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    AASHTO CA05-4-2015 Brief 5 The Nature and Pattern of Jobs.pdf

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    AASHTO CA05-4-2015 Brief 5 The Nature and Pattern of Jobs.pdf

    1、Brief 5. The Nature and Pattern of Jobs Ja Nuary 2015 Commuting in a merica 2013 The National Report on Commuting Patterns and TrendsAbout the AASHTO Census Transportation Planning Products Program Established by the American Association of State Highway and Transportation Officials (AASHTO) and the

    2、 U.S. Department of Transportation (U.S. DOT), the AASHTO Census Transportation Planning Products Program (CTPP) compiles census data on demographic characteristics, home and work locations, and journey- to-work travel flows to assist with a variety of state, regional, and local transportation polic

    3、y and planning efforts. CTPP also supports corridor and project studies, environmental analyses, and emergency operations management. In 1990, 2000, and again in 2006, AASHTO partnered with all of the states on pooled-fund projects to sup- port the development of special census products and data tab

    4、ulations for transportation. These census transpor- tation data packages have proved invaluable in understanding characteristics about where people live and work, their journey-to-work commuting patterns, and the modes they use for getting to work. In 2012, the CTPP was established as an ongoing tec

    5、hnical service program of AASHTO. CTPP provides a number of primary services: Special Data Tabulation from the U.S. Census BureauCTPP oversees the specification, purchase, and delivery of this special tabulation designed by and for transportation planners. Outreach and TrainingThe CTPP team provides

    6、 training on data and data issues in many formats, from live briefings and presentations to hands-on, full-day courses. The team has also created a number of electronic sources of training, from e-learning to recorded webinars to downloadable presentations. Technical SupportCTPP provides limited dir

    7、ect technical support for solving data issues; the pro- gram also maintains a robust listserv where many issues are discussed, dissected, and resolved by the CTPP community. ResearchCTPP staff and board members routinely generate problem statements to solicit research on data issues; additionally, C

    8、TPP has funded its own research efforts. Total research generated or funded by the current CTPP since 2006 is in excess of $1 million. Staff Penelope Weinberger, CTPP Program Manager Matt Hardy, Program Director, Policy and Planning Jim Tymon, Chief Operating Officer/Director of Policy and Managemen

    9、t Project Team Steven E. Polzin, Co-Author, Center for Urban Transportation Research, University of South Florida Alan E. Pisarski, Co-Author, Consultant, Falls Church, Virginia Bruce Spear, Data Expert, Cambridge Systematics, Inc. Liang Long, Data Expert, Cambridge Systematics, Inc. Nancy McGuckin,

    10、 Data Expert, Travel Behavior Analyst Contact Penelope Weinberger, e-mail: pweinbergeraashto.org, phone: 202-624-3556; or CTPPinfoaashto.org 2015 by the American Association of State Highway and Transportation Officials. All rights reserved. Duplication is a violation of applicable law. Pub Code: CA

    11、05-4 ISBN: 978-1-56051-575-3 2014 by the American Association of State Highway and Transportation Officials. All rights reserved. Duplication is a violation of applicable law.Commuting in America 2013: The National Report on Commuting Patterns and Trends Brief 5. The Nature and Pattern of Jobs This

    12、brief is the fifth in a series describing commuting in America. This body of work, sponsored by the American Association of State Highway and Transportation Officials (AASHTO) and carried out in conjunction with a National Cooperative Highway Research Program (NCHRP) project that provided supporting

    13、 data, builds on three prior Commut- ing in America documents that were issued over the past three decades. Unlike the prior reports that were single volumes, this effort consists of a series of briefs, each of which addresses a critical aspect of commuting in America. These briefs, taken together,

    14、comprise a comprehensive summary of American commuting. The briefs are disseminated through the AASHTO website (traveltrends.transportation.org). Accompanying data tables and an Executive Summary complete the body of information known as Commuting in America 2013 (CIA 2013). Brief 5 describes the ch

