Category Archives: economic indicator

State of the States: 2019

.. the State of the States reports and information service provide insights into demographic, economic & business characteristics.  Unique in their composition,  updated daily/weekly, the reports summarize what’s changing where & when and assessing what’s ahead. It organizes disparate Federal statistical data and presents those data in an organized, consumable manner. A resource to help determine how change might affect you, it is an indispensable resource for investors, leaders, policymakers, researchers and decision-makers. See State of the States main section for more information.  Your briefing notes, organized by state.

Some details .. the U.S. economy is slowing, dragged down by trade tensions and weak growth overseas. But there are few signs that the decade-long expansion is on the verge of stalling out. Real Gross Domestic Product (RGDP), the broadest measure of goods and services produced in the economy, rose at a 2.1 percent annual rate in 2019Q2, down from 3.1 percent in 2019Q1, according to preliminary data released by the Bureau of Economic Analysis on 7/26/19.

But what about the states, and what about related measures? In Texas, the 2019Q1 change from 2018Q4 was 5.1 percent annual rate. Texas ranked 2nd among all states. The 2019Q2 state GDP will be posted in section 6.5 on Nov. 7, 2019 (see in scheduled updates). How does Texas compare to other states and the U.S.  Answers are organized in the reports.  Create insights. Share with others.

Part of a multi-dimensional information resource, the state of the states report has been derived from the Situation & Outlook (S&O) database, updated daily. ProximityOne uses the historical S&O database to develop current demographic-economic estimate and projections.

View the U.S. or a State Report .. click a link
.. illustrative reports .. see more about report structure & options in report.
United States
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
District of Columbia
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

Demographic 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.

County Housing Patterns & Trends

.. at a time when “housing costs are going through the roof” and “affordable housing” are topics widely in play, current housing data at the county level are essential for business and public policy planning. In this section, new Census Bureau U.S. by county 2018 housing unit estimates are viewed .. and tools to access and use these data.

Patterns of Housing Unit Percent Change by County: 2010-2018
The graphic below shows patterns of county housing unit percent change from 2010 to 2018. Click graphic for larger view showing more detail.

– view developed using CV XE GIS software and associated GIS project.
– create similar maps for counties/areas using CV XE GIS & associated GIS project.

This section reviews the new 2018 county housing unit estimates (released May 2019) and tools and applications to analyze them. See more about topics covered here in this related Web section.

The U.S. housing stock grew by more than 1.15 million from 2017 to 2018, reaching over 138.5 million units. The growth rate of 0.8 percent from 2017 to 2018. The national housing stock increased by 6.7 million units (5.1 percent) between 7/1/2010 and 7/1/2018. But housing stock change was far from even as shown in the graphic presented above.

Total housing units are the “tip of the iceberg” to examine housing market characteristics. Yet, there are no other Federal statistical data for any other housing attribute for every county more recent than circa mid-2015. Those data are from the American Community Survey 5-year estimates for the period 2013-2017 — data going on 4 years old. For example, there are no Federal statistical data for all counties for the 2018 number of households or vacant units … let alone measures that would enable computing the size and location of affordable housing, one of many important housing market attributes. Use related 2018 and projected housing market data developed by ProximityOne available as part of the Situation & Outlook demographic-economic estimates and projections. Examine these data in context with other geographic and market characteristics in the metro Situation & Outlook reports.

Using the Interactive Table
Use the interactive table to view, rank, compare states and counties based on number of units annually 2010 to 2018 and related measures. Compare counties among metros or states .. or peer groups based on size. Here are two examples of using the table.

Largest Counties based on 2018 Housing Units
.. ranked on 2018 housing units .. click for larger view

Counties with 10,000 or more 2018 Housing Units
.. ranked on percent change 2010-2018 .. click 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.

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.

Metropolitan Area New Residential Construction in 2017

.. understanding the housing situation; examining housing supply and demand market conditions; assessing trends for metropolitan areas … and how metros of interest are changing .. tools and data to examine patterns and change.

During 2017, cities and counties in permit issuing places authorized the construction of 1,281,977 new privately owned housing units with a total valuation of $258.5 billion. This was 1.4 percent above the annual estimate of 1,264,051 housing units and is a 6.2 percent increase from the 2016 total of 1,206,642.

Patterns of New Residential Construction by Metropolitan Area
The following graphic shows the 20 largest metropolitan statistical areas (MSAs) based on the number of new residential housing units authorized in 2017. Click graphic for larger view showing MSAs labeled with rank and name.

View created with CV XE GIS. Click graphic for larger view.

Residential Construction Data Analytics — Using Tools & Data
Visit the related Web section to access interactive table and GIS/GeoSpatial analytical tools and data.

