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Appendix E Demographic Forecasting and Future Interstate Highway System Demands Guangqing Chi Highways have, since their creation, played an important role in trans- forming society and affecting population change (Baum-Snow 2007; Vandenbroucke 2008). The Interstate Highway Act was passed in 1956, and thus began the development of Interstate highway infrastructure in the United States. Now, the Interstate Highway System handles nearly 25 percent of the total vehicle-miles traveled and 40 percent of total truck traffic, with only 1.2 percent roadway centerline miles of the U.S. public road system. Although the Interstate Highway System used to be a symbol of Ameri- can growth and its economic machine, the Interstate Highway System (see Figure E-1) has rarely been expanded since its inception. The Interstate Systemâs activities of today mainly upgrade existing highways rather than construct new ones. In 2002, the Executive Director of the National Acad- emiesâ Transportation Research Board stated that a majority of the existing highway systems, especially the interstates and principal highways, would need to be revamped in the near future (Skinner 2002). In 2009 the Obama administration planned to heavily invest in the transportation infrastruc- ture with the American Recovery and Reinvestment Act. Furthermore, in 2017 the Trump administration proposed to revitalize the transportation infrastructure. In response to section 6021 of the Fixing Americaâs Surface Trans- portation Act of 2015, this special report addresses the actions needed to upgrade and restore the Interstate Highway System as a premier system for meeting the growing and shifting demands of the 21st century. As part of 313
314 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM this special report, this appendix focuses on demographic forecasting and future Interstate System demands. In particular, this appendix (1) provides up-to-date demographic information; (2) produces population projections into 2060 at the county level; (3) develops a method to identify counties that are projected to need additional (or less) Interstate capacity; and (4) discusses the implications of the aging population and baby boomers, the young population and millennials, immigrants, and telecommuting that affect travel demands. POPULATION AND INTERSTATE HIGHWAY SYSTEM AS OF 2016 Overview of Literature on PopulationâHighway Dynamics The relationship between population growth and highway investment has been studied in a vast literature that spans multiple disciplines, from sociol- ogy and geography to planning and economics. This diverse study base has resulted in a complex amalgam of empirical and theoretical approaches. While it is reasonable to assume that populationâhighway dynamics are two-directional, there is disproportionally more research on highway effects on growth than the other way around. The relationship between population FIGURE E-1 Interstate Highway System in the United States.
APPENDIX E 315 change (or economic growth) and highway improvement1 (or travel de- mand) has been found to be bidirectional and has feedback effects (Hobbs and Campbell 1967). Better highways or higher travel demand stimulate economic growth while the economic growth simultaneously increases demand for higher-quality highway access (Aschauer 1990; Mikelbank 1996). Highways cause population change and economic growth because the investment in highways alters the status quo of the social and economic balance. This, then, affects population growth or decline, depending on the locational advantage or disadvantage. Conversely, population change and economic growth affect travel demand and highways in that they have an influence on decisions about highway expansionsâgrowth in the popula- tion and economy causes demand for reliable and high-quality transpor- tation networks. Stephanedes and Eagle (1986) studied the interaction between highways and employment for 30 nonmetropolitan counties in Minnesota over a 25-year period. They found that investment in highways affected employment and then employment further affected investment in highways. In the following subsections, the literature on producing popula- tion projections for Interstate System planning is briefly summarized. Highway Impacts on Population Change Literature specifically examining the impacts of highways on population change is limited and mostly from the field of sociology (e.g., Chi 2010; Lichter and Fuguitt 1980; Perz et al. 2010; Voss and Chi 2006). There is, however, vast research on highway impacts on economic growth and development, as well as employment change, and it is supported by nu- merous theories and studies. The three most relevant theories are growth pole theory (Perroux 1955), neoclassical growth theory (Solow 1956), and central place theory (Christaller 1966). Growth pole theory predicts mutual geographic dependence of develop- ment and economic growth between metropolitan areas and the surround- ing rural areas using the concepts of spread and backwash; this dependence affects population change. In this theory, highways are considered a catalyst of change (Thiel 1962). Linking metropolitan areas to their surrounding areas by building a highway may not generate population growth in either area; population decline may also result. Neoclassical growth theory states that generally there are three inputs that produce outputs: land, capital, and labor. Highway investments, as a type of public capital, may be considered an input through a produc- tion function, which assumes relationships between various inputs and 1 Highway improvement, highway investment, and highway construction are used inter- changeably in this appendix.
