ML12340A658

From kanterella
Jump to navigation Jump to search
Official Exhibit - NYS000408-00-BD01 - Moss & Qing, the Emergence of the Super-Commuter (February, 2012)
ML12340A658
Person / Time
Site: Indian Point  Entergy icon.png
Issue date: 02/29/2012
From: Moss M, Qing C
New York Univ
To:
Atomic Safety and Licensing Board Panel
SECY RAS
References
RAS 22883, 50-247-LR, 50-286-LR, ASLBP 07-858-03-LR-BD01
Download: ML12340A658 (17)
v • d • e


Text

United States Nuclear Regulatory Commission Official Hearing Exhibit NYS000408 Entergy Nuclear Operations, Inc.

In the Matter of:

(Indian Point Nuclear Generating Units 2 and 3) Submitted: June 29, 2012 c:..\,.~p..R REGlI~;. ASLBP #: 07-858-03-LR-BD01

  • l~'~.

Docket #: 05000247 l 05000286 Exhibit #: NYS000408-00-BD01 Identified: 10/15/2012

  • 0 Admitted: 10/15/2012 Withdrawn:

~ ~

....,,1-

? ~

0.... Rejected: Stricken:

        • il Other:

The Emergence of the "Super-Commuter" rv~itchell L. r,~oss and Carson Qing Rudin Center for Transportation New York University \rliagner School of Public Service February, 2012 The twenty-first century is emerging as the century of the "super-commuter," a person

'vvho 'vvoiks in the cential county of a given metiopolitan aiea, but lives beyond the boundaiies of that metropolitan area, commuting long distance by air, rail, car, bus, or a combination of modes.! The super-commuter typicany traveis once or hvice \Iveekiy for \J\!ork , and is a rapidiy growing part of our workforce. The changing structure of the workplace, advances in telecommunications, and the global pattern of economic life have made the super-commuter a new force in transportation.

Many workers are not required to appear in one office five days a week; they conduct work frOiT! horne, reiT!ote locations, and even while driving or flying. The international growth of broadband internet access, the development of home-based computer systems that rival those of the workplace, and the rise of mobile communications systems have contributed to the emergence of the super-commuter in the United States. Super-commuters are well-positioned to take advantage of higher salaries in one region and lower housing costs in another.

~v1any 'vvoikeiS aie not expected to physically appeai in a single office at all: the global economy has made it possible for highly-skilled workers to be employed on a strictly virtual basis, acquiring ciients anY\A!here and communicating via email, phone and video conference.

Furthermore, the global economy has rendered the clock irrelevant, making it possible for people to \,AJork, virtually, in a different time zone than the one in \vhich they live. Simply put, the workplace is no longer fixed in one location, but rather where the worker is situated. As a result, city labor sheds (where workers live) have expanded over the past decade to encompass not just a city's exurbs , but also distant, non-local metropolitan regions , resulting in greater economic integration between cities situated hundreds of miles apart.

j'\jYU's Rudin Center has found that super-commuting is a gro\AJing trend in major United States regions, with growth in eight of the ten largest metropolitan areas. 1 1 Washington, D.C. is not included in this study, as no data is available.

OAGI0001555_00001

Key Findings 2

  • Across the country, city labor sheds (where workers live) are expanding rapidly and super-commuter growth rates are far outpacing workforce growth rates. Super-commuting is on the rise among workers in the centrai commuting counties of ten of the largest metropolitan labor forces in the nation, with the exceptions of Atlanta and Minneapolis. As a result, labor sheds have expanded to include non-local regions; this trend is particularly apparent in Los Angeles and Chicago, where commuters from Northern California and SI. Louis, respectively, account for an increasingly larger share of the labor force (Figures 5-6).
  • As of 2009, super-commuters accounted for the greatest percent of the workforce in both Dallas and Harris (Houston) counties in Texas, at approximately 13% . The "Texas Triang!e" corridor features two of the five fastest-growing super-commutes over the past decade (Figure 3), and three of the five most common super-commutes among the nation's major cities in 2009 (Figure 4).
  • Seveial cities' supei-commuting iates stand out with exceptional giovvth:

ii DaUas-Ft. V\forth to Houston (Harris Co.) super-commutes [lave more Ulan tripied since 2002; Austin and San Antonio to Houston super-commutes have both more than doubied

