L. 94-171 data and related details. Use the downloadable project and software to examine geodemographics and redistricting operations.

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.

 

Examining County Gross Domestic Product

.. what is the annual per capita real-valued output of counties of interest? How is this measure trending? Why is this important? This section reviews tools and data to examine county-level Gross Domestic Product (GDP) trends and patterns. The first ever county-level GDP estimates to be developed as a part of the official U.S. national scope GDP estimates were released in December 2018. The county GDP estimates join the county-level personal income by major source, both now part of the Regional Economic Information System (REIS). See more detail about topics reviewed in this post in the related County GDP web section.

Patterns of Real Per Capita GDP by County
The graphic below shows patterns of per capita real GDP, 2015, by county.

– View developed using CV XE GIS and related GIS project.
– create custom views; add your own data, using the GIS project.

Gross Domestic Product (GDP) by county is a measure of the value of production that occurs within the geographic boundaries of a county. It can be computed as the sum of the value added originating from each of the industries in a county.

Example … use this interactive table to see that 2015 Los Angeles County, CA total real GDP of $656 billion was just slightly larger that than of New York County, NY (Manhattan) at $630 billion. Yet, the total 2015 population of Los Angeles County of 10.1 million is 6 times larger than that of New York County of 1.6 million — see about steps. GDP provides very different size measures, and economic insights, compared to population.

In 2015, real (inflation adjusted) Gross Domestic Product (GDP) increased in 1,931 counties, decreased in 1,159, and was unchanged in 23. Real GDP ranged from $4.6 million in Loving County, TX to $656.0 billion in Los Angeles County, CA.

This post is focused on U.S. national scope county level estimates of Gross Domestic Product (GDP) annually 2012 through 2015. This marks the first time county level GDP estimates have been developed, a part of the Regional Economic Information System (REIS). Use the interactive table to rank, compare, query counties based on per capita GDP, current GDP, real GDP by type of industry. Use the related GIS project to develop thematic map views such as the one shown below. See more about these data.

Current Annual Estimates & Projections
ProximityOne uses these and related data to develop and analyze annual Situation & Outlook demographic-economic estimates and projections. GDP items included in the table below are included in the “annual 5-year” projections as shown in the schedule of release dates; next release April 18, 2019 and quarterly.

Examining County GDP Using GIS Tools
Use the County REIS GIS project. Make your own maps; select different item to map; modify colors, labels. Zoom in views of selected states shown below. Graphics open in a new page; expand browser window for best view. Patterns: see highlighted layer in legend to left of map; MSAs bold brown boundaries with white shortname label
counties labeled with name and 2015 per capita real GDP
.. Arizona .. Alabama .. California .. Colorado .. Iowa .. Georgia .. Kansas .. Missouri
.. New York .. Nevada .. North Carolina .. South Carolina .. Nevada .. Texas .. Utah .. Vermont

Using the County GDP Interactive Table
The graphic below illustrates use of the interactive table. Tools below the table have been used to view only per capita real GDP for all sectors (total sources) and for county with total population between 50,000 and 60,000. Counties were then ranked on 2015 per capita real GDP (rightmost column).

– click graphic for larger view.

Using County GDP: 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.

Assessing Why and How the Regional Economy is Changing

.. data, tools and insights .. which counties are experiencing the fastest economic growth? by what economic component? what does this look like on a per capita level? how might county economic change impact you? Use our county level annual estimates and projections to 2030 to get answers to these and related questions. Get started with the interactive table that contains a selection of these data for all counties and states.

Visual Analysis of Per Capita Personal Income Patterns
The following map shows changing patterns of economic prosperity, U.S. by county, based on percent change in per capita personal income, 2010 to 2017. Create variations of this view — this view uses a layer in the “US1.GIS” GIS project installed by default with all versions of the CV XE GIS software.
– click graphic for larger view.
– view developed with CV XE GIS software.

Measuring the economy and change. One important part of this is Personal Income and components of change. 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; how they rank and compare. The table provides access to 31 personal income related summary measures — the interactive table shows data for one of eight related subject matter groups. See more about the scope of subject matter descriptions.

Assessing How the Economy is Changing and How it Compares
The U.S. Per Capita Personal income (PCPI) increased from $40,545 in 2010 to $51,640 in 2017 — a change of $11,095 (27.4%). Compare the U.S. PCPI (or for any area) to a state or county of interest using the table. For example, Harris County, TX (Houston) .. click the Find GeoID button below the table .. increased from $45,783 in 2010 to $53,188 in 2017 — a change of $7,405 (16.2%).

Economic Profile; 2010-2017 & Change — An Example
The following graphic shows and example of the economic profile for Harris County, TX (Houston). Access a similar profile for any county or state.