316 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM outputs (Eberts 1990). Many neoclassical growth theory studies examine the connection between public capital and economic productivity through the production function (e.g., Dalenberg and Partridge 1997). As applied to highways, this theory predicts that as highway infrastructures increase, economic output also increases, and this in turn produces both population and employment growth. Central place theory considers the highway infrastructure to be a facili- tator of consumers, raw materials, finished goods, capital, and idea flows between central locations and their surrounding neighborhoods (Thompson and Bawden 1992). Therefore, highway infrastructure can be considered a facilitator of population flows as well, because it may promote both popula- tion inflows and outflows, depending on overall population redistribution trends and other factors affecting population change. Highways in and of themselves, however, do not cause changes in population. However, dissimilar, even contradictory, findings have been reported by empirical studies of varying geographic scales on the impacts of highways on population and economic change. For example, highways were found to have no or only minor effects on population and economic growth in some studies (e.g., Hulten and Schwab 1984; Jiwattanakulpaisarn et al. 2009; Voss and Chi 2006) yet were found to promote both population growth and economic growth in other studies (e.g., Boarnet et al. 2005; Cervero 2003; Goetz et al. 2010). These contradictory findings may result from the spatial heterogene- ity of highway impacts. That is, the impacts of highways on population change differ across rural, suburban, and urban areas because these area types have different socioeconomic and demographic characteristics as well as residents who may perceive highways differently (Chi 2010). A study on the impacts of highway expansions on population change conducted in Wisconsin at the minor civil division level by Chi (2010) found differing impacts across rural, suburban, and urban areas: highway expansions were found to have indirect effects on population change in rural areas, direct and indirect effects in suburban areas, and no statistically significant effects in urban areas. Population Impacts on Highway Investment Although much literature examines and several theories explain the im- pact that highways have on population change and economic growth, very few studies examine the impact of population growth on decisions to build new or expand existing highways, despite the fact that criteria for highway expansion decisions exist at the federal and state planning levels (U.S. DOT et al. 1998; Wisconsin DOT 1983, 2003). These criteria include public concerns, safety and congestion, economic benefit and cost, roadway
APPENDIX E 317 deficiencies, forecasts of future demand, and environmental impacts. A key indicator of safety and congestion is traffic volume. Traffic volume can in- crease slowly through natural regional growth, or it can increase abruptly from large in-migration. Public concern is a criterion because citizens are generally involved in the planning and decision process of constructing or expanding a highway through formal petitions and public hearings (Wis- consin DOT 2003). A study by Miller (1979) on nonmetropolitan U.S. counties in the late 1960s and early 1970s found that as highway construction began, population growth occurred, but then as construction was completed in the 1970s, population growth diminished. Lichter and Fuguitt (1980) also studied nonmetropolitan counties, comparing dates of highway comple- tion to mean populations at the time. They found that the earlier the date of completion was, the larger the population size was. Their data also re- vealed that interstate highways were constructed in counties with previous high net in-migration. More recently, Voss and Chi (2006) found that the dominant causal influence between population growth and highway con- struction appears to flow from highway construction to population growth. Note that population and economic growth leads to higher travel demand, but does not necessarily lead to highway investments. The United States has seen little highway investments over the past three decades, although it experienced continual population and economic growth (Giuliano and Dargay 2006). Overall, population growth and highway construction are closely re- lated. In the transportation planning process, often a region is predicted to experience significant population growth so that highway construction or investment will follow. The rest of this appendix focuses on the causal direction from population growth to highway investment to predict popu- lation and identify areas that could need more (or less) Interstate capacity. Population and Interstate Highway System in 2016 Figure E-2 shows total population and population density as of 2016 at the county level using the American Community Survey estimates of the Census Bureau. Populations are concentrated in the northwest corner of Washington and Oregon; California; lower Florida; the belt from Boston to Washington, D.C.; the belt from Minneapolis, Minnesota, to Pittsburgh, Pennsylvania, along I-90 and I-94; and from Atlanta, Georgia, to the Tri- angle of North Carolina. The Interstate Highway System is correlated with population distribu- tion (see Figure E-3). The nodes of the Interstate System are often located in high-density counties. This echoes the initial purpose of the Interstate
318 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM FIGURE E-2 Total population and population density as of 2016 in the United States.
