Category Archives: State trends

Real Quarterly GDP Trends: State of the States

.. real gross domestic product (RGDP) decreased in 46 states and DC in 2022Q1, as real GDP for the nation decreased at an annual rate of 1.6 percent. The percent change in real GDP in 2022Q1 ranged from 1.2 percent in New Hampshire to 9.7 percent in Wyoming. Updated quarterly GDP estimates have only a 3-month lag from the reference date (e.g., 2022Q1) to access date (e.g. June 2022). Used as a time series, these data provide insights into recent economic change and prospective future change. The RGDP estimates are developed by sector, enabling an assessment of which and how sectors are contributing to change. While we look at all states in this post, California is used as an example. Examine your state(s) of interest using the tools and data described here.

See this companion video illustrating some aspects of using VDA Web GIS with the state quarterly GDP.

Analyzing Real Quarterly GDP by State Using VDA MetroDynamics
Percent Change in Real GDP, 2021Q1 to 2022Q1, U.S. by State

.. create variations of this view using VDA Web GIS .. nothing to install.
.. about MetroDynamics GIS Project
.. click here to start VDA Web GIS

Examine Real Quarterly GDP by State by Sector
GDP is estimated quarterly for 21 sectors. the following graphic shows quarterly RGDP by sector for California. Use VDA to examine these data for state(s) of interest. Step-by-step how-to details below.

View the above data as an Excel file (save to file and open with Excel).

Using VDA Web GIS to Examine GDP by State – Mapping Patterns
Follow these steps:
Start VDA Web GIS
– Select MetroDynamics Project in next form.
.. VDA user interface appears
– select States in upper left dropdown
– in legend panel, uncheck “Metros Base ..”
– in legend panel, check the top 4 States layers on
– in legend panel, check “+” by “St RGDP%Ch 21q1-22q1” layer name
.. view now shows similar to view presented above.

– click a state to view a profile of the demographic-economic attributes.
.. the profile appears in lower left panel.
.. click the HTML button, lower left, to view the attributes in HTML format.

Using VDA Web GIS to Examine GDP by State — Table/Query
Complete the above steps, then click Query/Table button (below map at right)
– a table/grid now shows below the map window
.. the table has a row for each state; columns show subject matter items
– use Select Field button to select only a few items:
  .. state name
  .. RGDP2021Q1
  .. RGDP2022Q1
  .. RGDP2021Q1-2022Q1 change
  .. RGDP2021Q1-2022Q1 % change
.. table refreshes with view shown below (sorted on RGDP2021Q1-2022Q1 % change).

Looking Ahead; Updates
New quarterly GDP by state estimates for 2022Q2 and revised annual GDP by state estimates for 2017 to 2021 and will be released on September 30, 2022.

About GDP and Measurement
State GDP estimates are updated quarterly by the U.S. Bureau of Economic Analysis (BEA). The following terminology may be a useful reference.
Gross domestic product (GDP) by state is the market value of goods and services produced by the labor and property located in a state. GDP by state is the state counterpart of the nation’s gross domestic product, the most comprehensive measure of U.S. economic activity.
Current-dollar statistics are valued in the prices of the period when the transactions occurred—that is, at “market value.” Also referred to as “nominal GDP” or “current-price GDP.”
Real GDP values are inflation-adjusted statistics, these values exclude the effects of price changes.
State GDP is the lowest geographic level for which quarterly estimates of GDP are produced by BEA.
Seasonal adjustment and annual rates. Quarterly values are expressed at seasonally adjusted annual rates.
Quantities and prices. Quantities, or “real” measures, are expressed as index numbers with a specified reference year equal to 100 (currently 2012). Quantity indexes are calculated using a Fisher-chained weighted formula that incorporates weights from two adjacent periods (quarters for quarterly data and annuals for annual data). “Real” dollar series are calculated by multiplying the quantity index by the current dollar value in the reference year and then dividing by 100. Percent changes calculated from chained-dollar levels and quantity indexes are conceptually the same. Chained-dollar values are not additive, because the relative weights for a given period differ from those of the reference year.
Chained-dollar values of GDP by state are derived by applying national chain-type price indexes to the current dollar values of GDP by state for the 21 North American Industry Classification System-based industry sectors. The chain-type index formula that is used in the national accounts is then used to calculate the values of total real GDP by state and real GDP by state at more aggregated industry levels. Real GDP by state may reflect a substantial volume of output that is sold to other states and countries. To the extent that a state’s output is produced and sold in national markets at relatively uniform prices (or sold locally at national prices), real GDP by state captures the differences across states that reflect the relative differences in the mix of goods and services that the states produce. However, real GDP by state does not capture geographic differences in the prices of goods and services that are produced and sold locally.