  • Northern Caiifornia to Los Angeies (LA County) super-commutes have both more than doubled, in both San Francisco and San Jose MSAs
  • Boston to Manhattan super-commutes have more than doubled
  • Although super-commuters comprised only 3% of its workforce, Manhattan saw one of the fastest growth rates of these workers
  • Figure 7 illustrates the emerging super-commute corridors that will have increasingly closer social and economic integration within each other.
  • Super-commuters across the United States tend to be young (under 29 years old) and are more likely to be middle class than the average V"v'orker.
  • Future planning decisions should consider metropOlitan regions ' growth due to the increase of super-commuting and resultant inter-connectedness; while "twin cities" of the past typically sat 40 miles apart, the new "twin cities" stretch 100-200 miles away from one another, with ever-growing inter-commutes.

1 Source of Data: U.S. Census Longitudinal Employer-Household Dynamics OnTheMap data, hUp://onthemap.c es.census.gov/

2 OAGI0001555_00002

Figure 1

1) Harris Co. (Houston), TX 251 :000 workers; 13.2% of workforce
2) Dallas, TX 176,000; 13,2%
3) Maricopa Co. (Phoenix), AZ 131,000; 8.6%
4) Fulton Co. (Atlanta), GA 47,700; 7.5%
5) Philadelphia, PA 42,100; 7.3%

Figure 2

1) Harris Co. (Houston), TX 98.3% increase
2) Los Ange!es, CA 76.7% increase
3) King Co. (Seattle), WA 60.4% increase
4) Manhattan (New York City), NY 60% increase
5) Philadelphia, PA 49.9% increase Figure 3
1) Dallas-Fort Worth to Houston, TX +218% (+35,600 total)
2) San Jose to Los Angeles, CA +153% (+7,600 total)
3) Yakima to Seattle, WA +131% (+3,000 total)
4) Boston, MA to Manhattan, NY +128% (+1,700 total)
5) San Antonio to Houston, TX +;;6% (+;6,700 totai) 3 OAGI0001555_00003

Figure 4 op uper-commu es mong aJor . . lies,

11) Tucson to Phoenix, AZ 3.6% of workforce (54,400 total)

! 2) Houston to Dallas, TX 3.3% (44,300 total)

I 3) Dallas-Fort Worth to Houston. TX 2.7% (51,900 total) i 4) Austin to Dallas, TX 2.4% (32,400 total)

15) San Diego to Los Angeles, CA 2.2% (78,300 total)
  • ".lI,mong Top 5 supE'r-commuting home dE'stinations of centra! countiE's in 10 !argE'st mE'tro areas by workforcE' size in 2009.

Figure 5 Top Non-local labor Sheds of l",,1ajoi U.S_ Cities, 2009

.. Home doo;tnat:o ,of 1.O%.tc 2.0%8f *;;o~kfo:ce 4

OAGI0001555_00004

Figure 6 Top Non-local labor Sheds of Major U.S. Cities, 2002

- j-iC):llf" r:Fsti.1;'lti"n nf ~l,,'i' Th~f* 2.(f.;" rlf W"',f:Xf~

5()wc~:

/,;.:JTi:~.

u.s C~!!~l;\ i.u"1(iii~*:lirld frrl(;.'Uiel ;';u!Jsd ..*ufdDy,,'~':ni.~;.

Oi"'r;'-.! '-'f(~",lr",dJi" !W' ... 'i 'rk "'"';;'ul,il-". l,/,,'~ ,;'u ,i ;,", .-11/ '!,'-'f'-!l~":

f;" .. .,..' -"r,;;;""'-I' -;'i'j,;r,-", I" 1,-: ';j.~ .. ,~':, n'If"',I,; ,.

fDr [o./C'lN *'['(k"-'i'~. CDC" .f~r L;;ic~:qo* ."llfton for ~,IOll::a Each bubble represents a Metropolitan Statistical Area (MSA) located outside the Combined Statistical Area (CSA) of the central county.

Figure 7 Emerglng$uper-commutlng Corridors Among Major Citv Workforces, 2009 5

f,.,,,,,,,:;;<; ,(,.";':;,,, ,.:r.",:" ""',~.- """:~u' ;". ".,>,:;(!~, :""i,:c*"" ',.1 :*1.".'