APPENDIX E 319 Highway System, which is to connect principal cities and metropolitan areas and to serve the national defense (FHWA 1970). How does population distribution relate to the Interstate System? In 2010, the 1,444 counties with Interstate highways had 178,412 people on average (see Table E-1). In contrast, the 1,698 counties without Interstates had 29,941 people on average. The Interstate Highway System serves a larger population beyond those in the counties where the system falls. Voss and Chi (2006) found that Interstate highways have an influence over 20 miles of flight distance. In total there are 2,477 counties that fall within 20 miles of the Interstate Highway System. These counties had an average of 119,080 people in 2010, compared to an average of 20,312 people in the 665 counties that fall beyond 20 miles of the Interstate System. FIGURE E-3 Population Density in 2010 and the Interstate Highway System network. TABLE E-1 Descriptive Statistics of Population and Proximity to Interstate Highway System in 2010 N Mean SD Min. Max. Counties with Interstates 1,444 178,412 440,712 415 9,825,473 Counties without Interstates 1,698 29,941 78,950 83 2,510,240 Counties within 20 miles of the Interstate System 2,477 119,080 349,453 83 9,825,473 Counties beyond 20 miles of the Interstate System 665 20,312 29,348 90 293,415
320 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM POPULATION PROJECTIONS INTO 2060 AT THE COUNTY LEVEL Projection Methodology, Procedure, and Assumptions Cohort Component Methods There are many methods for population forecasting, including extrapola- tion projections and time series models, postcensal population estimation models, knowledge-based regression models and structural models, condi- tional probabilistic models, integrated land use models, population fore- casting by grid cells, and cohort component methods (Chi 2009; Smith et al. 2013; Wilson and Rees 2005). In this study, cohort component methods are selected to produce population projections into the future. A study evaluating the projection accuracy of U.S. population projec- tions from 1953 to 1999 (Mulder 2002) found that for a 10-year projection the mean percentage errors range from â18 percent to 30 percent and the mean absolute percentage errors range from 6 percent to 30 percent; and from â14 percent to 45 percent and from 12 percent to 45 percent respec- tively for a 20-year projection. Despite the large projection errors, cohort component methods provide the best projection accuracy (Smith et al. 2013). Cohort component methods are the default methods for population projections at the country, state, and county levels by the Census Bureau, state agencies that are in charge of their population projections, and com- mercial companies. Cohort component methods project the three components of popula- tion changeâbirths, deaths, and net migrantsâseparately for each birth cohort (i.e., persons born in a given year). The base population (by age, gender, and race or ethnicity) as of the projection launch year is projected each year by the projected survival rates and net migration rate. The births are projected and added to the population by applying the projected fertil- ity rates to the female population. Cohort component methods produce population projection by age and gender for each year, and the projections are typically more accurate than what are produced by other methods at the county level and above (Smith et al. 2013). Population projections used in this paper are produced by the Census Bureau and ProximityOne (a population projection consulting firm) using cohort component methods. The methods and procedures are detailed in the next section. The projection produced by the Census Bureau is at the national level, while the projec- tion produced by ProximityOne is at the county level. Projection accuracy is higher at the national level than that at the state level, and the latter is higher than that at the county level. This is because at finer levels the migra- tion, which is the most difficult to predict among the three components of population change, can affect population change greatly, but the variation
APPENDIX E 321 of net migration across space could cancel out each other at coarser (or aggregated) levels. Population Estimates, Projections, and Forecasting Population estimates, population projections, and population forecasting are often used in demographic forecasting work, but they refer to different things. Population estimates are estimates of a population on or before the current date. Population projections are predictions of a population into the future. For example, now it is April 2017. The Census Bureau has already released its population estimates for years 2011, 2012, 2013, 2014, 2015, and 2016. Projections are for 2017 and after. Both population estimates and projections are produced using methods based on some assumptions. Population estimates and projections are not observed factsâthey reflect best efforts to accurately determine these values at specific points in time. The difference between projections and forecasting is less obvious. A projection embodies one or more assumptions, and a forecast is a projection that is most likely to occur based on judgment. Nevertheless, âprojectionâ and âforecastâ are often used interchangeably. Estimation or Projection Methodology The population in year t as of July 1 for a county is estimated or projected as Pt = Pt â 1 + Bt â 1,t â Dt â 1,t + Mt â 1,t where t = year t, on July 1; Pt = resident population as of July 1, year t; Pt â 1 = resident population as of July 1, year t â 1; Bt â 1,t = births during period (June 30)/t â 1 to (July 1)/t; Dt â 1,t = deaths during period (June 30)/t â 1 to (July 1)/t; and Mt â 1,t = net migrants during period (June 30)/t â 1 to (July 1)/t. The baseline launch year is 2010 because it is the latest decennial year in which the Census Bureau conducted population counting and it provides the most complete population data. For each subsequent year, the people are aged/advanced 1 year of age. The population estimates or projections are a product of population in the previous year, plus births that occur dur- ing the 1-year period, minus deaths that occur during the 1-year period, and plus net migration that occurs during the 1-year period. That is,
322 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM P2011 = P2010 + B2010,2011 â D2010,2011 + M2010,2011 P2017 = P2016 + B2016,2017 â D2016,2017 + M2016,2017 P2060 = P2059 + B2059,2060 â D2059,2060 + M2059,2060 Population estimates and projections are developed for each individual county. This is done for each age (0â84 and 85+ years) by gender and race/ethnicity. The race/ethnicity is categorized as non-Hispanic white, non-Hispanic black, Hispanics, and others. Note that age-, gender-, and race/ethnicity-specific rates are used for births, deaths, and migration. The rates are discussed in the sections following. Totally, the projection work produces 3,221 (counties) Ã 86 (age groups) Ã 2 (genders) Ã 4 (races/ethnicities) Ã 44 (projection years 2017â2060) = 97,506,112 projections for different combinations. These elemental projections are then aggregated to each county for each year to produce total population projections for each county in each year. Establishing Baseline (Launch Point) Population Data The launch year is 2010 because that is the latest decennial year when the Census Bureau conducted population counting and it provides the most complete population data. The decennial census is based on April 1, 2010. However, it makes more sense to use the midyear as the point of reporting population. Plus, American Community Survey estimates are based on July 1. Therefore, before we begin, we need to adjust the decennial Census data from April 1, 2010, to July 1, 2010. The baseline population data estimated as of July 1, 2010, will be partitioned by 86 age groups by 2 genders by 4 race/ethnicity groups for each county. The baseline population data also single out populations in group quarters, which include college residence halls, nursing facilities, group homes, military quarters, correctional facilities, worker dormitories, and others. The populations in group quarters do not change from year to year in the same way that populations not in group quarters do because the formerâs age cohorts do not âageâ each year. Therefore, the populations in group quarters are treated separately but are added to the final population projection.