Data Analytics Web Sessions
Join me in a Data Analytics Web Session, every Tuesday, where we review access to and use of data, tools and methods relating to GeoStatistical Data Analytics Learning. 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.
 

Housing Price Index Updates & Trends

.. this past week we have updated Housing Price Index data and tools to examine patterns and trends for the U.S., states, metros and counties .. the Housing Price Index (HPI) is one of many measures useful to gain insights into the housing market. The HPI provides information on how housing value appreciation is changing for areas of interest. Use the interactive table to view, compare, sort metros/CBSAs based on annual HPI 2010-2017 and housing value appreciation during the period. These annual data, with a 2000 base index value of 100, provide insights into longer term patterns.  The HPI is alos updated quarterly for U.S./state/metro areas quarterly for analyses requiring more recent data.  These data are new as of February 2018.

Visual Analysis of Housing Price Appreciation
The following graphic shows housing value appreciation as of 2017 based on the HPI with 2000 base of 100 by county in the Charlotte, NC-SC metro area. See more about by HPI by county for the Charlotte metro.

– view developed using CV XE GIS and related GIS project.
– Click graphic for larger view and details.

See similar HPI 2017 patterns view for the Houston, TX metro.

Housing Price Appreciation 2010-2017 — Largest 10 Metros
This table, derived from the  interactive table, shows the largest 10 metros based on total population. the HPI 2010, HPI 2017, housing price appreciation 2010-2017 and total population are presented in the table. Click the CBSA code link to view HPI by county component for the metro and an extended series.

 Metro CBSA HPI2010 HPI2017 HPA1017 Pop2016
 New York   35620 159.53 172.76 8.29 20,153,634
 Los Angeles   31080 169.83 242.78 42.95 13,310,447
 Chicago   16980 117.48 124.58 6.04 9,512,999
 Dallas   19100 120.89 175.35 45.05 7,233,323
 Houston   26420 134.02 183.52 36.93 6,772,470
 Washington   47900 166.82 198.74 19.13 6,131,977
 PhiladelphiaA   37980 157.26 162.91 3.59 6,070,500
 Miami   33100 140.43 213.91 52.33 6,066,387
 Atlanta   12060 103.95 129.24 24.33 5,789,700
 Boston   14460 134.33 165.27 23.03 4,794,447

– Metro names abbreviated; use table to view full name and code.

Using the HPI Annual 2010-2017 Interactive Table
The following graphic illustrates use of the HPI Annual 2010-2017 interactive table. Click graphic for larger view. This view shows metros in the 250,000-300,000 population peer group. Set your own criteria using tools below the table. There are 23 metros in this group. The table has been sorted on housing price appreciation (HPA) from 2010-2017 (second column from right). It shows that the Merced, CA metro had the highest HPA — 82.13% di=uring this period.

Use the interactive table and examine areas of interest.

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.

 

 

State of the States: Demographic Economic Update

.. tools and resources to examine the demographic-economic state of the states .. in 2016, the U.S. median housing value was $205,000 while states ranged from $113,900 (Mississippi) to $592,000 (Hawaii). See item/column H089 in the interactive table to view, rank, compare, analyze state based on this measure … in context of related housing characteristics. These data uniquely provide insights into many of the most important housing characteristics.

Use new tools, data and methods to access, integrate and analyze demographic-economic conditions for the U.S. and states. These data will update in September 2018.

Approximately 600 subject matter items from the American Community Survey ACS 2016 database (released September 2017) are included in these four pages/tables:
• General Demographics
• Social Characteristics
• Economic Characteristics
• Housing Characteristics

GIS, Data Integration & Visual Data Analysis
Use data extracted from these tables in a ready-to-use GIS project. These ACS sourced data (from the four tables listed above) have been integrated with population estimates trend data, components of change and personal income quarterly trend data. See details in this section.

Examining Characteristics & Trends
Below are four thematic pattern maps extracted from the main sections listed above. Click a map graphic for a larger view. Use the GIS project to create variations of these views.

Patterns of Median Age by State
Yellow label shows the state USPS abbreviation; white label shows median age. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column D017 in the interactive table to view, rank, compare, analyze state based on median age.

Patterns of Educational Attainment by State
Yellow label shows the state USPS abbreviation; white label shows % college graduates. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column S067 in the interactive table to view, rank, compare, analyze state based on percent college graduates.

Patterns of Economic Prosperity by State
Yellow label shows the state USPS abbreviation; white label shows $MHI. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column E062 in the interactive table to view, rank, compare, analyze state based on median household income.

Patterns of Median Housing Value by State
Yellow label shows the state USPS abbreviation; white label shows $MHV. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column H089 in the interactive table to view, rank, compare, analyze state based on median housing value.

Examining Characteristics & Trends; Using Data Analytics
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.