_:.~.~,: ,*'h;,;:"*'; v.'<),U<.",-".-: f:,:,*,~~,j,,;.r""~} ,)",' ,)'13 >>':)' eM,'! ""!::'~~:";:->>':\v::,:

OAGI0001555_00005

Methodology This study classified any individual who lives beyond the census-defined Combined Statistical Area of their workplace as a "super-commuter." Using the U.S. Census Longitudina! Emp!oyer-Household Dynamics OnTheMap data tool 3 , the study analyzed home destination data for all workers in the centrai counties of the ten iargest metropoiitan regions in the United States by workforce size. For instance, in the case of the New York City metropolitan area, the workforce study area was the central county of Manhattan; individuals living within the New York City Metropo!itan Statistical ,a,rea (MS,l!..) and surrounding MS,a,s (i.e. Bridgeport, New Haven, Poughkeepsie, and Trenton) that were included as part of the CSA were considered part of the "local labor shed." Individuals of MSAs beyond the New York City-Newark-Bridgeport CSA were considered part of the non-local labor shed and classified as "super-commuters."

However, because OnTheMap does not identify the travel patterns of individuals in the non-local labor shed, this study cannot ascertain \"Ihether a!1 of these individuals can be considered "super-commuters" in the truest sense, since the study interpreted an actual super-commute as an occasionai (ciarify in parenthesis) iong-distance trip, such as once or twice per week, made for work purposes by a variety of intercity travel modes. These figures and trends on "super-commuting" should be interpreted as potential or likely super-commuters, since the data only reflects residential location. \lVhat these figures do represent for certain is the expansion of city labor sheds (vvhere workers live) beyond the exurbs of the metropolitan region, spilling into other regions that are hundreds of miies away.

Demographic Characteristics and Implications In general, the super-commuter is younger than the average worker. In fact, in all ten major centra! commuting counties, the proportion of 'Norkers younger than 29 years old among super-comrnuters was higher tI-lan tI-le sl-lare of under-29s of the entire workforce, indicating that a supercommuter is more likely to be less than 29 years old than the average worker (Figure 9).

However, older age groups of super-commuters are increasing; some of these trends can be attributed to demographics, since the US population as a whole is aging as the baby boomers reach retirement age. But in relative terms, vv'hen comparing the share of super-commuters of each age cohort (29 or younger, 30-54, or 55 or oider) with thai of the entire workforce, super-commuters still are increasingly represented by the older age cohorts. For instance, in Manhattan, the share of 55+ year-old workers in the workforce grew by 15% from 2002 to 2009, but among super-commuters, the share of 55+ workers grew by 21.6%. Similar trends were also present among super-commuters to Houston, Dallas, Philadelphia, and Minneapolis (Figure 10).

Segregating the super-commuters by income cohorts also reveal 1I-lat they are more likely to come from middle-ciass backgrounds (iess than $40,000 per year) than individuais in the iocai labor shed. In each of the ten major central commuting counties, high-income (earn more than

$40,000 per year) individuals represented a smaller proportion of super-commuters than that of the entire \Norkforce (Figure 11).

3 http://onthemap.ces.census.gov/

6 OAGI0001555_00006

The reiative prevaience of middie-income earners among super-commuters may aiso be reiated to the fact that super-commuters are younger than the average worker, when salaries tend to be lower. However, even though super-commuters are increasingly older, they are not necessarily increasingly more affluent in most major cities, vlJith the exceptions of i6..t!anta, Minneapo!is, and Seattle. VVhile in absolute terms, the total number of super-commuters in the highest income cohort has more than doubled In New York, Houston, and Seattle, the total number of workers in that income cohort has also grown at a fast rate: the percent change in the share of high-income workers among super-commuters has not kept pace with that of the workforce as a

\vhole (Figure 12). This data suggests that 'Nhi!e super-commuters are increasingly high-income in absoiute terms, they have increasingiy middie-ciass incomes when compared to the rest of the workforce. Thus, the super-commuting population should not be perceived as elite business travelers, but rather more representative of middle-income individuals who may opt for more affordable housing and means of transportation, sLlch as driving or intercity buses.