About VDA Web GIS
VDA Web GIS is a decision-making information resource designed to help stakeholders create and apply insight. VDA Web GIS has been developed and is maintained by Warren Glimpse, ProximityOne (Alexandria, VA) and Takashi Hamilton, Tsukasa Consulting (Osaka, Japan).

About the Author
Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and 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. Join Warren on LinkedIn.

Arizona’s Shifting Demographics

.. part of a state-by-state series .. these periodic posts examine how and why the state and its counties changed bwteen 2010 and 2020. Later posts will provide more of a drill-down look at change. Click the Follow link at right to receive new and updated information.

Census 2020 Arizona Demographics
The Arizona July 1, 2020 Census model-based population estimate of 7,421,401 compares to the Census 2020 population count of 7,151,502 people. The difference of -269,899 between the 2020 estimate and the 2020 count can be explained by several factors. First, the estimate is for a point in time that is three months later that the Census. There will be a tendency of the Census Bureau to adjust the Joly 1, 2020 population estimate to conform to the Census 2020 value. The July 1, 2020 estimate will likely be adjusted to reflect this change when the July 1, 2021 estimates are released April/May of 2022.

The 2020 population estimate is determined using a component method. The 2020 population estimate is the sum of the 2019 population estimate (7,291,843 for Arizona) and each of the following for the period July 1, 2019 through June 30, 2020 …
plus births (AZ 81,451)
less deaths (AZ 66,385)
plus international migration (AZ 9,272)
plus domestic migration (AZ 105,435)
plus an estimation residual (AZ -214)

Any one or a combination of these 6 estimate based values could be wrong, or the Census 2020 value could be wrong. It is likely a combination of all of these factors.

The remainder of this section is based on Census Bureau model-based estimates, released April 26, 2021. See more about these data for all U.S. counties in the Demographics 2060 section where Arizona demographic projections can be examined.

Visualizing Arizona Demographic Change
The following graphic illustrates how Arizona county demographics have changed from 2010 to 2020. The labels show the actual percent change; the color patterns, as shown in the legend, provide a visual thematic pattern view.

Examining the How and Why of Demographic Change
The following table shows a row for the state and each county, providing more detail as to the where, what/how much, how and why demographic change has occurred from 2010 to 2020.


Click graphic for larger view.

Looking Ahead
More geographically detailed data (counties for example) based Census 2020 (August 2021) will reveal much starker percentage differences between the 2020 estimates versus Census results. The ProximityOne annual estimates and projections to 2060 are developed using two basic series (and variation among those (low, base, high): Census 2020 based series and 2020 estimates series. See http://proximityone.com/demographics2060 for details.

Learn more — Join me in the Data Analytics Web Sessions
Join me in a Accessing & Using GeoDemographics Web Session where we discuss topics relating to measuring and interpreting the where, what, when, how and how much demographic-economic change is occurring and it’s impact.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and 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 Value Appreciation

.. U.S. housing prices rose nationwide in August, up 1.5% from the previous month, based on the FHFA Housing Price Index (HPI). Housing prices rose 8.0% from August 2019 to August 2020.

If you purchased a housing unit in 2019Q2 at $260,200 (the ACS 2019 median housing value), the value of the unit in 2020Q2 would be $271,000, an increase of 4.2%. A good deal in this era of low interest rates.

U.S. housing prices posted a strong increase in August .. the 1.5% increase is the largest one-month price increase observed since the start of the HPI measurement in 1991. This large month-over-month gain contributes to an already strong increase in prices over the summer. These price gains can be attributed to the historically low interest rates, rebounding housing demand and continued supply constraints.

