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Appendix D Economic Outlook Factors Affecting Highway Demand Mark Sieber and Glen Weisbrod1 BACKGROUND AND OVERVIEW Background The Interstate Highway System is the backbone of the U.S. road network. It carries 25 percent of the total vehicle-miles traveled (VMT) and almost 40 percent of the truck traffic in the United States. Recognizing that the core system design dates back more than 60 years, Congress in 2015 authorized funding for a study of actions needed to upgrade and restore the Interstate Highway System to meet the increasing and changing demands of the 21st century. This is one in a series of white papers commissioned as part of that study. It builds on two other papers developed for the study. One high- lighted the key role of the Interstate Highway System in supporting freight movements and showed national forecasts of future freight growth. A sec- ond white paper examined the national trend in traffic growth, measured as VMT, and its relationship to growth in population, economy (gross domestic product [GDP]), and land use density (Polzin [see Appendix C to this report]). This appendix examines more specifically how future highway demand will be increasingly affected by evolving shifts in the economy. 1 With assistance from Derek Cutler and Cecilia Viggiano. 267
268 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM Overview The objective of this appendix is to show how economic changes affect demand for Interstate Highway System travel, the range of ways that eco- nomic changes can evolve, and the implications for truck and car highway demand (including VMT patterns). Four specific elements are examined: 1. Economic factors: It shows how freight and passenger travel de- mand patterns are shifting in response to temporal, spatial, and sectoral changes in U.S. business and population activity patterns, as well as evolving technology shifts that are affecting industry productivity, buying and selling, and transportation patterns. These factors are changing economic activity locations as well as freight and passenger traffic patterns. 2. Trend effects: It utilizes a long-term history, and a series of alter- native long-term economic forecasts to show how the above-cited shifts in spatial, sectoral, and productivity characteristics of the economy have affected past, and will affect future, Interstate High- way System freight and passenger travel demand (including VMT patterns and trends). 3. Economic outlook alternatives: It portrays economic outlook fore- casts reflecting alternative assumptions about changes in future economic drivers such as fuel prices, trade, and economic pro- ductivity. It uses the alternative forecasts to illustrate uncertainty factors, and their range of possible impacts on future Interstate Highway System travel demand. 4. Interpretation: It provides a context for interpreting how alter- native economic futures can affect the range of future Interstate Highway System travel needs and their sensitivity to future uncer- tainties. This will also provide a basis for subsequent use of the information to assess the potential for over- or underinvestment and their implications. This appendix presents forecasts of changes over 10-, 20-, 30-, and 50-year time periods. However, for clarity, it utilizes the 30-year forecasts to drill down and show how various economic change factors are evolving to affect future highway demand and investment needs. How the Economy Drives Highway Demand Patterns There are many ways of viewing the growth of highway demand. Since the Interstate Highway System was authorized 60 years ago, the U.S.
APPENDIX D 269 population has grown 74 percent. Over this same period, the number of registered automobiles has increased 239 percent. Over the past 30 years alone (1985â2015), overall highway traffic (as measured by VMT) has grown 74 percent. Importantly, the various factors underlying the growth of highway travel demand (e.g., population, income, car ownership, and truck movements) are all driven by the same set of core changes over time in the pattern of economic activity. Behavioral Relationships We can see these relationships by considering the schematic in Figure D-1 and the corresponding concepts of economic base and economic geography that explain compositional and locational shifts in economic activity among regions and their consequences. (In this nomenclature, a region can be a county, a metro area, or a state.) The core drivers of the economy are basic or traded industries, that is, industries that locate where it is most feasible and profitable to do so be- cause their products can be sold nationally or internationally. (This includes most mining, agricultural, forestry, manufacturing, technology services, and supply chain activities). Over time, the size, composition, and location pat- terns of these industries shift among regions, and so do the corresponding job and income opportunities. Population growth follows the changes in basic job opportunities, and other population-serving industries (educa- tion, health care, retail stores, and personal services) follow population movements. There are changes in truck and car generation rates, locations, dis- tances, and overall VMT that result from these changes in economic activity and their related shifts in job and population patterns. FIGURE D-1 How changes in the economy affect car and truck VMT. NOTE: O-D = origin-destination.
270 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM Traffic Consequences The evolution of economic activity over time can be viewed in terms of changes in regional economic growth and composition (specialization). This has the following consequences: 1. Economic growth affects employment. More employment means more commuter trips. 2. Economic growth generally leads to higher income, increasing consumption of goods and thus also demand for freight trans- portation. More income also increases demand for personal and recreation and tourism travel, and purchases of automobiles. 3. Shifts in regional economic specialization reflect the division of labor, both internationally and spatially within the United States. A more advanced division of labor can mean more regional economic specialization, shifting the location of economic activity (traded industries), the types of products being produced and shipped, and their originâdestination pattern. This also leads to shifts in freight mode split as well as the location and length of truck trips. More trade, with longer shipments, generally means more truck traffic on the Interstate Highway System. 4. Shifts in the location of traded industries also lead to location shifts in population patterns and population-serving industries. That, in turn, drives further growth in traffic on highways within the af- fected regions. Bottom Line While economic growth drives overall traffic (VMT) growth, it also leads to critical changes in the location of generated highway traffic, car and truck mix of traffic growth, and trip distance and originâdestination pattern of that traffic. This can have profound implications for the future adequacy of the Interstate Highway System network and affect investment priorities. Organization of This Appendix The next section shows how economic change has been affecting these various aspects of highway demand. The third section then explores the im- plications for the baseline future and demonstrates the range of alternative economic futures. Failure to anticipate possible future scenarios can lead to potentially either âstrandingâ overinvestments in highways or failing to adequately invest in future highway needs.