Geographic Characteristics and impiications The emergence of the super-commuter has created unique geographic characteristics for many metropolitan areas. As Figures 4-5 show, the growth in super-commuting has made the geographic boundaries of metropolitan areas increasingly challenging to define. As a rule of thumb, the U.S. Census Bureau bases its metropolitan area boundaries on the degree of "social and economic integration, as measured by commuting to work" between adjacent areas and the urban core. But as labor sheds expand and commuting patterns become increasingly interregional, particularly in Texas, California, and the Northeast Corridor, the applicability of commuting patterns to define metropolitan geographies is less relevant today than a decade ago. Given ii-lese advances in telecommunications, the degree of "social and economic integration" between regional urban centers has increased dramatically over the past decade, as illustrated by these recent trends in super-commutes.

The implications of the growth in super-commuting on the geographic characteristics of metropolitan regions reinforce theories and interpretations of American cities as increasingly integrated: Jean Gottmann (1961) was the first to introduce the concept of a "megalopolis" based on the siring of urban aggiomerations aiong ihe Northeast Corridor exiending from Washington D.C. to Boston, highly connected by a vast intercity transport infrastructure consisting of short flights, superhighways, long-distance buses, and passenger rail". More recently, think tanks such as the Regiona! Plan ,.6.,ssociation and the Brookings Institution have also inteipieted 21 st century Ameiican cities as incieasingly "megalopolitan" in natuie to advocate ior investments in intercity transport inirastructure such as high-speed raii"', or ior a shift towards "mega-regional" planning and closer economic cooperation between cities". This shift would certainly apply to regions such as the Arizona "Sun Corridor" from Tucson to Phoenix, the "Texas Triangle" mega-region, and in Ca!ifornia, a!1 of 'v".thich are nov..' already '..veU-esiablisi'"led super-cornmuie corridors, suggesting a greaier degree of economic iniegraiion.

Such an approach to metropolitan planning may also be relevant in the future for regions where super-commuting is rapidly growing, such as Portland-Seattle in the Pacific Northwest, SI.

7 OAGI0001555_00007

Louis-Chicago and Detroit-Chicago in the iviidwest, and Piiisburgh-Phiiadeiphia and Boston-New York City in the Northeast.

This expansion of city labor sheds exemplifies how the economic geography of American cities has evolved in the information age, as cities begin to share labor/commuter sheds and social and economic activities become increasingly inter-regional. '/Vhi!e city-regions, such as iviinneapolis-St. Paul, San Francisco-Oakland, tile Nortll Carolina Researcll Triangle, and Dallas-Fort Worth, are already highly integrated due to proximity, technological advances over the past 20 years in broadband, mobile communications, and teleconferencing has made geographic proximity a less relevant precondition for metropolitan integration. A new "Twin Cities" can be characterized by Phoenix-Tucson: Phoenix super-commuters from Tucson accounted for a greater share of the county's workforce than any of the 10 major counties included in this study. While traditional Twin Cities like Dallas-Fort Worth are typically situated no more than 40 miles from each other, the Phoenix-Tucson "Sun Corridor" stretches for more than 100 miles. Similarly, the emerging "Texas Triang!e" cities are more than 200 miles from each other, compared to the original Triangle metropolis of Raleigh-Durham-Chapel Hill, 'vvhich are no more than 30 miies apart.

These trends towards urban Integration and "super-commuting" are not necessarily limited to the United States To compete in the global economy, nations around the world are seeking to establish economically competitive "mega-regions" that are highly connected both in terms of socia! and economic activity and infrastructure, such as the Pear! River Deita and Yangtze River Deita rnegaiopoiises in Crlina, trle Rio-Sao Pauio corridor in Brazii, and the Gauteng rnega-region in South Africa, with enormous investments in high-speed rail and super-highway systems. Richard Florida, et al. (2007) argues that in the 21" century global economy, these integrated mega-regions wil! play an increasingly important role in both advanced and emerging nations as drivers of economic grov"v'th v . Thus, the gro'v"v'th in super-commuting nationwide and the increased ievei of economic integration between distant cities can present metropoiitan regions with tremendous opportunities to become more economically competitive through increased coordination in goals, resources, and policymaking.

