Extrapolations

This is a collection of long-term forecasts based on quantitative data from diverse sectors. Long-term means 20 years or more. Diverse means forecasts in a wide range of activities such as transportation, education, food, shelter, entertainment, technology, etc. You can help grow the collection. Please check our list of desired indicators and submit suggestions to extrapolations@kk.org. We're also collecting and crossposting any and all attempts to extrapolate the future on Tumblr and Pinterest. You can follow us on Twitter too.

Crime


Summary

This collection of data includes the following indicators, dates, and sources:
violent/property crime rates, 1994-2015, U.S. Dept. of Justice
white collar crime prosecutions, 1995-2015, TRAC
executions, 1976-2016 & 1608-2002, Death Penalty Info Center
adult correctional population, 2014-1980, DoJ
incarceration rate, 1925-2014, DoJ and Sourcebook of Criminal Justice Stats
state and federal confinement and community facilities, 1979-2005 (quinquennial), DoJ

Findings

Crime Rates

Crime in the United States
by Volume and Rate per 100,000 Inhabitants, 1994–2015


Google Spreadsheet

Note: The violent crime figures include the offenses of murder, rape (legacy definition), robbery, and aggravated assault.

Note: The property crime figures include the offenses of burglary, larceny-theft, and motor vehicle thefts.

Src for 1996-2015:
U.S. Department of Justice. Accessed October 24, 2016.
Crime in the United States 2015.
Table 1: Crime in the United States.

Src for 1994, 1995:
U.S. Department of Justice. Accessed October 24, 2016.
Crime in the United States 1995.
Section II: Crime Index Offenses Reported [PDF]

*

White Collar Crime

For every 100,000 people in the United States, there are 5,317 arrests that are directly related to white collar crime.

In August 2014, it was reported that there were 512 total white collar prosecutions that occurred in the United States.

On a year to year comparison with August 2013, the 512 incidents are 6.2% lower.

It is estimated that 1 out of every 4 households will become the victim of a white collar crime at some point.

More than 88% of white collar crime incidents are never reported to law enforcement agencies, although about half of all incidents are reported to someone, such as a supervisor.

White collar crime has been moving away from stealing money from companies to stealing money from people. The most frequently cited charge that leads a prosecution attempt is aggravated identity theft. This charge accounts for 18.6% of the total charges that were filed within the last month. Mail fraud or conspiracy charges to commit offenses that defraud the country are also popular charges that are filed. In total, however, bank fraud and wire fraud are still the most popular white collar offenses that are investigated.

Src:
Brandon Gaille. Nov 2014.
34 Surprising White Collar Crimes Statistics.

*

White Collar Crime Prosecutions, 1995-2015

trac-white-collar-crime-prosecutions-1995-2015

trac-white-collar-crime-prosecutions-change-1995-2015

trac-white-collar-crime-top-charges-1995-2015

Src:
TRAC Reports. July 2015.
Federal White Collar Crime Prosecutions At 20-Year Low.
Transactional Records Access Clearinghouse. Syracuse University.

***

Capital Punishment

The Death Penalty Information Center (DPIC) tracks and aggregates historic data on capital punishment in the United States.

DPIC’s modern data set goes back to 1976

dpic-executions-1976-2016

DPIC has also collected execution data going back to 1608 in its “[Espy File],” based on research compiled by M. Watt Espy and John Ortiz Smykla. The Espy data is available in a few different formats at the DPIC website, but Time has published an interactive info graphic showing the total number of executions per year, integrating the Espy data with DPIC’s modern data.

Srcs:

DPIC. Updated October 19, 2016. Accessed November 3, 2016.
Executions by Year.
Executions in the U.S. 1608-2002: The Espy File.
“Espy File Data.” XLS

Chris Wilson. July 24, 2014.
Every Execution in U.S. History in a Single Chart.
Time.

TO DO: EXTRACT ANNUAL TALLIES OF EXECUTIONS FROM ESPY DATA FILE.

***

Incarceration

The Bureau of Justice Statistics tracks data on the US correctional population going back to at least 1980.

bjs-adult-correctional-population2014-1980


Google Spreadsheet

Src:
Bureau of Justice Statistics. Accessed November 3, 2016.
Key Statistic: Total Correctional Population.
“Estimated number of persons supervised by U.S. adult correctional systems, by correctional status, 1980-2014.” [XLS]
U.S. Department of Justice.

*

A compilation of historic incarceration rates, 1925-2014, is published a WikiCommons, citing data from the “Sourcebook of Criminal Justice Statistics.

ualbany-incarceration-rates-1925-2014


Google Spreadsheet

Src:
Smallman12q. January 2010. Accessed November 3, 2016.
(Subsequently updated by other users)
File:U.S. incarceration rates 1925 onwards.png
Wikimedia Commons.

Citing:
U.S. Department of Justice, Bureau of Justice Statistics.
and
University of Albany.
Sourcebook of Criminal Justice Statistics (2003).
Table 6.28, P.500.

*

State and Fed facilities (confinement and community facilities)

The “Census of State and Federal Adult Correctional Facilities” has been conducted every 5 to 7 years since 1974. The census reports include a count of the number of facilities which were included in the survey. Below are excerpts from 1979-2005.

Confinement AND Community Facilities
1979 – 791
state confinement – 568
1984 – 903
state confinement – 694
1990 – 1,287
state confinement – 957
1995 – 1,500
state confinement – 1,084
2000* – 1,668
state confinement – 1,023
2005 – 1,821 (nearly all growth in private facilities)

Note: 2000 was the first year that specifically called out private facilities.

Src:
Bureau of Justice Statistics. 1979-2005.
Census of State and Federal Correctional Facilities.” [multiple reports]
Data Collection: Census Of State And Federal Adult Correctional Facilities.
U.S. Department of Justice.

Tags: , ,

Posted by cc on November 15, 2016 at 9:00 am | comment count



Government


Summary

This collection of data includes the following indicators, dates, and sources:
passports circulating, 1989-2015, Dept. of State
passports issued, 1974-2015, Dept. of State
licensed drivers, 1960-2014, Dept. of Transportation
biometric ID usage rates in hospitals, 2008-2012, Raymonde Charles et al.
voting rate, 1978-2014 & 1964-2014, Census Bureau
voter registration, 1966-2014 & 1828-1956, Census Bureau & Congressional Quarterly Press
people working in government, 2014/2024, BLS
federal laws passed, 1973-2015 & 1947-2013, GovTrack & Brookings Inst.

Findings

Personal Identification

Passports

U.S. Passports Circulating (1989-2015) and Issued per Year (1974-2015)
Note: As of 1996, passports issued statistics are tabulated for the fiscal year.


Google Spreadsheet

Src:
US Department of State. Accessed October 17, 2016.
“Passports Statistics.”

Note:
The Department of State has been issuing exclusively biometric/electronic passports since 2007.

Here’s a map showing the state-by-state distribution of Americans with active passports, for the year 2013.

expeditioner-percent-americans-with-passport-2013

The map is based on the State Department data given above for the number of passports issued in the last 10 years, divided by the total US population (per the Census Bureau, minus the ~12 million undocumented residents and ~13 million legal permanent residents who cannot obtain passports).

Src:
Matt Stabile. February 2014.
How Many Americans Have A Passport?
The Expeditioner.

*

Licensed Drivers, Vehicle Registrations, and Resident Population (In Millions)
1960-2014


Google Spreadsheet

Src:
Department of Transportation. January 2016.
Highway Statistics 2014.

*

Gov’t Issued ID

The 2012 American National Election Survey asked survey respondents about what type of government-issued photo identification they possessed. The survey indicates that 6.3% of respondents do not have a valid, government-issued photo ID.

These are the total weighted percentages in responses.

Question: Do you have a non-expired Driver’s License?
Variable name: dem3_driver
Has: 83.9%
Does not have: 15.4%
Don’t know: 0%
Refused: 0.6%
Total number of respondents: 6,112

Question: Do you now have a non-expired U.S. passport, or do you not have one?
Variable name: dem3_passport
Has: 40.8%
Does not have: 58.4%
Don’t know: 0.2%
Refused: 0.6%
Total number of respondents: 5,914

Question: (If no valid driver’s license or passport) Do you have another form of non-expired, government issued photo ID, such as a state-issued ID or military ID?
Variable name: dem3_govtid
Has: 5.9%
Does not have: 6.3%
Inapplicable: 87.3%
Don’t know: 0%
Refused: 0.5%
Total number of respondents: 5,914

Src:
American National Election Studies. May 28, 2015.
User’s Guide and Codebook for the ANES 2012 Time Series Study.
The University of Michigan and Stanford University.
Pp. 732-734.

Other source notes:
Description: Demographics3
Position: Pre-election survey, section-item no. 62.7-12, 62.7-13

NOTE: ANES confirmed by email that 2012 was the first year this data was collected. The same questions will be asked in the 2016 post-election survey, and results will be published at the end of the first quarter of 2017.

Although ANES has not collected any previous data on gov’t-issued ID possession rates, a couple other surveys have been conducted recently, in the context of voter ID requirements. For example:

2006 — the Brennan Center (NYU School of Law) commissioned a survey (of 987 voting-age Americans) finding that 11% of respondents did not have ready access to government-issued photo ID.
[Src]

2001 — The Carter-Ford Commission on Election Reform found that 6-11% of voting-age citizens lacked state-issued photo ID.
[Src]

*

Biometric Data Tracking

Biometric Update is a research and news source with a pretty wide range of news articles, research papers, white papers, and overviews describing current biometric identification technologies. The Government Purchasing news articles may be of particular interest. The statistics presented on the site are largely industry-focused.

search terms:
biometric identification adoption rates
mobile driver’s license (Iowa pilot in 2016)
e-driving licenses
e-passports
border management
national IDs

*

White Paper:
Rawlson O’Neil King. June 2014.
National and Civil ID White Paper.
Biometrics Research Group

Gives an overview of the format and use-cases for ePassports, eIDs, and electronic voting enrollment. Briefly describes (emphasizing shortcomings) the US social security number and driver license with regard to their use as identification.

*

Research report:
Smithers Pira. July 2016.
The Future of Personal ID to 2021.
Contact: Stephen Hill shill@smithers.com; Josh Rabb jrabb@smithers.com
Note: This research firm focuses on packaging, paper and print industry supply chains.

Tables & Figures:
Trends in personal identification
The evolution of the ePassport
Market forecast of for personal ID by technology 2016-2021
Unit forecast of (2016-2021):
traditional MRP
ePassports
traditional national ID
eID
driving licences
traditional visas
eVisas
health cards
electoral systems
vital documents
The evolving landscape of personal identification 2016-2021

I have NOT established contact with this firm to inquire about data sharing, but, as noted above, the Department of State has been issuing exclusively biometric/electronic passports since 2007.

*

Research report:
TechNavio, May 2016
Biometrics Market In North America 2016-2020
Contact: americas@technavio.com

Excerpts:

Market research analysts at Technavio have predicted that the biometrics market in North America will grow steadily at a moderate CAGR of more than 12% by 2020.

Owing to an increase in investments and the early adoption of biometric technology, the biometric market in North America will have a constant demand from the government sector. According to this market research analysis, this segment will account for about 40% of the total market share by 2020 and will dominate the market throughout the forecast period.

*

Research report:
TechNavio, October 2015
Global Law Enforcement Biometrics Market 2015-2019
Contact:

Technavio’s analysts forecast the global law enforcement biometrics market to grow at a CAGR of 13.35% over the period 2014-2019.

*

Research report:
TechSci Research, May 2016.
Global Biometrics Market By Type (Fingerprint Recognition, Facial Recognition, Hand/Palm Recognition, Iris Scanner, Voice Recognition, Vein Scanner & Others), By End Use Sector, By Region, Competition Forecast and Opportunities, 2011 – 2021.

Includes market size and forecast value for North American Government applications (as well as other regions and sectors.

*

Data on the use of biometric information by government agencies is fairly hard to come by. Aside from the few reports mentioned above, I’ve found some data on the adoption rates of biometric data within US hospitals. Not sure if this might have any implications for adoption rates in other sectors, like government.

Excerpts:

Biometric devices and their accompanying software in healthcare institutions permit the automatic authentication of patient and provider identity for different purposes such as secure EHR system access, and patient verification31. The most common hospital implementation of biometrics are the use of fingerprint and iris scanning32, 33. The unique authentication methods of biometrics make it difficult to mismatch and forge identities since no two irises or fingerprints are the same.

The use of fingerprint scanning had an average annual adoption increase of 1.23% per year from 2008, leading to a total of 15.9% (n=871) adoption within all hospital respondents (n=5467) in 2012. Iris scanning technology has an average annual adoption rate of 0.02% from the same time frame, and is only currently being used in 13 hospitals (0.02%) in 2012. Only 2.49% (n=136) hospitals in 2012 plan to expand or adopt the fingerprint technology in the following years, in contrast to only 12 hospitals (0.22%) for iris scanning.

Low adoption may be due to the costs in implementing biometrics within existing EHR systems and workflows.

biometrics-use-in-hospitals-2008-2012

Src:
Raymonde Charles Y. Uy et al. November 2015.
The State and Trends of Barcode, RFID, Biometric and Pharmacy Automation Technologies in US Hospitals.
AMIA Annual Symposium Proceedings Archive.

*

Examples of companies/technologies currently being deployed in the US:

Unisys integrates NEC’s facial recognition software in CBP project at JFK airport.
Biometric Update. May 2016

Excerpt:
NEC‘s top NIST rated facial matching technology will be used to compare the image taken during the normal inspection process to the image stored on the traveler’s e-passport. The initial deployment will apply to first time Visa Waiver Program (VWP) travelers and returning U.S. citizens with e-Passports. … Unisys worked together with NEC to develop this entry/exit screening solution, which allows CBP officers to capture a live facial image. The facial image from electronic passports is then compared to the live captured image. If the images do not match, travelers may be subject to additional screening by CBP officers.

***

Voting Registration and Rates

Voting Rates in Congressional and Presidential Elections: 1978 to 2014

census-voting-rates-1978-2014

Src:
U.S. Census Bureau.
Who Votes? Congressional Elections and the American Electorate: 1978–2014.” July 2015.
Figure 2, P. 4.

*

The Current Population Survey collects data on voting and voter registration in November of even-numbered years, and has done so since 1964. It provides information about voting and registration by many characteristics, including age, sex, race, and education. Because the data are from a survey, they are subject to sampling error.


Google Spreadsheet

Src:
U.S. Census Bureau. February 2012.
Table A-1. Reported Voting and Registration by Race, Hispanic Origin, Sex, and Age Groups: November 1964 to 2014 (NOTE: Voting rates corrected February 2012).
Historical Reported Voting Rates.

[XLS file]

*

Voter Turnout in Presidential Elections: 1828 – 2012

Year % Turnout of Voting Age Population
1828 57.6%
1832 55.4%
1836 57.8%
1840 80.2%
1844 78.9%
1848 72.7%
1852 69.6%
1856 78.9%
1860 81.2%
1864 73.8%
1868 78.1%
1872 71.3%
1876 81.8%
1880 79.4%
1884 77.5%
1888 79.3%
1892 74.7%
1896 79.3%
1900 73.2%
1904 65.2%
1908 65.4%
1912 58.8%
1916 61.6%
1920 49.2%
1924 48.9%
1928 56.9%
1932 56.9%
1936 61.0%
1940 62.5%
1944 55.9%
1948 53.0%
1952 63.3%
1956 60.6%

Note: Voting Age Population includes those ineligible to vote such as felons. Because of this, V.A.P. figures are naturally lower than if the Voting Eligible Population (V.E.P.) is used as the denominator.

Note: Figures for 1960-2012 are also given on the source page, which cites data compiled by Gerhard Peters from data obtained from the Federal Election Commission.

Src:
Gerhard Peters and John T. Woolley. Accessed October 24, 2016.
The American Presidency Project: Voter Turnout in Presidential Elections 1828-2012.

Citing:
Sources:
(1824-1956) – Lyn Ragsdale, Vital Statistics on the Presidency (Washington, D.C.: Congressional Quarterly Press, 1998), 132-38.

***

Number of People Working in Gov’t 2014/2024


Google Spreadsheet

Src:
Bureau of Labor Statistics. Accessed October 26, 2016.
Employment Projections.
Industry-occupation matrix data, by occupation — Total, all occupations
[XLS]

***

Laws Passed

GovTrack aggregates publicly available data on the number of federal laws passed during each two-year Congressional session. Data are available going back to 1973.


Google Spreadsheet

Enacted Laws: Enacted bills and joint resolutions (both bills and joint resolutions can be enacted as law)
Passed Resolutions: Passed resolutions (for joint and concurrent resolutions, this means passed both chambers)
Got A Vote: Bills and joint/concurrent resolutions that had a significant vote in one chamber
Failed Legislation: Bills and resolutions that failed a vote on passage or failed a significant vote such as cloture, passage under suspension, or resolving differences
Vetoed Bills (w/o Override): Bills that were vetoed and the veto was not overridden by Congress
Other Legislation: Bills and resolutions that were introduced, referred to committee, or reported by committee but had no further action

Src:
GovTrack. Accessed November 3, 2016.
Congress > Bills > Statistics and Historical Comparison > Bills by Final Status.

*

Brookings Institution also aggregates figures on Congressional activity. This data set covers 1947-2013.


Google Spreadsheet

Src:
Raffaela Wakeman et al. July 9, 2013 (updated August 2014).
“Vital Statistics on Congress: Data on the U.S. Congress – A Joint Effort from Brookings and the American Enterprise Institute.”
[PDF]

Brookings Institution
contact: vitalstatistics@brookings.edu

Tags: ,

Posted by cc on November 14, 2016 at 11:44 pm | comment count



Environment


Summary

This collection of data includes the following indicators, dates, and sources:
Land Use
urban/developed km2, 1992-2100, USGS
forest km2, 1992-2100 & 1982-2012, USGS & USDA
forest (mil hectares), 2010-2030(2100), Pardee
deforestation (mil hectares), 2010-2100, Pardee
cropland km2, 1992-2100 & 1982-2012, USGS & USDA
grassland/shrubland km2, 1992-2100 & 1982-2012, USGS & USDA
hay/pasture km2, 1992-2100 & 1982-2012, USGS & USDA
wetland km2, 1992-2100, USGS
Conservation Reserve Program, 1985-2012, USDA
agricultural demand (mil met tons), 2010-2030(2100), Pardee
agricultural productions (mil met tons), 2010-2030(2100), Pardee
yield in agriculture (tons/hectar), 2010-2030(2100), Pardee
Air Quality
carbon emissions from fossil fuels (bil tons), 2010-2100, Pardee
carbon emissions cumulative change (bil tons), 2010-2100, Pardee
Water Use
water usage (cubic Km), 2010-2030(2100), Pardee
water use cumulative change (cubic Km), 2010-2100, Pardee
Mining
active mines, 2004-2013, CDC
Climate Change
max temperatures, 1950-2099, USGS
precipitation, 1950-2099, USGS
snowpack, 1950-2099, USGS
soil water storage, 1950-2099, USGS
sea-level rise, 1800-2100, NCA citing Kemp, Church, Narem, Parris, Etheridge
sea-level warming, 1900-2010, NCA citing Chavez, Etheridge
extreme precipitation events, 1900-2000, NCA citing Kunkel
water demand change, 2005/2060, NCA citing Brown
water supply risk, 2050, NCA citing Roy et al.
atmospheric carbon dioxide, 1900-2000, NCA citing Etheridge
sea surface pH, 1900-2000, NCA citing Etheridge
Northeaster fisheries shifting north, 1970-2010, NCA citing Pinsky and Fogarty

Findings

Land Use

The U.S. Geological Survey tracks and forecasts several categories of land use, with charts and maps showing change under four different scenarios from 1992 through 2100. The land-use categories include acreage that is 1) urban/developed, 2) forest, 3) cropland, 4) grassland/shrubland, 5) hay/pasture, and 6) wetland.

