“[M]en and women’s average commuting times may be roughly the same, but men actually travel at significantly faster speeds and, as a consequence, cover larger distances. In general, trips made by women, particularly women with children were made at significantly lower travel speeds. (see table below: women with children, for instance, travel an average distance of 7.92km at an average speed of 9.98km/hr, as opposed to an average distance of 9.96km for men with children, which translates into a speed of 12.27km/hr).
Table 1: Travel times, distances and speeds for work trips for men and women.
Work Trips. ENMODO 2009. Expanded Survey
Average Time (min) Average Distance (km) Average Speed (km/hr) Women without Children 45.3 7.50 9.92 Men without Children 43.3 8.67 12.01 Women with Children 47.7 7.92 9.98 Men with Children 48.7 9.96 12.27
How can we explain those differences? Our hypothesis is that women’s travel choices are limited in part by household maintenance activities, which force them to rely on comparatively slower modes: the survey finds that women walk more than men and take buses, while men are using cars and trains more.
If women are indeed constrained to smaller commutes, it also means they have access to fewer employment opportunities – with inevitable consequences on their wage rates and related labor market outcomes. The map below highlights the stark contrast in job accessibility between men and women in the Buenos Aires Metropolitan Area: in parts of the city, men with children have access to over 80% more jobs than their female counterparts.”
Our Accessibility Observatory is featured in nice, detailed article in Atlantic Cities by Emily Badger: This Map Wants to Change How You Think About Your Commute
“When we think about this as economists, we know that every trip that is made is worth it – the value outweighs the cost of taking it – or it wouldn’t have happened,” says Andrew Owen, the director of the recently created Accessibility Observatory at the University of Minnesota. “It’s a little bit disingenuous to use metrics that only talk about the cost of travel.”
Read the article for details. More maps coming soon.
Standard urban economics discusses Economic Base Theory. A nice definition is via Tim Chapin:
The economic base technique is grounded in the assumption that the local economy can be divided into two very general sectors: 1) a basic (or non-local) sector or 2) a non-basic (or local) sector.
Basic Sector: This sector is made up of local businesses (firms) that are entirely dependent upon external factors. For example, Boeing builds and sells large airplanes to companies and countries located throughout the world. Their business is dependent almost entirely upon non-local firms. Boeing does not sell planes to families or households locally, so their business is very much dependent upon exporting their goods. Manufacturing and local resource-oriented firms (like logging or mining) are usually considered to be basic sector firms because their fortunes depend largely upon non-local factors, they usually export their goods.
Non-basic Sector:The non-basic sector, in contrast, is composed of those firms that depend largely upon local business conditions. For example, a local grocery store sells its goods to local households, businesses, and individuals. Its clientele is locally based and, therefore, its products are consumed locally. Almost all local services (like drycleaners, restaurants, and drug stores) are identified as non-basic because they depend almost entirely on local factors.
Economic development practice is to entice/enhance “basic” industry. The example of Boeing is especially timely, given the recent issue of Boeing potentially moving airframe production if it didn’t get labor givebacks. I don’t imagine most of the places that Boeing was considering moving to have an airframe sector, or upstream or downstream vendors or customers, or a workforce skilled in airframe manufacturing, which would generate benefits beyond “jobs, jobs, jobs”. Similarly, ED advocates often argue for new infrastructure , despite at best weak evidence that in a mature (road, rail, transit) network there will be much accessibility gain, and thus little resulting economic development.
But the key point to remember from welfare economics is that everything is non-basic at a global level, and everything is basic at the household level. While it might be locally preferred to have more basic employment (we get money in exchange for stuff), that makes no difference on the global scale. Economic development practice is parochial (which is no surprise as it is funded by place-based local and state governments).
Yet that is not to say that local development is neither good nor bad. The reason it might actually be better to have local concentrations is because of various types of economies: in particular economies of scale of various kinds (including economies of agglomeration, which in places with very large employers, may all be internalized), and network economies. These economies produce spillovers, not just for the firm, but also for upstream and downstream supplies and customers, and potentially for competitors as well. I will call these Spillover Sectors.
Economies of scale mean that the cost goes down the more that is produced, (economies of scale are within firm, economies of agglomeration are within place, but between firms), so we can lower global costs if we specialize. The core reasons for this include large fixed costs associated with plants.