APPENDIX E 323 Projecting Births A new birth cohort is formed each year to be added to the population. For example, the cohort that is born between July 1, 2016, and June 30, 2017, is added to the population in 2017. Births are projected in three steps: (1) projecting age- and race/ethnicity-specific fertility rates; (2) applying the rates to the corresponding racial/ethnic female population age 15 to 54 years; and (3) splitting the births into boys and girls based on a boyâgirl ratio. Overall, the age- and race/ethnicity-specific fertility rates decline over time. To avoid extreme change in the fertility rates, the decline in the crude birth rate for any county from 2010 to 2060 is limited to â0.05. If a countyâs crude birth rate is projected to decline more than 0.05 from 2010 to 2060, the decline is adjusted to 0.05. Projecting Deaths Deaths are subtracted from the population each year. For example, deaths that occurred between July 1, 2016, and June 30, 2017, are subtracted from the population in 2017. Deaths are projected in two steps: (1) projecting age-, gender-, and race/ethnicity-specific death rates for each county and (2) applying the rates to people of the corresponding age, gender, and race/ ethnicity. Overall, the age-, gender-, and race/ethnicity-specific death rates increase over time. To avoid extreme change in the death rates, the increase in the crude death rate for any county from 2010 to 2060 is limited to 0.05. If a countyâs crude death rate is projected to increase more than 0.05 from 2010 to 2060, the increase is adjusted to 0.05. Projecting Net Migration Net migration is added to the population each year. For example, net mi- gration between July 1, 2016, and June 30, 2017, is added to the popula- tion in 2017. Net migration is projected in two steps: (1) projecting age-, gender-, and race/ethnicity-specific net migration rates for each county and (2) applying the rates to people of the corresponding age, gender, and race/ ethnicity. The migration rates are projected by following the migration pat- terns exhibited from 2010 to 2016. Producing Total Population Projections The total populations are projected for each county in each year by adding projected population from the previous year, births from the previous year, and net migration from the previous year and then subtracting deaths from the previous year.
324 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM In practice, population projections are often adjusted to improve fore- casting accuracy. Adjusting population projections can involve many steps. Two major considerations are (1) modifications to rein in severely abnormal change rates and (2) adjustment to (or control of) national projections (Voss and Kale 1986). Modification of abnormal change (growth or decline) rates is used to soften the occasional high population change rates that emerge when making population projections. If the population change rate in a county is unusually high, the projected rate is softened under the assump- tion that rapid population change cannot be sustained for long periods. If a county is projected to have a population of fewer than 100 people or even negative population in any given year, the projected population is set at 100 people. The projected populations for each county after adjustment are ag- gregated to the national level and compared and adjusted to the national population projections prepared by the Census Bureau. The latter is seen as the gold standard for population projections in the United States. However, the Census Bureau does not produce population projections for states or counties. Note that the projections are made under the assumption that no major local or national disasters will occur between now and 2060. Unfortunately, this assumption becomes less valid as time passes. This is probably partly why the Census Bureau does not produce population projections for any subnational levels. This appendix uses projections that reflect the most likely (or mid-level) demographic trends; alternative assumptions could be used to develop different projections. Population Projection Results Following the methodology and procedure described in the previous sec- tion, populations at the county level are projected into 2060. Figure E-4 shows population in 2010 and projected populations in 2020, 2030, 2040, 2050, and 2060. Figure E-5 shows population density in the corresponding years. It seems that both population and population density increase over the years and across the United States. However, these maps do not tell where population growth or decline will occur. Figure E-6 shows the change in population size, the percentage change in population size, and the change in population density from 2010 to 2060. Population growth areas seem to be concentrated in the border states of the West, South, and East, including Washington, Oregon, California, Arizona, Utah, Colorado, southeast Texas, the Gulf Coast counties, Florida, counties on the East Coast from Florida to Massachusetts, Hawaii, as well as the triangle between Atlanta, Georgia, the Triangle of North Carolina, and Nashville, Tennessee.
APPENDIX E 325 FIGURE E-4 Population in 2010 and projected populations in 2020, 2030, 2040, 2050, and 2060. continued
326 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM FIGURE E-4 Continued
APPENDIX E 327 FIGURE E-5 Population density in 2010 and projected population densities in 2020, 2030, 2040, 2050, and 2060. continued
328 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM FIGURE E-5 Continued
APPENDIX E 329 FIGURE E-6 Population change, percentage population change, and population density change, 2010â2060.