APPENDIX D 271 HOW THE ECONOMY HAS INFLUENCED TRAVEL DEMAND TO DATE This section examines past trends and current patterns concerning the relationship of highway demand and economic growth. By examining this issue, we can identify factors that will also be relevant for forecasting future highway needs (later in the section on what we can expect). Aggregate VMT Growth Hides Shifting Factors Aggregate Trends There has been a continuing long-term trend in which VMT has grown, along with the growth of economic activity (GDP), employment, popula- tion, and income. Figure D-2 shows how the growth trend for national VMT compares to the growth trend for national GDP over 84 years. Similar graphs can be made by relating VMT to growth in population or total household income. However, these aggregate trends mask a number of important shifts that offset each other when looking at overall national statistics but become critically important when viewing localized highway needs. They include the following: FIGURE D-2 National VMT and GDP trends. SOURCE: FHWA 2017, Table VM-202. VMT Total (Billions)
272 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM â¢ Changes in the spatial pattern of workforce participation patterns over time; â¢ Changes in the relative levels of worker income and their spatial pattern over time; â¢ Changes in the regional location pattern of VMT growth on high- way networks; â¢ Changes in the car/truck ratio on highways; â¢ Changes in the origin, destination, and distance characteristics of car and truck trips, reflecting both longer supply chains nationally and longer commute patterns in major, growing metro areas; â¢ Changes in the share of truck movement going to and from air, sea, or rail terminals or land borders; and â¢ Changes in the types of freight carried by trucks and their service to supply chains and distribution centers (which reflects evolu- tion to lean manufacturing and integrated supply chain technolo- gies, building on IT/telecommunication advances and vertical integration). These factors have had offsetting impacts on the observed national-level traffic and economic trends that were previously shown in Figure D-2: â¢ Some of these factors decrease VMT growth. They include growth over time in air and sometimes also rail alternatives to highway travel, which are applicable for some intercity freight and pas- senger movements. They can also include improvements in truck utilization (fewer empty backhauls) for some industries. â¢ Some of these factors increase VMT growth. They include rising income levels, growth of international trade, longer supply chains, more international trade, and the spatial expansion of large labor markets over time. â¢ Some of these factors shift the location of VMT growth, but not necessarily change its rate nationally. They include changes in manufacturing and supply chain locations, and consolidation of distribution centers. So, in the end, the total level of VMT may appear to have grown in step with the economyâs long-term growth, but there have also been important shifts in the location and composition of traffic, which have affected total traffic levels on different parts of the highway system. These same types of trends continue to occur and will be important as we consider expecta- tions for future traffic growth and future highway investment needs. For instance, Figure D-3 shows that truck VMT have been growing faster than passenger car VMT. And of course, trucks have a much larger impact on
APPENDIX D 273 road capacity utilization and degradation than cars. Next, we examine how VMT composition and location patterns are also changing. Location of Economic Activity and Its Composition Is Shifting Intercity Highway Needs Concentration of Economic Growth The location of economic activities occurring in the U.S. economy has been shifting significantly over time, and that is changing the pattern of highway use for freight and passenger travel. High-growth industries such as wholesale trade and computer and electronic manufacturing are concen- trated in a few parts of the United States, particularly in the megaregions of the Southeast and Southwest, with pockets in Northeast and Northwest metro areas. One of the indicators for the location of economic activities is the spatial distribution of jobs. Jobs lead directly to commuting trips, of which 86 percent are by cars as drivers or passengers (BTS 2017b). Jobs are also an indicator for supply and demand of shipped goods for traded industries. About two-thirds of all freight tons are carried by trucks (FHWA and BTS 2013). The spatial pattern of employment growth follows shifts in key growth industries. Figure D-4 shows the spatial pattern of overall jobs by county as of 1985. Figure D-5 then shows how that spatial pattern has since shifted from 1985 to 2015, reflecting systematic losses in some parts of the country and increased gains in others. FIGURE D-3 Truck and passenger car VMT growth, 1985â2015. NOTE: There was a redefinition of vehicle types in 2007, followed by the economic crisis from 2008 onward, which explains the rapid changes around these years. SOURCE: BTS 2017a, Table 1-35.
274 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM FIGURE D-4 Employment 1985, by county. FIGURE D-5 Change in employment, 1985â2015, by county.
APPENDIX D 275 Key Differences in Highway Reliance Among Industries There are systematic and large differences among industries in terms of the extent to which they generate truck traffic (VMT). We can break down the factors driving truck traffic growth into three components: freight trip generation rates, truck reliance rates, and trip lengths, all of which vary sys- tematically among industry. These differences among industries are shown in Table D-1. While there is also some variation in these rates over time in these statistics, they are small compared with the fundamental differences among industry sectors. This is a critical point, for the mix of economic activities occurring in the U.S. economy has been shifting significantly over time, and that is changing the pattern of highway use for freight travel. Consequences of Industry Growth and Decline Patterns for Traffic Growth As the economy evolves, there are changes in the industry mix of economic activity. The evolving shifts in economic activity combine with the above- cited differences in truck traffic generation, to affect highway freight flows in the United States. This shows up in various ways: â¢ Industry products with high freight tonnage and relatively low value per ton, such as petroleum, coal, mining and mineral products, chemicals, and primary metals have less of an impact on highway demand because much of their typical shipment distance is by rail. â¢ On the other hand, output of high computer and electronic tech- nology products has grown domestically. Their high value and weight, continued growth, and global nature of their markets all support increased use of air freight, which also generates regional truck distribution shipments among airports, regional distribution centers, and customers. Ultimately, this still grows truck traffic but shifts its originâdestination pattern. â¢ Apparel, leather, and computer and miscellaneous consumer goods are increasingly being delivered to massive centralized warehouses by large trucks and then delivered to households via light trucks operating within metropolitan areas. This phenomenon has con- centrated truck cargo movements in metropolitan areas. â¢ Effects of regional economic specialization lead to the concentration and consolidation of industries in specific regions. The locations of these producer concentrations have shifted with the ongoing trend toward more technology-based industries and products. â¢ As service industries have grown, so has the volume of metropoli- tan truck deliveriesâa market segment that is not well captured by current freight shipment statistics.
276 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM TABLE D-1 Differences in Tonnage, Truck Reliance, and Shipment Lengths, by Industry Industry Tonnage (millions) Tons per Employee By Truck (%) By Multiple Modes* (%) Miles per Shipment Value per Ton ($1,000s) Crop production 1,493 992.5 80.6 2.4 637.3 357 Animal production 237 202.7 91.7 1.6 715.6 1,060 Forestry and logging 337 2,321.1 91.3 0.1 1,521.2 49 Fishing, etc. 6 58.0 93.2 1.9 366.1 1,349 Oil and gas extraction 778 956.9 29.2 0.5 77.5 721 Mining, quarrying, and support 4,133 5,379.6 61.7 2.6 353.7 74 Food manufacturing 985 545.1 88.5 2.6 545.9 1,125 Beverage and tobacco product manufacturing 185 747.1 90.5 3.1 315.0 1,658 Textile mills and products manufacturing 33 134.4 88.8 6.7 268.2 8,569 Apparel manufacturing 10 58.0 89.0 9.2 340.6 12,996 Leather product manufacturing 4 105.4 87.3 11.6 613.1 12,594 Wood product manufacturing 430 962.5 89.5 3.1 787.4 574 Paper manufacturing 246 653.2 82.5 3.4 808.2 982 Printing 18 32.0 92.0 6.7 406.5 4,190 Petroleum and coal products manufacturing 3,845 33,362.4 34.1 0.6 179.4 596 Chemical manufacturing 761 963.7 61.8 2.9 331.6 2,390 Plastics and rubber products manufacturing 107 151.8 78.4 4.3 649.2 3,252 Nonmetal mineral product manufacturing 1,029 2,403.3 92.0 1.7 488.7 205
APPENDIX D 277 The combination of all these effects leads to shifts in the freight inten- sity of industries in different areas of the country. Freight intensity is defined here as the tonnage of incoming and outgoing freight per employee, rela- tive to the national average. Figure D-6 shows the relative freight intensity of counties as of 1985, which reflects differences in the mix of industries located in various areas. Figure D-7 shows how freight intensities have grown or fallen between 1985 and 2015, which also reflects the change in industry mix at those locations. The relative freight intensity ratio has been highest in traditionally industrialized areas such as parts of Michigan and Ohio. However, it decreased in many of those areas between 1985 and 2015. Meanwhile, other countiesâ industry mixes have grown more freight- intensive relative to the national average. The measure used to represent freight intensity is explained in the first section of the Addendum. Industry Tonnage (millions) Tons per Employee By Truck (%) By Multiple Modes* (%) Miles per Shipment Value per Ton ($1,000s) Primary metal manufacturing 375 924.0 79.8 3.9 731.9 1,218 Fabricated metal manufacturing 235 155.3 89.4 3.1 543.4 2,409 Machinery manufacturing 123 107.8 91.9 3.3 2,181.7 5,958 Computer and electronics manufacturing 53 54.3 87.8 8.9 333.1 19,062 Electrical equipment and appliance manufacturing 40 99.1 92.1 4.6 785.6 10,803 Transportation equipment manufacturing 270 167.6 85.0 5.1 381.2 5,461 Furniture manufacturing 55 130.5 95.8 1.6 408.6 4,903 Miscellaneous manufacturing 72 106.2 88.5 6.8 274.5 7,835 Wholesale trade 384 59.6 96.3 1.5 431.8 3,644 Media and information 19 5.5 92.3 6.2 361.0 4,111 Business services 248 20.7 92.6 1.7 517.3 123 *Multiple modes include truckârail, truckâair, and truckâmarine shipments. SOURCE: U.S. Census Bureau 2007. TABLE D-1 Continued
278 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM FIGURE D-6 Freight demand intensity relative to U.S. average, 1985, by county. FIGURE D-7 Change of freight demand intensity relative to U.S. average, 1985â 2015, by county.