    15、anges taking place in employment patterns in the U.S. from the perspective of how this might influence commuting. This brief completes the information about the work force and employment presented in Briefs 3, 4, and 6. Jobs Versus Workers Brief 3 described workers as a component of the population a

    16、nd provided a comprehensive overview of changes in the workforce as they relate to the demographic characteristics of the population. Brief 4 provided more detailed descriptive data covering the geographic location of workers. Not surprisingly, there is a strong inherent relationship between jobs an

    17、d workersneither can exist without the other, at least not for any length of time. At the national level, aggregate disparities between jobs and workers can be explained by measures of vacant positions and unemployed workers. These measures do not add particular insight when trying to understand com

    18、muting trends. However, at more detailed levels of geogra- phy, there can be significant variations between the nature and counts of jobs and counts of appropriately-credentialed workers, and these disparities can influence commuting patterns as workers travel to fill available positions. Brief 15 d

    19、iscusses the flow of workers between geographies; this brief provides summary information on the location of jobs by geography. The geographic location of jobs is influenced by a host of considerations. The top factors include access to markets or customers for retail and service activities, access

    20、to labor force, and access to materials/resources for jobs that involve working with physical commodities. The location of some employment types is constrained by the need to be in proximity to certain locations. For example, rapid growth in employment in energy extraction in North Dakota is driven

    21、by and dependent on being in proximity to the states oil- and gas-bearing formations. Other jobs, such as healthcare, materialize in proximity to populations that 2014 by the American Association of State Highway and Transportation Officials. All rights reserved. Duplication is a violation of applic

    22、able law.4 Commuting in America 2013: The National Report on Commuting Patterns and Trends need services. In some situations, the growth of jobs (e.g., North Dakota energy extraction) attracts workers and, subsequently, generates more jobs to provide services to the growing population. In other case

    23、s, the growth of population is associated with the appeal or ame- nities in a given area, which then creates new employment (e.g., retirees moving to mild Southern climates, creating service and healthcare jobs to serve that population). Attractive, amenity-rich areas can also attract employment who

    24、se location is not constrained by access to natural resources or local markets (i.e., software, pharmaceuticals, some technologies, and some services that are dependent upon national or international markets), which subse- quently attracts population and supporting employment. Commuting patterns are

    25、 created as the various factors that influence the location of jobs and households play themselves out. Brief 4, in a series of tables 1 , described current population levels and their geographic dis- tribution patterns and further traced population trends for the main national geographic units from

    26、 19902010. These tables establish the framework for examining worker and job trends. Table 5-1 provides a national-level summary for 2010 for population and the associated worker and jobs levels within those geographic categories for metropolitan areas. Figure 5-1 presents the distribution of worker

    27、s, population, and jobs by area type graphically. Table 5-1. Geographic Distribution of Population, Workers, and Jobs, 2010 Geography Population Workers Workers per Capita Jobs Jobs per Worker MetroCentral Cities 75,283,196 27,899,370 0.37 40,536,506 1.45 MetroOther Principal Cities 24,065,670 9,340

    28、,785 0.39 13,267,941 1.42 MetroSuburbs 163,103,266 71,420,007 0.43 57,306,197 0.80 MetroAll 262,452,132 108,660,162 0.41 111,110,644 1.02 Non-Metro (by Subtraction) 46,293,406 28,280,848 0.61 25,830,366 0.91 T otal U.S. 308,745,538 136,941,010 0.44 136,941,010* 1.00 Central City Share 24.3% 20.3% 29

    29、.6% Other Principal City Share 8.8% 6.8% 9.7% Suburban Share 52.8% 52.2% 41.8% Non-Metro Share 15.0% 20.7% 18.9% *For purposes of analysis, total U.S. jobs set to equal workers. Source: Summary of ACS data 1Commuting in America 2013, Brief 4, “Population and Worker Dynamics, ” Tables 4-7, 4-8, 4-9.