330 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM There seem to be more counties that will experience population decline. This includes many counties from the northeast corner to the Appalachian region, counties bordering the Great Lakes except Lake Michigan, counties along the Mississippi River, the Deep South states, and Alaska. IDENTIFYING COUNTIES THAT MAY NEED ADDITIONAL OR LESS INTERSTATE HIGHWAY SYSTEM CAPACITY Population Change from 2010 to 2060 and Proximity to the Interstate Highway System As discussed in the review of populationâhighway dynamics, there is gener- ally a positive relationship between population change and highway needs. To identify counties that may need additional or less Interstate capacity based on the projected population change and proximities to the Interstate System, spatial overlay methods and proximity analysis are used. The as- sumption here is that population in each county, regardless age, gender, and race/ethnicity, behaves the same in terms of driving over the next 50 years. The potential implications of different demographic groups are discussed in the next section. Figure E-7 shows the Interstate Highway System and the projected population and population density in 2060. The nodes of the Interstate System are often located in populated or high-density counties. There are 1,444 counties with Interstate highways; these counties are projected to have an average of 247,207 people in 2060. In contrast, there are 1,698 counties without Interstates; these counties are projected to have an average of 34,203 people in 2060. When counties that fall within 20 miles of the Interstate Highway System are included, there are 2,477 counties with an average of 161,821 people in 2060. There are 665 counties that are beyond 20 miles of the Interstate System, with a projected average of 21,372 people in 2060 (see Table E-2 for the descriptive statistics). Figure E-8 shows projected population change, percentage population change, and population density change from 2010 to 2060 and the Inter- state System. The Interstate Highway System passes through both growing counties and declining counties. It is not clear in Figure E-8 how counties with Interstate highways compare to those without. Counties with Interstate highways are compared to those without by population change from 2010 to 2060 (see Table E-3). The former is projected to gain an average of 68,795 people over the 50 years, whereas the latter is projected to gain an average of only 4,262 people in the same time period. On average, the counties with Interstates are projected to gain 15.51 percent population but the counties without Interstate highways are project to lose 4.28 percent population. Note that the mean of percentage change is calculated as the average of percentage change in each county.
APPENDIX E 331 FIGURE E-7 Projected population and population density in 2060 and the Inter- state Highway System. TABLE E-2 Descriptive Statistics of Population and Proximity to the Interstate System in 2060 N Mean SD Min. Max. Counties with Interstate highways 1,444 247,207 637,467 104 12,099,604 Counties without Interstate highways 1,698 34,203 110,294 100 3,263,590 Counties within 20 miles of the Interstate System 2,477 161,821 504,828 104 12,099,604 Counties beyond 20 miles of the Interstate System 665 21,372 40,346 100 477,731
332 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM FIGURE E-8 Population change, percentage population change, and population density change, 2010â2060, and the Interstate Highway System.
APPENDIX E 333 The overall population change from 2010 to 2060 in the United States is 38.56 percent for counties with Interstates and 14.23 percent for counties without Interstates. Counties Along or Close to the Interstate Highway System That May Need Additional or Less Capacity The counties that are projected to gain or lose population along the Inter- state Highway System are highlighted in Figure E-9. The upper map shows the counties that are projected to gain population from 2010 to 2060. These are the counties that may need additional Interstate capacity based on their population projections. The needs are particularly strong in counties along I-5 from Washington to San Diego, California; counties from Los Angeles, California, to Phoenix, Arizona, along I-10; counties from Los Angeles to Albuquerque, New Mexico, along I-40; counties from Los Angeles to Utah along I-15; counties along I-20, I-35, and I-45 spreading from Dallas, Texas; counties along I-20 from San Antonio, Texas, to Pensacola, Florida; the lower Florida counties; counties in the big triangle of Atlanta, Georgia, the Triangle of North Carolina, and Nashville, Tennessee; counties along I-95 from Washington, D.C., to Boston, Massachusetts; and counties from Minneapolis, Minnesota, to Detroit, Michigan, along I-90 and I-94. The lower map of Figure E-9 shows the counties that are projected to lose population from 2010 to 2060. These are the counties that could need less Interstate capacity based on their population projections. These coun- ties include those from Cleveland, Ohio, to Boston, Massachusetts, along I-90; those from Rockford, Illinois, to Memphis, Tennessee, along I-39 and I-55; and those along I-25 in New Mexico. Counties that fall within 20 miles of the Interstate System are projected to gain an average of 42,742 people over the 50 years (see Table E-4); these counties are projected to gain an average of 8.11 percent population. TABLE E-3 Population Change from 2010 to 2060 and Proximity to the Interstate Highway System N Mean SD Min. Max. Population change, 2010â2060 Counties with Interstates 1,444 68,795 244,524 â378,001 3,529,548 Counties without Interstates 1,698 4,262 37,741 â103,561 753,350 Percentage population change, 2010â2060 Counties with Interstates 1,444 15.51% 46.75% â79.70% 281.10% Counties without Interstates 1,698 â4.28% 40.13% â79.80% 531.40%
334 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM Counties that fall beyond 20 miles of the Interstate System are projected to gain an average of only 1,060 people; on average these counties are projected to lose 7.45 percent population. Note that the mean percentage change is calculated as the average percentage change in each county. The overall per- centage population change from 2010 to 2060 in the United States is 35.89 percent for counties within 20 miles of the Interstate System and 5.22 percent for counties beyond 20 miles of the Interstate Highway System. The counties that are projected to potentially need additional Interstate capacity based on the 20-mile criterion are highlighted in Figure E-10. Based on their decreased populations, the counties that are projected to potentially need less Interstate capacity based on the 20-mile criterion are highlighted in Figure E-11. Overall, the results are similar to those based FIGURE E-9 Projected growing or declining counties along the Interstate Highway System.
