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.

Housing Price Index 2017Q3-2018Q3

.. this past week the 3rd quarter 2018 (2018Q3) Housing Price Index (HPI) was released for the U.S., states and metros. As a leading economic indicator, the HPI often gives insights into how the housing market and economy might be changing in the months ahead. The fact that the HPI data are quarterly and become available with a short lag time makes the measure even more valuable. This section provides an update on the HPI 2018Q3 and quarterly data for the past year. See the related Web page for more detailed data and access to the HPI data via interactive table.

Visual Analysis of 2017Q3-2018Q3 HPI Patterns
The following graphic shows housing value appreciation 2017Q3-2018Q3 by metro based on the HPI.

Click graphic for larger view and details. This view developed using CV XE GIS and related GIS project. Members of the ProximityOne User Group (join now, no fee) may used the CV XE GIS software and GIS project to create similar views with different HPI measures. Zoom-in. Add labels. Add other geography/data. Create views/graphics for reports and stories.

The Larger Picture
The HPI is calculated using home sales price information from Fannie Mae- and Freddie Mac-acquired mortgages. By itself, the HPI provides limited insights into the broader picture of “the why” and “how otherwise” states and metros are changing. The Situation & Outlook Metro Profiles provide an integrated view of the HPI measure in combination with other economic, demographic and business activity measure. View the HPI integrated with other subject matter … choose a metro. Metro Profiles are updated continuously and are available for each of the metropolitan area.

HPI Interactive Table
Use the HPI interactive table to view/rank/compare the non-seasonally adjusted “all transactions” HPI for the most recent 5 quarters for all Metropolitan Statistical Areas (MSAs), states and the U.S. The graphic shown below illustrates use of the interactive table to rank all metros in descending order on the percent change over the past year.

Updates & Related Measures
Quarterly HPI measures are used to updated the interactive table, GIS project and Metro Profiles. HPI by county, ZIP Code and census tract are updated annually. The 2018 county, ZIP Code and census tract HPI data are scheduled for release in February 2019.

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.

Block Group Demographic Data Analytics

.. use tools described here to access block group data from ACS 2016 (or ACS2017 in December 2018) using a no cost, menu driven tool accessing the data via API. Select from any of the summary statistic data. Save results as an Excel file or shapefile. Add the shapefile to a GIS project and create unlimited thematic pattern views. Add your own data. Join us in a Data Analytics Web session where use of the tool with the ACS 2017 data is reviewed.

See related Web section for more details.
– examine neighborhoods, market areas and sales territories.
– assess demographics of health service areas.
– create maps for visual/geospatial analysis of locations & demographics.

Illustration of Block Group Thematic Pattern Map – make for any area

– click graphic to view larger view
– pointer (top right) shows location of Amazon HQ2

Topics in this how-to guide (links open new sections/pages)
• 01 Objective Thematic Pattern Map View
• 02 Install the CV XE GIS software
• 03 Access/Download the Block Group Demographic-Economic Data
• 04 Download the State by Block Group Shapefile
• 05 Merge Extracted Data (from 03) into Shapefile (04)
• 06 Add Shapefile to the GIS Project; Set Intervals
• 07 Viewing Profile for Selected Block Group
• 08 BG Demographics Spreadsheet
• 09 Block Group Demographics GIS Project
• 10 Why Block Group Demographics are Important

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.

Outlook 2060

.. reach this blog at http://outlook2060.com .. see related Demographics 2060 .. this blog focuses on topics regarding the current situation and outlook .. what is happening now, historical trends and into the future .. geographic, demographic and economic characteristics for wide-ranging types of geography .. what will change where, when, by how much .. and how change might it impact you .. data resources and tools enabling a deeper dive; relating to decision-making. Get email updates when posted, click button at right. Planned topics in week of (month ahead):
.. what these new data are telling us in context of other data; accessing the data ..
• 05/27 .. K-12 Schools: Sources & Uses of Funds by School District
• 05/27 .. City/SubCounty Population Patterns & Trends; New 2018 Estimates
• 05/27 .. Housing Patterns & Trends by County/Metro; New 2018 Estimates
• 05/27 .. City/County Building Permits; Monthly Update; 2019M4
• 06/03 .. Housing Price Index; Metro+ Patterns & Trends; 2019Q1
• 06/03 .. Local Area Employment Situation; City/County/Metro; 2019M4
• 06/03 .. Diversity Patterns by County; An Update
• 06/10 .. Establishments, Employment, Earnings; County/Metro; QCEW 2018Q4
• 06/17 .. Population by Age-Gender-Race/Origin; County; 2018 Annual Update
• 06/24 .. State Quarterly Personal Income; 2019Q1
• 06/24 .. City/County Building Permits; Monthly Update; 2019M5
• 06/24 .. CES Metro Employment, Hours, Earnings; 2019M5

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.