APPENDIX D 279 Urban Population Patterns Follow the Economy and Shift Metropolitan Highway Needs The spatial pattern of population growth over 30 years is shown in Fig- ure D-8. The pattern generally mimics the spatial pattern of employment growth over the same period, which was shown as Figure D-5, even though there are few areas with an absolute decrease of population numbers. Popu- lation movements have tended to follow job creation because workers tend to move to where the jobs are. The key point to note is that past population growth has been largely concentrated in a relatively small number of metropolitan areas. Popula- tion losses are apparent for rural areas of Maine, parts of the Appalachian region, and the Mississippi River Valley. This trend means that some areas will have reductions in passenger car traffic on highways, whereas others will have disproportionately higher than average growth in local highway demand. Estimates of passenger VMT demand are derived using the Bureau of Transportation Statistics 2009 National Household Travel Survey (NHTS) FIGURE D-8 Population growth, by county, 1985â2015 (showing shapes of megaregions).
280 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM Transferability Statistics research (Manson et al. 2017).2 The change in VMT generation rate, expressed as VMT per household, is shown in Figure D-9 for the period between 19903 and 2015. The map shows a dispersed pattern with a tendency to decreasing VMT per household in the East and West, and increasing in the Midwest. The variation in VMT generation rate among regions affects the use of highways, which is the reason why this is yet another factor to be con- sidered when estimating future volumes on the Interstate Highway System. Daily VMT per household depends mainly on the household size, the num- ber of workforce participants per household, and the level of income. The areas with a rising VMT generation rate appear to roughly correspond to 2 This research provides regression coefficients for estimating household trip-making and VMT based on sociodemographic characteristics. Separate regressions are available for regions of the country and the urban, suburban, and rural portions of each region. The Transferability Statistics classification of urban, suburban, and rural areas is made at the Census tract level based on urbanization and population density. This was calculated for both 1990 and 2015. Counties were assigned classifications by summing population across tracts and assigning the county the dominant classification. For the 2015 baseline, county-level estimates are based on the 2011â2015 American Community Survey. The variables of interest were also acquired from the 1990 decennial Census through the National Historical Geographic Information System (Manson et al. 2017). 3 Data for 1985 are not available, but would have to be generated as a mean between 1980 and 1990. FIGURE D-9 Growth in ratio of daily passenger car VMT per household, by county, 1990â2015 (estimates).
APPENDIX D 281 areas of stagnant employment shown earlier in Figure D-5. This trend may reflect lower income growth and/or more workers per household, though further work will be necessary to confirm these relationships. Growth in total daily passenger car VMT can be computed by consid- ering the VMT per household ratio together with growth in the number of households in each county. Figure D-10 shows estimates of this metric in terms of its spatial distribution. In large parts of the United States, daily VMT increased considerably between 1990 and 2015. Decreasing or stagnating areas may be found for instance in the Midwest and along the Mississippi River. This map is particularly useful in illustrating locations where car VMT growth is occurring. It may also be interesting in the future to consider rates of VMT per square mile. Bottom Line As Americaâs economy evolves over time, there are systematic changes in location and composition of economic activity. These systematic industry activity changes translate into substantial changes in the level and pattern of truck freight travel patterns as well as car traffic within metropolitan areas. The past and current relationships shown in this section provide a basis for estimating the impacts of economic future forecasts in the next section. FIGURE D-10 Growth of total daily passenger car VMT, by county, 1990â2015 (estimates).
282 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM WHAT CAN WE EXPECT FOR THE FUTURE? The information in the preceding section on how the economy affects highway traffic provides a basis for now considering expectations about the long-term future evolution of the U.S. economy and its implications for future highway traffic. This section is organized into three main parts. 1. It presents a baseline economic and demographic forecast for the United States and examines how it is expected to change future highway travel demand. 2. It then presents a series of alternative economic forecasts that reflect differing assumptions about energy and transport cost changes, international trade policies, and global economic growth. It then discusses the difference in highway travel impact associated with these alternative future forecasts. 3. Finally, it discusses additional scenarios and factors that can also affect the future economy and highway travel demand. The analysis that is presented in this section focuses on 30-year fore- casts for clarity and simplicity of discussion. However, the Addendum presents additional forecasts and analysis for shorter (10- and 20-year) time frames and a longer (50-year) time frame. Baseline Economic Outlook and Highway Travel Consequences Definition of Baseline American industry relies on short-, medium-, and long-term models pro- vided by private firms to forecast future demographic and economic changes. The two best-known firms are Moodyâs Analytics and IHS Markit (formerly Global Insight). In general, the two services provide similar forecasts. Al- though the Federal Highway Administration (FHWA) Office of Policy relies on IHS Markit for its VMT forecasts, the analysis in this appendix used Moodyâs to access detailed year-by-year forecasts of demographic shifts and industry sector shifts by detailed categories for every county in the United States covering a 30-year period. (The forecasts were later extrapolated to 50 years; see Addendum for details.) For reference purposes, Moodyâs baseline forecast shows 0.68 percent annual employment growth rate over 2015â2045, whereas the IHS Markit forecast shows 0.75 percent. The corresponding GDP annual growth rates are 1.87 percent for Moodyâs and 2.06 percent for IHS Markit. Thus, the two forecast sources track closely together, although the Moodyâs growth numbers are slightly lower.
APPENDIX D 283 Moodyâs data used for this study include highly detailed demographic and economic forecasts. The demographic forecasts included information on changes in population, households, household size, type, workforce, retirees, and children. The economic forecasts included information on GDP (value added), employment (jobs), and worker income generated for 53 industry sectors. All forecasts are disaggregated for each of more than 3,000 counties, for each year. The source of the baseline demographic and economic forecasts was the Moodyâs U.S. macro model. It estimates how the economy, population, and workforce will shift in future years under explicit scenario assumptions such as slowly growing global markets, increasing productivity and stable cost-competitiveness, generally stable energy and other resource prices, stable international trade regulations, strengthening of the dollar against foreign currencies, slowly rising inflation and interest rates, and full em- ployment growth that is not constrained by labor market size. Alternative assumptions are considered later, in the section on alternative economic futures. In each case, the Moodyâs national macro model forecasts of economic growth are allocated to states and counties based on a second Moodyâs model that considers their relative competitiveness for attracting and grow- ing each of the industry sectors. The TREDPLAN4 analysis system was then applied to calculate and display further implications of alternative scenarios, including demographic and economic shifts for intercity flows of investment, income spending, people, and freight. Baseline Economic Change and Highway Travel Implications The forecast of 30-year change in employment by industry is represented in Figure D-11 for the largest industries. The expectation of overall 42.5 million additional jobs in 2045 (+23 percent) is the aggregation of 53 indus- tries with major shifts in workforce demand among themselves. Specifically, the forecasts show higher than average growth will occur in 13 industries, which make up 60 percent of todayâs overall jobs; lower than average growth will occur in 40 industries. Most of the industries with the highest growth are service industries, which follow the population shifts and therefore will be spread according to population distribution across the country. This part of growth changes will emphasize the concentration trend of people and jobs in metropolitan areas and, above all, in the nationâs megaregions, where highway use will grow accordingly. This will raise planning challenges insofar as the megaregions transcend metro and state boundaries. 4 See https://www.tredis.com/products/tredplan.