Reasons for Economies of agglomeration are also plentiful (from the Transportation Economics Wikibook):
|Type of scale economy||Example|
|Internal||1. Pecuniary||Being able to purchase intermediate inputs at volume discounts|
|Technological||2. Static technological||Falling average costs because of fixed costs of operating a plant|
|3. Dynamic technological||Learning to operate a plant more efficiently over time|
|External or Agglomeration||Localization||Static||4. Shopping||Shoppers are attracted to places where there are many sellers|
|5. Adam Smith Specialization||Outsourcing allows both the upstream input suppliers and downstream firms to profit from productivity gains because of specialization|
|6. Marshall labor pooling||Workers with industry-specific skills are attracted to a location where there is a greater concentration.a|
|Dynamic||7. Marshall-Arrow-Romer Learning-by-doing||Reductions in costs that arise from repeated and continuous production activity over time and which spill over between firms in the same place|
|Urbanization||Static||8. Jane Jacobs innovation||The more that different things are done locally, the more opportunity there is for observing and adapting ideas from others|
|9. Marshall labor pooling||Workers in an industry bring innovations to firms in other industries; similar to no. 6 above, but the benefit arises from the diversity of industries in one location.|
|10. Adam Smith division of labor||Similar to no. 5 above, the main difference being that the division of labor is made possible by the existence of many different buying industries in the same place|
|Dynamic||11. Romer endogenous growth.||The larger the market, the higher the profit; the more attractive the location to firms, the more jobs there are; the more labor pools there, the larger the market—and so on|
|12. Pure agglomeration||Spreading fixed costs of infrastructure over more taxpayers; diseconomies arise from congestion and pollution|
Source: World development report 2009: reshaping economic geography By World Bank, Adapted from Kilkenny, Maureen (1998) “Economies of Scale” Lecture for Economics 376, Rural, Urban, and Regional Economics, Iowa State University, Ames Iowa
Economies of scale are so pervasive we don’t notice them. Every road is an instance of economies of scale, we walk/ride/drive along roads because it is faster than going across unimproved space, even though it is less direct, but we individually could not afford to build the road, so we share the fixed costs with lots of people. The cost per person for roads is lower the more persons we spread the cost over. Economies of scale may also be played out (exhausted) at the margins we observe. Just because we had economies of scale in the roads we have built to date does not mean there are still economies of scale waiting to be picked up off the street like the proverbial $10 bill.
Two economists are walking down the street when one points to the ground and says, “Look, a ten dollar bill!”
The second economist replies, “That’s crazy. If that was a ten dollar bill someone would have picked it up already.”
In fact, most of the easy things have been done. Not to be as pessimistic as Tyler Cowan, but it is true that we pick the the projects with the highest Benefit/Cost ratios (low-hanging fruit) first, and work our way down-the list (up the tree), until the cost of building the project outweighs the benefits (the cost of getting the fruit outweighs the pleasures of consuming it). Clearly new projects are often on the low B/C side of the equation.
Network economies mean that the value of something increases the more people who use it. These are also so pervasive we don’t always notice them. The more people who use MSP airport, the better the airport is for me, because it will have more flights. Roads are also examples of network economies, as the more people who use the road, the higher quality road we will build and the more accessibility (by auto) I will have. Thus we have interstate highways because we have hundreds of millions of drivers. If there were only one driver, even Bill Gates, we would not have an interstate system.
So to get back to types of employment. When doing economic development we should not be thinking about Basic vs. Non-basic. We should be thinking about employment that has benefits from concentration, either economies of scale and agglomeration, or network externalities, or both, and then working toward establishing concentrations of those sectors to maximize the benefits to society. This usually means considering where local strengths already are, rather than starting from scratch. Complement the existing rather than dropping in an alien business. The job multiplier from two jobs paying $75,000 may be the same, but the one in a spillover sector will lower costs for others in the sector and/or improve benefits. It means not going after projects just because they generate jobs, but encouraging firms to relocate into specialist concentrations where there are spillover benefits from those concentrations.
In contrast, sectors which have losses with concentration (think natural monopolies, where competitors split the market so that no firm can recover fixed costs), should be encouraged to remain dispersed.
I will be talking, over the Internet, in Raleigh-Durham on January 8 about accessibility and transit at the RTA Transit Innovations Series.
The Regional Transportation Alliance has launched a new RTA Transit Innovations Series to support and advance current discussions on transit in Wake County.
The sessions include in person and/or videoconference presentations from experts on bus rapid transit and related innovations and research including express lanes, freeway caps, land use, circulators, and periodic comparisons with various rail transit options such as commuter rail, streetcars, and light rail.
(Download pdf overview of the RTA Transit Innovations Series here).