USGS-urban-dev-and-forest-land-area-1992-2100

USGS-crop-and-grass-land-area-1992-2100

USGS-pasture-and-wetland-land-area-1992-2100

img src:
Terry Sohl, et al. December 2012.
The Completion of Four Spatially Explicit Land-use and Land-cover (LULC) Scenarios for the Conterminous United States.” P.28
U.S. Geological Survey.

*

The USDA’s National Resources Conservation Service (NRCS) has published a periodic National Resources Inventory (NRI) since 1977, with data being collected annually since 2000. The contemporary reports give acreage counts for non-Federal lands, including cropland, Conservation Reserve Program lands, pastureland, rangeland, forest land, and other rural land.

Excerpts:

Table 2 – Land Cover/use of non-Federal rural land, 1982-2012 (quinquennial)
In thousands of acres, with margins of error

USDA-land-use-1982-2012

Note: Acreages for Conservation Reserve Program (CRP) land are established through geospatial processes and administrative records; therefore, statistical margins of error are not applicable and shown as a dashed line (–). CRP was not implemented until 1985.

Table 9 – Changes in land cover/use between 1982 and 2012
In thousands of acres, with margins of error

USDA-land-use-change-1982-2012

Similar tables for five-year intervals within the 1982-2012 are also presented in the report (pp.41-46).

Cropland
A land cover/use category that includes areas used for the production of adapted crops for harvest. Two subcategories of cropland are recognized: cultivated and noncultivated. Cultivated land comprises land in row crops or close-grown crops and also other cultivated cropland; for example, hayland or pastureland that is in a rotation with row or close-grown crops. Noncultivated cropland includes permanent hayland and horticultural cropland.

Pastureland
A land cover/use category of land managed primarily for the production of introduced forage plants for livestock grazing. Pastureland cover may consist of a single species in a pure stand, a grass mixture, or a grass-legume mixture. Management usually consists of cultural treatments: fertilization, weed control, reseeding, renovation, and control of grazing. For the NRI, includes land that has a vegetative cover of grasses, legumes, and/or forbs, regardless of whether or not it is being grazed by livestock.

Rangeland
A broad land cover/use category on which the climax or potential plant cover is composed
principally of native grasses, grasslike plants, forbs or shrubs suitable for grazing and browsing, and introduced forage species that are managed like rangeland. This would include areas where introduced hardy and persistent grasses, such as crested wheatgrass, are planted and such practices as deferred grazing, burning, chaining, and rotational grazing are used, with little or no chemicals or fertilizer being applied. Grasslands, savannas, many wetlands, some deserts, and tundra are considered to be rangeland. Certain communities of low forbs and shrubs, such as mesquite, chaparral, mountain shrub, and pinyon-juniper, are also included as rangeland.

src:
USDA, August 2015.
2012 National Resources Inventory: Summary Report.”
pp. 3-2, 3-39, 3-47, 4-1

*

For projected data on farmlands, 2014-2025, see the “Crop Acreage” section of the Food research round-up, citing “USDA Agricultural Projections to 2025.”

*

International Futures is a forecasting platform developed by Barry Hughes, based at the Pardee Center at the University of Denver. Among its many forecasts are a small set of agriculture and environment indicators.

Excerpt:

Quinquennial agriculture and environment indicators, United States, Working File
Pardee-crops-forest-carbon-emit-water-use-2010-2030

Forecast data through 2100 is available at the site for each indicator, if you click through. For example, here’s the chart for millions of hectares of forest land through 2100:
Pardee-forest-land-2010-2100

The charting tools offer several options, including specialized displays for particular issues. For example, the Advanced Sustainability Analysis, which calculates fossil fuel use, carbon emissions, deforestation, and water use in terms of intensity per million GDP, thousand population, and thousand labor. These calculations are also forecast through 2100, accessible by changing the “select year” parameter of the display.

Raw annual deforestation (million hectares), 2010-2100 (via the Advanced Sustainability Analysis table):
Pardee-raw-annual-deforestation-2010-2100

TO DO: EXTRACT ANNUAL DATA POINTS BY CLICKING THROUGH ON THE INDIVIDUAL INDICATORS FROM THE REPORT. THIS ALSO GIVES ACCESS TO THE FORECAST FIGURES THROUGH 2100.

Src:
International Futures. Accessed August 22, 2016.
Basic Report – USA, Working File.”
Advanced Sustainability Analysis — USA, Working File
The Pardee Center. University of Denver.

*

This 2010 report includes a round-up of recent projections of forest land conversion in the United States. The report discusses socioeconomic drivers of land-use change affecting forest area, and defines five categories of change: afforestation, deforestation, forest fragmentation, forest parcelization, and increased numbers of structures on forest land.

Here’s the summary of projected land-base changes affecting US forests:

Alig-land-change-projections-affecting-forests

Src:
Ralph Alig et al. 2010.
Conversions of Forest Land: Trends, Determinants, Projections, and Policy Considerations.” In Advances in Threat Assessment and Their Application to Forest and Rangeland Management.
U.S. Department of Agriculture, Forest Service, Pacific Northwest and Southern Research Stations.
p.14

Air Quality

Raw annual carbon emissions (billion tons), 2010-2100
Pardee-carbon-emit-raw-annual-2010-2100

Cummulative change in carbon emissions, percent (billion tons), 2010-2100
Pardee-carbon-emit-cum-change-2010-2100

TO DO: EXTRACT ANNUAL DATA POINTS

Src:
International Futures. Accessed August 22, 2016.
Advanced Sustainability Analysis — USA, Working File
The Pardee Center. University of Denver.

*

More data on carbon emissions can be found under the Energy Mix blog post.

Water Use

Water use (cubic kilometers), cumulative change in raw values, percent, 2010-2100 (via the Advanced Sustainability table):
Pardee-water-use-cum-change-2010-2100

TO DO: EXTRACT ANNUAL DATA POINTS

Src:
International Futures. Accessed August 22, 2016.
Advanced Sustainability Analysis — USA, Working File
The Pardee Center. University of Denver.

Mining

MSHA-active-mines-2004-2013

src:
CDC. Accessed August 24, 2016.
Number of Active Mines by Sector and Year, 2004-2013.”
Statistics: All Mining
citing:
Mine Safety and Health Administration (MSHA)

TO DO: CONTACT MSHA TO CONFIRM SOURCE, AND INQUIRE ABOUT OLDER DATA.

Climate Change

In 2013, NASA released climate projection data through 2099 for the continental United States that is being used to quantify climate risks to the nation’s agriculture, forests, rivers and cities.

The excerpts below shows the change for the 1950-2005 historic period versus the 2050-2074 forecast period. Max temperatures are trending up, precipitation is staying about the same, snow pack is trending down (dramatically in the Western mountains), and water stored in the soil column is trending down.

Excerpts:

Max Temperatures – High Emissions Scenario (RCP8.5)
NASA-NEX-DCP30-max-temps-high-emit-1950-2074

Max Temperatures – Low Emissions Scenario (RCP4.5)
NASA-NEX-DCP30-max-temps-low-emit-1950-2074

Precipitation — Low Emissions
NASA-NEX-DCP30-precip-low-emit-1950-2074

Snow Water Equivalent — Low Emissions
NASA-NEX-DCP30-snow-low-emit-1950-2074
(Snow Water Equivalent — the liquid water stored in the snowpack)

Soil Water Storage – Low Emissions
NASA-NEX-DCP30-soil-stor-low-emit-1950-2074
(Soil water storage: the water stored in the soil column)

src:
USGS. Accessed August 24, 2016.
National Climate Change Viewer.”

NASA NEX DCP30 National Climate Change Viewer

The full NEX-DCP30 dataset includes 33 climate models for historical and 21st century simulations for four Representative Concentration Pathways (RCP) greenhouse gas (GHG) emission scenarios developed for AR5. … We include 30 of the 33 models in the viewer that have both RCP4.5 and RCP8.5 data; the remaining two scenarios, RCP2.6 and RCP6, are available in the NEX-DCP30 data set.

The NCCV allows the user to visualize projected changes in climate (maximum and minimum air temperature and precipitation) and the water balance (snow water equivalent, runoff, soil water storage and evaporative deficit) for any state, county and USGS Hydrologic Unit (HUC).

To create a manageable number of permutations for the viewer, we averaged the climate and water balance data into four climatology periods: 1950–2005, 2025–2049, 2050–2074, and 2075–2099.

src:
USGS. May 2014.
U.S. Geological Survey – National Climate Change Viewer: Tutorial and Documentation.”

*

The National Climate Assessment (NCA), conducted by the U.S. Global Change Research Program, aggregates a mix of historic quantitative data, data projections, and qualitative descriptions of the impacts of the climate change trends that are being seen and are most likely to continue. Impacts on seven sectors are described: human health, water, energy, transportation, agriculture, forests, and ecosystems.

Citations are provided in-context below. The source information for the NCA report is at the very bottom.

Excerpts:

NCA-extreme-precip-events-1900-2000

One measure of heavy precipitation events is a two-day precipitation total that is exceeded on average only once in a 5-year period, also known as the once-in-five year
event. As this extreme precipitation index for 1901-2012 shows, the occurrence of such events has become much more common in recent decades. Changes are compared to the period 1901-1960, and do not include Alaska or Hawai‘i. (Figure source: adapted from Kunkel et al. 2013 (7)).
p.25

7. K. E. Kunkel, et al. 2013.
Monitoring and understanding trends in extreme storms: State of knowledge.”
Bulletin of the American Meteorological Society, 94.

Past and Projected Changes in Global Sea Level:
NCA-sea-level-1800-2100

Figure shows estimated, observed, and possible amounts of global sea level rise from 1800 to 2100, relative to the year 2000. Estimates from proxy data (4) (for example, based on sediment records) are shown in red (1800-1890, pink band shows uncertainty), tide gauge data in blue for 1880-2009 (5), and satellite observations are shown in green from 1993 to 2012 (6). The future scenarios range from 0.66 feet to 6.6 feet in 2100 (7). These scenarios are not based on climate model simulations, but rather reflect the range of possible scenarios based on other kinds of scientific studies. The orange line at right shows the currently projected range of sea level rise of 1 to 4 feet by 2100, which falls within the larger risk-based scenario range. The large projected range reflects uncertainty about how glaciers and ice sheets will react to the warming ocean, the warming atmosphere, and changing winds and currents. As seen in the observations, there are year-to-year variations in the trend. (Figure source: Adapted from Parris et al. 2012 (7), with contributions from NASA Jet Propulsion Laboratory).
p.30

4. A. C. Kemp, et al. 2011.
Climate related sea-level variations over the past two millennia.”
Proceedings of the National Academy of Sciences, 108, 11017-11022.

5. J. A. Church, et al. 2011.
Sea-level rise from the late 19th to the early 21st century.”
Surveys in Geophysics, 32, 585-602.

6. R. S. Nerem, et al. 2010.
Estimating mean sea level change from the TOPEX and Jason altimeter missions.”
Marine Geodesy, 33, 435-446.
Article is behind a paywall. Might be able to get even more current data from Nerem’s website.

7. A. Parris, et al. 2012
Global Sea Level Rise Scenarios for the United States National Climate Assessment.”
NOAA Tech Memo OAR CPO-1, 37 pp. National Oceanic and Atmospheric Administration.

NCA-water-withdrawals-2005-2060

The effects of climate change, primarily associated with increasing temperatures and potential evapotranspiration, are projected to significantly increase water demand across most of the United States. Maps show percent change from 2005 to 2060 in projected demand for water assuming (a) change in population and socioeconomic conditions consistent with the A1B emissions scenario (increasing emissions through the middle of this century, with gradual reductions thereafter), but with no change in climate, and (b) combined changes in population, socioeconomic conditions, and climate according to the A1B emissions scenario. (Figure source: Brown et al. 2013 (4).)
p.43

4. T. C. Brown, et al. 2013.
Projecting fresh water withdrawals in the United States under a changing climate.”
Water Resources Research, 49, 1259-1276/

NCA-water-supplies-2050

Climate change is projected to reduce water supplies in some parts of the country. This is true in areas where precipitation is projected to decline, and even in some areas where precipitation is expected to increase. Compared to 10% of counties today, by 2050, 32% of counties will be at high or extreme risk of water shortages. Numbers of counties are in parentheses in key. Projections assume continued increases in greenhouse gas emissions through 2050 and a slow decline thereafter (A1B scenario). (Figure source: Reprinted with permission from Roy et al. 2012 (7). Copyright American Chemical Society).
p.44

7. S. B. Roy, et al. 2012.
Projecting water withdrawal and supply for future decades in the U.S. under climate change scenarios.
Environmental Science & Technology, 46, 2545−2556.

Key Climate Variables Affecting Agricultural Productivity

Frost-free season is projected to lengthen across much of the nation. Taking advantage of the increasing length of the growing season and changing planting dates could allow planting of more diverse crop rotations, which can be an effective adaptation strategy.

The annual maximum number of consecutive dry days (less than 0.01 inches of rain) is projected to increase, especially in the western and southern parts of the nation, negatively affecting crop and animal production. The trend toward more consecutive dry days and higher temperatures will increase evaporation and add stress to limited water resources, affecting irrigation and other water uses.

Hot nights are defined as nights with a minimum temperature higher than 98% of the minimum temperatures between 1971 and 2000. Such nights are projected to increase throughout the nation. High nighttime temperatures can reduce grain yields and increase stress on animals, resulting in reduced rates of meat, milk, and egg production.

p.47

NCA-ocean-warming-1900-2010

Sea surface temperatures for the ocean surrounding the U.S. and its territories have risen by more than 0.9°F over the past century. (Figure source: adapted from Chavez et al. 2011 (3)).
p.58

3. F. P. Chavez, et al. 2011.
Marine primary production in relation to climate variability and change.”
Annual Review of Marine Science, 3, 227-260.

NCA-CO2-ocean-impacts-1900-2000

As heat-trapping gases, primarily carbon dioxide (CO2) (panel A), have increased over the past decades, not only has air temperature increased worldwide, but so has the ocean surface temperature (panel B). The increased ocean temperature, combined with melting of glaciers and ice sheets on land, is leading to higher sea levels (panel C). Increased air and ocean temperatures are also causing the continued, dramatic decline in Arctic sea ice during the summer (panel D). Additionally, the ocean is becoming more acidic as increased atmospheric CO2 dissolves into it (panel E). (CO2 data from Etheridge 2010, Tans and Keeling 2012, and NOAA NCDC 2012; SST data from NOAA NCDC 2012 and Smith et al. 2008; Sea level data from CSIRO 2012 and Church and White 2011; Sea ice data from University of Illinois 2012; pH data from Doney et al. 2012 (4,5)).
p.59

4. D. M. Etheridge, et al. 2010.
Law Dome Ice Core 2000-Year CO2, CH4, and N2O Data, IGBP PAGES/World Data Center for Paleoclimatology.”
Data Contribution Series #2010-070. NOAA/NCDC Paleoclimatology Program, Boulder, CO.

CSIRO. 2012.
The Commonwealth Scientific and Industrial Research Organisation.”

J. A. Church and N. J. White. 2011.
Sea-level rise from the late 19th to the early 21st century.”
Surveys in Geophysics, 32, 585-602.

University of Illinois. 2012.
Sea Ice Dataset
University of Illinois, Department of Atmospheric Sciences.

S. C. Doney, et al. 2012.
Climate change impacts on marine ecosystems.”
Annual Review of Marine Science, 4, 11-37.

5. P. Tans and R. Keeling. 2012.
Trends in Atmospheric Carbon Dioxide, Full Mauna Loa CO2 Record.”
NOAA’s Earth System Research Laboratory.

NCA-fisheries-shifting-north-1970-2010

Ocean species are shifting northward along U.S. coastlines as ocean temperatures rise. As a result, over the past 40 years, more northern ports have gradually increased their landings of four marine species compared to earlier landings. While some species move northward out of an area, other species move in from the south. This kind of information can inform decisions about how to adapt to climate change. Such adaptations take time and have costs, as local knowledge and equipment are geared to the species that have long been present in an area. (Figure source: adapted from Pinsky and Fogerty 2012 (19)).
p.61

19. M. L. Pinsky and M. Fogarty. 2012.
Lagged social-ecological responses to climate and range shifts in fisheries.”
Climatic Change, 115, 883-891.

src:
Jerry M. Melillo, et al. May 2014.
Highlights of Climate Change Impacts in the United States: The Third National Climate Assessment.”
U.S. Global Change Research Program.

TO DO: EXTRACT DATA FROM SOURCES

Tags: , , , ,

Posted by cc on September 8, 2016 at 4:51 pm | comment count



Downtowns


Summary

This collection of data includes the following indicators, dates, and sources:

Acreage
urban acreage, 1992-2100 & 2000-2050 & 1950-2010, USGS & Lincoln Inst & US Census
Population
urban population, 1950-2050, United Nations
young adults by proximity to center, 1990/2012, UVA
elderly by proximity to center, 1990/2012, UVA
white residents by proximity to center, 1990/2012, UVA
black residents by proximity to center, 1990/2012, UVA
population by proximity to center, 1990/2012 & 2000/2010, UVA & US Census
population distribution by proximity to center, 2000/2010, US Census
Jobs
metro area jobs, 2002/2011 5-yr period, US Census
skilled jobs by proximity to center, 1980-2010 decadal, US Census
Education
full-time workers with BA+ by proximity to center, 1980-2010 decadal, US Census
educational attainment by proximity to center, 1990/2012, UVA
Desirability/Walkability
competitiveness of city centers, 2002/2011 5-yr period, City Observatory/US Census
cities most likely to be WalkUPs in the future, GWU
Personal Income
per capita income by proximity to center, 1990/2012, UVA
proportion residents living below poverty line by proximity to center, 1990/2012, UVA
home prices by proximity to center, 1980-2010 decadal, US Census
Housing and Density
occupied housing units by proximity to center, 1990/2012, UVA
percent of rented housing by proximity to center, 1990/2012, UVA
population density by proximity to center, 1990/2012, UVA

NOTE: Might be worth talking to someone from MIT’s Center for Advanced Urbanism, or an editor from City Lab or Next City for suggestions of additional “downtown” indicators and possible data sources, as well as more forecast data, which is quite lacking in this round-up.

keywords:
urban development
central business districts
city centers

data desired but lacking:
traffic congestion
construction trends
walkability (longitudinal data)
energy consumption per capita (vs. rural)

Findings

Urban Acreage

The U.S. Geological Survey tracks and forecasts several categories of land use, with charts and maps showing change under four different scenarios from 1992 through 2100. The land-use categories include acreage that is 1) urban/developed, 2) forest, 3) cropland, 4) grassland/shrubland, 5) hay/pasture, and 6) wetland.

Urban/Developed Land Area in Four Scenarios, 1992-2100
USGS-urban-developed-land-area-1992-2100

Excerpt:

Researchers at the USGS Earth Resources Observation and Science Center have developed the FOREcasting SCEnarios of land-cover change (FORE-SCE) model that is based on consistent and systematic historical data derived from Landsat satellite imagery of rates and spatial patterns of land cover change over many years. As part of USGS research to assess potential greenhouse gas fluxes and carbon storage in vegetated landscapes, FORE-SCE has been used to produce projected, annual land-cover maps from 1992 through 2100 for four future scenarios for the conterminous United States. The land cover maps provide 250-meter resolution information for 17 different land-use and land-cover classes, offering an unprecedented combination of thematic detail and spatial resolution for land-cover projections.