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 the New York Metro is Changing

.. or more precisely, how the New York Metropolitan Statistical Area (MSA) is changing. As of Census 2010 the New York MSA (officially the New York-Newark-Jersey City, NY-NJ-PA MSA) consisted of 20 counties. With the new OMB metropolitan statistical areas defined as of February 2013, the New York MSA became 22 counties, absorbing the Poughkeepsie, NY MSA two counties (Dutchess and Orange). The Poughkeepie MSA was removed from the official MSAs. The delineation remained that way until the new September 2018 delineations when the Census 2010 delineation was restored. Now, the Poughkeepsie, NY MSA exists as a 2 county area and the New York MSA exists as a 20 county area (both as they existed geographically in Census 2010).

These metro-county relationships are shown in the graphic presented below. The Poughkeepsie, NY MSA is shown with the blue cross-hatch to the north and the New York MSA is shown with the salmon color pattern.

– view developed using the CV XE GIS software and related GIS project.
– see the related New York Metro Situation & Outlook report.

What Difference Does it Make?
A lot! First, during the interim period 2013-2018, the Poughkeepsie, NY MSA lost the metropolitan area identity/status as conferred by the OMB delineations. It might have been omitted from size class market development and research analyses. Related, that metro was not included as a tabulation or estimation area of MSAs by Federal statistical agencies. An example of the impact is that the official demographic estimates for the Poughkeepsie, NY MSA developed by the Census Bureau were not tabulated as such and omitted from various statistical reports. Also, the removal of designation and now adding the designation back, creates a hiccup in the time series — affecting both the Poughkeepsie NY MSA and the New York MSA.

Detailed Demographic Profiles for New York MSA and Poughkeepsie, NY MSA
.. click link to view profile.

New York-Newark-Jersey City, NY-NJ-PA MSA
  Bergen County, NJ (34003)
  Essex County, NJ (34013)
  Hudson County, NJ (34017)
  Hunterdon County, NJ (34019)
  Middlesex County, NJ (34023)
  Monmouth County, NJ (34025)
  Morris County, NJ (34027)
  Ocean County, NJ (34029)
  Passaic County, NJ (34031)
  Somerset County, NJ (34035)
  Sussex County, NJ (34037)
  Union County, NJ (34039)
  Bronx County, NY (36005)
  Kings County, NY (36047)
  Nassau County, NY (36059)
  New York County, NY (36061)
  Putnam County, NY (36079)
  Queens County, NY (36081)
  Richmond County, NY (36085)
  Rockland County, NY (36087)
  Suffolk County, NY (36103)
  Westchester County, NY (36119)
  Pike County, PA (42103)

Poughkeepsie-Newburgh-Middletown, NY (CBSA 39100)
  Dutchess County, NY (36027)
  Orange County, NY (36071)

Looking Forward
The September 2018 CBSA delineations define counties that will be used for Census 2020 (likely, there could be yet further changes) — 384 MSAs in the U.S. In the cases of the New York MSA and the Poughkeepsie, NY MSA, it appears that the geography (component counties) used for Census 2010 will be the same as for Census 2020. Going forward, ProximityOne estimates and projections will use the most current vintage of CBSAs.

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.

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.

State Population & Components of Change: 2010-2016

.. data and tools to examine how state demographics are changing 2010-2016 … using the new 2016 population and components of changes estimates. The U.S. population changed from 308,758,105 (2010) to 323,127,513 (2016), a change of 14,369,408 (4.7%). Only three states lost population. See the growth rates for DC and the remaining states in this table. Highest growth rates were in D.C., North Dakota, Texas, Utah and Colorado.

Patterns of Population Change, 2010-2016, by State
The following graphic shows the percent population change by state with labels showing the rank among all states based on the percent change in population, 2010-16.

View created with CVGIS and related GIS project. Click graphic for larger view.

Resources to Analyze these Data
Use our tools to view and analyze annual population estimates, 2010 to 2016, rankings and components of change for the U.S., regions and states. Use the interactive table below in this section to view, rank, compare these data. Use the GIS tools and ready-to use project described below in this section to create maps for states and regions of interest. Create thematic maps for any of the fields/measures shown in the interactive table. Change color patterns and labels. Integrate your own data.

Using Interactive Table
Use the interactive table to view, rank, compare, query states based on a selection of demographic measures. The following graphic illustrates how the table can be used. Click graphic for larger view.

The graphic shows the largest 10 states ranked in descending order based on 2016 population. The column “PopChg Rank 10b16” (second from right) shows the rank of this state, among all states, based on the population change from 2010 to 2016. The rightmost column shows the state’s rank for the period based on percent change in population over the period.

Largest 10 States based on 2016 Population

Try it yourself. Use the table to examine state patterns and characteristics based on your selected criteria.

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.