With the exploration of new and emerging transit innovations, the development of a bus rapid transit-based alternative(s) as a basis for comparison with the current draft plan, and the clarification and prioritization of goals and objectives, our community can evaluate the potential mobility and economic benefits of transit for our community and make an informed decision on our enhanced regional transit future in Wake County.
There will be no cost to attend any of the events in the RTA Transit Innovations Series. Scroll down or click here if you are interested in sponsoring either an individual session or the entire RTA Transit Innovations Series.
Detailed schedule of all past and future RTA Transit Innovations Series events.
RTA Transit Innovations Series
Session 2: Research on land use and tradeoffs
Wednesday, January 8, 2014, 3:30 pm EST
Greater Raleigh Chamber of Commerce
Presenters, via Cisco WebEx videoconference:
- David Levinson, Ph.D., University of Minnesota
- Editor of the Journal of Transport and Land Use and Director of the NEXUS research group
- Stephanie Lotshaw, Manager, U.S. and Africa, Institute for Transportation and Development Policy
- Author of More Development for your Transit Dollar
I am quoted:
There is an institutional divide between transportation planning and management and land planning and management. Mobility measures still dominate discussions of system performance in transportation. Also transportation agencies feel they do not control land use, so that including it in the performance measures is not helpful, while land planning agencies feel they do not control transportation.
We do of course recommend overcoming this institutional divide.
A recommended federal measure would provide a benchmark for the state and local agencies, which then could develop their own accessibility metrics.
The article also cites Brendon Slotterback’s proposal for a Department of Accessibility
Sarah Fecht writes about How Traffic Jams Decentralize Cities:
“In a new paper in Physical Review Letters, [Marc] Barthelemy and his colleague, Remi Louf, have constructed a mathematical model to explain how cities and their surrounding suburbs evolve to be polycentric. Their findings suggest that population size and automobile traffic congestion play large roles in driving the creation of alternative hot spots, even in small- to medium-size cities. “It’s an interplay between how attractive the place is, and how much time it takes to go there,” he says. At first everyone goes to the city center, but as the city becomes increasingly crowded it becomes more difficult to get there. Eventually subcenters spring up toward the city’s outskirts, providing more convenient locations for residents to work and shop. Cities with accommodating transportation networks remain centralized longer, but once population density passes a certain threshold, cities inevitably become polycentric, Barthelemy says.
David Levinson, a transportation engineer at the University of Minnesota, says it is not altogether surprising to find a relationship between population size and the number of urban subcenters. A group of economists made that assumption a few decades ago. Barthelemy counters that the economic models were “fuzzy” and untested. “After 20 pages of calculation, they don’t have a prediction and they don’t test their model,” Barthelemy says. “We can test our results against data.”
Having a clearer understanding of the evolution of metropolitan polycentricity could prove useful, Levinson says, especially considering that two thirds of the world’s population is expected to be urban by the year 2050. “There’s a lot of urbanization left to happen,” Levinson says. “If planners imagine a city to take a particular form, but that’s not the way the city wants to behave, we’ll be making unwise investments.”“
Major American cities get a report card each year on their mobility, focusing chiefly on how fast motorists can drive on their highways. In coming years, however, cities will have another way of understanding their transportation systems thanks to the work of the Accessibility Observatory at the University of Minnesota.
The new Observatory will go beyond congestion rankings to focus on accessibility: a measure that examines both land use and the transportation system.
“Focusing solely on mobility and traffic delay doesn’t provide a complete picture of how thetraffic system is functioning,” says Professor David Levinson, the RP Braun/CTS Chair in Transportation and principal investigator for the Observatory. “Travelers may be able to reach their desired destinations in a reasonable amount of time despite congestion because their cities have greater density of activities. In short, these travelers enjoy better access to destinations.”
The Accessibility Observatory, a program of CTS and the Department of Civil Engineering (CE), will focus on the research and application of accessibility based transportation system evaluation. It will be guided by a threefold mission:
- To advance the field of transportation system evaluation through research of new data sources and methods for accessibility evaluation.
- To develop standards and tools to facilitate the use and communication of accessibilitybased metrics in transportation planning, engineering, and evaluation.
- To apply its tools and expertise in support of continual improvements in the planning, design, engineering, and analysis of transportation systems.
The Observatory’s initial goal will be the development, application, and continuous improvement of a system for multimodal accessibility evaluation, says Andrew Owen, the Observatory’s director and a CE research fellow. Outputs from this system will be publicized through annual reports summarizing trends in accessibility across major U.S. metropolitan areas.