284 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM Other industries show different spatial growth and decrease patterns, which do not necessarily correlate with population growth. These patterns are further explored for four example industries (see Figures D-12âD-15). The trucking and warehousing and storage industries, which are mapped together in Figure D-12, are forecast to show an overall growth of 58,000 jobs over the next three decades. The additional jobs occur not only in metropolitan areas, but also in hotspots along major Interstate highways because highway accessibility is obviously crucial to this industry. Even though the absolute change in the number of jobs is modest, the freight- related nature of this industry makes its location important as a generator of traffic on Interstate highways. The professional, scientific, and technical services industry (see Figure D-13) is projected to add 4.7 million jobs by 2045. Much of its growth is projected to occur in the megaregions, although there are also many counties outside of those areas that are expected to see job growth in this industry sector. Because of its size and its magnitude of change, the spatial pattern of this industry is important for future traffic volumes on Interstate highways. In particular the high labor intensity of this service industry increases the density of urban commuting trips. This can also put pressure on urban Interstate highways unless there is increased use of other modes. The machinery manufacturing industry (see Figure D-14) is forecast to continue its decline in terms of domestic jobs in the United States. Between FIGURE D-11 Forecast change in national employment, by industry, 2015â2045.
APPENDIX D 285 FIGURE D-12 Trucking and warehousing and storage: Spatial pattern of job growth and decrease, by county, 2015â2045. FIGURE D-13 Professional and scientific and technical: Spatial pattern of job growth and decrease, by county, 2015â2045.
286 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM FIGURE D-14 Machinery manufacturing: Spatial pattern of job growth and de- crease, by county, 2015â2045. FIGURE D-15 Wood, paper, and furniture manufacturing: Spatial pattern of job growth and decrease, by county, 2015â2045.
APPENDIX D 287 2015 and 2045, it is forecast to lose 369,000 jobs. The analysis shows that this loss will be widely dispersed and not particularly concentrated in areas that have traditionally been manufacturing centers. The effect on highway travel will also be dispersed. The wood, paper, and furniture manufacturing industries (see Figure D-15) are expected to lose about 250,000 jobs over the next 30 years. These decreases occur mostly in rural areas close to lumber sources. This pattern is highly concentrated and is projected to lead to slow population growth in many of the affected areas. This can reduce demand for Interstate highway travel to and from these areas, although that also depends on the extent of rail use. In some of the wooded areas, there is also rising tourism that can have an offsetting effect on area VMT. Future shifts in the employment growth and decline in each county can lead to further substantial impacts on the overall spatial pattern of na- tionwide employment. This is shown in Figure D-16, which illustrates the Moodyâs Analytics model (baseline) forecast for 2015â2045 employment growth patterns. The spatial pattern of employment growth reflects a shift in growth rates among industries (see Addendum), and their interaction with differing state-level tax and related economic policies. Shifts in freight mix will also be an important factor affecting freight use of Interstate highways. âFreight intensityâ refers to the extent to which FIGURE D-16 Forecast change in employment, by county, 2015â2045.
288 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM economic activities require incoming freight shipments for their operations. There is a systematic variation in freight intensity associated with different industries (see Addendum Table D-A1). Since the local industry mix var- ies widely among areas, so does the freight intensity of economic activity. Figure D-17 shows the spatial pattern of change in freight intensity (rela- tive to the U.S. average change) that is forecast to occur between 2015 and 2045. The forecast pattern indicates growing industrial and hence freight intensity in parts of the West, South, and Southeast/Mid-Atlantic regions. By adding assumptions regarding future truck and rail mix, it will also be possible to show the expected intensity of future truck cargo generation. Detailed information about the industry changes over time are provided in the Addendum. Baseline Demographic Change and Highway Travel Implications The baseline economic growth of traded industries is projected to also drive shifts in workforce and population location patterns, which will then also attract population-serving activities. Figure D-18 shows the expected impact on population growth patterns and the evolution of megaregions. Counties forecast to have higher than average growth include some areas FIGURE D-17 Forecast change in freight intensity relative to U.S. average, by county, 2015â2045. NOTE: More information about freight intensity is provided in the Addendum.
APPENDIX D 289 that are already fast-growing, including Southern California, the Bay Area, the Texas Triangle, southern Florida, and some other metropolitan areas. These areas will also experience higher than average increases in commut- ing traffic on area highways, unless there are substantial efforts to shift more commuting to alternative modes. Where highways are already con- gested today, the future situation may be particularly challenging. The study team applied forecast data presented in this report to fore- casts of future VMT per household that were derived from Bureau of Transportation Statistics 2009 NHTS Transferability Statistics research. The results indicate that the ratio of VMT per household will grow mainly in the Midwest and the West (see Figure D-19). The highest growth rates appear in the dynamically changing areas in the Southwest. Growth in total passenger VMT (see Figure D-20) increases in the fast-growing mega- regions, in the West, but also in the East and North. Most of the counties with decreasing or stagnating passenger VMT are part of the Midwest or the South. Reasons may be relative changes in the household size, in the workforce participation, or in the level of income. FIGURE D-18 Forecast change in population by county, 2015â2045 (showing shapes of megaregions).
290 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM FIGURE D-19 Forecast growth in ratio of daily passenger VMT per household, 2015â2045. FIGURE D-20 Forecast growth in total daily passenger VMT, 2015â2045.
APPENDIX D 291 Alternative Economic Futures and Highway Travel Consequences There is significant uncertainty about future economic changes, since there may be unforeseen factors that will affect the assumptions made about rela- tive changes in U.S. productivity and cost-competitiveness, energy and other resource prices, international trade regulations, or other factors. This section explores implications of changing these assumptions. Other possible causes of future economic uncertainty, such as weather events, seismic events, or other unforeseen political or social disruption events, are discussed in an example later in the section on additional sources of future economic change. For illustrative purposes, we consider three alternative futures and their implications for changing highway travel demand. They were selected from the eight alternative scenarios provided by Moodyâs Analytics (2017). The development of economic indicators for the scenarios is demonstrated in the Addendum. The first two alternative futures represent extreme economic devel- opments in one or the other way, while the third alternative has mixed outcomes: 1. Stronger U.S. economic prosperity.5 Upside scenario of more posi- tive global growth, increasing U.S. exports, greater nonresidential investment, and additional job growth of 1.8 million jobs by 2045. 2. Protracted economic slump.6 Downside scenario of recession with falling stock market, lower bond prices, reduced trade and U.S. exports, higher China tariffs, and reduction in job growth by 18 million jobs by 2045 compared with the baseline. 3. Lower fuel and transportation costs.7 Scenario of low oil prices, reduced transportation cost, lower inflation, lower business costs, and additional job growth by 6.0 million jobs. Each of these alternative futures leads to a different mix of growth among industry sectors, as well as among locations. These differences are illustrated in the maps shown in Figures D-21âD-23 and as graphs in Fig- ures D-A1 and D-A2 in the Addendum. 1. Stronger U.S. economic prosperity. This scenario (see Figure D-21) shows greater output and job growth, compared with the baseline scenario. The shift is still greatest in specific âgrowth hotspotsâ in 5 Moodyâs Analytics (2017) scenario âStronger Near-Term Growth,â with temporary effects to 2020 extrapolated to persist to 2030. 6 Moodyâs Analytics (2017) scenario âProtracted Slump,â with temporary effects to 2020 extrapolated to persist to 2030. 7 Moodyâs Analytics (2017) scenario âLow Oil Price,â with temporary effects to 2020 ex- trapolated to persist to 2030.