The four land cover scenarios that were modeled are based, in turn, on carefully-defined environmental scenarios from the Intergovernmental Panel on Climate Change (IPCC), ensuring that the projected land cover maps may be used in assessment frameworks consistent with IPCC scenario characteristics. The scenarios vary in terms of both climate and socioeconomic conditions in the future.

The A1B scenario is characterized by very high economic growth, strong technological innovation, and open, global economies and societies. Projected land use changes include sprawling urban growth, agricultural expansion, and heavy use of forested lands for wood products.

The A2 scenario is characterized by moderate economic growth, very high population growth, and less open economies and societies. Land use changes include very high urban growth, massive expansion of agricultural lands to feed a growing population, and loss of natural landscapes.

The B1 scenario has high economic growth, moderate population growth, and a focus on environmental sustainability. Land-use change is modest, with compact urban growth and modest increases in agricultural land.

The B2 scenario has moderate economic growth, low population growth, and a focus on environmental sustainability. Natural landscapes are preserved and even expanded in this scenario, with a reduction in lands devoted to agriculture.

Image Src:
Terry Sohl, et al. December 2012.
The Completion of Four Spatially Explicit Land-use and Land-cover (LULC) Scenarios for the Conterminous United States.” P.28
U.S. Geological Survey.

NOTE: This PDF includes the same charts for Forest, Cropland, Grassland/Shrubland, Hay/Pasture, and Wetland

Excerpt Src:
Jon Campbell. Sep 2014.
Modeling a Changing American Landscape
USGS Science Features.
contact: Terry Sohl, sohl@usgs.gov

TO DO: CONTACT TERRY SOHL, sohl@usgs.gov, FOR DATA POINTS. MIGHT BE AVAILABLE VIA ONE OF THE (HUGE) EXCEL FILES ON THIS PAGE.

*

The Lincoln Institute has also projected urban land coverage based on a 1990-2000 sample of 120 global cities.

Three projections are made based on three different assumptions about density change over time: (a) no density change; (b) a 1 percent annual density decline; and (c) a 2 percent annual density decline.

US Urban Land Cover Projections in Three Scenarios, 2000-2050
Lincoln-Inst-urban-land-cover-2000-2050

Src:
XLS: “Urban Land Cover Projections for Countries and Regions, 2000-2050
Via:
Shlomo Angel, et al. 2010.
Section 3 – Urban, National, and Regional Data.”
Atlas of Urban Expansion. Lincoln Institute of Land Policy.

*

Demographia.com, maintained by Wendell Cox (a pro-automobile urban planner who favors low-density planning), has aggregated a few urbanizations statistics from the US Census Bureau. Indicators include urban land area (square miles), urban population, urban households, population density, and household density, as well as annual percent change for all of the above. Decadal data points are available from 1950 through 2010.

src:
Demographia. 2012.
Urbanization in the United States from 1945.”
Demographia.com, Wendell Cox Consultancy.
citing:
US Census Bureau

TO DO: EXTRACT/CONFIRM DATA.

Urban Population

Proportions of urban and rural population in the current country or area in per cent of the total population, 1950 to 2050.

UN-proportion-urban-rural-population-1950-2050

Total urban and rural population

UN-total-urban-rural-population-1950-2050

Urban population of the current country by size class of its urban agglomerations in 2014.

UN-US-city-size-class-1950-2030

The light blue area is a residual category, which includes all cities and urban agglomerations with a population of less than 300,000 inhabitants. The size classes correspond to the following legend:

UN-US-city-size-class-legend-1950-2030

src:
United Nations. 2014
Country Profile: United States of America,” in World Urbanization Prospects: The 2014 Revision.
Department of Economic and Social Affairs, Population Division.

TO DO: EXTRACT DATA. ANNUAL DATA AVAILABLE HERE.

*

dark red – 2012
orange – 1990

Juday-population-50-metro-1990-2012

Juday-young-adults-50-metro-1990-2012

Juday-elderly-50-metro-1990-2012

Juday-white-residents-50-metro-1990-2012

Juday-black-residents-50-metro-1990-2012

src:
Luke Juday. Accessed August 19, 2016.
The Changing Shape of America’s Metro Areas.”
University of Virginia. Demographics Research Group.
citing: 1990 Census data and the 2008-2012 American Community Survey

*

Based on the Census Bureau’s data for the 51 major metropolitan areas (those with more than 1 million population).

Cox-metro-pop-growth-2000-2010

Cox-metro-pop-growth-and-distro-2000-2010

src:
Wendell Cox. October 2012.
Flocking Elsewhere: The Downtown Growth Story.”
New Geography.

citing:
US Census Bureau. September 2012.
Patterns of Metropolitan and Micropolitan Population Change: 2000 to 2010.”

Metro Area Jobs

City Observatory analyzed Census Bureau data from the 2002-2007 period to the 2007-2011 period and finds that after a long period of decentralization, economic and demographic indicators are now favoring city centers.

Excerpts:

When we compared the aggregate economic performance of urban cores to the surrounding metro periphery over the four years from 2007 to 2011, we found that city centers—which we define as the area within 3 miles of the center of each region’s central business district—grew jobs at a 0.5 percent annual rate. Over the same period, employment in the surrounding peripheral portion of metropolitan areas declined 0.1 percent per year. When it comes to job growth, city centers are out-performing the surrounding areas in 21 of the 41 metropolitan areas we examined. This “center-led” growth represents the reversal of a historic trend of job de-centralization that has persisted for the past half century.

CityObs-jobs-change-city-centers-peripheries-2002-2011

src:
Joe Cortright. February 2015.
Surging City Center Job Growth.”
City Observatory.

*

Economists at Columbia University and the Getulio Vargas Foundation have also analyzed Census Bureau data from 1980 to 2010, finding that center cities and downtown living are making a come back. Their analysis is based on data from 27 heavily populated U.S. cities, from the CBD to 35 miles away from the center of the cities. Their report includes an interesting graphic on skilled jobs, although these are not the exclusive focus of the report. Elsewhere in this roundup, I’ve also excerpted a graphic for home prices and and education which follow the same trend.

Excerpts:

Skilled Jobs:
Edlund-et-al-skilled-jobs-by-centrality-1980-2010

src:
Lena Edlund, et al. 2015.
Bright Minds, Big Rent: Gentrification and the Rising Returns to Skill.”
National Bureau of Economic Research. NBER Working Paper No. 21729.

via:
Eric Jaffe. November 2015.
Why the Wealthy Have Been Returning to City Centers.”
Atlantic City Lab.

Education

Full-time workers with at least a bachelor’s degree working 40 or 50 hours per week:
Edlund-et-al-women-with-degrees-by-centrality-1980-2010
The data for men show similar trends, with shares rising a bit more toward the periphery.

src:
Lena Edlund, et al. 2015.
Bright Minds, Big Rent: Gentrification and the Rising Returns to Skill.”
National Bureau of Economic Research. NBER Working Paper No. 21729.

via:
Eric Jaffe. November 2015.
Why the Wealthy Have Been Returning to City Centers.”
Atlantic City Lab.

*

dark red – 2012
orange – 1990

Juday-ed-attain-50-metro-1990-2012

red – 1990-2012 change
black – baseline change for whole metro area

Juday-ed-change-50-metro-1990-2012

src:
Luke Juday. Accessed August 19, 2016.
The Changing Shape of America’s Metro Areas.”
University of Virginia. Demographics Research Group.
citing: 1990 Census data and the 2008-2012 American Community Survey

Desirability/Walkability

In City Observatory’s analysis of 2002-2007 and 2007-2011, referred to above, they also came up with a competitiveness calculation which favors city centers.

Excerpt:

We undertook a shift-share analysis that allowed is to separate out the effects of changing industry mix from relative competitiveness. The data make it clear that city centers are more competitive in 2011 than they were in 2007. While city centers had a negative competitive effect in the 2002-07 period, their relative competitiveness for industry has been equal to peripheral locations from 2007-11.

CityObs-competition-city-centers-peripheries-2002-2011

src:
Joe Cortright. February 2015.
Surging City Center Job Growth.”
City Observatory.

*

Researchers at The George Washington University School of Business identified and analyzed 558 walkable urban places (WalkUPs) in the 30 largest metropolitan areas in the United Station, and then ranked the 30 metros according to their current walkable urbanism. This research, published in 2014, is an update to the Brookings Institution’s initial scoring in 2007.

The researchers find that the most walkable urban areas are correlated with substantially higher GDPs per capita and percentages of college graduates over 25 years old. They also find that walkable urban office spaces command a 74% rent-per-sq-foot premium over rents in drivable suburban areas.

They assert that walkable urban development is not limited to center cities, but includes the urbanization of suburbs.

They predict future demand for tens of millions square feet of walkable urban development and hundreds of new WalkUPs.

Walkable urban places are defined as having 1.4 million square feet or more of office space and/or 340,000 square feet or more retail space, as well as a Walk Score value greater than or equal to 70 at the 100 percent location of the WalkUP.

Current Ranking

GWU-walkable-urbanism-rankings-2014

Future Ranking
Note: This ranking refers to the level of expected future walkability, but does not define a particular point in time in the future. Although there are only 6 metro areas currently ranked as highly walkable, 9 are expected to be highly walkable in the future.

GWU-walkable-urbanism-rankings-future

src:
Christopher B. Leinberger & Patrick Lynch. 2014.
Foot Traffic Ahead: Ranking Walkable Urbanism in America’s Largest Metros.”
The George Washington University School of Business.

citing:
CoStar for office and retail data
Walk Score index
Local transit agency web sites
The American Community Survey for educational attainment & population data
U.S. Bureau of Economic Analysis for per capita GDP

Personal Income

dark red – 2012
orange – 1990

Juday-per-cap-income-50-metro-1990-2012

Juday-below-pov-line-50-metro-1990-2012

red – 1990-2012 change
black – baseline change for whole metro area

Juday-income—change-50-metro-1990-2012

src:
Luke Juday. Accessed August 19, 2016.
The Changing Shape of America’s Metro Areas.”
University of Virginia. Demographics Research Group.
citing: 1990 Census data and the 2008-2012 American Community Survey

*

Home Prices:
Edlund-et-al-home-prices-by-centrality-1980-2010

src:
Lena Edlund, et al. 2015.
Bright Minds, Big Rent: Gentrification and the Rising Returns to Skill.”
National Bureau of Economic Research. NBER Working Paper No. 21729.

via:
Eric Jaffe. November 2015.
Why the Wealthy Have Been Returning to City Centers.”
Atlantic City Lab.

Housing & Density

dark red – 2012
orange – 1990

Juday-occupied-housing-50-metro-1990-2012

Juday-percent-rented-50-metro-1990-2012

Juday-pop-density-50-metro-1990-2012

src:
Luke Juday. Accessed August 19, 2016.
The Changing Shape of America’s Metro Areas.”
University of Virginia. Demographics Research Group.
citing: 1990 Census data and the 2008-2012 American Community Survey

Models of Change

The University of Virginia’s Demographics Research Group has analyzed the demographic trends of 66 major US metropolitan areas with regard to their distance from the city center. City Lab reports that, in many cases, the findings help to support Aaron’s Renn’s “new donut” model of cities, although some cities continue to follow other growth models, referred to as “magnetic” cities and “old donut” cities.

Juday-new-donut-1990-2012

In the “old donut” model, growth and wealth are concentrated in the suburbs.

In the “magnetic” model, growth and income are highest in the center and gradually decline all the way to the periphery.

In the “new donut” model, city centers and outer-ring suburbs have the highest performing indicators, but the inner ring suburbs are characterized by decline.

src:
Tanvi Misra. March 2015.
This Chart Tool Shows How City Centers Are Doing Better Than Inner Suburbs.”
Atlantic City Lab.
citing:
Aaron Renn. September 2014.
The New Donut.”

and also citing:
Luke Juday. March 2015.
The Changing Shape of American Cities.”
University of Virginia. Weldon Cooper Center for Public Service.
which cites: 1990 Census data and the 2008-2012 American Community Survey

The University of Virginia also released a charting tool associated with their report. In addition to showing charts for individual cities, it also includes charts for a composite of the 50 largest metropolitan areas.

The charts below (also excerpted elsewhere in this roundup) show the “new donut” model.

dark red – 2012
orange – 1990

Juday-per-cap-income-50-metro-1990-2012

Juday-ed-attain-50-metro-1990-2012

red – 1990-2012 change
black – baseline change for whole metro area

Juday-income—change-50-metro-1990-2012

Juday-ed-change-50-metro-1990-2012

src:
Luke Juday. Accessed August 19, 2016.
The Changing Shape of America’s Metro Areas.”
University of Virginia. Demographics Research Group.

*

A US Census Bureau report from 2012 also shows a “new donut” model of population change for the period 2000-2010, although Wendell Cox argues that the growth in city centers is over-exaggerated. Cox created the following graphics (also excerpted above) based on the Census Bureau’s data for the 51 major metropolitan areas (those with more than 1 million population).

Cox-metro-pop-growth-2000-2010

Cox-metro-pop-growth-and-distro-2000-2010

Cox puts it this way, and it’s true, based on the data: “The one percent flocked to downtown and the 99 percent flocked to outside downtown.” The literal figures are 1.3% and 98.7%.

src:
Wendell Cox. October 2012.
Flocking Elsewhere: The Downtown Growth Story.”
New Geography.

citing:
US Census Bureau. September 2012.
Patterns of Metropolitan and Micropolitan Population Change: 2000 to 2010.”

Other Resources

MIT Center for Advanced Urbanism
CAU’s Twitter feed
“Future of Suburbia” conference program, conference videos

increased mobility for everyone
greater need for proximity
more of the same
more exurbia
more growth at the core
more gentrified neighborhoods with trees and shopping
more dev in the suburbs with skyscrapers and higher density
for a multi-nucleated urban system

Amanda Kolson Hurley. June 6, 2016.
The “Future of Suburbia,” according to MIT.”
Architect.
Somewhat critical review of the MIT Center for Advanced Urbanism conference on suburbs, spring 2016. Lists a few other centers and researchers examining suburbs. Not a lot of data sources though.

Here’s a news article from MIT promoting the conference.

Joel Budd. June 2016.
Healthy, Happy And Hands Free.”
1843 Magazine.

Vision of the future of cities as impacted by driverless cars. Very short.
The elderly, young, and disabled will be more mobile.
Parking lots could be turned into green spaces, or offices or housing.
People might spend less time commuting, or they might commute farther.
Downtowns AND distant villages could both become more appealing.
Suburbs may dwindle.

Reporting:
Atlantic CityLab
Next City



Shopping


Summary

This collection of data includes the following indicators, dates, and sources:

Retail Space
shopping center growth, 1975-2014, Int’l Council of Shopping Centers
number of private retail establishments, 2001-2015, Bureau of Labor Statistics (BLS)
store count by category, 2010/2015/2020, Kantar Retail
store square footage by category, 2010/2015/2020, Kantar Retail
Consumer Spending
indexed personal spending, 1950-2016, Trading Economics
percent personal spending, 2016/2017/2020, Trading Economics
personal expenditures deflated, 1901-2003, BLS
food, clothing, and housing expenditures, 1901-2003, BLS
food expenditures, 1901-2003, BLS
non-necessities expenditures, 1901-2003, BLS
Time Spent Shopping
avg hours per day purchasing consumer goods, 2003-2015, BLS
avg % of people purchasing consumer goods per day, 2003-2015, BLS
avg hours per day for persons so-engaged purchasing consumer goods, 2003-2015, BLS
Online Shopping
retail ecommerce sales as a percent of total US retail sales, 2014-2019, eMarketer
worldwide ecommerce sales growth, 2013-2019, eMarketer
US retail sales as a % of worldwide retail, 2014-2019, eMarketer
US ecommerce sales as a % of total worldwide retail sales, 2014-2019, eMarketer
retail formats % distribution, 2010/2015/2020, Kantar Retail
online share of sales by category, 2009/2014/2020, Kantar Retail
Mall Habits
avg mall visits per month, ~2012, ICSC
avg length of mall visits, ~2012, ICSC
avg monthly spending at malls, 2010/2012, ICSC

Findings

Retail Space
With the U.S. having an estimated 48 square feet of retail space per citizen, the footprint is poised to decline “pretty fast,” Jan Kniffen said.

“On an apples-to-apples basis, we have twice as much per-capita retail space as any other place in the world. The U.K. is second. They’re half of what we are. So, yes, we are the most over-stored place in the world,” he told CNBC’s “Squawk Box.”

In his view, about 400 of America’s 1,100 enclosed malls will fail in the coming years. Of the survivors, about 250 will thrive and the rest will struggle. Likewise, Macy’s probably needs 500 of its roughly 800 existing stores, he said.

src:
Tom DiChristopher. May 12, 2016.
1 in 3 American malls are doomed: Retail consultant Jan Kniffen.
CNBC.

Note: This article, though published a year earlier, takes a completely opposite tone of the one above.
Amanda Kolson Hurley. March 2015.
Shopping Malls Aren’t Actually Dying.
The Atlantic: CityLab.

*

ICSC-shopping-center-growth-1975-2014

Between 2000 and 2008, U.S. shopping center space – gross leasable area – grew by an annual average rate of 2.6% or a net addition of 169 million square feet (sq. ft.) of retail space per year. However, beginning in 2009, the supply increment slowed dramatically to about one-tenth of that pace. In 2013, the addition of new retail supply grew at its slowest pace in more than 40 years. According to Cushman & Wakefield, over the next three years (2014-2016), the addition of new supply will pick up somewhat as 120.5 million sq. ft. are added to U.S. shopping center inventory. This moderated supply growth is a positive sign going forward (see Figure 2).

According to the U.S. Bureau of Labor Statistics, the total number of U.S. private retail establishments grew from 1,023,696 in 2011 to 1,028,242 in 2012 – an increase of 4,546 establishments. Preliminary 2013 figures show a further increase of 7,887 retail establishments over 2012 figures to 1,036,129.

src:
International Council of Shopping Centers. 2014.
Shopping Centers: America’s First and Foremost Marketplace.

citing:
[CoStar]
and BLS

*

The Bureau of Labor Statistics tracks the number of establishments as part of its Workplace Trends tracking. The following chart and data reflect the number of private retail establishments from 2001 through 2015.

BLS-private-retail-establishments-2001-2015-chart

BLS-private-retail-establishments-2001-2015-data

src:
Bureau of Labor Statistics. Accessed August 8, 2016.
Quarterly Census of Employment and Wages
Series Id: ENUUS00020544-45
Area: US Total
Industry: NAICS 44-45 Retail trade
Owner: Private
Type: Number of Establishments
linked via “IAG: Retail Trade – NAICS 44-45

*

Over the next five years, Kantar Retail forecasts that U.S. retail square footage will grow more slowly than the number of stores; in other words, the average store built will be smaller. Conversely, in the previous five years, square footage grew more quickly than stores, resulting in the addition of relatively larger stores (Figure 7).