    30、2014 by the American Association of State Highway and Transportation Officials. All rights reserved. Duplication is a violation of applicable law.5 Brief 5. The Nature and Pattern of Jobs Figure 5-1. Distribution of Jobs, Workers, and Population by Area Type Source: Summary of ACS data Key points: M

    31、etro areas have approximately 85 percent of the nations population, 79 percent of its workers, and 81 percent of the jobs. Workers per capita is lowest in the central cities and is similarly modest in the other principal cities. It is higher in the suburbs and significantly higher in non-metro areas

    32、. In something of an inverse relationship, jobs per worker is greatest in central cities and other principal cities and lowest in the suburbs. Jobs per worker is somewhat higher in non-metro areas but well below levels in central cities. While age is a factor (children and retirees), central cities

    33、have the lowest labor force participation, yet the greatest ratio of jobs per worker. Comparing workers and jobs in metro areas provides an important insight. There are roughly 2.5 million more jobs than workers in metropolitan areas, meaning there is a net flow each day of non-metro workers into me

    34、tro areas. Approximately 20 percent of suburban workers must travel outside the suburbs to find employment, and more than 30 percent of central city and other principal city jobs must be filled by commuters from outside the geography. 0% 10% 20% 30% 40% 50% 60% Central City Share Other Principal Cit

    35、y Share Suburban Share Non-Metro Share Jobs Workers Population 2014 by the American Association of State Highway and Transportation Officials. All rights reserved. Duplication is a violation of applicable law.6 Commuting in America 2013: The National Report on Commuting Patterns and Trends Table 5-2

    36、 itemizes population, workers, and jobs by Metro area size for all Metropoli- tan Statistical Areas (MSAs) and Consolidated Statistical Areas (CSAs) of over one million population. This encompasses 130 MSAs, with some CSAs, such as New Y ork, comprising up to seven separate MSAs. The far right-hand

    37、column in this table summarizes “surplus jobs, ” which is the difference between total MSA workers and total MSA jobs. A positive surplus jobs number means that workers from surrounding areas travel to the respective MSA to fill the available positions. Of the 54 CSAs included in the Table 5-2, all

    38、but 11 import workers. Table 5-3 itemizes population, workers, and jobs for the central cities within the respective CSAs. As defined for the purposes of this series of briefs, each MSA has oneand only onecentral city, representing the Prin- cipal City with the largest population. CSAs are shown in

    39、italics in the tables. Core cities remain relatively worker- poor and job-rich, relying on suburbs and, to some extent, non-metro areas to provide workers. 2014 by the American Association of State Highway and Transportation Officials. All rights reserved. Duplication is a violation of applicable la

    40、w.7 Brief 5. The Nature and Pattern of Jobs Table 5-2. Population, Workers, and Jobs by Metro Area Size, 2010 Source: Cambridge Systematics, summary of ACS data CSA/MSA Name Number of MSAs Population Size Group MSA Population (2010) T otal MSA Workers (2010) T otal MSA Jobs (2010) Surplus Jobs in MS

    41、A (2010) New York CSA 7 Over 5M 22,886,737 9,672,282 9,657,479 (14,803) Los Angeles-Riverside CSA 3 Over 5M 17,877,006 6,968,876 7,036,843 67,967 Chicago CSA 3 Over 5M 9,686,021 4,159,124 4,244,251 85,127 Washington-Baltimore CSA 6 Over 5M 8,981,561 4,103,105 4,246,093 142,988 San Francisco-San Jose

    42、 CSA 7 Over 5M 8,153,696 3,371,058 3,463,350 92,292 Boston-Providence CSA 5 Over 5M 7,686,843 3,746,882 3,761,760 14,878 Philadelphia CSA 6 Over 5M 7,067,807 3,082,013 3,033,987 (48,026) Dallas CSA 2 Over 5M 6,547,091 2,836,239 2,925,743 89,504 Miami CSA 3 Over 5M 6,126,770 2,279,074 2,277,159 (1,91