292 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM FIGURE D-21 Jobs in stronger U.S. economic prosperity scenario compared with baseline, 2045. FIGURE D-22 Jobs in protracted economic slump scenario compared with baseline, 2045.
APPENDIX D 293 metropolitan areas, particularly the megaregions. Growth of ser- vice industries is more dispersed. The overall effect of this scenario is to accentuate the magnitude of growth in areas that are already growth hotspots. 2. Protracted economic slump. This scenario (see Figure D-22) rep- resents more than a temporary recession. Job growth is reduced considerably, which again mostly affects the growth hotspots in metropolitan areas and particularly the megaregions. Negative ef- fects on service industries are more widely dispersed. The overall effect of this scenario is to diminish the magnitude of growth in areas that are already growth hotspots. 3. Lower fuel und transportation costs. The âreduced fuel costâ sce- nario (see Figure D-23) has a more spatially distinct impact. Lower fuel prices reduce cost (and increase productivity) for producers and consumers. However, they negatively affect profits for energy industries and their supply chains. Petroleum and shale production areas can see particularly negative impacts. As each future change occurs in industry composition and location pat- terns, there will be corresponding shifts in originâdestination patterns for FIGURE D-23 Jobs in reduced fuel cost scenario compared with baseline, 2045.
294 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM both commuting and freight movements. To portray these shifts in traffic movements, it is necessary to first consider matrices of interindustry (buy and sell) relationships and their spatial characteristics, and then consider how the forecast industry location shifts will affect them. The outcome of this process is illustrated in Figure D-24, which shows the expected impact on freight movements for the scenario of lower fuel costs. Similar types of calculations and visualizations can also be done for other scenarios. This scenario was chosen to illustrate the effect because it presents clear GDP impacts that differ substantially among industries and that lead to significant changes in freight movement patterns, volumes, and distances (affecting tonnage and ton miles), all of which can then be assigned to the highway network. The scenario in Figure D-24 shows reductions in freight tonnage (blue lines) on highway routes in those parts of the country that produce petroleum and shale oil (which suffer revenue losses from lower oil prices). The scenario shows an increase in freight tonnage (red lines) on highway routes where manufacturers and shippers gain productivity and profitability. FIGURE D-24 Changes in freight flows for the lower fuel and transportation costs scenario.
APPENDIX D 295 Additional Sources of Future Economic Change: Planning Under Uncertainty Conditions Difference Between Economic Factors and Other Uncertainty Factors The preceding section discussed uncertainties about the economy, with alternative assumptions regarding economic factors such as evolving long- term shifts in trade, inflation, investment, and prices, which can affect the future pattern of industry and spatial economic growth. This section discusses other uncertainties that can also affect the economy (and hence highway VMT), although their cause may be geopolitical, site or geological, or climate related rather than aspects of the economy itself. â¢ Geopolitical/trade factors tend to focus on relationships between countries, usually via tariffs (although they may also include em- bargoes) that have the long-term effect of shifting import/export flows among certain combinations of nations. For instance, changes in trade with China, Mexico, South America, and Russia have all been discussed in the press as possibilities for the future. In many cases, extending these shifts among international trade partners means extending shifts among West Coast, East Coast, or Gulf Coast seaports, or sometimes also affecting Canadian and Mexican border movements. Changes in use of the Panama or Suez canals can have similar spatial economic effects. â¢ Severe site events can knock out specific airports, bridges, or high- way links for an extended period. To varying degrees, such facilities are used for domestic or international business activities (freight imports and exports, worker travel, or customer or visitor travel). Consequently, events affecting use of those facilities can also have economic impacts on specific affected industries and areas and can also lead to shifts in highway demand for long periods of time. They include â geological factors such as severe earthquakes, volcanoes, tsuna- mis, and landslides; â structural failures such as collapse of a major bridge, tunnel, or viaduct structure; â weather events such as a tornado or hurricane; and â terrorist actions such as bombs that knock out ports or termi- nals or highways that serve them. Although it is not possible to predict where these site events will occur, it is possible to rate sites by their vulnerability to such events and then apply
296 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM Monte Carlo simulations to calculate the economic impact of such events taking place at different locations. From an economic impact perspective, the cause does not necessarily matter. After all, multiple causes can lead to the same direct impact on a site and then produce similar impacts on certain industries and regions. â¢ Climate factors can have long-term consequences for the viability of economic activities that are located along ocean, lake, and river coasts, or that depend on access corridors through those areas. These effects tend to affect broad areas due to regional coast flood- ing (affected by rising sea levels), river valley flooding (affected by melting mountain ice), or forest/brush fires (affected by heat and drought). The severity of weather events is also exacerbated by climate change. In all cases, regardless of the reason for uncertainty, economic impact will occur insofar as specific industry or location concentrations are particu- larly hard hit. The highway VMT consequences follow from the economic activity shifts. Example: International Trade Shift We can illustrate the distortion effect on highway freight VMT by consider- ing the example of an international trade policy that shifts U.S. grain exports so that more go to Asia and less to Mexico. This example was developed by applying a trade impact scenario via TREDPLAN,8 based on Moodyâs baseline forecast9 and international trade patterns from WISERTrade.10 In this example, shown in Figure D-25, there is a gain of activity at various ports that directly serve Asia (mostly West Coast), or that serve Asia via the Panama Canal (Gulf Coast and Southeast United States). There is a corresponding loss of activity at various land ports (border crossings) at the Mexican border, as well as a smattering of smaller airports located farther away (used for shipping specialty products). The affected highway corridors were identified based on originâ destination patterns of grain export shipments. They are shown in Figure D-26. Apparent impacts include less reliance on congested I-35 in Texas and higher dependence on access to Seattle and congested California ports. 8 See https://www.tredis.com/products/tredplan. 9 See https://www.economy.com/products/alternative-scenarios. 10 See http://www.wisertrade.org/home/portal/index.jsp.
APPENDIX D 297 FIGURE D-25 Illustration of ports affected by shift of U.S. grain exports to Asia instead of Mexico. FIGURE D-26 Highway traffic links affected by shift of U.S. grain exports to Asia instead of Mexico.