8 OAGI0001555_00008

MANHATTAN Center of New York Ciiy-Newark-Bridgepori eSA Metropolitan Area of Residence for Non- 2009 Total Percent

2) AibanY1 NY 7,700 +47.5%

3, Syracuse. NY 3.400 +51.2%

4, Boston, MA-NH 3.100 +128%

5) Buffaio, NY 2,;00 -7.2%
6) Binghamton. NY 2.300 +75.5%

increase in super-commuters 2002-09 7) Allentm',;n, PA-NJ 2,300 +71.2%

H% growth in primary jobs 2002-09 8) Rochesrer, f'lJY 2,100 +83.g%

>~, UUU super-commuters 9~ Hartford , CT 1.900 +62:.2%

"",n,

.) -/0 of workforce

..,. ..,. ..,. ,. ,. 10} East Stroudsburg, PA 1,600 +129%

i&.i&., i&.UU total increase in super-commuters

..tInOI I ;:I 70 more likely to be 29 years or younger than average worker 49% more likely to earn less than $15,000 per year than average worker

.,t: 1:.0'-*. .. _ .... _. ____ .

~U. 'ttII IU Increase In snare or super-commurers earnmg more rnan :54U,uuulyear "28.3% increase in share oftotai IVIanhattan workers earning more than $40,OOOlyear. indicates that in relative terms, super-commuters are stU; have increasingiy iower to middie income characteristics than the rest of the workforce.

Pert"nt Change in Manhattan Super-Commuter. by I MSA of R.,sidence, 2002-09

'1

.-:~'X

'W M"<ftf;".~ t{)C~:("'<>"l~

@ T"'*k<*j<t...<'):'.:<":<'<<,,..~.

9 OAGI0001555_00009

TOP 10 SOURCES OF L.A. COUNTY'S SUPER-COMMUTING WORKFORCE LOS ANGELES Los Angeles County Center of Los Angeles-Long Beach-Riverside CSA

1) San Diego, CA 78,300 +47.4%
2) San Francisco, CA 35,700 +113%
3) Bakersfield, CA 27,600 +59.2%
4) San Jose, CA 12,500 +153%
5) Santa Barbara, CA 10,500 +26.5%
6) Sacramento, CA 10,400 +170%
7) Fresno. CA 7.800 +129%

7fi 7 01. growth in super-commuters 2002-09

  • ....... I U

., t:!0£ ... . . . .....

8) San Luis Obispo, CA 5,800 +42.5%

~. U 10 growth In prtmaryJobs 2002-09

.,-:l -:l

~'ttI~,UUV nnn super-commurers . 9) Visal;a, CA S,30!) +132%

6.4%; of workforce 10) EI Centro, CA 4,400 +73.5%

101 ,300 total increase in super-commuteis 290/0 more likely to be 29 years or younger than average worker 31 % growth in share of workers earning more than $40,OOOlyear, 2002*09 11 % growth in share of super-commuters earning more than .$4Q,QQQlyea" 2QQ2-09 S,,<.<r~ . , ~<"~ £;-..."s ..,,1.c"iJi""""'*'-~!

£m,<<,,,,,,,'~<-f!cu.-<<Jh,,,Jd C>"""',icos

-)--

10 OAGI0001555_00010

CHiCAGO Metro olitan Area of Residence for 2009 Total Percent Non-local Cook County Worker Super- Change Cook County commuters 2002-09 Center of Chicago-f'-Iaper"iffe-Jl.1ichigan City CSA

1) Rockford, IL 13,700 +4.8%
2) Peoria, It 7,700 +66.7%
3) St. louis, MO-IL 4,675 +94.8%
4) Champaign, IL 4,660 +64.2%

"Ii ...... n * ""." AOt

5) Springfield, It .),oJ'tu "rQ.).'t:to
6) Bloomington, Il 3,290 +67.5%

41.6%

A. ",nl growth in super-commuters 2002-09 7) Mi!waukee, WI 3,100 +5.2%

U *~ ~/o growth in primary jobs 2002-09 f t ft 1'\ I'\. I'\.