Kantar-stores-size-2010-2020

As Figure 7 indicates, nearly half of new stores over the next five years will be smaller footprint drug, discounter, and convenience stores. As a result, retailers will need to deliver even greater differentiation and specialization from this growth in available points of commerce. Shrunken versions of larger boxes will not suffice. Shoppers will demand that small formats earn their reason for being. Going forward, we expect greater efforts toward differentiation in the small-box space, with in-store marketing (versus simply merchandising) gaining traction.

src:
Kantar Retail. 2015.
REinvent Format: Adapting to 21st-Century Retailing
Pp.9, 15
Press contact: Victoria Bradshaw, victoria.bradshaw@kantarretail.com

EMAILED KANTAR RETAIL 8/9/16 TO INQUIRE ABOUT ADDITIONAL DATA POINTS (FOR THIS AND ALL OTHER KANTAR CHARTS MENTIONED IN THIS RESEARCH ROUNDUP).

Consumer Spending

Trading Economics make a short, five-year forecast (currently, to 2020) of various US consumption indicators, based on US Bureau of economic Analysis (BEA) data going back to 1969.

Each indicator has its own page summarizing current data and the forecast to 2020, along with a chart which can be expanded to show data back to ~1950. Each indicator’s page also includes a summary of the forecasts for related indicators. For example, the data on the “United States Personal Spending Forecast 2016-2020” page.

TradingEcon-personal-spending-1950-2016

TradingEcon-personal-spending-2016-2020

TradingEcon-consump-indicators-2016-2020
(Note: No units are given in this summary. Generally, the much larger numbers are billions of USD, and the smaller numbers are percentages or index values.)

Trading Economics forecasts are frequently updated (several times per week).

src:
Trading Economics. Accessed August 6, 2016.
United States Personal Spending: Forecast 2016-2020.

*

The Bureau of Labor Statistics published a 100-year compilation of national consumer spending data from 1901 through 2003.

Excerpts:

While no two families spend money in exactly the same manner, indicators suggest that families allocate their expenditures with some regularity and predictability. Consumption patterns indicate the priorities that families place on the satisfaction of the following needs: Food, clothing, housing, heating and energy, health, transportation, furniture and appliances, communication, culture and education, and entertainment.

In this report, economic and demographic profiles of U.S. households in the aggregate, as well as profiles of households in New York City and Boston, are presented. New York City and Boston are included because they are two of the country’s oldest urban areas. The report examines how, over a 100-year period, standards of living have changed as the U.S. economy has progressed from one based on domestic agriculture to one geared toward providing global services.

The report provides an in-depth assessment of U.S. households at nine points in time, beginning with 1901 and ending with 2002–03. The text highlights changes in family structure and economic conditions and examines factors that have altered and influenced both society and households. (P.1)

During the 100-year period, household expenditure patterns also demonstrated great variability. … In real dollars, calculated with 1901 as the base, expenditures also demonstrated a notable increase. In 1901, as noted, the average U.S. family had $769 in expenditures. By 2002–03, that family’s expenditures would have risen to $1,848, a 2.4-fold increase. (Chart 40, pp.66-67)

BLS-expenditures-deflated-1901-2003

The material well-being of families in the United States improved dramatically, as demonstrated by the change over time in the percentage of expenditures allocated for food, clothing, and housing. In 1901, the average U.S. family devoted 79.8 percent of its spending to these necessities. By 2002–03, allocations on necessities had been reduced substantially, for U.S. families to 50.1 percent of spending. (Chart 41, pp.66, 68)

BLS-spending-food-clothing-housing-1901-2003

The continued and significant decline over the century in the share of expenditures allocated for food also reflected improved living standards. In 1901, U.S. households allotted 42.5 percent of their expenditures for food; by 2002–03, food’s share of spending had dropped to just 13.2 percent. (Chart 41, p.68-69)

BLS-spending-food-1901-2003

In 2002–03, the average U.S. family could allocate 49.9 percent ($20,333) of total expenditures for a variety of discretionary consumer goods and services, while the average family in 1901 could allocate only 20.2 percent, or $155, for discretionary spending [eg: family car, reading and education, personal care products, recreation and entertainment, healthcare, alcohol, charitable giving, etc]. (Chart 43, p.70)

BLS-spending-non-necessities-1901-2003

src:
US Bureau of Labor Statistics. May 2006.
100 Years of U.S. Consumer Spending: Data for the Nation, New York City, and Boston.

Time Spent Shopping

The American Time Use Survey has been conducted annually since 2003. Among many other indicators, it tracks the amount of time Americans age 15 and older spend purchasing goods and services.


Google Spreadsheet

src:
Bureau of Labor Statistics. 2003-2015.
American Time Use Survey. ATUS Tables.
“Table A-1. Time spent in detailed primary activities and percent of the civilian population engaging in each activity, averages per day by sex, annual averages.” All years, 2003-2015

NOTE: The “Purchasing goods and services” section of the source table is further itemized. The full itemization is as follows:

Purchasing goods and services
>Consumer goods purchases
>>Grocery shopping
>Professional and personal care services
>>Financial services and banking
>>Medical and care services
>>Personal care services
>Household services
>>Home maintenance, repair, decoration, and construction (not done by self)
>>Vehicle maintenance and repair services (not done by self)
>Government services
>Travel related to purchasing goods and services

The itemization follows from greatest to smallest use of time, EXCEPT for travel, which is the second largest use of time. Grocery shopping generally accounts for about a quarter of the broader consumer goods category, and this is true over the full time period with a slight increase over time (groceries generally hold steady, but the broader category total slowly decreases over time).

Online Shopping

Retail Ecommerce Sales as a Percent of Total Retail Sales in the US, 2014-2019
2014 — 6.4%
2015 — 7.1%
2016 — 7.8%
2017 — 8.4%
2018 — 9.1%
2019 — 9.8%

Retail Ecommerce Sales Worldwide, 2014-2019
Showing total ecommerce retail sales, percent change, and percent of total retail sales.

Emarketer-online-retail-2014-2019

Retail ecommerce sales in North America will rise 14.4% this year to reach $367.44 billion, largely due to increased spending from existing digital shoppers. The region will see consistent double-digit growth through 2019, fueled by expanding online categories, increased average order values and growing mcommerce sales.

Total Retail Sales Share Worldwide, by Region, 2014-2019
Emarketer-total-retail-share-worldwide-2014-2019

Total Ecommerce Sales as a Percent of Total Retail Worldwide, by Region, 2014-2019
Emarketer-ecommerce-share-worldwide-2014-2019

src:
eMarketer. 2015
Worldwide Retail Ecommerce Sales: Emarketer’s Updated Estimates And Forecast Through 2019.”

*

eMarketer’s previous forecasts

US online retail spending
2015 — 7.1%
2016 — 7.7%
2017 — 8.3%
2018 — 8.9%

Emarketer-online-sales-2013-2018

src:
eMarketer. December 2014.
Retail Sales Worldwide Will Top $22 Trillion This Year.”

*

Figure 3: Percent Sales Importance of Retail Formats – 2010 to 2020 [US]

PWC-retail-formats-2010-2020

Non-store retail, driven by online today, and likely mobile and tablet commerce in 2020, is projected to be the fastest growing retail channel in the future. Conversely, Supermarket, Drug and especially Mass channel retailers are likely to face a tough growth environment in the coming 2015-2020 period—even if job and income growth surmount global pressures. Likewise, Supercenters, as a percent of total US sales, will decrease to 12.7% from 14.4% today.

src:
PwC/Kantar Retail. 2012.
Retailing 2020: Winning In A Polarized World.
P.9

*

Kantar-online-sales-shares-by-category-2009-2020

src:
Kantar Retail. 2015.
REinvent Format: Adapting to 21st-Century Retailing
Figure 22: U.S. Online Shares of Sales by Category
P. 21.

Mall Habits

CC’s Note: I’m trying to flesh these single-year data points out. Hoping to get more data from ICSC on the items they’re responsible for below.

*

JCDecaux is an international, outdoor advertising company. They have collected and published the following statistics on mall shopping (most stats seem to be from 2012).

75% of all Americans visit a mall at least once a month. [2]

On average, shoppers visit 3.4 times per month and stay
1 hour and 24 minutes. [1]

Average Time Spent Shopping by Age [1]
Ages 14-17: . . . . . . . . 95 minutes
Ages 18-24: . . . . . . . . 81 minutes
Ages 25-34: . . . . . . . . 79 minutes
Ages 35-44: . . . . . . . . 86 minutes
Ages 45-54: . . . . . . . . 88 minutes
Ages 55-64: . . . . . . . . 87 minutes
Ages 65+: . . . . . . . . . 89 minutes

Average Money Spent Per Visit [4]
Specialty Stores — $109.91
Anchor Stores — $92.80

Monthly Shopping Frequency by Age [4]
Ages 12-17: . . . . . . . . 3.7 times
Ages 18-24: . . . . . . . . 3.2 times
Ages 25-34: . . . . . . . . 3.0 times
Ages 35-44: . . . . . . . . 2.9 times
Ages 45-54: . . . . . . . . 2.9 times
Ages 55-64: . . . . . . . . 3.0 times
Ages 65+: . . . . . . . . . 3.6 times

Shopper spending at malls per month increased from $316.80
in 2010 to $330.82 in 2012. [1]

src:
JCDecaux. Accessed August 8, 2016.
The Mall Phenomenon.”

citing
1 – ICSC (International Council of Shopping Centers)
PR: Noelle Malone, nmalone@icsc.org
EMAILED 8/8/16 – GOT A REPLY – EXPECTING UPDATED DATA SOON.
2 – Journal of Shopping Center Research
1994-2007 full text archives freely available, but no search

http://jrdelisle.com/JSCR/

Couldn’t track the source
3 – Glimcher Reality Trust
4 – Alexander Babbage, Inc.

Predictions/Scenarios

2030: Half of America’s shopping malls have closed

“For much of the 20th century, shopping malls were an intrinsic part of American culture. At their peak in the mid-1990s, the country was building 140 new shopping malls every year. But from the early 2000s onward, underperforming and vacant malls – known as “greyfield” and “dead mall” estates – became an emerging problem. In 2007, a year before the Great Recession, no new malls were built in America, for the first time in half a century. Only a single new mall, City Creek Center Mall in Salt Lake City, was built between 2007 and 2012. The economic health of surviving malls continued to decline, with high vacancy rates creating an oversupply glut.*

A number of changes had occurred in shopping and driving habits. More and more people were living in cities, with fewer interested in driving and people in general spending less than before. Tech-savvy Millennials (also known as Generation Y), in particular, had embraced new ways of living. The Internet had made it far easier to identify the cheapest products and to order items without having to be physically there in person. In earlier decades, this had mostly affected digital goods such as music, books and videos, which could be obtained in a matter of seconds – but even clothing was eventually possible to download, thanks to the widespread proliferation of 3D printing in the home.* Many of these abandoned malls are now being converted to other uses, such as housing.”

src:
FutureTimeline.net. Accessed August 1, 2016.
Half of America’s shopping malls have closed.”

*

The Future Real Estate Shopping Experience [undated scenario]

Highlights:

No real estate agents.

VR-based anytime tours that let you see what your stuff would look like in the new place, try different landscaping and remodels.

A machine-learning algorithm monitors your experience to learn your likes and dislikes, recommending other homes to visit.

An AI helps you to write your bid and contact your bank to make an offer on the spot.

src:
Peter Diamandis. March 2015.
Disrupting Real Estate.”

*

Global forces affecting the consumer sector in 2030

Exhibit 1
Five dominant forces — and an underlying set of trends — will drive change in the consumer landscape over the next 15 years.

McKinsey-five-forces-consumption-2030

Exhibit 2
Trends that could most affect consumer companies.

McKinsey-five-forces-impact-consumption-2030

src:
Richard Benson-Armer, Steve Noble, and Alexander Thiel. December 2015.
The Consumer Sector In 2030: Trends And Questions To Consider.”
McKinsey & Company.

*

PwC conducts an annual consumer survey, “Total Retail.” The results of the survey published in 2015

PwC. February 2015.
Physical Store Beats Online as Preferred Purchase Destination for U.S. Shoppers, According to PwC.”

*

Harvard Business Review presented a near-future shopping scenario in the opening of it’s 2011 article on the future of shopping. The article predicted that the scenario would arrive within a handful of years (not quite).

The article closes with some suggestions for how retail stores can use digital technologies innovatively to meet emerging consumer desires.

src:
Darrell K. Rigby. December 2011.
The Future of Shopping.”
Harvard Business Review.

Other Possible Sources/Contacts

Maureen McAvey
Maureen McAvey is the Bucksbaum Family Chair for Retail at the Urban Land Institute (ULI) in Washington, D.C. She concentrates on urban retail and has led several special projects around demographics and future urban development. She is also a senior staff adviser to ULI’s Building Healthy Places Initiative. [Src]
Email: Maureen.McAvey@uli.org

AT Kearney
Conducts surveys of consumer shopping preferences and behaviors.
EG: “The Omnichancel Consumer Preferences Study

Tags: , , , ,

Posted by Claudia Lamar on September 7, 2016 at 9:55 pm | comment count



Religion


Summary

This collection of data includes the following indicators, dates, and sources:

religious affiliation, 2010-2050, 1948-2015, 1972-2014, Pew, Gallup, GSS
no religious preference, 1972-2014, GSS
traditional/secular-rational index, 2010-2030, Pardee
church attendance, 1992-2015, 1990-2012, Gallup, GSS
church buildings/congregations, 1990-2014, 1992-2012 select years, 1952v2010, 1980-2010 (decadal), Dodge, US EIA, ASARB
median age of practitioners, 2010-2050, Pew
new religions, 1990, 2001, 2008, ARIS
belief in life after death, 1973-2014, GSS
spouses religious preference, 1973-2014, GSS
confidence in organized religion, 1973-2014, GSS
attidude about bible prayer in public schools, 1974-2014, GSS
frequency of prayer, 1983-2014, GSS
strength of religious affiliation, 1974-2014, GSS
degree of fundamentalism, 1972-2014, GSS
religion in which raised, 1973-2014, GSS

Findings

Affiliation

In the United States, the [religiously] unaffiliated are projected to grow from an estimated 16% of the total population (including children) in 2010 to 26% in 2050. (But note: atheists, agnostics and other people who do not affiliate with any religion will make up a declining share of the world’s total population.)

US Christians will decline from more than three-quarters of the population in 2010 to two-thirds in 2050, and Judaism will no longer be the largest non-Christian religion. Muslims will be more numerous in the U.S. than people who identify as Jewish on the basis of religion.

Pew-religious-distro-2010-2050

NOTE: Decadal data from 2010 to 2050 are available here.

src:
Pew Research Center. April 2, 2015.
The Future of World Religions: Population Growth Projections, 2010-2050.
Overview

Pew-religious-switching-2010-2050

src:
Pew Research Center. April 2, 2015.
Chapter 1: Main Factors Driving Population Growth — Religious Switching.

Pew-relig-comp-switching-2050

src:
Pew Research Center. April 2015.
The Future of World Religions: Population Growth Projections, 2010-2050.
p.161

*

Since 1948, Gallup has polled Americans on their religious affiliation. The question wording has changed a bit over time, but the questions have always asked explicitly about Protestant, Roman Catholic, and Jewish affiliation. Starting in 2000, the poll added Mormon and Muslim affiliation. Values for responses of “Other” “None” and “No Answer” have also been recorded since 1948.

Gallup-relig-affiliation-1948-2015-data

Gallup-relig-affiliation-1948-2015-chart

src:
Gallup. Accessed July 26, 2016.
IN DEPTH: TOPICS A TO Z — Religion.

chart via:
Statista. 2016.
Self-described religious identification of Americans from 1948-2015.
citing Gallup data (above)

*

What is your religious preference? Is it Protestant, Catholic, Jewish, some other religion, or no religion? 1972-2014

src:
Tom W. Smith, et al. 1972-2014.
Rs religious preference.
General Social Surveys. NORC at the University of Chicago.
contact: Eric Young, External Affairs Manager, young-eric@norc.org

TO DO: EXTRACT DATA FROM GSS. CLARIFY THE FIGURES ON THE GSS WEBSITE.

*

Figure 1. No Religious Preference (%) by Year, 1972-2014
GSS-no-relig-pref-1972-2014

src:
Michael Hout, Tom W. Smith. March 2015.
Fewer Americans Affiliate with Organized Religions, Belief and Practice Unchanged.
General Social Surveys. NORC at the University of Chicago.

*

The Pardee Center (University of Denver) maintains a forecast database called “International Futures.” The “Social” subset includes an index for “Traditional/Secular-Rational” outlook for the US (scroll to the bottom of the list). Annual index values are available for 2010-2030.

src:
International Futures. Accessed July 26, 2016.
Basic Report – USA, Working File.
The Pardee Center. University of Denver.

Note: This indicator refers to the cultural dimensions of “traditional values” and “secular-traditional values” defined by the World Values Survey, here.

TO DO: EXTRACT DATA.

Attendance

Gallup-church-attendance-weekly-1992-2015

Gallup-church-attendance-frequncy-1992-2015

src:
Gallup. Accessed July 26, 2016.
IN DEPTH: TOPICS A TO Z — Religion.

*

GSS-church-attendance-frequency-1990-2012
src:
Ben Leubsdorf. December 2014.
“Decline in Church-Building Reflects Changed Tastes and Times.”
Wall Street Journal.
citing:
General Social Survey (GSS)

This chart refers to The General Social Survey question, “How often do you attend religious services?” The variable name is “attend.” GSS data for this question/variable available 1972-2014, but the data on their website is given in absolute numbers.

src:
Tom W. Smith, et al. 1972-2014.
How often r attends religious services.
General Social Surveys. NORC at the University of Chicago.
contact: Eric Young, External Affairs Manager, young-eric@norc.org

TO DO: EXTRACT DATA FROM GSS. CLARIFY THE FIGURES ON THE GSS WEBSITE. ASK ABOUT CONVERTING TO PERCENTAGE OF US POPULATION, AS THE FIGURES WERE QUOTED BY THE WSJ.

Church Buildings

Construction of religious buildings in the U.S. has fallen to the lowest level at any time since private records began in 1967. Religious groups will build an estimated 10.3 million square feet this year, down 6% from 2013 and 80% since construction peaked in 2002, according to Dodge Data & Analytics. In terms of dollars, spending on houses of worship totaled $3.15 billion last year, down by half from a decade earlier, according to Commerce Department figures.

There are signs the long decline in church-building may have hit bottom. While construction is down this year, the pace of spending has inched up since the end of 2013, the Commerce Department said. Two private firms, FMI and Dodge Data & Analytics, both expect spending to rise modestly in 2015.

But a return to the building boom of a dozen years ago—in 2002, religious groups built 51.9 million square feet, Dodge says—faces headwinds. Dodge said in its latest report that “the level of activity will remain extremely low by historical standards.”

Behind the decline is a confluence of trends: a drop in formal religious participation, changing donation habits, a shift away from the construction of massive megachurches and, more broadly, a growing taste for alternatives to the traditional house of worship.

Dodge-church-construction-1990-2014

src:
Ben Leubsdorf. December 2014.
“Decline in Church-Building Reflects Changed Tastes and Times.”
Wall Street Journal.
citing:
Dodge Data & Analytics

*

A decline in church membership and religious service attendance has weighed heavily on religious building construction over the past 13 years. Things didn’t get much better in 2015. Starts slid 5 percent (9.3 msf), though dollars grew 5 percent ($1.8 billion). A 5.6 percent rise in donations ($482 billion) has helped this sector. In 2016, expect a 3 percent gain (9.6 msf) and 5 percent added dollar value ($1.9 billion).

src:
Jeff Gavin. January 2016.
2016 Construction Outlook.
Electrical Contractor.

*

Religious Buildings, 1992, 1995, 1999, 2003, 2012.