298 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM CONCLUSIONS AND NEXT STEPS This section summarizes findings to date and issues that remain to be addressed. Findings to Date This appendix has shown how evolving changes in the U.S. economy will lead to critical changes in the location of generated highway traffic, car and truck mix, and originâdestination patterns of highway traffic. This finding can have profound implications for the future adequacy of the Interstate Highway System network and for the location of congestion points, and it can affect investment priorities to support our nationâs continued economic vitality. More generally, the appendix provides a base of information about economic drivers that influence demand for Interstate highways and their metropolitan area extensions. It shows how the U.S. economy has evolved and will continue to evolve differently, with shifts occurring in patterns of jobs, income, and business output (GDP). It shows how these patterns are shifting among industries (sectors of the economy) and locations of economic activityâwhich also affects population movements and highway traffic patterns. It means that even if the Interstate System has adequate capacity for anticipated VMT growth, that capacity may not be located where it is most needed. The analysis of alternative futures also showcases how economic un- certainty factors regarding global growth and transportation-related fuel prices can affect longer-term economic patterns across the United States. It shows that changes in current exchange rates, investments, and prices do not just affect overall growth rates across the board; they can also af- fect some industries and locations more than others. This finding can also have important consequences for assessing risk of either overinvestment in highway infrastructure with resulting stranded assets, or underinvesting in highway infrastructure with resulting capacity shortfalls and foregone economic productivity. In fact, both conditions can occur simultaneously, along different parts of the Interstate Highway System. Next Steps: Remaining Research Needs This appendix focused on establishing the economic determinants of VMT change. More work is needed to apply this information to develop models and forecasts of future VMT on the Interstate System. In particular, there is a need to develop forecasts of multiple alternative futures based on projections of the trip generation and originâdestination consequences of
APPENDIX D 299 changes in international trade, domestic trade, and other economic change scenarios. In addition to better developing VMT projections, more work is needed to develop alternative economic futures in sufficient detail to support a robust risk and uncertainty analysis. More work is also needed to apply these uncertainties to a complete highway network model to identify where the risks and vulnerabilities of the Interstate Highway System are greatest. Finally, to move forward in planning for the future of the Interstate Highway System, there will be a need to consider the nationâs economic de- pendence on the Interstate Highway System and the economic consequences of inadequately investing where capacity and performance are most criti- cally needed. The work reported in this appendix provides a starting basis and structure for moving forward on this topic. REFERENCES Abbreviations BTS Bureau of Transportation Statistics FHWA Federal Highway Administration BTS. 2017a. Table 1-35: U.S. Vehicle-Miles (Millions). National Transportation Statistics. U.S. Department of Transportation, Washington, D.C. https://www.bts.gov/archive/ publications/national_transportation_statistics/table_01_35. BTS. 2017b. Table 1-41: Principal Means of Transportation to Work (Thousands). National Transportation Statistics. U.S. Department of Transportation, Washington, D.C. https:// www.bts.gov/archive/publications/national_transportation_statistics/table_01_41. FHWA. 2017. Highway Statistics 2016. Table VM-202. U.S. Department of Transportation, Washington, D.C. https://www.fhwa.dot.gov/policyinformation/statistics/2016. FHWA and BTS. 2013. Freight Facts and Figures 2013. U.S. Department of Transportation, Washington, D.C. https://ops.fhwa.dot.gov/freight/freight_analysis/nat_freight_stats/ docs/13factsfigures/pdfs/fff2013_highres.pdf. Manson, S., J. Schroeder, D. Van Riper, and S. Ruggles. 2017. IPUMS National Historical Geographic Information System: Version 12.0 [Database]. University of Minnesota, Minneapolis. Moodyâs Analytics. 2017. U.S. Macroeconomic Outlook Alternative Scenarios. https://www. economy.com/home/products/samples/moodys-analytics-us-alternative-scenarios.pdf. U.S. Census Bureau. 2007. Commodity Flow Survey (CFS). https://www.census.gov/programs- surveys/cfs/data/tables.2007.html.
300 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM ADDENDUM Freight Intensity Estimation Freight intensity of demand is an ad hoc measure designed to reflect the spatial concentration of industries that demand a high level of freight goods for their production processes. This was estimated by using an input-output model (IMPLAN version 536, sector detail) and calculating the value of inputs related to bulk commodity goods11 as a percentage of total economic output of that industry. The industries were aggregated to a 53-sector grouping and graphically sorted based on intensity to identify an approxi- mate break in the intensity of demand. The red bars in Figure D-A1 indicate manufacturing industries with a higher than average freight demand. The blue bars indicate industries that have a lower than average freight demand. This calculated ratio is used in the section on key differences in highway reliance among industries (see Figures D-6 and D-7) and in the section on highway travel implications of baseline economic change (see Figure D-17) to show the spatial pattern of freight-intensive industries in the economy of each county. Of course, using these same ratios for comparisons over time assumes that production functions and capital/labor ratios do not change materially among industries over time. (That assumption can be refined in further studies.) 11 Based on the Standard Classification of Transported Goods. FIGURE D-A1 Identification of industries with highest intensity of freight demand (fraction of output, 53 sectors).
APPENDIX D 301 Baseline Scenario Over 50 Years The following tables show baseline forecasts for 2015â2065 in terms of employment and output. TABLE D-A1 Baseline Employment by Industry Over Time Industry Employment (jobs) 2015 2025 2035 2045 2065 Crop production 1,504,219 1,553,335 1,437,193 1,308,874 1,052,234 Animal production 1,167,083 1,213,600 1,128,760 1,030,862 835,066 Forestry and logging 144,994 153,717 142,696 130,451 105,961 Fishing, etc. 111,784 113,921 104,981 95,629 76,924 Support for agriculture and forestry 543,932 548,091 505,459 460,254 369,845 Oil and gas extraction 813,174 809,828 755,166 691,787 565,030 Mining, quarrying, and support 768,207 758,842 705,784 642,296 515,320 Utilities 684,932 673,233 647,567 601,346 508,904 Construction and buildings 10,156,166 12,472,113 13,189,748 14,122,909 15,989,230 Food manufacturing 1,806,898 1,773,716 1,553,541 1,294,188 775,481 Beverage and tobacco product manufacturing 247,889 242,653 212,101 176,432 105,092 Textile mills and products manufacturing 247,249 218,213 188,978 177,739 155,259 Apparel manufacturing 175,023 153,378 132,910 124,782 108,525 Leather product manufacturing 34,323 30,746 27,107 25,688 22,851 Wood product manufacturing 447,265 412,290 369,860 344,538 293,894 Paper manufacturing 376,600 346,021 309,344 287,660 244,294 Printing 557,848 500,048 440,331 417,149 370,784 Petroleum and coal products manufacturing 115,264 108,615 96,752 87,210 68,127 Chemical manufacturing 789,829 728,788 636,208 564,808 422,009 Plastics and rubber products manufacturing 707,430 648,666 560,229 491,749 354,789 Nonmetal mineral product manufacturing 428,006 387,527 343,319 324,396 286,551 continued