The HPI has various limitations as a measure to assess the housing market. One important limitation is that it a measure in isolation; other related demographic-economic measures are not included. This is unlike the American Community Survey (ACS) estimates of the median housing value ($MHV), used as an annual, year-over-year measure of housing value appreciation.

Median Housing Value
The U.S. ACS 1-year estimate of median housing value ($MHV) increased from $229,700 in 2018 to $240,500 in 2019. The ACS 2020 estimate, which will be impacted by the pandemic, will not be available until September 2021. The ProximityOne 2020 estimate of $MHV is $270,500.

Click this API link to view a CSV-like file showing the 2019 median household income and median housing value by state. Join me in a Data Analytics Web Session (see below) to integrate these data into a map view like shown below. Add other data.

Patterns of Median Housing Value by State

– view developed using ProximityOne CV XE GIS
– click graphic for larger view

An advantage of using the ACS or ACS-like $MHV data is that this measure is synchronized with other related measures, like total population, total housing units, housing units by tenure and age built and so on. Though a popular measure to assess geographically comparable housing values, the $MHV has many limitations. A key limitation is that few survey responders really know the value of their home. Other limitations have to do with the definition itself and how the data are collected/developed. ACS $MHV measures value of only occupied housing units and excludes houses on 10 or more acres and housing units in multi-unit structures. See more. While there are other Federal sources of $MHV, it remains that the usabilty aspects of the ACS or ACS-like measures are second to none.

Learn more — Join me in the Situation & Outlook Web Sessions
Join me in a Situation & Outlook Web Session where we discuss topics relating to measuring and interpreting the where, what, when, how and how much demographic-economic change is occurring and it’s impact.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and 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.

Personal Consumption Expenditures by Type & State

.. using Personal Consumption Expenditures (PCE) measures to monitor/examine the strength of a regional economy and consumer buying trends in that region and compare among regions … PCE estimates released in October 2019, show that state personal consumption expenditures increased 5.1 percent in 2018, an acceleration from the 4.4 percent increase in 2017. The percent change in PCE across all states ranged from 7.3 percent in Utah to 3.6 percent in West Virginia.

In 2018, across all states and D.C., per capita PCE was $42,757. Per capita PCE by state ranged from a high of $55,095 (MA) to a low of $31,083 (MS). Per capita PCE in D.C. $63,151. Use the interactive table to example per capita and total PCE by state for 24 categories annually 2010 to 2018.

Per Capita Personal Consumption Expenditures by Category; U.S. 2018
— how does your situation and areas of interest compare to U.S. overall?
— view, sort, query by state and year in the interactive table

Goods and services purchased by people are personal consumption expenditures (PCE). These data provide insights into the strength of a state economy and consumer buying trends. As a major component of GDP, PCE growth has recently accounted for much of the GDP growth. The data reviewed in this section are developed by the Bureau of Economic Analysis (BEA, released each October). ProximityOne develops regional PCE estimates by metro and county. More about PCE.

See related sections:
• State Real Median Household Income
• State Annual Gross Domestic Product by Industry

Per Capita Consumption Expenditures by State, 2018
The following graphic shows patterns of 2018 per capita personal income expenditures (PCE). Intervals show distribution in quintiles, equal number of states per interval. The 2018 U.S. per capita PCE was $42,757. Use CV XE GIS project to examine PCE by types, per cpaita vs total, different years and change. Integrate additional subject matter and types of geography. Click graphic for larger view with details. Expand browser window for bets quality view.

– view developed with ProximityOne CV XE GIS and related GIS project & datasets.

Using the Interactive Table
— which areas have the highest health care expenditures?
Use the interactive table to examine personal consumption expenditures by type and state annually for the period 2010-2018. The following view illustrates use of the table. This view shows use a query to examine only health care expenditures. The table was then sorted in descending order to show the areas with the highest per capita health care expenditures in 2018.

Try using the interactive table to existing states or categories 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.

U.S. & State Real Median Household Income Trends

.. during the past two years, 2017 and 2018, the real median household income increased by $1,627. Some states experienced a decline in real median household income in the past two years. During the previous two years, 2015 and 2016, the real median household income increased by $3,329. See details in interactive table (opens new page).