The first such report came out this past spring. Access Across America, published by CTS, evaluated the accessibility provided by the road and highway systems in 51 U.S. metropolitan areas. “The study was the first systematic comparison of accessibility to jobs by car,” Levinson says. “It demonstrated the feasibility and the value of applying consistent accessibility evaluation methods across many cities.”
The Access Across America report was widely cited by transportation policy practitioners and commentators. For example, Reihan Salam of the National Review Online wrote that focusing on “accessibility rather than infrastructure spending levels as such will get us much closer to tackling the frustrations that plague commuters.”
Access Across America provided aggregate metro-level accessibility metrics. The Accessibility Observatory will expand on this work by providing accessibility evaluations that can be analyzed at much smaller areas, Owen explains.
The Accessibility Observatory will also build on earlier work conducted at the University of Minnesota, including the Access to Destinations research study. The study, a multi-phase, multidisciplinary effort incorporating theoretical as well as practical research, built local expertise and prepared the University for next steps into the future of accessibility research and evaluation. CTS led the study; funding sponsors included the Minnesota Department of Transportation, Hennepin County, and the McKnight Foundation, in cooperation with the Metropolitan Council.
CTS is creating and hosting a new mobile-friendly and dynamic website for the Observatory. The site includes an interactive map/calculator, research reports, and other materials.
Levinson predicts improved accessibility, more real-time transportation data, and cleaner cities.
What does the future hold for transportation? University of Minnesota civil engineering professor David Levinson shared his thoughts as part of a panel of transportation experts in a series of videos from The Week magazine. Some highlights from Levinson’s predictions are below.
Urban mobility in 10 years
Over the next 10 years, Levinson predicts the emergence of driverless cars on the road, more car sharing and bike sharing programs, and more real-time information about buses and traffic congestion. “The future is already out there in pieces, but it will be much more systematically deployed in 10 years,” he says.
He also predicts that cities will be cleaner, with more electric cars and lower levels of tailpipe emissions, even for transit vehicles and trucks. “Cities will be more pleasant places to live,” he says.
Mobility versus accessibility
“We’ll need to think about transportation not as providing mobility but providing accessibility,” Levinson says. “It’s not just how fast we move on the network, but about how many things we can reach.” According to Levinson, connecting people to the places they want to go is not only a transportation issue, but also a land-use issue.
The challenge, Levinson says, is that these issues are often governed by different organizations. “Land use is generally locally managed, and transportation is funded at least in part by the federal and state government…They have different objectives,” he says. Improvements in accessibility will require better coordination and alignment of these transportation and land-use objectives.
The role of data
According to Levinson, accurate and reliable transportation data are and will continue to be important because they can provide real-time information to help travelers plan in real-time. And although data are already being used to provide information to drivers, transit users, and flyers, there are still areas where data are incomplete—such as for travel time on urban arterials.
“We’re in process,” Levinson said. “We’re going to be doing a lot better in five years than we are today, and we’re doing a lot better today than we were five years ago. But we’re not there yet in terms of being able to fully exploit the information that’s out there.”
- Anderson, Paul, David Levinson and Pavithra Parthasarathi (2013) Accessibility Futures. Transactions in GIS, 2013, 17(5): 683–705
This study uses accessibility as a performance measure to evaluate a matrix of future land use and network scenarios for planning purposes. The concept of accessibility dates to the 1950s, but this type of application to transportation planning is new. Previous research has established the coevolution of trans- portation and land use, demonstrated the dependence of accessibility on both, and made the case for the use of accessibility measures as a planning tool. This study builds off of these findings by demonstrating the use of accessibility-based performance measures in the Twin Cities Metropolitan Area. This choice of performance measure also allows for transit and highway networks to be compared side-by-side. For roadway modeling, zone-to-zone travel time matrix was computed using stochastic user equilibrium (SUE) assignment with travel time feedback to trip distribution. A database of schedules was used on the transit networks to assign transit routes. This travel time data was joined with the land use data from each scenario to obtain the employment, population, and labor accessibility from each traffic analysis zone (TAZ) within specified time ranges. Tables of person-weighted accessibility were computed for 20 minutes with zone population as the weight for employment accessibility and zone employment as the weight for population and labor accessibility. Maps of accessibility by zone were produced to show the spatial distribution of accessibility across the region. The results show that a scenario where population and employment growth are concentrated in the center of the metropolitan area would produce the highest accessibility no matter which transportation network changes are made. However, another scenario which concentrates population growth in the center of the metropolitan area and shifts employment growth to the periphery consistently outperforms the scenario representing the projected 2030 land use without any growth management strategy.