6; Quad Cities, IA-IL 3,000 +57.5%

~~,UUU super-commuters

.. .. 01 9) Detroit, MI 2,300 +131%

....... 70 of workforce 29,1 00 total increase in super-commuters 10) Indianapolis, IN 2,100 +85.3%

.,nOL ..... __ . i........_ _ . ------------------'

"'"V 10 more liKely to De 29 years or younger Inan average worKer 260/0 jess iikeiy io earn more than $40,OOOlyear than average worker Percent Change In Cook County 5upeH'.commuters by MSA of.' Re-sldenc-I! 2001T{l9 mi t,~: u<t; ~~"",r>'::3"<':

11

~,::: .$.,~. * :; N:

, I , 1 , .

OAGI0001555_00011

HOUSTON Metro olitan Area of Residence for 2009 Total Percent Non-local Harris County Worker Super- Change Haiiis County commuters 2002-09 Center of Houston-Ba;'town-Huntsvilfe CSA

1) Dallas-Fort Worth, TX 51,900 +218%
3) San Antonio, TX 31,100 +116%
4) Beaumont, TX 5,600 +0,0%

4,4.00

- 6) Corpus Christi, TX 4,100 +32,2%

growth in super-cotntnuters 2002-09 7) E! Campo, TX 4,000 +0.0%

9.30/0 growth in primary jobs 2002-09 6; Victoria, TX 2,730 +34,0%

251,200 supe,-commuie,s 9) Killeen-Temple, TX 2,660 +50,4%

13.2% of workforce 10). M¢All$i1, .TX: ~,500 +219%

124,500 total increase in sup8r~commut8rs 170/0 more like!}1 to be 29 }o/ears or younger than average Lil/orker 7 !! less likely to earn more than $4Q,OQQ/year than average worker Percent Change in Harris Cm.mty Sop-er-(:tHl'Hnuters by MS.a,pf ResiQence2:0()1--09 12 OAGI0001555_00012

DALLAS Metro olitan Area of Residence for 2009 Total Percent Non-local Dallas County Worker Super- Change Dallas County commuters 2002-09 Center of Dallas-Fort ~Alorth CSA

1) Houston, TX 44,300 +52.1%
2) Austin, TX 32,400 +51.5%
3) San Antonio, TX 13,800 +57.6%
4) Waco, TX 5,600 +0.0%

... ~nT

5) Tyler, IX liliAn

.. , .... UU -").v'lo

- 6) Killeen-Temple, TX 4,100 +32.2%

38.4% growth in super-cotntnuters 2002-09 7) LDngview, TX 4,000 +0.0%

1.70/0 growth in primary jobs 2002-09 6; Corsicana, TX 2,730 +34.0%

175,700 supe,-commuie,s 9) Abilene, TX 2,660 +50.4%

13.2% of workforce

10) McAllen, TX 2,500 + 219%~

48,700 total increase in sup8r~commuters 15% more like!}1 to be 29 }o/ears or younger than average Lil/orker 11 %less likely to earn more than .$4Q,QQQ/year than average worker ..~.'

Percent chan:ge in Danes county SHpe-r-.:.::ommut~r:s bV MS.A. of R~std;enre 1-002-4)9 13 OAGI0001555_00013

Fulton County Center of Atianta-Sandy Springs-Gainesville CSA County Labor Force Growth Rate 2002-09: -3.4%

47,700 super-commuters (7.5% of workforce), 19.5% decrease since 2002 Top 5 MSAs of residence for super-commuters, percent change 2002-09:

1) Augusta, GA-SC 4,200 super-commuters, -22.6% since '02
2) Macon, 3,800, -23.4%
3) Columbus, GA-AL, 3,500, -21.6%
4) Athens, GA, 2,900, -97%
5) Rome, GA., 2,000, +4.7%

Philadelphia County Center of Phi!ade!phia-Camden-Vineland CSA County Labor Force Gro'vvth Rate 2002-09: +1.5%

42,100 super-commuters (7.3% of workforce), 49.9% increase since 2002 Top 5 MSAs of residence for super-commuters, percent change 2002-09:

'1) Aiientown-Bethiehem, PA-Nj, 6,300 super-commuters, +41.1% since '02

2) New York City, NY-NJ-PA, 5,800, +42.8%
3) Pittsburgh, 4,200, +95.2%
4) Harrisburg, 3,200, +30%
5) Lancaster, 3,160, +42.1%

Maricopa County Center of Phoenix-Mesa-Scottsdale MSA 2002 home destination data is not available.