Real median household income in the U.S. increased 0.8 percent between the 2017 ACS and 2018 ACS based on the American Community Survey (ACS 2018). The U.S. MHI, based on ACS 2018 (released September 2019), was $61,937. The national MHI has been increasing since 2013. The increase from 2017 is smaller than the prior 3 years, during which MHI increased between 1.8 percent and 3.3 percent annually. This was the second consecutive year that U.S. MHI was higher than 2007.

Household income as used here is the combined gross income of all members of a household, defined as a group of people living together, who are 15 years or older. The median household income is used to examine the economic health of an area or to compare living conditions between geographic regions.

Use the interactive table and related Geographic Information System (GIS) resources to examine income trends and geographic patterns. See details on using GIS project.

Patterns of Real Median Household Income Change; 2016-2018
— change during two calendar years labeled with 2018 real MHI
— click link for larger view; expand browser window for best quality view.

– view developed using ProximityOne CV XE GIS and related GIS project.
– geospatial analyze income characteristics integrated with your data to examine patterns; gain insights.

Median Household Income in the United States: 2005–2018

U.S. & State Median Household Income: Annually 2005–2018 — Interactive Table
The following static graphic illustrates use of the U.S. & State MHI interactive table. This view shows the 10 states/areas ranked on the 2018 real median household income. See pointer, note that D.C. had the highest real 2018 MHI.  

Try it yourself. Use the table to examine different patterns … like which states experienced a decline in a selected year or over a selected period.

Alternative Measures of MHI
There are other ways to measure/estimate MHI. Possibly the most notable alternative is the Census/BLS Current Population Survey (CPS). This topic will be covered in an upcoming blog .. and how ACS and CPS MHI estimates differ. While the CPS can be used to develop state and higher level geography estimates, ACS might be preferred as MHI estimates can also be developed for counties, cities, census tracts and block groups .. and many other political/statistical areas not possible using CPS.

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.

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.

State of the States: 2018 Population & Components of Change

.. Welcome to 2019 .. how the U.S., states and world population are changing … the Census Bureau estimates the U.S. population is 328,231,337 as of January 1, 2019. This represents an increase of 2,013,241, or 0.62 percent, from New Year’s Day 2018 (326,218,096). The population as of Census Day (April 1) 2010, was 308,745,538 and has grown by 19,485,799, or 6.31 percent.

This section updates January 2020, with corresponding 2019 updates and additional details. Follow (click follow button at upper right) to receive updates on this and geographic, demographic and economic change with drill-down to the street intersection level.

In January 2019, the U.S. is expected to experience one birth every 8 seconds and one death every 11 seconds. Meanwhile, net international migration is expected to add one person to the U.S. population every 29 seconds. The combination of births, deaths and net international migration will increase the U.S. population by one person every 19 seconds … one net international migrant every 34 seconds.

The world population on January 1, 2019 is estimated to be 7,541,221,651. The world has experienced a population increase of 96,777,770, or 1.3 percent, from New Year’s Day 2018 (population 7,444,443,881). During January 2019, 4.8 births and 1.9 deaths are expected worldwide every second.

Patterns of Population Change by State, 2010-2018
The following graphic shows patterns of percent population change from 2010 to 2018. Use the associated GIS project to examine different years or subject matter items. Click graphic for larger view; expand browser window for best quality view.

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

How the U.S. Population is Changing
The following graphic shows how the population of the U.S. has changed from 2010 to 2018 and how the population might change 2019 through 2020. Click graphic for larger view; opens in new page. The population is as of July 1 for each year. The components of change (birth, deaths and migration) are for the period July 1 through June 30 for that year.

Population for each year is computed by the population identity equation:
  P[t]=P[t-1] + B[t,t-1] -D[t,t-1] + M[t,t-1]
Viewing the larger image, see how each of the components of change are impacting the total population and population change.
… see more detail about these data for the U.S. and by state at http://proximityone.com/states2018.htm.

More About Population Trends, Patterns and Characteristics
See more about how population dynamics; use the interactive tables in these sections:
  • School Districts — http://proximityone.com/sdtrends.htm
  • Cities — http://proximityone.com/places2017.htm
  • Counties — http://proximityone.com/countytrends2017.htm
  • Metros — http://proximityone.com/metros.htm
  • States — http://proximityone.com/states2018.htm

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.

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.