302 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM Industry Employment (jobs) 2015 2025 2035 2045 2065 Primary metal manufacturing 405,483 345,648 293,973 294,099 294,350 Fabricated metal manufacturing 1,515,650 1,292,039 1,099,951 1,082,180 1,046,636 Machinery manufacturing 1,145,136 969,793 825,621 775,851 676,310 Computer and electronics manufacturing 968,065 889,448 763,589 672,061 489,004 Electrical equipment and appliance manufacturing 401,509 368,426 327,094 301,570 250,520 Transportation equipment manufacturing 1,613,540 1,588,006 1,631,493 1,625,293 1,612,893 Furniture manufacturing 420,986 404,183 382,307 357,701 308,490 Miscellaneous manufacturing 680,610 624,546 556,892 516,722 436,382 Wholesale trade 6,443,610 5,912,392 5,274,378 4,891,133 4,124,645 Retail trade 18,026,221 19,241,384 19,533,894 20,742,242 23,158,938 Air transportation 492,667 511,947 508,301 493,861 464,982 Rail transportation 208,010 213,176 211,272 204,986 192,413 Water transportation 76,415 77,736 76,778 74,079 68,681 Truck transportation 2,114,043 2,187,086 2,173,695 2,113,140 1,992,030 Transit and ground transportation 1,081,420 1,123,903 1,132,230 1,122,827 1,104,022 Pipeline transportation 49,589 51,639 51,699 50,407 47,824 Scenic and sightseeing transport support 732,246 850,774 936,574 1,075,197 1,352,442 Couriers, messengers and postal service 1,516,438 1,648,381 1,745,696 1,843,748 2,039,853 Warehousing and storage 1,022,957 1,094,506 1,115,386 1,081,879 1,014,864 Media and information 3,356,782 3,408,581 3,403,326 3,452,451 3,550,702 Finance and insurance 9,939,217 10,805,384 11,819,397 13,378,990 16,498,175 Real estate, rental, and leasing 8,125,814 8,958,662 10,116,908 11,784,507 15,119,706 TABLE D-A1 Continued
APPENDIX D 303 Industry Employment (jobs) 2015 2025 2035 2045 2065 Professional, scientific, and technical 14,400,183 16,149,377 17,534,598 19,135,320 22,336,762 Management services 2,354,727 2,680,167 2,987,841 3,343,850 4,055,869 Business services (administration, support, waste) 11,972,258 13,390,775 14,431,016 15,630,989 18,030,935 Education services 3,708,034 4,059,884 4,406,005 4,725,075 5,363,214 Health care and social assistance 21,185,100 23,665,834 25,586,549 27,797,594 32,219,684 Arts, entertainment, and recreation 4,064,867 4,691,052 5,142,333 5,879,001 7,352,337 Lodging 1,488,830 1,729,720 1,905,623 2,191,752 2,764,011 Restaurants and drinking establishments 13,047,911 15,107,136 16,598,909 19,013,447 23,842,524 Other services 11,856,998 13,188,597 14,107,001 15,175,911 17,313,730 Government (public administration) 22,565,361 24,065,241 25,622,095 27,072,716 29,973,957 TABLE D-A1 Continued TABLE D-A2 Baseline Output by Industry Over Time Industry Output (millions of dollars) 2015 2025 2035 2045 2065 Crop production 200,447 225,019 256,185 280,998 330,625 Animal production 203,998 241,716 277,261 307,020 366,537 Forestry and logging 11,837 14,698 16,661 18,288 21,542 Fishing, etc. 7,445 9,732 11,211 12,340 14,599 Support for agriculture and forestry 34,491 41,347 47,606 52,628 62,672 Oil and gas extraction 216,618 233,636 213,487 191,264 146,819 Mining, quarrying, and support 231,886 250,238 227,278 200,110 145,775 Utilities 756,043 880,407 959,780 1,015,325 1,126,416 Construction 1,703,879 2,105,786 2,209,755 2,261,891 2,366,164 Food manufacturing 955,854 902,133 878,139 863,954 835,584 Beverage and tobacco product manufacturing 218,969 210,549 209,184 209,878 211,264 continued
304 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM Industry Output (millions of dollars) 2015 2025 2035 2045 2065 Textile mills and products manufacturing 66,132 67,216 67,716 67,793 67,948 Apparel manufacturing 19,823 20,379 20,248 19,860 19,083 Leather product manufacturing 8,070 8,330 8,270 8,129 7,847 Wood product manufacturing 106,328 134,466 168,957 207,410 284,316 Paper manufacturing 225,308 274,032 332,838 396,485 523,778 Printing 90,469 93,109 91,817 89,772 85,683 Petroleum and coal products manufacturing 451,997 573,415 673,650 784,554 1,006,361 Chemical manufacturing 1,174,022 1,429,874 1,670,998 1,938,843 2,474,533 Plastics and rubber products manufacturing 246,803 292,234 333,835 379,070 469,539 Nonmetal mineral product manufacturing 135,735 167,923 206,456 247,168 328,592 Primary metal manufacturing 281,137 330,562 384,827 432,084 526,598 Fabricated metal manufacturing 395,002 469,410 556,883 635,857 793,804 Machinery manufacturing 496,023 563,837 662,953 765,445 970,429 Computer and electronics manufacturing 550,279 859,682 1,331,497 1,932,443 3,134,333 Electrical equipment and appliance manufacturing 162,465 203,281 256,307 317,309 439,313 Transportation equipment manufacturing 1,124,302 1,496,830 1,905,149 2,232,592 2,887,479 Furniture manufacturing 82,382 94,008 106,308 117,504 139,895 Miscellaneous manufacturing 189,949 239,284 297,830 362,965 493,235 Wholesale trade 1,655,910 2,073,713 2,580,157 3,145,545 4,276,322 Retail trade 1,472,336 1,889,020 2,376,010 2,915,317 3,993,930 Air transportation 202,027 268,796 342,445 430,541 606,734 Rail transportation 84,438 108,380 136,113 169,230 235,463 Water transportation 62,514 83,829 106,066 130,161 178,350 Truck transportation 349,964 454,628 570,930 710,173 988,659 Transit and ground transportation 73,832 91,492 109,817 130,587 172,127 TABLE D-A2 Continued
APPENDIX D 305 Industry Output (millions of dollars) 2015 2025 2035 2045 2065 Pipeline transportation 35,734 47,218 61,352 78,240 112,017 Scenic and sightseeing transport support 123,116 162,613 205,658 256,390 357,854 Couriers, messengers, and postal service 162,065 200,763 243,780 293,329 392,429 Warehousing and storage 104,703 151,911 217,731 308,081 488,781 Media and information 1,639,214 2,217,025 2,815,322 3,531,935 4,965,162 Finance and insurance 2,441,631 2,843,859 3,153,913 3,469,123 4,099,543 Real estate, rental, and leasing 3,231,264 3,764,937 4,166,190 4,577,163 5,399,109 Professional, scientific, and technical 2,368,846 3,144,850 3,993,965 4,974,890 6,936,739 Management services 573,327 756,200 953,161 1,179,644 1,632,611 Business services (administration, support, waste) 854,640 1,140,949 1,456,972 1,824,483 2,559,504 Education services 270,411 335,960 420,752 511,106 691,814 Health care and social assistance 2,104,237 2,641,309 3,340,731 4,102,232 5,625,235 Arts, entertainment, and recreation 323,475 407,984 502,922 608,348 819,200 Lodging 160,853 204,828 254,758 310,118 420,839 Restaurants and drinking establishments 785,304 988,863 1,222,948 1,487,741 2,017,327 Other services 985,886 1,312,254 1,668,414 2,079,417 2,901,423 Government (public administration) 2,306,486 2,659,056 3,096,137 3,550,682 4,459,772 TABLE D-A2 Continued