131,100 super-commuters (8.6% of workforce) in 2009 Top 5 MSAs of residence for super-commuters in 2009

1) Tucson, 54,400 super-commuters
2) Prescott, ,11,Z: 18,500
3) Yuma, 8,700
4) Lake Havasu City-Kingman, 8,100
5) Flagstaff, 8,000 NOTE: 9) Los Angeies, 3,400 Hennepin County Center of Minneapolis-Sl. Paul-Sl. Cloud CSA 40,000 super-commuters (5.2% of workforce), 2.5% decrease since 2002 Top 5 MSAs of residence for super-commuters, percent change 2002-09:
1) Duluth, MN-WI, 5,300 super-commuters, -13.5% since '02
2) Rochester, MN, 4,100, -12.2%
3) Mankato, MN, 2,160, -3.4%
4) Brainerd , MN, 1,670 , -16%
5) Wi!lmar, MN, 1,050, +10.3%

14 OAGI0001555_00014

King County Center of ::;eattie-Tacoma-Oiympia CSA 71,000 super-commuters (6.8% of workforce), 60.4% Increase since 2002 Top 5 MSAs of residence for super-commuters, percent change 2002-09:

1) Portland, OR-WA, 12,900 super-commuters, + 72.8% since '02
2) Spokane, 7,700, +7.2%
3) Bellingham, WA, 6,700, +20.4%
4) Yakima, WA, 5,300, +131%
5) Kennewick, WA, 4,800, + 112%

Demographics of Super-Commuters Figure 9 Percent Under 29 Years Old by County Workforce and Super-commuters, 2009 35.0% ,'. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..

30.0%

25.0%

~

~ 20.0%

o

~

~ 15.0%

~

10.0%

5.0%

0.0%

LA. CHI HOU D.A.L .A.TL PH! PHX M!N SE.A.

Primary City

~VVorkfOice ,~::: SUpeiGOmmuters 15 OAGI0001555_00015

Figure 10 Percent Change in the Share of County Workforce and Super-commuters Oider than 55 Years, 2002-09

~, 40.0%

ci o

35.0%

C\I 30.0%

g, 25.0%

iii

... 20.0%

U c:

~

15.0%

10.0%

Q) 0- 5.0%

NYC LA CHI HOU DAl ATl PH! MIN SEA Primary City "Workforce ';;; Supercommuters Figure 11 Percent Earning More than $40,000rfear by County Workforce and Supercommuters, 2009 70.0%

60.0%

_ 50.0%

-5

~ 40.0%

~ 30.0%

.... 20.0%

10.0%

0.0%

NYC LA CHI HOU DAL ATL PHI PHX MIN SEA

~~~i>'!; Primary City

~~~

~AA~~~

  • <<"."",'<<C~'*"'*'"***~.**':'''''' IlWorkforce ,::; Supercommuters 16 OAGI0001555_00016

Figure 12 Percent Change in Share of County \"Jorkforce and Supercommuters Earning More than $40,000lYear 2002-09 60.0%

50.0%

~ 40.0%

0" 30.0%

~

~

~

0. 20.0%

10.0%

0.0%

lA CHI HOU DAl All PHI MIN SEA Primary City

.. Workforce  :::~ Supercommuters References I Rigby, Rhymer. "Business Traveier: The Rise of the Super-Commuters." The Financiai Times. 27 December 20*j*j.

II Guiiman, Jean. Mf;:igaiupuii::;; Thf;:i UrVan;zf;:icJ NurUlf;:iaSlf;:irn Sf;:iaVUard uflhf;:i UnHf;:icJ Slalf;:is. 15 iVia[Ch 1964. The MiT Press.

III Hagler, Yoav & Todorov1ch, Petra. "\l\/here High Speed Rail \l'Jorks Best." America 2050.17 September 2009.

rv Lang, Robert & Nelson, Arthur. "Megapolitan America." The Design Observer. 14 November 2011.

v F!orida, Richard, Gu!den, Tim, & Me!!ander, Char!otta. "The Rise ofthe Mega Region." October 2007 17 OAGI0001555_00017

Retrieved from "https://kanterella.com/w/index.php?title=ML12340A658&oldid=2459188"