Google Spreadsheet

srcs:

US US Energy Information Administration.
“Commercial Buildings Energy Consumption Surveys.”
Various years, stated below.

2012 CBECS Survey Data.
Table B2. Summary table: total and medians of floorspace, number of workers, and hours of operation, 2012.

“2003 CBECS Survey Data.”
Table B2. Summary Table: Totals and Medians of Floorspace, Number of Workers, and Hours of Operation for Non-Mall Buildings, 2003.

https://www.eia.gov/consumption/commercial/data/2003/pdf/b2.pdf

1999 CBECS Survey Data.
Table B2. Summary Table: Totals and Medians of Floorspace, Number of Workers, Hours of Operation, and Age of Building

1995 CBECS Survey Data.
Table 2. Summary Table: Totals and Medians of Floorspace, Number of Workers, Hours of Operation, and Age of Building, 1995

1992 CBECS Survey Data.
Table A1. Summary Table of Square Feet, Hours of Operation and Age of Building, 1992

NOTE: Prior to 1992, religious buildings were grouped (unitemized) into a larger category called “Assembly,” which also included entertainment buildings (eg: museums, concert halls), recreational facilities (eg: gyms, indoor pools), and social/public/civic assembly buildings (eg: auditoriums, convention halls).

*

The Association of Statisticians of American Religious Bodies (ASARB) collects data on religious congregations going back to 1952.

An excerpt from their 2010 Census:

ASARB-religious-census-overview-1952v2010

Congregations: Congregations may be churches, mosques, temples, or other meeting places. A congregation may generally be defined as a group of people who meet regularly (typically weekly or monthly) at a pre-announced time and location.

src:
Association of Statisticians of American Religious Bodies (ASARB). May 2012.
U.S. Religion Census 2010: Summary Findings.
Congregations defintion

Congregations from previous ASARB censuses are made available via the Association of Religion Data Archives (ARDA).

Year — Congregations
2010 — 344,894
2000 — 268,254
1990 — 255,173
1980 — 231,708

Totals by individual religious group are available at the ARDA website.

NOTE: Estimates of Muslim, Hindu, and Buddhist congregations only included in 2000 and 2010 census totals.

src:
Association of Religion Data Archives (ARDA). Accessed July 27, 2016.
U.S. Membership Report.

Age of Adherents

The following figure contains GLOBAL data:

Pew-age-disto-by-relig-2010v2050

The following figure contains North American data.

Pew-age-breakdown-2010

src:
Pew Research Center. April 2015.
The Future of World Religions: Population Growth Projections, 2010-2050.
Pp.40, 160.
contact:
Conrad Hackett, Demographer, chackett@pewresearch.org
Katherine Ritchey, Communications Manager


Google Spreadsheet

src:
Pew-Templeton Global Religious Futures Project. 2015.
“Median Age.”

New Religions

The Pew “Future of World Religions” report referenced above classifies new/emerging religions under their “Other Religions” category. The end of the report (p.124) includes an overview of the religions included in this category, “Spotlight on Other Religions.” Among the handful of faiths that are called out in this section, Wiccans are the only new group called out in the US specifically, and the report explains that reliable estimates of their numbers are not available. Other new groups called out in the report, but not described with any geographic predominance, are Cao Dai, I-Kuan Tao, Mandaeism, the Rastafari movement, the Rātana movement, Scientology and Yazidism.

referring to:
Pew Research Center. April 2015.
The Future of World Religions: Population Growth Projections, 2010-2050.
P. 124-125.

*

The US Census does not ask questions about religious affiliation, but some of its reports have included data collected by the American Religious Identification Survey (ARIS). ARIS has been conducted in 1990, 2001, and 2008.

The ARIS 2008 report includes a “New Religious Movements and Other Religions” category, which includes Scientology, New Age, Eckankar, Spiritualist, Unitarian-Universalist, Deist, Wiccan, Pagan, Druid, Indian Religion, Santeria, Rastafarian.

Excerpts from the 2008 report:

“The category of the New Religious Movements and Other Religions is a mixed one and includes many groups often referred to as cults. The 2008 survey revealed marked increase in preferences for personalized and idiosyncratic responses as well as increases in the Neo-Pagan groups.” p.7

“The 2008 findings confirm the conclusions we came to in our earlier studies that Americans are slowly becoming less Christian and that in recent decades the challenge to Christianity in American society does not come from other world religions or new religious movements (NRMs) but rather from a rejection of all organized religions.” p.3

“Divorce appears to be widespread and no religious tradition is immune, nor are Nones the most likely to be currently divorced. Catholics’ divorce rate is close to the national average. Divorce rates are lowest among Mormons and Jews, traditions known for the emphasis they place on married life and the family. Divorced and separated persons, on the other hand, are most common in the New Religion Movements, other minority religions, and the Pentecostal/ Charismatic tradition.” p.13

ARIS2008-other-religions-1990-2001-2008
p.3

src:
Barry A. Kosmin, Ariela Keysar. March 2009.
American Religious Identification Survey (ARIS 2008).
Trinity College.

*

Although their list does not indicate rates of growth, ProCon.org published a list of US religions and denominations which includes the date founded, total members, and members as a percentage of the total adult “religious” population (based on 2001 data). ProCon.org aggregated its list largely from ARIS, referenced above, but also supplemented from a few other reputable sources. The list is sorted by membership size as of 2001.

The list includes a total of 313 religions and denominations. The overall group is broken down into 28 of the largest groups, with expanded sections on 35 Christian denominations, 124 “Other” religions, and 127 “New Age” religions.

Here are excerpts from the list, focusing on new or undated groups:

Name — Founding Date — Members (percent)
Other unclassified — N/A — 386,000 (.231%)
Neo-Paganism — Unknown — 140,000 (.084%)
New Age — 1960s — 68,000 (.041%)
Scientology — 1953 — 55,000 (.033%)
Humanism — Unknown — 49,000 (.029%)
Eckankar — 1965 — 26,000 (.016%)
Cao Daism — 1926 — 25,000 (.015%)
Rastafarianism — 1930s — 11,000 (.007%)

src:
ProCon.org. Accessed August 1, 2016.
“All Religions and Denominations in the US.”

Source note: ProCon.org is a widely cited non-profit publishing non-partisan research on controversial issues. [Wikipedia — ProCon.org — Reception]

Other Indicators

TO DO: DATA NEEDS TO BE EXTRACTED FROM THE FOLLOWING

Belief in Life After Death, 1973-2014, GSS

Spouses religious preference, 1973-2014, GSS

Confidence in organized religion, 1973-2014, GSS

Bible prayer in public schools, 1974-2014, GSS

How often does r pray, 1983-2014, GSS

Strength of affiliation, 1974-2014, GSS

How fundamentalist is r currently, 1972-2014, GSS

Religion in which raised, 1973-2014, GSS

Tags: , , ,

Posted by Claudia Lamar on August 3, 2016 at 10:56 pm | comment count



Education


Summary

This collection of data includes the following indicators, dates, and sources:
teachers: preschool-postsecondary, special ed, career, 2014/2024, BLS
teachers: elementary & secondary, public and private schools, 1955-2023, BLS & NCES
teachers: public charter schools, 1999-2012, NCES
pupil/teacher ratios: elementary & secondary, 1955-2023, NCES
enrollment: elementary & secondary, public & private, 1955-2023, NCES
enrollment: public charter schools, 1999-2012 (NCES)
enrollment: homeschooled K-12 students, 1999/2003/2007/2012, NCES
enrollment: postsecondary and postbac, public and private, 1947-2025, NCES
ed attainment: high school graduates, public and private, 1869-2024, NCES
ed attainment: GED test-passers (and takers), 1971-2013, NCES
ed attainment: degrees conferred, 1869-2024, NCES
ed attainment: % high school dropouts, 1960-2014, NCES
school numbers: elementary public & private, 1980-2013 & 1869-2013, NCES
school numbers: secondary public & private, 1980-2013 & 1869-2013, NCES
school numbers: public charter, 1980-2013, NCES
school numbers: colleges public, private & community, 1980-2013, NCES
online courses/MOOCs, 2002-2014, Babsen & NCES
presence of arts in education, 1999/2009, NCES

Findings

Teachers and Ratios

BLS Occupational Outlook 10-year forecasts for teachers

Number and Change in Teaching Jobs
Type 2014 total increase by 2024 % change
Preschool 441,000 +29,600 7%, as fast as average
K & Elementary 1,517,4000 +87,800 6%, as fast as average
Middle School 627,500 +36,800 6%, as fast as average
High School 961,600 +55,900 6%, as fast as average
Special Ed. 450,700 +28,100 6%, as fast as average
HS Equiv. 77,500 +5,500 7%, as fast as average
Postsecondary 1,313,000 +177,000 13%, faster than average
Career & Tech 231,800 +10,200 4%, slower than average

Src:
Bureau of Labor Statistics. Accessed July 18, 2016.
Occupational Outlook Handbook. US Department of Labor.
Preschool Teachers
Kindergarten and Elementary School Teachers
Middle School Teachers
High School Teachers
Special Education Teachers
Adult Literacy and High School Equivalency Diploma Teachers
Postsecondary Teachers
Career and Technical Education Teachers

*

Since 1991, The National Center for Education Statistics has annually issued a report of ~10-year forecasts called “Projections of Education Statistics.” Here are excerpts from the most recent set of forecasts.

Figure 6: Actual and projected numbers for elementary and secondary teachers, by control of school: Fall 1998 through fall 2023 (p.10)
NCES-elementary-secondary-teachers-by-school-type-1998-2023

The total number of elementary and secondary teachers:
* increased 9 percent between 1998 and 2011, a period of 13 years; and
* is projected to increase 8 percent between 2011 and 2023, a period of 12 years.

The number of teachers in public elementary and secondary schools:
* increased 10 percent between 1998 and 2011; and
* is projected to increase 10 percent between 2011 and 2023.

The number of teachers in private elementary and secondary schools:
* was 5 percent higher in 2011 than in 1998; and
* is projected to be 3 percent lower in 2023 than in 2011.

Figure 7: Actual and projected numbers for the pupil/teacher ratios in elementary and secondary schools, by control of school: Fall 1998 through fall 2023 (p.11)
NCES-elementary-secondary-pupil-teacher-ratios-by-school-type-1998-2023

Table 8: Public and private elementary and secondary teachers, enrollment, pupil/teacher ratios, and new teacher hires: Selected years, fall 1955 through fall 2023 (p.48).

TO DO: EXTRACT DATA FROM THIS TABLE.

src:
National Center for Education Statistics. April 2016.
Projections of Education Statistics to 2023.
contact: William J. Hussar, William.Hussar@ed.gov

Previous projections are available here.

Enrollment

Figure 1: Actual and projected numbers for enrollment in elementary and secondary schools, by control of school: Fall 1998 through fall 2023. (p.5)
NCES-elementary-secondary-enrollment-by-school-type-1998-2023

Enrollment in public elementary and secondary schools:
* increased 6 percent between 1998 and 2011; and
* is projected to increase 5 percent between 2011 and 2023.

Enrollment in private elementary and secondary schools:
* decreased 12 percent between 1998 and 2011; and
* is projected to be 7 percent lower in 2023 than in 2011.

Table 1: Enrollment in educational institutions, by level and control of institution: Selected years, 1869–70 through fall 2023 (p.35)

TO DO: EXTRACT DATA FROM THIS TABLE.
NOTE: THIS DATA (THROUGH 2025) ALSO APPEARS TO BE IN AN [HTML TABLE WITH AN EXCEL DOWNLOAD OPTION]

Figure 16: Actual and projected numbers for total enrollment in all postsecondary
degree-granting institutions: Fall 1998 through fall 2023 (p.24)
NCES-postsecondary-enrollment-1998-2023

Total enrollment in postsecondary degree-granting institutions:
* increased 42 percent from 1998 to 2012, a period of 14 years; and
* is projected to increase 15 percent, to 24 million, from 2012 to 2023, a period of 11 years.

TO DO: EXTRACT DATA FROM TABLE 13 (data avail 1947-2023) (P. 54-55).

Figure 20: Actual and projected numbers for enrollment in all postsecondary degree-granting institutions, by level of degree: Fall 1998 through fall 2023 (p.26)
NCES-postsecondary-enrollment-by-degree-type-1998-2023

Enrollment of undergraduate students in postsecondary degree-granting institutions:
* increased 43 percent between 1998 and 2012; and
* is projected to increase 14 percent between 2012 and 2023.

Enrollment of postbaccalaureate students in postsecondary degree-granting institutions:
* increased 41 percent between 1998 and 2012; and
* is projected to increase 25 percent between 2012 and 2023.

TO DO: EXTRACT DATA FROM TABLES 16 AND 17 (data avail 1967-2023) (P.60-62).

Figure 22: Actual and projected numbers for enrollment in all postsecondary degree-granting institutions, by control of institution: Fall 1998 through fall 2023 (p.27).
NCES-postsecondary-enrollment-by-school-type-1998-2023

Enrollment in public postsecondary degree-granting institutions:
* increased 34 percent between 1998 and 2012; and
* is projected to increase 15 percent between 2012 and 2023.

Enrollment in private postsecondary degree-granting institutions:
* increased 71 percent between 1998 and 2012; and
* is projected to increase 16 percent between 2012 and 2023.

[Data back to 1947 avail in Table 13.]

src:
National Center for Education Statistics. April 2016.
Projections of Education Statistics to 2023.
contact: William J. Hussar, William.Hussar@ed.gov

*

Table 216.30: Number and percentage distribution of public elementary and secondary students and schools, by traditional or charter school status and selected characteristics: Selected years, 1999-2000 through 2013-14

TO DO: EXTRACT DATA FROM THIS TABLE

src:
National Center for Education Statistics. Accessed July 18, 2016.
Digest of Education Statistics: 2014.
Table 216.30
AND
Digest of Education Statistics: 2015
Table 216.30

*

Table 206.10: Number and percentage of homeschooled students ages 5 through 17 with a grade equivalent of kindergarten through 12th grade, by selected child, parent, and household characteristics: 2003, 2007, and 2012

TO DO: EXTRACT DATA FROM THIS TABLE

src:
National Center for Education Statistics. Accessed July 18, 2016.
Digest of Education Statistics: 2014.
Table 206.10

This NCES article gives a figure for homeschooled students in 1999 having been 0.9 million (1.7%).

Educational attainment

Table 9: High school graduates, by sex and control of school: Selected years, 1869–70 through 2023–24 (p.49).

TO DO: EXTRACT DATA FROM THIS TABLE.

Table 21: Degrees conferred by degree-granting postsecondary institutions, by level of degree and sex of student: Selected years, 1869–70 through 2023–24

TO DO: EXTRACT DATA FROM THIS TABLE (P.66).

src:
National Center for Education Statistics. April 2016.
Projections of Education Statistics to 2023.
contact: William J. Hussar, William.Hussar@ed.gov

*

Table 219.60: Number of people taking the general educational development (GED) test and percentage distribution of those who passed, by age group: 1971 through 2013

TO DO: EXTRACT DATA FROM THIS TABLE.

src:
National Center for Education Statistics. Accessed July 18, 2016.
Digest of Education Statistics: 2014.
Table 219.60.

*

Table 219.70: Percentage of high school dropouts among persons 16 to 24 years old (status dropout rate), by sex and race/ethnicity: Selected years, 1960 through 2014

TO DO: EXTRACT DATA FROM THIS TABLE.

src:
National Center for Education Statistics. Accessed July 18, 2016.
Digest of Education Statistics: 2015.
Table 219.70.

Number of Schools

Table 105.50: Number of educational institutions, by level and control of institution: Selected years, 1980-81 through 2013-14

Includes: elementary, secondary (and combined), and postsecondary schools

TO DO: EXTRACT DATA FROM THIS TABLE.

Note: Data for 1980-2000 is decadal, data for 2003-2013 is annual.

src:
National Center for Education Statistics. Accessed July 18, 2016.
Digest of Education Statistics: 2015.
Table 105.50: Number of educational institutions, by level and control of institution: Selected years, 1980-81 through 2013-14.

Data for 2001 and 2002 are available from NCES here.

*

Table 214.10: Number of public school districts and public and private elementary and secondary schools: Selected years, 1869-70 through 2013-14

TO DO: EXTRACT DATA FROM THIS TABLE.

src:
National Center for Education Statistics. Accessed July 18, 2016.
Digest of Education Statistics: 2015.
Table 214.10

*

EMAILED WILLIAM HUSSAR 7/19/16 TO INQUIRE ABOUT PROJECTIONS FOR NUMBER OF SCHOOLS.
UPDATE 7/20: HUSSAR CONFIRMS THAT NCES DOES NOT PRODUCE A PROJECTION FOR THIS, AND IS UNAWARE OF ANY OTHER SOURCE THAT DOES.

Online Courses

Total and Online Enrollment in Degree-granting Postsecondary Institutions – Fall 2002 through Fall 2011
Babsen-total-and-online-postsecondary-enrollment-2002-2011-data

Babsen-total-and-online-postsecondary-enrollment-2002-2011-graph

Percent of Postsecondary Institutions With Some Form Of Online Offering – 2002 and 2012
Babsen-pcnt-postsecondaries-offering-online-courses-2002v2012

src:
Babson Survey Research Group. January 2013.
Changing Course: Ten Years of Tracking Online Education in the United States
contact:
I. Elaine Allen, Jeff Seaman
bsrg@babson.edu

*

Starting in 2014, Babsen started using enrollment data from NCES’s Integrated Postsecondary Education Data System (IPEDS) in its reports. IPEDS has collected data on distance education enrollments since fall 2012.

The previous Babsen measure of “online offerings” had a broader definition than the IPEDS definition. Babsen included any offering of any length to any audience at any time. IPEDS only included classes taken by students enrolled in a degree program, excluding non-credit courses, continuing education courses, courses for alumni, and courses for students not registered for a degree program.

Changes in Distance Enrollments
Babsen-total-and-online-postsecondary-enrollment-2012-2014-data

Enrollment By Type Of Course – Degree-Granting Institutions – 2012-2014
Babsen-total-and-online-postsecondary-enrollment-2012-2014-chart
MOOCs seem to be plateauing.

Note: although MOOCs share a number of characteristics with distance courses, they have several key differences. Those participating are no registered students at the school; they are designed for unlimited participation and open access via the web — no tuition is charged; there is typically no credit given for completion of the MOOC.

Excerpt:
The number of institutions that report that they either have or are planning a Massive
Open Online Course (MOOC) has remained relatively steady. In 2012 12.0% of
institutions fell in this category (2.6% offering a MOOC, and 9.4% with plans to offer
them). In 2013, the number increased to 14.3% (5.0% offering a MOOC and 9.3%
planning). Results for 2014 saw this drop a bit to 13.6% (8.0% offering a MOOC
and 5.6% planning). This year’s results follow this same pattern; 11.3% reporting
that they have a MOOC, and an additional 2.3% are planning one, for the same
13.6% total as last year.

Only a small portion of higher education institutions are engaged with MOOCs, and
adoption levels seem to be plateauing. The total number of institutions reporting a
current or planned MOOC remained stable in 2015. While the fraction of institutions
engaged in MOOCs may be relatively small, these does not mean that the number of
students impacted is also small. With many MOOCs having enrollments in the
thousands, or even higher, the number of students touched by a MOOC can easily
match that of those taking distance education courses.