APPENDIX E 335 TABLE E-4 Population Change from 2010 to 2060 and Proximity to the Interstate Highway System N Mean SD Min. Max. Population change 2010â2060 Counties within 20 miles of the Interstate System 2,477 42,742 191,554 â378,001 3,529,548 Counties beyond 20 miles of the Interstate System 665 1,060 16,661 â103,561 203,613 Percentage population change 2010â2060 Counties within 20 miles of the Interstate System 2,477 8.11% 44.29% â79.80% 281.10% Counties beyond 20 miles of the Interstate System 665 â7.45% 42.67% â79.60% 531.40% FIGURE E-10 Counties neighboring the Interstate System with projected increasing populations.
336 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM on the with-or-withoutâInterstate network results, but the former includes more surrounding counties. Counties Without Interstate Highways But Projected to Experience Rapid Population Growth and Population Density Increase The counties identified in the previous section either have the Interstate highways or are within 20 miles of the system. The remaining counties of the United States could still have the potential to be provided with a new Interstate highway, if they have high population density and are predicted to experience rapid population growth. To identify these possible counties, two criteria are used. One, they should rank in the top 50 percent among all growing counties as measured by population growth rate. Two, they should rank the top 50 percent among all growing counties as measured by population density increase. Figure E-12 highlights counties that do not have an Interstate highway. These counties are scattered from the northwest corner of Washington to the west of Colorado, from the southeast corner of New Mexico to Houston, Texas, to the tristate counties of Montana and Dakotas, northwest of North Dakota, and to Hawaii. FIGURE E-11 Counties neighboring the Interstate System with projected decreas- ing populations.
APPENDIX E 337 IMPLICATIONS OF AGING POPULATION, MILLENNIALS, IMMIGRANTS, AND TELECOMMUTING Population Pyramids and Age Variations of Interstate System Users Demographic characteristics can play a role in travel patterns and the demand for different travel modes. In the United States the number of vehicle-miles traveled (VMT) per person grew until 2007, declined to 2014 (Sivak 2013), and has bounced back since then. The overall long-term growth in miles traveled may be attributed to changing demographics or an improving economy (Zmud et al. 2014). Depending on the amount of driving, the types of preferred transportation, and the reasons for driving, different demographic groups may need Interstates more or less than other demographic groups (Tilley 2017). To understand the age variations of the Interstate System users, it is helpful to understand the population pyramids of the United States. In 2016, the U.S. population was approximately equally distributed from age 0 to age 60 but declined quickly after that (see Figure E-13). This suggests that the U.S. population is still a relatively âmatureâ population. FIGURE E-12 Growing counties that do not have the Interstate highways. NOTE: The highlighted counties are selected based on both the top 50 percent population growth rate and the top 50 percent population density increase (the difference of population density between 2060 and 2010).
338 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM Population pyramids from 2010 to 2060 are illustrated in Figure E-14. Although all age groups are projected to increase over the 50 years, the elderly (age 65 and older) will increase more. This is shown in Figure E-15, where each age group is presented as a percentage of the total population. The Aging Population and the Baby Boomers The population of the United States is aging, meaning a larger share of the population is composed of older people. In terms of transportation, one of the most notable cohorts is made up of the baby boomers, those born between 1946 and 1964 (Zmud et al. 2014). This large cohort has now reached retirement and makes up the largest portion of elderly people. Unlike previous cohorts, many baby boomers are choosing to retire in the same place where they lived during their working years and do not plan to give up their driving habits (Alsnih and Hensher 2003). Studies have shown that increasing numbers of older people continue to have driverâs licenses and to drive (Sivak and Schoettle 2011a, 2011b; Stokes 2012). Yet, even with the continued presence of baby boomers on the road, overall older people still tend to drive less than middle-age people. They take fewer daily trips, travel shorter distances, and have shorter travel times than people under age 64 (Collia et al. 2003). While older people may FIGURE E-13 Population pyramid in 2016.