    43、5) Houston-The Woodlands-Sugar Land, TX 1 Over 5M 5,920,416 2,457,177 2,528,846 71,669 Atlanta CSA 3 Over 5M 5,658,953 2,266,993 2,355,493 88,500 Detroit CSA 4 Over 5M 5,218,852 2,005,783 2,003,676 (2,107) Phoenix-Mesa-Scottsdale, AZ 1 2.55M 4,192,887 1,622,185 1,661,476 39,291 Seattle CSA 4 2.55M 4

    44、,060,107 1,730,685 1,803,498 72,813 Minneapolis CSA 2 2.55M 3,537,952 1,735,516 1,788,768 53,252 Cleveland-Akron CSA 3 2.55M 3,184,862 1,362,394 1,414,028 51,634 San Diego-Carlsbad, CA 1 2.55M 3,095,313 1,253,748 1,230,279 (23,469) Denver CSA 3 2.55M 3,090,874 1,392,312 1,435,097 42,785 Portland-Sal

    45、em CSA 5 2.55M 2,921,408 1,225,938 1,227,612 1,674 Orlando-Daytona CSA 3 2.55M 2,818,120 1,138,371 1,169,678 31,307 St. Louis, MO-IL 1 2.55M 2,787,701 1,228,715 1,256,692 27,977 Tampa-St. Petersburg-Clearwater, FL 1 2.55M 2,783,243 1,066,064 1,046,561 (19,503) Pittsburgh CSA 2 12.5M 2,480,739 1,115,

    46、507 1,134,900 19,393 Sacramento CSA 2 12.5M 2,316,019 893,921 880,252 (13,669) Kansas City CSA 3 12.5M 2,247,497 1,014,911 1,034,639 19,728 Charlotte-Concord-Gastonia, NC-SC 1 12.5M 2,217,012 888,779 910,853 22,074 Salt Lake City CSA 3 12.5M 2,211,842 909,632 931,095 21,463 Las Vegas CSA 2 12.5M 2,1

    47、51,455 852,167 857,108 4,941 San Antonio-New Braunfels, TX 1 12.5M 2,142,508 835,629 801,317 (34,312) Cincinnati, OH-KY-IN 1 12.5M 2,114,580 931,060 941,995 10,935 Indianapolis-Muncie CSA 3 12.5M 2,082,342 911,722 988,169 76,447 Columbus, OH 1 12.5M 1,901,974 827,727 877,731 50,004 Milwaukee CSA 2 1

    48、2.5M 1,751,316 811,299 864,872 53,573 Austin-Round Rock, TX 1 12.5M 1,716,289 753,790 800,514 46,724 Virginia Beach-Norfolk-Newport News, VA-NC 1 12.5M 1,676,822 676,349 674,008 (2,341) Nashville-DavidsonMurfreesboroFranklin, TN 1 12.5M 1,670,890 712,750 767,209 54,459 Raleigh-Durham CSA 2 12.5M 1,6

    49、34,847 709,566 812,046 102,480 Greensboro-Winston-Salem CSA 3 12.5M 1,515,527 615,083 628,035 12,952 Hartford-New London CSA 2 12.5M 1,486,436 663,581 719,182 55,601 Louisville CSA 2 12.5M 1,384,046 599,192 617,510 18,318 Jacksonville, FL 1 12.5M 1,345,596 569,775 653,161 83,386 Memphis, TN-MS-AR 1 12.5M 1,324,829 543,898 570,953 27,055 New Orleans CSA 2 12.5M 1,310,963 507,643 540,521 32,878 Oklahoma City, OK 1 12.5M 1,252,987 515,376 546,958 31,582 Harrisburg-York CSA 4 12.5M 1,219,422 564,795


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