Role Of Moocs At Your Institution – 2012 To 2015
Babsen-MOOCs-2012-2015

src:
Babson Survey Research Group and Quahog Research Group. February 2016.
Online Report Card: Tracking Online Education In The United States.
contact:
I. Elaine Allen, Jeff Seaman
bsrg@babson.edu

TO DO: ASK BABSEN WHO IS TRACKING MOOC TAKERS AND OTHER ONLINE LEARNERS NOW THAT THEY’RE USING THE NARROWER IPEDS DATASET.

Arts Education

1999 vs. 2009

Figure 1
Percent of public elementary schools reporting instruction designated specifically for various arts subjects and percent incorporating dance and drama/theatre into other subject or curriculum areas: School years 1999–2000 and 2009–10

NCES-arts-education-elementary-1999v2009

More detailed data are provided in supplemental tables 1, 12, 128, and 139.

Figure 4
Percent of public secondary schools reporting whether various arts subjects were taught at the school: School years 1999–2000 and 2008–09

NCES-arts-education-secondary-1999v2009

More detailed data are provided in supplemental tables 70 and 154.

src:
National Center for Education Statistics. April 2012.
Arts Education in Public Elementary and Secondary Schools: 1999-2000 and 2009-10.
US Department of Education. Pp. 5, 9.

Predictions

The Hoover Institution published a series of essays predicting what the American primary and secondary education system might look like in 2030. Mostly qualitative.
src:
Hoover Institution, 2010
American Education in 2030

*

By 2030 over 50% of Colleges will Collapse
src: Thomas Frey, July 2015.
By 2030 over 50% of Colleges will Collapse

Tags: , , ,

Posted by Claudia Lamar on July 28, 2016 at 10:40 pm | comment count



Transportation: Air and Train Travel


Summary

This collection of data includes the following indicators:
AIR TRAVEL
revenue passenger miles, 2014-2040 & 2014-2034, US Energy Information Administration (EIA), Boeing
seat miles demanded by plane size, 2014-2040, EIA
annual passengers on US-based flights, 2003-2015, Dept. of Transportation (DoT)
annual passengers to/from the US, 2015-2036, FAA
passengers to/from/within the US CAGR, 2014-2034, IATA
number of aircraft by type, 1965-2014, DoT
number of certificated aircraft, 1960-2005, Statista (citing AIA, DoT, FAA)
number of commercial aircraft by size, 2006-2036 & 2014/2034, FAA, Boeing
number of general aircraft by size, 2006-2036, FAA
number of airlines, [forthcoming data] & 1950/2002 & speculation, DoT, Aviation Mgmt College, Boeing
number of airports, 1980-2014 & current count by size, DoT, FAA
incoming intl travel and “mega-cities”, 2012/2032, Airbus
PERSONAL DRONES
consumer drone market USD millions, 2013-2024, Grand View Research
RAIL TRAVEL
passenger miles light rail and heavy rail, 1980-2014, DoT
passenger miles commuter rail and Amtrak, 1960-2014, DoT
miles of subway trackway, 1997-2014, DoT
high speed rail development map, 2015-2030 & undated, US High Speed Rail Association, DoT

Findings

Miles Flown

Travel Demand — Revenue Passenger Miles (billion miles)
EIA-air-travel-demand-rev-passenger-miles-2014-2040

Note: Revenue revenue passenger miles are calculated by multiplying the number of revenue paying-passengers aboard the vehicle by the distance traveled. Sometimes abbreviated to RPM or RPK.

Seat Miles Demanded (total and by plane size)
EIA-air-travel-seat-miles-demand-by-plane-size-2014-2040

src:
US Energy Information Administration. 2016.
Annual Energy Outlook 2016
Transportation Sector
Table: Air Travel Energy Use

NOTE: ONLY THE DATA TABLES ARE CURRENTLY AVAILABLE. THE EXECUTIVE SUMMARY AND OTHER NARRATIVE PARTS OF THE REPORT WILL BE AVAILABLE AFTER JULY 21, 2016. CHECK BACK HERE.

*

Boeing-air-traffic-growth-RPKs-2014-2034

“Owing to network carrier capacity discipline, we think that the domestic US market is ripe for even higher growth than previously forecast. Our revised domestic forecast has traffic growth in the range of 2.5 to 3.0 percent over the next five years. With a load factor of 83 percent for 2014 (and average load factors in excess of 80 percent over the past few years), network carriers may be prompted to further ease their capacity discipline in the face of competitive pressures and continued economic recovery.”

src:
Boeing. 2015.
Current Market Outlook: 2015–2034.” P. 23, 42.
contact: BoeingCurrentMarketOutlook@Boeing.com

Passengers Flying

The U.S. Department of Transportation’s Bureau of Transportation Statistics (BTS) reported today that U.S. airlines and foreign airlines serving the United States carried an all-time high of 895.5 million systemwide (domestic and international) scheduled service passengers in 2015, 5.0 percent more than the previous record high of 853.1 million reached in 2014. The systemwide increase was the result of a 5.0 percent rise from 2014 in the number of passengers on domestic flights (696.2 million in 2015) and 4.7 percent growth from 2014 in passengers on U.S. and foreign airlines’ flights to and from the U.S. (199.4 million in 2015)

Annual Total Passengers on US-Based Flights
DOT-passengers-US-based-flights-2003-2015

Data available from the source (table, or excel)

src:
Department of Transportation. March 2016.
2015 U.S.-Based Airline Traffic Data.
Bureau of Transportation Statistics.
media contact: Dave Smallen, 202-366-5568

TO DO: SEE IF THE DEPT. OF TRANSPORTATION HAS OLDER FIGURES.

*

FAA-air-passengers-to-and-from-US-2015-2036

FAA-commercial-air-carriers-general-2015-2036

FAA-US-commercial-air-passengers-2015-2036

Enplanements = passengers

Note: Mainline carriers are defined as those providing service primarily via aircraft with 90 or more seats. Regionals are defined as those providing service primarily via aircraft with 89 or less seats and whose routes serve mainly as feeders to the mainline carriers.

src:
Federal Aviation Administration. Accessed July 1, 2016.
FAA Aerospace Forecast: Fiscal years 2016-2036.

*

Traffic to, from and within the US is expected to grow at an average annual growth rate of 3.2% that will see 1.2 billion passengers by 2034 (559 million more than 2014).

src:
IATA. October 2014.
New IATA Passenger Forecast Reveals Fast-Growing Markets of the Future.

TO DO: INQUIRE ABOUT NEWER FORECAST
David Oxley, IATA Senior Economist, oxleyd@iata.org
OR corpcomms@iata.org

Number and Types of Commercial Jets

Table 1-13: Active U.S. Air Carrier and General Aviation Fleet by Type of Aircraft (Number of carriers)

Annual data available 1965-2014

src:
US Department of Transportation. Accessed July 1, 2016.
Table 1-13: Active U.S. Air Carrier and General Aviation Fleet by Type of Aircraft (Number of carriers).”

TO DO: PULL DATA OUT INTO A GOOGLE SPREADSHEET

*

Number of aircraft of U.S. certificated air carriers from 1960 to 2005

The timeline shows the number of U.S. certificated air carrier aircraft from 1960 to 2005. In 2000, there were 8,055 certificated air carrier aircraft in the United States.

Statista-certificated-aircraft-1960-2005

src:
Statistia. Accessed July 8, 2016.
Number of aircraft* of U.S. certificated air carriers from 1960 to 2005.

citing:
AIA; Dept. of Transportation; Federal Aviation Administration

FORECAST BELOW

*

US Commercial Aircraft Forecast
(CC’s notes: includes scheduled air services – pilot is paid, must have commercial pilot certificate)

The number of aircraft in the U.S. commercial fleet is forecast to increase from 6,871 in 2015 to 8,414 in 2036, an average annual growth rate of 1.0 percent a year. Increased demand for air travel and growth in air cargo is expected to fuel increases in both the passenger and cargo fleets.

FAA-US-commercial-aircraft-2006-2036

NB: narrow-body
WB: wide-body

General Aviation Forecast
(CC’s notes: does not include schedule air services – pilot not paid, private pilot certificate is sufficient)

The active general aviation fleet is projected to increase at an average annual rate of 0.2 percent over the 21-year forecast period, growing from an estimated 203,880 in 2015 to 210,695 aircraft by 2036.

FAA-active-general-aircraft-2006-2036

LSA: light-sport-aircraft (category established in 2005)

Note: An active aircraft is one that flies at least one hour during the year.

src:
Federal Aviation Administration. Accessed July 1, 2016.
FAA Aerospace Forecast: Fiscal years 2016-2036.

*

Boeing-traffic-fleet-growth-2014-2034

src:
Boeing. 2015.
Current Market Outlook: 2015–2034.” p.42
contact: BoeingCurrentMarketOutlook@Boeing.com

Number of Airlines

The Dept. of Transportation has a simple PDF list of certificated air carriers and commuter air carriers, but there’s no “member since” info and presumably doesn’t include former members.

https://www.transportation.gov/policy/aviation-policy/certificated-air-carriers-list

https://www.transportation.gov/policy/aviation-policy/commuter-air-carriers-list

https://www.transportation.gov/policy/aviation-policy/licensing/US-carriers

Air Carrier Fitness Division
Office of Aviation Analysis
Dept. of Transportation
1200 New Jersey Ave, SE
Washington, DC 20590
United States
Phone: (202) 366-9721
Business Hours:
8:30am-5:00pm ET, M-F

EMAILED LAURALYN REMO, laura.remo@dot.gov, JULY 8, 2016.
Caitlin Harvey, caitlin.harvey@dot.gov, wrote back and shared the following Excel files (with data from 1978-2016):
Commuter Carrier List.xls
Certificated Carrier List.xls

*

Certificated airlines in the US
1950 – 17 airlines
2002 – 12 airlines

src:
Aviation Management College.
Introduction to Aviation Economics.
Slide 15.

*

“Post the 2008 downturn, the introduction of the ultra-low-cost carrier (ULCC) business model in the United States is literally taking off. Spirit Airlines is the fastest growing domestic airline, recording double-digit growth. Frontier Airlines, which is undergoing a change in strategy, is expected to challenge Spirit in the quest to become the preeminent ULCC in the United States. The expectation is that over time, the industry will further consolidate, with the LCC and smaller network carriers becoming potential consolidation targets.

[emphasis mine]

src:
Boeing. 2015.
Current Market Outlook: 2015–2034.” P.42
contact: BoeingCurrentMarketOutlook@Boeing.com

Number of Airports

Table 1-3: Number of U.S. Airports

Annual data available 1980-2014

src:
US Department of Transportation. Accessed July 6, 2016.
Table 1-3: Number of U.S. Airports.

NOTE: THESE FIGURES ARE MUCH HIGHER THAN THOSE BELOW DESCRIBING THE NUMBER OF US AIRPORTS WHERE REGIONAL AIRLINES OPERATE. THOSE FIGS MIGHT BE REFERRING TO “CERTIFICATED” AIRPORTS, BUT DATA FOR THESE AIRPORTS ARE ONLY AVAILABLE 1994-2004.

TO DO: PULL DATA OUT INTO A GOOGLE SPREADSHEET

*

A total of 614 U.S. airports are served by regional airlines, with 70% (431 airports) relying exclusively on regional airlines for their scheduled service.

The United States’ air transportation network is the most developed in the world, but is evolving as airlines battle rising costs. While regional aircraft operate approximately 33% of commercial flights worldwide, 50% of all commercial flights in the United States are flown by regional aircraft with less than 100 seats. According to the Regional Airline Association (RAA), average capacity of U.S. regional aircraft has increased from 37 seats in 2000 to 50 seats in 2005 and to 56 seats in 2013. Average trip length increased from 476 kilometres in 2000 to 763 kilometres in 2013. These trends are expected to continue as new large regional aircraft replace 20-to59-seat aircraft.

src:
Bombardier. July 2014.
Bombardier Commercial Aircraft Market Forecast 2014-2033.
P.31

citing:
Regional Airline Association (RAA)

*

2014
Total FAA Towers – 264
Total Contract Towers – 252

2014 airport hubs
30 large hub airports (1%+ total US passenger enplanements)
31 medium hub airports (.25-.99%)
74 small hub airports (.05-.249%)
381 non-hub airports non-hub airports (less than .05%)
Total: 516

For example, Atlanta was the busiest large hub in 2014, and it saw 6.13% of total US enplanements in 2014.

Enplanements at large hubs expected to increase at an annual rate of 2.0% through 2040. Operations (take-offs and landings) at these hubs are forecast to increase at an annual rate of 1.6%.

Medium and small hubs are forecast to increase at 2.0% and 1.7% annually, respectively. Operations at medium hubs expected to grow at 1.3% annually. Operations at small hubs are forecast to grow at .8% per year.

Non-hub operations accounted for 52% of total operations at FAA and Federal contract towers. General aviation operations (e.g.: private) accounted for the majority of operations at these smaller airports.

src:
Federal Aviation Administration. 2015.
Terminal Area Forecast Summary: Fiscal Years 2015-2040.

contact:
Roger Schaufele, Jr.
Manager
Forecast and Performance Analysis Division
Office of Aviation Policy and Plans
202-267-3306
Roger.Schaufele@faa.gov

EMAILED ROGER SHAUFELE JULY 8, 2016.

ALSO TRY CONTACTING THE FAA OFFICE OF THE ASSOCIATE ADMIN FOR AIRPORTS. NO EMAIL, PHONE IS DISCONNECTED.

*

Airport Data retrieval form from the FAA.

TO DO: CONTACT FAA FOR AN ANNUAL TALLY. NOT SURE BEST CONTACT AVENUE.
TRY THE FORM HERE. OR THE OFFICE OF THE ASSOCIATE ADMIN FOR AIRPORTS

Incoming Intl Travel to US

Airbus-airline-origin-destination-flows-2012-2032

In 2012, the US has one “aviation mega-city” receiving more than 50,000 daily long-haul passengers. In 2032, there will be five.

Long haul traffic: flight distance >2,000nm, excl. domestic traffic

citing: GMF 2013; Cities with more than 10,000 daily passengers

src:
Bob Lange. September 2013.
Global Market Forecast 2013-2032.
Airbus. P. 15, 29

Personal Drones

Grand View Research is tracking the consumer drone market, and although the summary for their recent report does not include much unit data, the forecast does show the relative growth across three consumer applications: prosumer, toy/hobbyist/DYI, and photogrammetry.

North America consumer drone market by technology, 2012 – 2022 [sic] (USD Million)
GVR-consumer-drone-market-2013-2024

src:
Grand View Research. May 2016.
Consumer Drone Market Analysis By Product (Multi-Rotor, Nano), By Application (Prosumer, Toy/Hobbyist, Photogrammetry) And Segment Forecasts To 2024.

Rail Passenger Miles

Table 1-40: U.S. Passenger-Miles (Millions)

Includes
Light rail: 1980-2014
Heavy rail: 1980-2014
Commuter rail: 1960-2014
Intercity/Amtrak: 1960-2014

Note: This table also includes figures for air, highway, bus and ferry travel.

src:
US Department of Transportation. Accessed July 11, 2016.
Table 1-40: U.S. Passenger-Miles (Millions).

TO DO: PULL DATA OUT INTO A GOOGLE SPREADSHEET

Definitions src

Heavy Rail: includes subways, elevated railways, and metropolitan (metro) railways and refers to an electric railway with the capacity to transport a heavy volume of passenger traffic and characterized by exclusive rights-of-way, multicar trains, high speed, rapid acceleration, sophisticated signaling, and high-platform loading.

Light Rail: A streetcar-type vehicle operated on city streets, semiexclusive rights-of-way, or exclusive rights-of-way. Service may be provided by step-entry vehicles or by level boarding.

Commuter Rail: Urban passenger train service for short-distance travel between a central city and adjacent suburb. Does not include rapid rail transit or light rail service.

Amtrak: Operated by the National Railroad Passenger Corporation of Washington, D.C., this rail system was created by the Rail Passenger Service Act of 1970 (P.L. 91-518, 84 Stat. 1327) and given the responsibility for the operation of intercity, as distinct from suburban, passenger trains between points designated by the Secretary of Transportation.

Miles of Trackway

Subway: 1997-2014 (in separate annual reports)

src:
US Department of Transportation ~1997-2014.
NTD Data Reports.
Federal Transit Administration.

TO DO: EXTRACT DATA

High-Speed Rail

The High Speed Rail Association has published a US network phasing plan showing construction phases from 2015-2030.

US_HSR_Phasing_Map-2015-2030

src:
US High Speed Rail Association. Accessed July 11, 2016.
US HSR Network Phasing Plan.

NOTE: This plan may reflect expect START dates for construction, rather than completion. For example, while work on phase 1 of California’s high-speed rail system began in 2014, it’s not expected to be complete until 2029. src

*

In 2009, the Department of Transportation published a strategic plan for US high-speed rail development, which designated 10 high-speed corridors.

DoT-high-speed-rail-2009-plan-map

Note: The plan does not include a specific timeline for completion of the high-speed corridors.

src:
US Department of Transportation. April 2009.
High-Speed Rail Strategic Plan.” P.6

Tags: , , , , , , ,

Posted by Claudia Lamar on July 15, 2016 at 10:31 pm | comment count



Transportation: General Transit and Cars


Summary

This collection of data includes the following indicators:
vehicles per household, 1969-2009, Dept. of Transportation
licensed drivers per household, 1969-2009, Dept. of Transportation
vehicles per licensed driver, 1969-2009, Dept. of Transportation
vehicles per worker, 1969-2009, Dept. of Transportation
daily person trips, 1969-2009, Dept. of Transportation
daily person miles of travel (PMT), 1969-2009, Dept. of Transportation
daily vehicle trips, 1969-2009, Dept. of Transportation
daily vehicle miles of travel (VMT), 1969-2009, Dept. of Transportation
total annual VMT, 1994-2032 & 2014-2044 & 1970-2098, Dept. of Transportation (Frontier Group), Thomas
total annual VMT for light-duty vehicles (LDV), 2014-2040, US Energy Information Administration (EIA)
average person trip length (miles), 1969-2009, Dept. of Transportation
average vehicle trip length (miles, 1969-2009, Dept. of Transportation
avg annual PMT/household by purpose, 1983-2009, Dept. of Transportation
avg annual person trips/household by purpose, 1983-2009, Dept. of Transportation
avg person trip length (miles) by purpose, 1983-2009, Dept. of Transportation
availability of household vehicles, 1969-2009, Dept. of Transportation
vehicle prevalence by age and type, 1977-2009, Dept. of Transportation
distribution of workers by commute mode, 1969-2009, Dept. of Transportation
commute patterns by mode of transportation, 1977-2009, Dept. of Transportation
avg commute time to work, 1980-2013 & 2005-2014, Census Bureau
Chicago metro commute, 2000-2030, Alex Anas
LDV sales, 2014-2040 & 1970-2100, EIA, Thomas
vehicle production vs. car sharing, 2015-2030, Morgan Stanley
Alternative-fuel cars sales, 2014-2040 & 2000-2050 EIA, Nat’l Research Council
autonomous vehicle sales, -2035 & 2014-2036 & -2040 IHS, BCG, Jiang, IEEE
autonomous vehicle dev timeline, 2015-2030, PwC

Findings

General

The Department of Transportation has been collecting data about daily personal travel patterns via two different, periodic surveys going back to 1969. Subsequent survey years have been: 1977, 1983, 1990, 1995, 2001, 2009, and 2016 (underway).