APPENDIX E 339 FIGURE E-14 Population pyramids in 2010, 2020, 2030, 2040, 2050, and 2060. make fewer trips, they often couple multiple destinations within one trip (going to the store, visiting a relative, running an errand, and then return- ing home) (Alsnih and Hensher 2003). Older people drive at different times than younger people, with much of the older populationâs driving occurring between the hours of 9:00 a.m. and 4:00 p.m. They cite congestion as a particular driving concern (Collia et al. 2003). Although older people may not drive as much, they may still require the conveniences of the Interstate System through their use of online and delivery services, which allow them the convenience of shopping without leaving their own homes (Alsnih and Hensher 2003). Older people also prefer to drive (rather than fly or take a train) when going on long-distance
340 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM trips, and they drive more miles on these trips than younger people (Collia et al. 2003). Figure E-16 shows the distribution of the aging population in 2015. As we look to the future, the population of older people (age 65 and older) will begin to rapidly increase (see Figure E-17). We expect that between 2010 and 2060 the share of people in this age group will jump from 13 percent of the population to more than 23 percent. In raw numbers, the aging population will double from just more than 40 million people to more than 98 million. Most notably, the share of the oldest older population, those over 80 years old, will greatly increase. In 2010 the 80 and older population was 11 million people, but it is projected that by 2060 it will be almost 40 million. Baby boomers, the cohort of babies born after World War II, is a gen- eration of adults now entering retirement age. For this analysis, baby boom- ers comprise those born between 1946 and 1964. In 2010, the 81 million baby boomers made up 26 percent of the population (see Figure E-18). In the coming decades, as they age and eventually die, the population of baby boomers is expected to decrease, as will their share of the population. By 2060, all baby boomers are expected to be over age 95 and will make up less than 1 percent of the total population. FIGURE E-15 Population pyramids in percentages in 2010 and 2060. FIGURE E-16 Distribution of aging population in 2015 at the county level.
APPENDIX E 341 The Young Population and the Millennials Interestingly, fewer young people are obtaining their driverâs licenses than in previous generations. Although 77 percent of 18-year-olds in 1990 had a driverâs license, a study in 2013 found that only 54 percent of 18-year- olds did (Research Triangle Institute 1991; Tefft et al. 2013). It is possible that these young people weigh the benefits of cost, convenience, and the environment when making driving decisions. Following the millennial generation, a new cohort of the population is entering the age requirements permitting them to drive. Millennials, the generation of younger adults born in the 1980s and 1990s (Zmud et al. FIGURE E-17 Projected aging population (age 65+) in the United States, 2010â2060. FIGURE E-18 Projected population of baby boomers (born 1945â1964) in the United States, 2010â2060.
342 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM 2014), are a popular subset of the population for study. Millennials are more likely to want to live in cities and to use public transportation for their commutes than older adults (Belden Russonello Strategists 2013; Ralph et al. 2016; Zmud et al. 2014). Millennials may demand less from the Interstate System because of their mix of different modes of transportation, their urban living, and their environmental concerns (Sakaria and Stehfest 2016). Cost is the primary driver behind millennial transportation choices. The distribution of the young population in 2015 is shown in Figure E-19. The population of young people, those between ages 15 and 34, will remain fairly stable over time (see Figure E-20). While the number of young people is expected to increase from 84 million people in 2010 to almost 98 million in 2060, the share of young people in the overall population will decrease from 27 percent to 23 percent. The shares of young people by different age categories, such as 15â19, 20â24, and 25â34, are expected to remain fairly consistent across decades. For this analysis, the millennial cohort comprises those born between 1982 and 1996 (Pew Research Center 2013). Millennials in 2010 made up almost 21 percent of the total population, when they were between the ages of 15 and 29. Although the number of millennials remains fairly stable over time, the share of the population occupied by millennials is expected to decrease over time. By 2060, when millennials are between the ages of 65 and 79, they are expected to make up 15 percent of the total population (see Figure E-21). Immigrants About 12.6 percent of the U.S. population is foreign born (Chatman and Klein 2009). Overall, it appears that immigrants are less likely than native- born Americans to drive in private cars and are more likely to use forms of public transportation available in cities. Zmud and colleagues (2014) found that foreign-born Hispanic and Asian workers used public transportation twice as much as native-born workers, and Chatman and Klein (2009) found that foreign-born workers were about three times more likely to use public transportation than native-born workers. Even when traveling between cities, private shared transportation such as greyhound buses are used by immigrants at higher rates (Chatman and Klein 2009). It is possible that with the emergence of new immigrant destinations in smaller cities and rural communities, immigrant use of private cars for transportation and use of the Interstate System for both daily and long-distance trips may increase (Tal and Handy 2010). The distribution of immigrants in 2015 is shown in Figure E-22. The population of those born outside the United States is projected to in- crease steadily between 2010 and 2060 (see Figure E-23). Additionally, the
APPENDIX E 343 FIGURE E-19 Distribution of the young population in 2015 at the county level. FIGURE E-20 Projected young population (ages 15â34) in the United States, 2010â2060. FIGURE E-21 Projected population of millennials (born 1982â1996) in the United States, 2010â2060.
344 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM percentage of the population comprising those born outside the country is projected to increase from 13 to 19 percent. Among the foreign-born popu- lation, Hispanics make up the largest racial/ethnic category. In 2010, almost half the foreign-born population was Hispanic. However, the portion of the foreign-born population comprising people who are not Hispanic is projected to increase over time. Telecommuting Adults, young and old, are now more connected to technology than ever. Ninety-one percent of Americans own a cell phone, and more than half own a smartphone (Pew Research Center 2013). Young people who grew up with the Internet and other forms of technology are now of driving and working age. Although some believed that technology might decrease the need for travel, particularly reducing work commutes through the development of FIGURE E-22 Distribution of immigrants in 2015 at the county level. FIGURE E-23 Projected population of immigrants in the United States, 2010â2060.