306 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM Changes in Characteristics of the Economy The following tables show forecasts of change in the industry mix, produc- tivity, and trip distances over 2015â2045. TABLE D-A3 Economic Shifts by Industry, 2015â2045 Industry Distribution of Employment (%) Distribution of GDP (%) 2015 2045 2015 2045 Crop production 0.80 0.57 0.50 0.41 Animal production 0.62 0.45 0.37 0.31 Forestry and logging 0.08 0.06 0.04 0.03 Fishing, etc. 0.06 0.04 0.03 0.03 Support for agriculture and forestry 0.29 0.20 0.15 0.13 Oil and gas extraction 0.43 0.30 0.86 0.44 Mining, quarrying, and support 0.41 0.28 0.79 0.40 Utilities 0.36 0.26 1.72 1.33 Construction 5.38 6.11 4.29 3.23 Food manufacturing 0.96 0.56 1.00 0.51 Beverage and tobacco product manufacturing 0.13 0.08 0.44 0.24 Textile mills and products manufacturing 0.13 0.08 0.10 0.06 Apparel manufacturing 0.09 0.05 0.04 0.02 Leather product manufacturing 0.02 0.01 0.01 0.01 Wood product manufacturing 0.24 0.15 0.17 0.19 Paper manufacturing 0.20 0.12 0.31 0.31 Printing 0.30 0.18 0.23 0.13 Petroleum and coal products manufacturing 0.06 0.04 0.88 0.85 Chemical manufacturing 0.42 0.24 1.83 1.71 Plastics and rubber products manufacturing 0.37 0.21 0.42 0.37 Nonmetal mineral product manufacturing 0.23 0.14 0.27 0.28 Primary metal manufacturing 0.21 0.13 0.32 0.28 Fabricated metal manufacturing 0.80 0.47 0.82 0.75 Machinery manufacturing 0.61 0.34 0.83 0.72 Computer and electronic manufacturing 0.51 0.29 1.40 2.86
APPENDIX D 307 TABLE D-A3 Continued continued Industry Distribution of Employment (%) Distribution of GDP (%) 2015 2045 2015 2045 Electrical equipment and appliance manufacturing 0.21 0.13 0.30 0.33 Transportation equipment manufacturing 0.85 0.70 1.56 1.76 Furniture manufacturing 0.22 0.15 0.15 0.12 Miscellaneous manufacturing 0.36 0.22 0.45 0.49 Wholesale trade 3.41 2.11 5.91 6.40 Retail trade 9.55 8.97 5.41 6.12 Air transportation 0.26 0.21 0.49 0.60 Rail transportation 0.11 0.09 0.25 0.29 Water transportation 0.04 0.03 0.10 0.12 Truck transportation 1.12 0.91 0.80 0.92 Transit and ground transportation 0.57 0.49 0.19 0.20 Pipeline transportation 0.03 0.02 0.14 0.18 Scenic and sightseeing transport support 0.39 0.46 0.36 0.42 Couriers, messengers, and postal service 0.80 0.80 0.60 0.62 Warehousing and storage 0.54 0.47 0.34 0.57 Media and information 1.78 1.49 4.73 5.77 Finance and insurance 5.26 5.78 7.20 5.75 Real estate, rental, and leasing 4.30 5.09 12.53 10.12 Professional, scientific, and technical 7.63 8.27 8.21 9.82 Management services 1.25 1.45 2.01 2.35 Business services (administration, support, waste) 6.34 6.76 3.19 3.88 Education services 1.96 2.04 0.97 1.05 Health care and social assistance 11.22 12.02 7.35 8.17 Arts, entertainment, and recreation 2.15 2.54 1.04 1.11 Lodging 0.79 0.95 0.58 0.64 Restaurants and drinking establishments 6.91 8.22 2.50 2.70
308 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM TABLE D-A3 Continued Industry Distribution of Employment (%) Distribution of GDP (%) 2015 2045 2015 2045 Other services 6.28 6.56 2.77 3.34 Government (public administration) 11.95 11.70 12.04 10.57 Total 100.00 100.00 100.00 100.00 TABLE D-A4 Shifts in Freight Shipping Distances, 2015â2045 Tonnage Driven Statistics 2015 Change, 2015â2045 (%) Ton miles 6,993,628.98 40 0â50 miles 50,871 64 51â100 miles 150,784 62 101â200 miles 345,974 56 201â500 miles 859,608 57 501+ miles 5,586,392 36 Vehicle-miles traveled 1,274,134 41 0â50 miles 9,587 64 51â100 miles 28,596 62 101â200 miles 63,238 56 201â500 miles 191,986 57 501+ miles 980,727 36 TABLE D-A5 Changes in Productivity and Income by Industry, 2015â2045 Industry Change in Output per Employee, 2015â2045 (%) Change in Income per Employee, 2015â2045 (%) Crop production 61 66 Animal production 70 66 Forestry and logging 72 74 Fishing, etc. 94 93 Support for agriculture and forestry 80 77 Oil and gas extraction 4 5 Mining, quarrying, and support 3 7 Utilities 53 53 Construction -5 -5 Food manufacturing 26 26
APPENDIX D 309 Industry Change in Output per Employee, 2015â2045 (%) Change in Income per Employee, 2015â2045 (%) Beverage and tobacco product manufacturing 35 30 Textile mills and products manufacturing 43 41 Apparel manufacturing 41 38 Leather product manufacturing 35 33 Wood product manufacturing 153 154 Paper manufacturing 130 130 Printing 33 32 Petroleum and coal products manufacturing 129 127 Chemical manufacturing 131 122 Plastics and rubber products manufacturing 121 119 Nonmetal mineral product manufacturing 140 139 Primary metal manufacturing 112 110 Fabricated metal manufacturing 125 124 Machinery manufacturing 128 126 Computer and electronics manufacturing 406 398 Electrical equipment and appliance manufacturing 160 162 Transportation equipment manufacturing 97 94 Furniture manufacturing 68 67 Miscellaneous manufacturing 152 150 Wholesale trade 150 150 Retail trade 72 72 Air transportation 113 113 Rail transportation 103 102 Water transportation 115 114 Truck transportation 103 103 Transit and ground transportation 70 63 Pipeline transportation 115 127 TABLE D-A5 Continued continued
310 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM Alternative Scenarios The alternative scenarios used here have a common property: strong and differing assumptions about economic conditions over the first 10 years (2015â2025), followed by an adjustment toward equilibrium (diminishing the severity of the trend) over the next 5 years (2015â2025), with earlier gains or losses then sustained for the rest of the study period (2025â2045). Impacts beyond that time frame are merely extrapolations of the 2035â 2045 trends. These scenarios were derived from Moodyâs Analytics scenarios, but adjusted to reflect more sustained long-term economic impacts. Whereas the original Moodyâs scenarios assumed a 10-year period of economic shock and equilibrium adjustment, the forecasts shown here sustain the impacts over a longer 20-year period. In any case, it is notable that the employment difference among scenarios in (see Figure D-A2) is substantially greater than the output difference among scenarios (see Figure D-A3). Industry Change in Output per Employee, 2015â2045 (%) Change in Income per Employee, 2015â2045 (%) Scenic and sightseeing transport support 42 41 Couriers, messengers, and postal service 49 47 Warehousing and storage 178 178 Media and information 109 108 Finance and insurance 6 5 Real estate, rental, and leasing -2 0 Professional, scientific, and technical 58 58 Management services 45 44 Business services (administration, support, waste) 64 63 Education services 48 48 Health care and social assistance 49 48 Arts, entertainment, and recreation 30 30 Lodging 31 31 Restaurants and drinking establishments 30 30 Other services 65 65 Government (public administration) 28 29 TABLE D-A5 Continued
APPENDIX D 311 FIGURE D-A2 Projections of employment by scenario. FIGURE D-A3 Projections of output by scenario.
312 NATIONAL COMMITMENT TO THE INTERSTATE HIGHWAY SYSTEM Note that output (rather than GDP) has some advantage for forecast- ing changes in travel demand because it reflects the total value of goods produced and goods shipped (whereas GDP reflects the portion of output value that is incremental personal and business income). GDP is roughly 55 percent of total output. (In 2015, GDP was $18 trillion whereas output was $33 trillion.)