Abstract:

The 2009 National Household Travel Survey (NHTS) provides data to characterize daily personal travel patterns across the country. The survey includes demographic data on households, vehicles, people, and detailed information on daily travel by all modes of transportation. NHTS survey data is collected from a sample of households and expanded to provide national estimates of trips and miles of travel by travel mode, trip purpose, and other household attributes. When combined with historical data from the 1969, 1977, 1983,1990, and 1995 NPTS and the 2001 NHTS, the 2009 NHTS serves as a rich source of detailed travel data over time for users. This document highlights travel trends and commuting patterns in eight key areas – summary of travel and demographics, household travel, person travel, private vehicle travel, vehicle availability and usage, commute travel patterns, temporal distribution, and special populations.

NHTS-table2-major-travel-indicators-1969-2009

NHTS-table3-summary-travel-stats-1969-2009

NHTS-table5-avg-annual-miles-trips-length-by-purpose-1983-2009

NHTS-table17-households-by-vehicle-availability-1969-2009

NHTS-table20-vehicle-count-age-by-type-1977-2009

NHTS-table25-workers-by-commute-mode-1969-2009

NHTS-table27-commute-patterns-by-mode-1977-2009

src:
A. Santos, et al. 2011.
Summary Of Travel Trends: 2009 National Household Travel
Survey.

U.S. Department of Transportation.

NOTE: 2016 SURVEY IS UNDERWAY

*

The Bureau of Transportation Statistics publishes historic data on annual passenger-miles in aggregate, broken down by method of transportation. The chart currently shows data from 1960-2014.

Src:
Department of Transportation. Bureau of Transportation Statistics. Accessed November 8, 2016.
Table 1-40: U.S. Passenger-Miles (Millions).”
XLS

TO DO: EXTRACT DATA

Commute

The Census Bureau (in addition to the Dept. of Transportation) has asked survey questions about daily travel patterns going back to 1980 (and back to 1960 for a couple of very specific questions). Questions have been asked during the decennial census (since 1980, maybe 1960), and during the “American Community Survey” (going back to 2005).

Census-commute-time-1980-2013

src:
Beth Jarosz and Rachel T. Cortes. September 2014.
In U.S., New Data Show Longer, More Sedentary Commutes.
Population Reference Bureau.

citing:
U.S. Census Bureau, Decennial Census 1960, 1970, 1980, 1990, 2000, and American Community Survey 2013.

Mean Travel Time to Work (minutes)
2005 – 25.1
2006 – 25.0
2007 – 25.3
2008 – 25.5
2009 – 25.1
2010 – 25.3
2011 – 25.5
2012 – 25.7
2013 – 25.8
2014 – 26.0

src:
United States Census Bureau. 2005-2014.
“American Community Survey.” Table S0802: Means of Transportation to Work by Selected Characteristics.
links above

*

This article presents data and extrapolations explaining why urban commute times have not increased more dramatically, despite decades of urban sprawl.

One study (Alex Anas, SUNY Buffalo) extrapolates commute times for the Chicago metro area from 2000 to 2030. In that time, there is a 24% jump in population, leading to 19% more urbanized land (sprawl), but only a 4.5% rise in commute time (from 30 minutes to 31.7 minutes).

Another study (MIT Senseable City Lab) examines cell phone data to track commutes around the world. The study finds travel time, on average across the world, to be largely independent of distance.

The article says that these studies seems to support the theory of “travel time budgets,” developed first by Yacov Zahavi and further by Cesar Marchetti (that travel budgets have averaged about an hour throughout history, and across the world). Both studies seem to support the idea that people adapt their lifestyles to accommodate an average travel time budget, whether by changing mode of transportation (e.g.: switching to public transportation), moving closer to their jobs, or reducing trips that aren’t commutes.

src:
Eric Jaffe. June 2014.
Why Commute Times Don’t Change Much Even as a City Grows.
The Atlantic: CityLab

More information about Anas’ extrapolation model, which includes several complex indicators, can be found on this page at his personal website:
The RELU-TRAN Model and its applications

TO-DO: ANAS’ MODEL MAY BE IN THE PROCESS OF BEING APPLIED TO LOS ANGELES AND OTHER METROS. INQUIRE ABOUT GENERALIZATION TO THE US.

Total Vehicle Miles Traveled

The new report’s 30-year estimates predict even less rapid growth in driving, forecasting that total driving miles will increase only 0.75 percent annually from 2012 to 2042. With population growth estimated to average 0.7 percent each year, this leaves per-person driving miles essentially flat. “This represents a significant slowdown from the growth in total VMT experienced over the past 30 years, which averaged 2.08% annually,” says the report.

FrontierGroup-DOT_forecasts-1994-2032

src:
Phineas Baxandall. January 2015.
The Feds Quietly Acknowledge the Driving Boom Is Over.
StreesBlogUSA.

citing:
Federal Highway Administration. May 2014.
FHWA Forecasts of Vehicle Miles Traveled (VMT): May 2014.
and:
U.S. PIRG/Frontier Group (graphic src)

*

The Federal Highway Administration’s spring 2016 forecast revises the growth outlook even further downward.

Excerpt:
Growth in total VMT by all vehicle types is projected to average 0.92% annually over the next 20 years (2014-2034). Over the entire 30-year forecast period (2014-2044) the average annual growth rate is projected to be 0.61% annually, as growth is projected to slow to 0.30% annually during the last decade (2034-2044). This outlook represents a significant slowdown from the growth experienced over the past 30 years, when growth in total VMT averaged 2% annually, although more detailed analysis shows that growth in overall motor vehicle travel per Capita was already slowing throughout most of that period.

[Emphasis mine]

src:
Federal Highway Administration. May 2016.
FHWA Forecasts of Vehicle Miles Traveled (VMT): Spring 2016.
Department of Transportation.

*

Transportation: Travel Indicators: Light-Duty Vehicles = 8,500 lbs

EIA-LDV-2014-2040

Visit the source URL for data (many export options).

src:
US Energy Information Administration. 2016.
Annual Energy Outlook 2016
Transportation Sector
Table: Light-Duty Vehicle Energy Consumption by Technology Type and Fuel Type

NOTE: ONLY THE DATA TABLES ARE CURRENTLY AVAILABLE. THE EXECUTIVE SUMMARY AND OTHER NARRATIVE PARTS OF THE REPORT WILL BE AVAILABLE AFTER JULY 21, 2016. CHECK BACK HERE.

*

The National Hydrogen Association created a few projections of US Annual Vehicle Miles Traveled (VMT) between 2007 and 2012. Their model performs a linear extrapolation from the EIA’s Annual Energy Outlook (AEO) for 2012, which projects VMT through 2023. Their extrapolation goes through the end of the 21st century. (Results are published at the lead author’s website, “Alternative Vehicles”.)

NHA-VMT-1970-2100

src:
C.E. Thomas. 2013.
LDV VMT & Sales.” Alternative Vehicles.
contact: thomas@cleancaroptions.com, faq@cleancaroptions.com

TO DO: CONTACT DR. C.E. (SANDY) THOMAS TO ASK IF THERE HAS BEEN A RECENT UPDATE.

LDV Sales Projection

Light-Duty Vehicle Sales: Total Sales, Cars and Light Trucks
EIA-total-vehicle-sales-by-fuel-type-2014-2040

Light-Duty Vehicle Sales: Percent Alternative Cars
EIA-pcnt-alternative-car-sales-2014-2040

Light-Duty Vehicle Sales: Alternative-Fuel Cars
EIA-alternative-fuel-cars-sales-2014-2040

Visit the source URL for data (many export options).

src:
US Energy Information Administration. 2016.
Annual Energy Outlook 2016
Transportation Sector
Table: Light-Duty Vehicle Energy Consumption by Technology Type and Fuel Type

*

NHA-LDV_Sales-1970-2100

src:
C.E. Thomas. 2013.
LDV VMT & Sales.” Alternative Vehicles.
contact: thomas@cleancaroptions.com, faq@cleancaroptions.com

TO DO: CONTACT DR. C.E. (SANDY) THOMAS TO ASK IF THERE HAS BEEN A RECENT UPDATE.

*

5.3.1 Baseline Cases

Excerpt:
In the [business as usual] case, new-vehicle sales increase to 22.2 million in 2050 from 10.8 million units in 2010 (a year in which sales were severely depressed due to the recession). Diesel, hybrid, and plug-in hybrid vehicles make modest gains in market share (Figure 5.1). The total stock of LDVs increases from about 220 million in 2010 to 365 million in 2050.

NAP-BAU-LDVs-2000-2050
FIGURE 5.1 Vehicle sales by vehicle technology for the business as usual scenario.

FCEVs: fuel cell electric vehicles
BEVs: battery electric vehicles
PHEVs: plug-in hybrid electric vehicles
HEVs: hybrid electric vehicles
ICEs: internal combustion engines

Note: In this model total new car sales and annual vehicle miles traveled (VMT) are assumed to be the same as in the projections from the Annual Energy Outlook 2011

src:
National Research Council. 2013.
Transitions to Alternative Vehicles and Fuels.
Chapter: 5 Modeling the Transition to Alternative Vehicles and Fuels.
The National Academies Press.

*

Production Vs. Sharing

morganstanley-car-production-vs-sharing

Src:
The Economist. January 2016.
The driverless, car-sharing road ahead.”

Autonomous Vehicle Sales

IHS forecasts 76 million autonomous vehicles will have been sold globally through 2035, with 21 million of those being sold that year.

“The U.S. market is expected to see the earliest deployment of autonomous vehicles as it works through challenges posed by regulation, liability and consumer acceptance. Deployment in the U.S. will begin with several thousand autonomous vehicles sold in 2020, which will grow to nearly 4.5 million vehicles sold in 2035, according to IHS Automotive forecasts. As in many other markets, a variety of use cases and business models are expected to develop around consumer demand for personal mobility.”

IHS expects a global CAGR of 43% between 2025 and 2035.

src:
IHS. June 2016.
CORRECTING and REPLACING IHS Clarifies Autonomous Vehicle Sales Forecast – Expects 21 Million Sales Globally in the Year 2035 and Nearly 76 Million Sold Globally Through 2035.
contacts:
Michelle Culver michelle.culver@ihs.com
press@ihs.com

TO DO: ASK IF THEY CAN SHARE ANNUAL DATA POINTS.

*

“In 2035, AV sales will account for 25% of the market.”

BCG-autonomous-vehicle-global-market-penetration-2015-2035

src:
Boston Consulting Group. April 2015.
Revolution in the Driver’s Seat.
P.18

Note: The report uses expectations for the U.S. as an accurate proxy for the global market-penetration. This is based on adoption rates in the U.S. for adaptive cruise control being in line with overall global adoption.

*

Cars sold globally 2014-2036

2014 – total 90M+, autonomous or self-driving 15M+
2030 – 50% autonomous or self-driving

Jiang-car-sales-by-region-2014-2036

Jiang-car-sales-2014-2036

src:
Tao Jiang et al. 2015
Self-Driving Cars: Disruptive or Incremental?
Applied Innovation Review, 1. P.6

NOTE: The authors are from Google, Samsung, Yahoo, and Altera, but the data above is not sourced.

TO DO: CONFIRM SOURCES FOR ABOVE DATA. (HAVEN’T BEEN ABLE TO FIND EMAIL ADDRESSES FOR ANY OF THE AUTHORS – MIGHT HAVE TO REACH OUT VIA LINKEDIN, OR THE JOURNAL’S EDITORS.)

*

In 2012, IEEE said that it expected autonomous vehicles to account for up to 75% of cars on the road (globally) by 2040.

TO DO: TRACE THE SOURCE. POSSIBLY ALBERTO BROGGI, UNIV. PARMA, ITALY.

src:
IEEE. September 2012.
Look Ma, No Hands!
IEEE News Releases

Autonomous Vehicle Development Timeline

Exhibit 7: Possible time line of autonomous car innovation

PWC-Exhibit007-development-timeline-2015-2030

src:
Richard Viereckl et al. September 2015.
Connected Car Study 2015: Racing ahead with autonomous cars and digital innovation.
Strategy&. PwC.

NOTE: Although this paper is focused on the European Union, I believe this timeline is general to the industry as a whole.

Tags: , , ,

Posted by Claudia Lamar on July 14, 2016 at 10:04 pm | comment count



Food


This collection of data includes the following indicators:
Crop Acreage, 2014-2025, USDA
Meat Production, 1990-2025, USDA
Meat Consumption, 1909-2013; 1990-2025, USDA
Meat Imports and Exports, 2014-2025, USDA
Organic Food Market CAGR 2015-2020, TechSci
Organic Food Sales, 1994-2014; 2006-2015, USDA; Organic Trade Association (OTA)
Organic Food Acreage, 2003-2014; 2008-2014; 1992-2011, OTA; USDA
Organic Acreage as a % of Total, 1995-2050, Steve Savage
Organic Food Premiums, 2004-2010, Nielsen/USDA
Genetically Engineered Corn and Soy, 2001-2015, USDA
Farmers’ Markets, 1994-2015, USDA & LocalHarvest
CSA Growth, 1980-2016, LocalHarvest
Food-Miles, 1997/2004, 1969, 1980, 2001, Weber & Matthews, Dept. of Defense, Hendrickson, Pirog
Farms By Size, 2002-2012, USDA
Grocery Delivery Services, 2014 & 2023, Bricks Meets Clicks
Income Spent on Food, 1970-2007, USDA
% of Food Purchased Away from Home, 1970-2012, USDA
Total Spending on Dining Out v. Groceries, 1992-2015, Commerce Dept.
% of Dinners Eaten at Home and Made at Home, 1974-2014, NPD Group
Food at Home v. Away By Income, 1956-2008, Smith
Time Spent Cooking, 1965-2008, Smith

In addition to these data sets, I’ve also included a link to a set of scenarios published by the Institute For The Future.

Crop Acreage

The USDA has published a report of 10-year agricultural projections annually at least since 2005. The reports are a business-as-usual projection for crops, livestock, farm income, and agricultural trade. Excerpted below are projections for crop acreage.

Includes the following macroeconomic assumptions (annual projections)
GDP
Disposable personal income
Personal consumption expenditures
Labor compensation per hour
Civilian unemployment rate
Nonfarm payroll employees
Total population
(p.16)

USDA-macroeconomic-assumptions-2014-2025

Excerpts:

Over the long run, steady global economic growth provides a foundation for increasing crop demand, with gains in world consumption and trade. Although crop prices are projected to be below recent records, they remain above pre-2007 levels. U.S. plantings for the eight major crops continue to fall during the second half of the projection period, to about 244 million acres by 2025. Corn and soybeans decrease the most. Increasing yields provide most of the gains in U.S. production.

USDA-US-planted-area-1990-2025

Farm programs of the Agricultural Act of 2014 are assumed to be extended through the projection period. Acreage enrolled in the Conservation Reserve Program (CRP) is assumed at levels slightly below the legislated maximum of 24 million acres.

USDA-Conservation-reserve-program-acreage-1990-2025

USDA-acreage-major-crops-and-CRP-2014-2025

src:
Paul Westcott and James Hansen, February 2016.
USDA Agricultural Projections to 2025
p.19, 28
contact: westcott@ers.usda.gov, jhansen@ers.usda.gov

Meat Production/Consuption

The USDA produces a 10-year forecast for many agricultural indicators, including meat production and consumption.

Excerpts:

The U.S. livestock sector is projected to increase production over the next decade, an expansion that reflects several factors. Feed costs have fallen from recent highs and are projected to rise only moderately over the next 10 years. Also, demand for meats and dairy products in both the domestic market and for export is projected to be strong. As a result, total U.S. red meat and poultry production rises over the projection period. Milk production also increases over the next decade.

USDA-meat-production-1990-2025

As production increases, consumption of red meats and poultry is projected to rise from about 211 pounds per person in 2015 to about 219 pounds toward the end of the projection period. Although this level consumption is below those in 2004-07 of more than 221 pounds per person, it represents a rebound from a low of 202 pounds per person in 2014.
commerce-dept-total-spending-food-away-groceries-1992-2015

USDA-meat-consumption-1990-2025

USDA-per-capita-meat-consumption-2014-2025

USDA-beef-long-term-projections-2014-2025

USDA-pork-long-term-projections-2014-2025

USDA-young-chickens-long-term-projections-2014-2025

USDA-turkey-long-term-projections-2014-2025

USDA-egg-long-term-projections-2014-2025

USDA-dairy-long-term-projections-2014-2025

USDA-import-export-long-term-projections

src:
Paul Westcott and James Hansen, February 2016.
USDA Agricultural Projections to 2025
p.39, 40, 44-47, 83-92
contact: westcott@ers.usda.gov, jhansen@ers.usda.gov

*

The USDA collects data on food and nutrient availability for consumption, which they describe as proxies for actual consumption at the national level.

Red Meat, Poultry, and Fish
1909-2013, pounds available/consumed per year, broken down by type of meat

Also available in the following Google Sheet.
original source file

src:
USDA Economic Research Service. Accessed June 6, 2016.
Food Availability (Per Capita) Data System.

Organic Food

Research firm TechSci forecasts that the global organic food market will have a CAGR over 16% during 2015-2020.

src:
TechSci Research. 2015.
Global Organic Food Market Forecast & Opportunities, 2020.
via [PR Newswire]

Media Contact: Ken Mathews ken.mathews@techsciresearch.com

Previous forecasts had estimated the US CAGR for 2013-2018 to be 14%.

EMAILED THE FIRM 6/21 TO SEE IF THEY CAN SHARE THE MOST RECENT US FIGURES

UPDATE: Karan Chechi, Research Director with TechSci Research, confirms by email that the US market will have a CAGR of 16.27% during 2015-2020.

src:
Email correspondence via Kalpana Verma, June 23, 2016
citing Karan Chechi

*

The Organic Trade Association conducts an annual survey describing the previous year’s organic food sales. In 2015, organic food sales were up 11% over the previous year (the overall food market’s growth was just 3%). Nearly 5% of all the food sold in the US in 2015 was organic.

OTA-organics-sales-2006-2015

Organic fruits and vegetables remain the largest of all the major organic categories, with sales up 10.5%. Almost 13% of the produce sold in the US is now organic.

OTA also reports short-comings in the organics supply chain. Although organic food sales make up nearly five percent of total food sales, acreage devoted to organic agriculture is less than one percent of total U.S. cropland.

OTA-organic-acreage-vs-food-sales-2003-2014

src:
Organic Trade Association. May 19, 2016.
U.S. organic sales post new record of $43.3 billion in 2015.
and
U.S. Organic State of the Industry.” Accessed June 21, 2016.

Media Contact: Maggie McNeil, mmcneil@ota.com

In previous years, the OTA has given very short forecasts for growth.

EMAILED 6/21 TO INQUIRE ABOUT RECENT FORECASTS, AND REQUESTING A COPY OF THE EXECUTIVE SUMMARY.
UPDATE: NO OFFICIAL FORECASTS, BUT THEY EXPECT GROWTH TO REMAIN STRONG FOR THE FORESEEABLE FUTURE

*

U.S. sales of organic products were an estimated $28.4 billion in 2012—over 4 percent of total food sales—and will reach an estimated $35 billion in 2014, according to the Nutrition Business Journal.

The number of farmers’ markets in the United States has grown steadily from 1,755 markets in 1994, when USDA began to track them, to over 8,144 in 2013

src:
USDA. May 2016.
Organic Market Overview.