APPENDIX E 345 telecommuting technology, the impact has been mixed (Zmud et al. 2014). Issues of broadband access, particularly in rural communities, and Internet connectivity through devices other than computers may still necessitate in-person working. However, expansion of new forms of technology may change the needs for interstate and highway transportation in the future for both the commutes of people and the delivery of goods. Telecommuting is the act of doing work at home. With e-mail, social media, and other forms of remote working, many people have already incorporated some elements of telecommuting into their jobs. Jobs that for- mally incorporate telecommuting may allow employees to work from home 1 day a week or may allow workers to complete all work remotely. In 2010, management, business, financial, professional, and related occupations had the largest percentage of their workforce engaging in some amount of telecommuting, with almost 33 percent (see Figure E-24). Unsurprisingly, those who worked in production occupations had the smallest portion of their workforce working from home, and other occupations that require hands-on or face-to-face service also had small portions of their workforces engaging in remote work. It is likely that certain occupations may be able to greatly increase their telecommuting workforce in the future but that other occupations will not. As a final note, it should be emphasized that population is only one factor associated with VMT and Interstate System demands. VMT is also related to employment growth, GDP, and GDP per capita, as shown in Figure E-25. These factors should be considered when predicting future Interstate System demands. FIGURE E-24 Percentage of workers doing some or all of their work from home in the United States, 2010.
346 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM CONCLUSIONS Population growth demands higher Interstate System capacity. To upgrade and restore the Interstate Highway System as a premier system for the 21st century, demographic forecasting is a must before any transportation plan- ning and decision activities. This appendix provides population projections into 2060 at the county level for the entire United States using cohort- component methods. The United States is projected to experience popula- tion growth across all age groups over the next 50 years. The projected growth, however, varies across the entire United States. Population growth areas seem to be concentrated in the border states of the West, South, and East, as well as the triangle between Atlanta, Georgia, the Triangle of North Carolina, and Nashville, Tennessee. Population decline areas include many counties from the northeast corner to the Appalachian region, counties bordering the five Great Lakes except Lake Michigan, counties along the Mississippi River, the Deep South states, and Alaska. This appendix also identifies the counties that may need additional or less Interstate capacity based on the projected population change and proximities to Interstate highways by using spatial overlay methods and proximity analysis. Only the counties that fall within 20 miles of existing FIGURE E-25 Vehicle-miles traveled, total population, GDP, GDP per capita, and employment in the United States, 1990â2015. NOTE: All numbers are standardized (year 1990 = 100) to better visualize the as- sociation between their corresponding lines.
APPENDIX E 347 Interstate highway are included in the analysis. The areas that may need additional Interstate capacity, based on their population projections, are particularly strong in counties along I-5 from Washington to San Diego, California; counties from Los Angeles, California, to Phoenix, Arizona, along I-10; counties from Los Angeles to Albuquerque, New Mexico, along I-40; counties from Los Angeles to Utah along I-15; counties along I-20, I-35, and I-45 spreading from Dallas, Texas; counties along I-20 from San Antonio, Texas, to Pensacola, Florida; the lower Florida counties; counties in the big triangle of Atlanta, Georgia, the Triangle of North Carolina, and Nashville, Tennessee; counties along I-95 from Washington, D.C., to Bos- ton, Massachusetts; and counties from Minneapolis, Minnesota, to Detroit, Michigan, along I-90 and I-94. The counties that may need less Interstate System capacity based on their population projections include those from Cleveland, Ohio, to Boston, Massachusetts, along I-90; those from Rock- ford, Illinois, to Memphis, Tennessee, along I-39 and I-55; and those along I-25 in New Mexico. This appendix also identifies the counties with high population density but without Interstates that are predicted to experience rapid population growth because these counties could still have a potential to be invested with a new Interstate highway or corridor. These counties are scattered from the northwest corner of Washington to the west of Colorado; from the southeast corner of New Mexico to Houston, Texas; the tristate coun- ties of Montana and the Dakotas; northwest of North Dakota; and Hawaii. Note that the Interstate System demands also vary by demographic groups. The U.S. population is aging quickly and the percentage of the ag- ing population is rising, from 13 percent of the total population in 2010 to 23 percent in 2060. Both the baby boomers and the millennials will have a declining share of the total population. Immigrants are projected to increase from about 13 percent in 2010 to 20 percent in 2060. Telecommuting could affect the usage of the Interstate Highway System as well. That said, future work could provide population projections for these specific demographic groups and for finer geographic scales. For exam- ple, population projections by age and projections of immigrants at the county level could provide useful information for the local decision mak- ers. Population projection at subcounty levels could be particularly useful for metropolitan areas, where the Interstate Highway System needs could vary greatly. For example, the Interstate System is seen as a disamenity to immediate neighborhoods but as an amenity (because of accessibility) to neighborhoods just a few blocks away. Producing rigorous population pro- jections by different demographic groups and at finer scales could provide more useful information for decision makers and policy makers in better deciding where to expand or invest in the Interstate Highway System.
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