Contact: Catherine Greene, cgreene@ers.usda.gov

http://www.ers.usda.gov/ers-staff-directory/catherine-greene.aspx

*

USDA-organic-food-sales-and-growth-1994-2014

USDA-monthly-nonGMO-products-2010-2014

src:
Catherine Greene, et al. February 2016.
Economic Issues in the Coexistence of Organic, Genetically Engineered (GE), and Non-GE Crops.” Report EIB-149.
Economic Research Service/USDA
p.8, 10

*

Nielsen Homescan data is an annual, nationally representative panel of households’ retail food purchases. USDA organic food certification began in 2002, and Nielsen started tracking whether a product was organic in 2004. USDA’s Economic Research Service conducted a study using the Nielsen data from 2004 through 2010 to compare sales data over the period. Each product tracked was ranked by percent of organic sales, percent of organic purchase quantity, and percent of organic transactions (Table 1).

USDA-organic-eggs-sales-table-2004-2010

The study also calculated price premiums for organic products (Table 2).

USDA-organic-eggs-price-premiums-table-2004-2010

USDA-organic-eggs-price-premiums-chart-2004-2010

USDA-organic-spinach-price-premiums-chart-2004-2010

USDA-organic-vegs-price-premiums-chart-2004-2010

USDA-organic-beans-coffee-price-premiums-chart-2004-2010

USDA-organic-soup-price-premiums-chart-2004-2010

Products tracked include eggs and dairy, fruits and vegetables, single-ingredient processed foods (eg: canned beans, coffee), multi-ingredient processed food (eg: bread), and baby food. Only products with UPCs were tracked (no premium meat and poultry were tracked).

src:
Andrea Carlson and Edward C. Jaenicke. May 2016.
Changes in Retail Organic Price Premiums from 2004 to 2010.
Economic Research Report No. ERR-209. USDA.
Summary and Appendix tables available here.

TO-DO: EXTRACT DATA FROM PAPER, AND/OR CONTACT NIELSEN TO SEE IF WE CAN GET POST-2010 DATA.

*

USDA NASS Organic Production Survey

The USDA’s National Agricultural Statistics Service (NASS) has conducted three surveys of organic agricultural production in the US, first in 2008, then 2011, then 2014. Some data on organics production were also gathered as part of the 2012 Agricultural Census.

Organic Land Acres
2008: 4,077,337
2011: 3,648,896
2014: 3,670,560

Market Value of Organic Agricultural Products Sold
Year — Value of Crops sold (B) — Value of Livestock Poultry and Products Sold — Total Value of Ag Products Sold
2008 — 2.0 — 1.2 — 3.2
2011 — 2.2 — 1.3 – 3.5
2012 — N/A — N/A — 3.1
2014 — 3.3 — 2.2 — 5.5

src:
USDA NASS. September 17, 2015.
Data Release: 2014 Organic Survey.
Contact: Adam Cline, adam.cline@nass.usda.gov

*

The USDA Economic Research Service (ERS) has collected some historic data describing the extent of organic farmland acreage and livestock in the US. Data is available 1992-2011, and imported to the following Google Sheet.

src:
USDA ERS. Accessed June 2016.
Organic Production — Overview

Table 2: U.S. certified organic farmland acreage, livestock numbers, and farm operations [XLS]
contact: Catherine Greene, cgreene@ers.usda.gov

*

sustainablog-Organic-Percent-Trend-1995-2050

In fact, all those Organic acres put together still only represent 0.71% of the 370 million acres of US cropland. The amount of that cropland that was actually harvested in 2008 represented only 0.52% of the total. Organic cropland area has been growing, but only at 0.0385% per year on an absolute basis (see chart below). At that rate of growth, US Organic cropland will still represent less than 2.5% of the total in the year 2050. The math suggests that Organic will remain as a small niche market.

src: Steve Savage. August 2011.
Why Does Organic Seem Larger Than It Is?
contact: savage.sd@gmail.com
citing: USDA-NASS and USDA-ERS data

NOTE: Per his bio (last slide), Steve Savage is an independent agricultural technology consultant. He does NOT see organics as a viable solution for the overall sustainability and production challenges faced on a global level.

Genetically Engineered Crops

GE corn and soybeans are grown on more acres than any another crop in the United States. GE varieties of corn and soybeans were commercialized in 1996. By 2001, a quarter of the U.S. corn crop and over two-thirds of the soybean crop were planted with GE seed (fig. 3). In 2015, U.S. producers planted 89 million acres of corn and 85 million acres of soybeans with GE seed, accounting for 92 and 94 percent of the total planted acres for these crops (USDA-National Agricultural Statistics Service, 2015a) (fig. 3). One of the major uses of these crops is for animal feed, but they are also used to produce vegetable oil and as ingredients in many processed foods. A substantial amount of the corn crop—44 percent in 2015—is now used to produce alcohol for fuel use (USDA-ERS, 2015a).

USDA-GE-corn-soy-crops-2001-2015

src:
Catherine Greene, et al. February 2016.
Economic Issues in the Coexistence of Organic, Genetically Engineered (GE), and Non-GE Crops.” Report EIB-149.
Economic Research Service/USDA
p.11

Farmer’s Markets

The USDA has maintained a registry of farmers markets at least since 1994.

USDA-FarmersMarketDirectoryListing-1994-2015

src:
USDA Agricultural Marketing Service. Accessed June 24, 2016.
Linked via “Farmers Markets and Direct-to-Consumer Marketing.
JPG src

*

8,268 farmers’ markets operating in 2014, up 180 percent since 2006. Martinez et al. (2010)

In 2012, 7.8 percent of U.S. farms sold food through local food marketing channels, including direct-to-consumer (DTC) marketing channels (e.g., farmers’ markets, roadside stands, u-pick) and intermediated marketing channels (e.g., direct to restaurants, institutions or to regional food aggregators).

Regional food hubs are enterprises that aggregate locally sourced food to meet wholesale, retail, institutional and even individual demand (see box, “Regional Food Hubs”). Since 2006-07, the number of food hubs has increased by 288 percent (fig. 1).

Farm to school programs have multiple objectives, ranging from nutrition education to serving locally sourced food in school meals. According to the USDA Farm to School Census, 4,322 school districts have farm to school programs, a 430-percent increase since 2006 (fig. 1).

src:
USDA. January 2015.
Trends in U.S. Local and Regional Food Systems.

*

TO-DO: LOOK INTO THE Food Marketing Institute (2011 Trends survey)

Community Supported Agriculture

LocalHarvest-csa-growth-1980-2010

2010 Stats that might be available as series:
3,229 CSAs listed with LocalHarvest
the average sized CSA in the U.S. has 96 members
the median is 47
total number of shares offered by our CSAs is about 390,000

“If the number of CSAs keeps growing at the same rate as CSAs have been joining our site over the last three years, by 2020, there will be over 18,000 CSAs in the U.S.”

EMAILED LOCALHARVEST 6/24/16 TO INQUIRE ABOUT ANNUAL TALLIES AND RECENT FIGURES.
Guillermo Payet, President of LocalHarvest
gpayet@localharvest.org

src:
LocalHarvest, January 2010.
LocalHarvest Newsletter, January 28, 2010
image URL

UPDATE: LocalHarvest shared the following set of CSA and farmers’ markets tallies from their directory.

Src:
LocalHarvest. July 2016.
Private communication with Guillermo Payet, gpayet@localharvest.org

*

Data collected in 2012 by the U.S. Department of Agriculture indicates that 12,617 farms in the United States reported marketing products through a community supported agriculture (CSA) arrangement, a .5 percent increase over the 12,549 farms marketing through CSAs in 2007.

2012
Table 43. Selected Practices: 2012. In 2012 Census of Agriculture – State Data. p. 558. (2014) U.S. Department of Agriculture, National Agricultural Statistics Service.
See the column titled, “Marketed products through Community Supported Agriculture (CSA) (farms)” to find the number of farms that answered yes to the question, “At any time during 2012, did this operation market products through a community supported agriculture (CSA) arrangement?”
See also: 2012 Agricultural Census Home page

2007
Table 44. Selected Practices: 2007. In 2007 Census of Agriculture – State Data. p. 606. (2009) U.S. Department of Agriculture, National Agricultural Statistics Service.
See the column titled, “Marketed products through Community Supported Agriculture (CSA) (farms)” to find the number of farms that answered yes to the question, “At any time during 2007, did this operation market products through a community supported agriculture (CSA) arrangement?”
See also: 2007 Agricultural Census Home page

src:
AFSIC staff. April 2016.
Community Supported Agriculture: Surveys and Statistics.
USDA National Agricultural Library. Alternative Farming Systems Information Center.

*

The USDA Agricultural Marketing Service maintains several local food directories, including one for CSAs.

For questions about the Local Food Directories, please contact:
Edward Ragland, Economist
directoryupdates@ams.usda.gov
202.690.1327

EMAILED EDWARD RAGLAND 6/24/16 TO INQUIRE ABOUT HISTORIC STATISTICS.

src:
Local Food Directories
USDA Agricultural Marketing Service. Accessed June 24, 2016.

Food Miles

CC NOTES: Having trouble finding good time series data on this. The sources below cite data from individual locations (mostly iowa). Haven’t found any nationally representative time series averages. I wrote to Rich Pirog (6/24/16) at the Leopold Center to inquire about any national time series data, and he referred me to the paper by Weber and Matthews, below. They cite somewhat limited CFS data. I also emailed Matthews and he said it should be possible to pull additional CFS data for a more complete picture of change over time. See my additional notes below the excerpts for that paper.

*

“Globalization from 1997 to 2004 increased the average distance moved by food by around 25%, from 1640 km (1020 mi) directly and 6760 km (4200 mi) in total to 2050 km (1250 mi) directly and 8240 km (5120 mi) in total.”

“We suggest that dietary shift can be a more effective means of lowering an average household’s food-related climate footprint than “buying local.” Shifting less than one day per week’s worth of calories from red meat and dairy products to chicken, fish, eggs, or a vegetable-based diet achieves more GHG reduction than buying all locally sourced food.”

Src:
Christopher L. Weber and H. Scott Matthews. April 2008.
Food-Miles and the Relative Climate Impacts of Food Choices in the United States.”
Environ. Sci. Technol., 2008, 42 (10)

Citing: the US Census [Commodity Flow Survey] and Department of Commerce [Input-Output Accounts Data]

EMAILED THE PAPER AUTHORS 6/27/16
chris@2degrees-investing.org, hsm@cmu.edu
Neither of the authors have done any other work with this data, but Scott Matthews says it should be possible for us to pull additional historic CFS data to get a bigger picture of the change over time. Matthews says that they performed an “embedded transportation” calculation (total miles shipped from beginning to end) that wouldn’t show up in the CFS data. But we should be able to perform that same calculation using an input-output model (and perhaps referring to the discussion in Matthews’ paper.

TO-DO: PULL ADDITIONAL HISTORIC CFS DATA TO INFORM OUR EXTRAPOLATION.

*

Several surveys from different wholesale markets in the United States show that fruits and vegetables are traveling between 2,500 and 4,000 kilometers from farm to market, an increase of roughly 20 percent in the last two decades.

src:
Brain Halweil. 2002.
Home Grown: The Case for Local Food in a Global Market.
Worldwatch Paper 163. Worldwatch Institute.

citing:
United States surveys from Hora and Tick, op. cit. note 2, and Rich
Pirog et al., “Food, Fuel, and Freeways: An Iowa Perspective on How Far Food Travels, Fuel Usage, and Greenhouse Gas Emissions” (Ames, Iowa: Leopold Center for Sustainable Agriculture, Iowa State University, 2001), pp. 1, 2

*

A food mile is the distance food travels from where it is grown or raised to where it is ultimately purchased by the consumer or other end-user. One 1969 estimate of miles traveled by food in the United States cited an average distance of 1,346 miles (47). Calculations
made by John Hendrickson using a 1980 study examining transportation and fuel requirements estimated that fresh produce in the United States traveled an estimated 1,500 miles (48). Fresh produce arriving in Austin, Texas, was estimated to travel an average of 1,129 miles (49). An analysis of the USDA Agricultural Marketing Service’s
1997 arrival data from the Jessup, Maryland, terminal market found that the average pound of produce distributed at the facility traveled more than 1,685 miles (50). This same study showed the average distance for fruits to be transported was 2,146 miles, while
the average for vegetables was 1,596 miles (51).

src:
Rich Pirog, et al. 2001.
Food, Fuel, and Freeways: An Iowa perspective on how far food travels, fuel usage, and greenhouse gas emissions.
Leopold Center. Iowa State University.
p.9
contact: rspirog@iastate.edu

citing:
47: U.S. Department of Defense. 1969. U.S. Agriculture: Potential Vulnerabilities. Stanford Research Institute, Menlo Park, CA.
48: Hendrickson, John. 1996. “Energy use in the U.S. Food System: A Summary of existing research and analysis.” Sustainable Farming-REAP-Canada. Ste. Anne-de’Bellevue, Quebec. Vol 7, No 4. Fall 1997.
49: ibid.
50: Hora, Matthew, and Jody Tick. 2001. “From Farm to Table: Making the Connection in the Mid-Atlantic Food System.” Capital Area Food Bank of Washington D.C. report.

*

Recent studies have shown that this distance has been steadily increasing over the last fifty years. Studies estimate that processed food in the United States travels over 1,300 miles, and fresh produce travels over 1,500 miles, before being consumed.

src:
Holly Hill. 2008.
Food Miles: Background and Marketing.

also citing:
The Leopold Center, Iowa State University (a 1998 study looking at the distance that 30 convention fresh produce items traveled to reach the Chicago Terminal Market).

and citing:
statistics on the volume of world agricultural trade going back to 1961

Farm Size and Diversity

USDA-farms-by-size-2002-2012

USDA-total-and-avg-farm-land-1982-2012

USDA-farms-by-size-1982-2012

USDA-farm-acres-harvested-use-2007-2012

TO-DO: LOOK INTO OLDER AG CENSUSES FOR FARMS-BY-SIZE DATA

src:
USDA. May 2014.
2012 Census of Agriculture.

Grocery Delivery Services

Brick Meets Click forecasts that online grocery spending in the US will reach between 11% and 17% in most markets by 2023. Up from 4% in 2014.

src:
Bill Bishop. October 2014.
What’s ahead for online grocery? Updated growth forecast & implications?” Slide 2. Brick Meets Click.

NOTE: Brick Meets Click is a research and consulting firm that tracks online grocery sales and advises businesses on meeting this demand.

Meals at/away from home

The average U.S. consumer spent 9.8 percent of disposable personal income (income available after taxes) on all food in 2007—5.7 percent on food at home and 4.1 percent on food away from home. The percentage of disposable income spent on all food, food at home, and food away from home remained constant from 2005 to 2007.

USDA-income-spent-on-food-1970-2007

src:
Annette Clauson. September 2008.
Despite Higher Food Prices, Percent of U.S. Income Spent on Food Remains Constant.
USDA Economic Research Service.

*

Food purchased away from home as a share of household food expenses

USDA-percent-of-food-away-1970-2012

Chart Data available in the following Google Sheet.

Original chart data source

src:
Economic Research Service. Accessed June 6, 2016.
Food-Away-from-Home
US Department of Agriculture, Food Expenditures.

*

Spending on dining out vs. grocery store purchases (total in the US, NOT per capita)

commerce-dept-total-spending-food-away-groceries-1992-2015

src:
Michelle Jamrisko. April 14, 2015.
Americans’ Spending on Dining Out Just Overtook Grocery Sales for the First Time Ever.
Bloomberg

citing:
Commerce Department

*

The percentage of dinners eaten at home that were actually made at home in the U.S.

NPD-dinners-cooked-at-home-1974-2014

NOTE: No/few numeric values in this article.
TO-DO: CONTACT NPD FOR THE ACTUAL YEARLY VALUES

src:
NPD Group
via:
Roberto A. Ferdman. March 5, 2015.
The Slow Death Of The Home-Cooked Meal.
The Washington Post

*

Daily energy intake of US adults by food source, 1965-1966 to 2007-2008
Smith-et-al-food-home-away-by-income-1956-2008
Figure 1

Trends in Time Spent Cooking for US adults from 1965–1966 to 2007-2008
Smith-et-al-time-spent-cooking-1965-2008
Table 2

src:
Lindsey P. Smith, et al. 2013.
Trends in US home food preparation and consumption: analysis of national nutrition surveys and time use studies from 1965–1966 to 2007–2008.
Nutrition Journal, 12(45).

citing the following data sources for Figure 1:
Household Food Consumption Survey (HFCS) of 1965–1966 (n=4,114), Nationwide Food Consumption Survey (NFCS) of 1977–1978 (n=12,935), Continuing Survey of Food Intakes by Individuals (CSFII) of 1989–1991 (n=7,750), CSFII of 1994–1996 (n=6,894), National Health and Nutrition Examination Survey (NHANES) of 2003–2004 (n=3,138), and NHANES of 2007–2008 (n=3,734).

data sources for Table 2:
Multinational Comparative Time-Budget Research Project (MCTRP) of 1965–1966 (n=1,888), American’s Use of Time Project (AUTP) of 1975–1976 (n=3,190), AUTP of 1985–1986 (n=2,391), National Human Activity Pattern Survey (NHAPS) of 1992–1994 and National Time Diary Study (NTDS) of 1994–1995 (n=6,291), American Time Use Study (ATUS) of 2003–2004 (n=24,382), and ATUS of 2007–2008 (n=17,282). Percentages and mean time spent cooking are adjusted to be nationally representative.

Scenarios

The Institute For The Future has published a set of scenarios imagining how we might experience food in the next decades.

Excerpts:

We’re entering a curious world of vibrating forks and designer orange juice, of microfarming and meat printing, of virtual meals and drone delivery. How will these technologies interact with changing human needs and desires? In this future, what lengths will we go to for to convenient food experiences? How will we know if our food was sustainably produced? How fresh can we get it, and what will that mean? How will we define satisfaction?

In combination with our map of the decade, Seeds of Disruption: How Technology is Remaking the Future of Food, these forecast perspectives offer a tool for exploring the edges of technological possibility in food and developing insights into how to use them to meet human values and needs.

iftf-artifactsustainability
Concepts such as carbon footprints and food miles, humane treatment of animals, ecosystems management, and waste reduction are all big concerns for eaters today. However, as our ability to take all of these to the extreme increases, we’ll see the tradeoffs and choices become more dramatic, creating diverse new sustainability standards. While eating road-kill and invasive species are, today, fringe behaviors, in a decade, they could become commonplace.

iftf-artifact-satisfaction
The ability to directly and precisely manipulate the human senses will open a new frontier for creating food experiences. Initial attempts to rewire taste will likely be around curbing the hardwired drives for fats and sugars to improve health. However, as we develop a more nuanced understanding of both the chemical and psychological components that make up how we perceive food, people will start hacking the senses for many different goals—maximizing bliss, recreating nostalgic meal experiences, or making healthy, but bland, foods more enjoyable.

iftf-artifact-freshness
Freshness-sensing packaging and produce stickers will provide more precise expiry information than traditional “best by” labels. However, this information has the potential to overload consumers with metrics and considerations that don’t help them make decisions. To truly make this information actionable, people will need solutions that make interacting with the new data intuitive and enjoyable.

iftf-artifact-convenience
In a decade, new technologies of coordination will make it possible to order almost anything from anywhere and have it arrive at a designated place and time. New platforms and smart logistics systems are poised to disrupt the largely untapped market for fresh food delivery. As the cold chain expands in places such as Brazil or China, rapidly urbanizing areas might leapfrog the less efficient supermarket model in favor of streamlined food delivery systems.

Src:
Institute for the Future. October 2013.
Seeds of Disruption: Forecast Perspectives, Overview.”
Artifacts from the Future.”

Tags: , , ,

Posted by Claudia Lamar on July 13, 2016 at 9:29 pm | comment count