Infrastructure Spending Done Right

I wrote a piece for the Van Alen Institute: Infrastructure Spending Done Right. This is part of a wider Van Alen Report: America’s Infrastructure,  including articles by

Infrastructure Spending Done Right

Van Alen Institute: America's Infrastructure. Report 19.
Van Alen Institute: America’s Infrastructure. Report 19.

Infrastructure spending as stimulus appeals to politicians and voters because it would appear to kill three birds with one stone. Ostensibly, critical infrastructure is repaired or newly constructed, job opportunities are created for the unemployed, and the greater economy is set on course for growth. But how and where funding is spent frustrates these objectives. Federal funding often winds up disproportionately in rural areas at the expense of dense, growing cities where long-term economic benefits would be greater. Moreover, job creation is dubious given the high level of skill required for construction work and increased role of technology on the project site. Although greater investment in maintenance could both give relief to the unemployed and boost the benefits of existing infrastructure, politicians eager for ribbon cutting ceremonies often choose new infrastructure over repairing the roads, bridges and railways we currently have. David Levinson, transportation expert and professor at the University of Sydney, takes us though past and potential future infrastructure spending initiatives, and explains how setting the right priorities can ensure our infrastructure provides greater prosperity over the long term.

On December 6, 2008, in the throes of the Great Recession, then President-elect Barack Obama laid out key parts of his Economic Recovery Plan. In his radio address he boldly said “ … [W]e will create millions of jobs by making the single largest new investment in our national infrastructure since the creation of the federal highway system in the 1950s… If a state doesn’t act quickly to invest in roads and bridges in their communities, they’ll lose the money.” This plan turned into the American Recovery and Reinvestment Act, with a total budget of $831 billion. It dedicates $105 billion to infrastructure, of which $48 billion went to transport.

The value of the projects from the 2009 stimulus remains questionable. Projects tended to fall in rural areas (mostly road resurfacings) not because the work was essential, but because they were “shovel-ready” and easy to do. The projects were easy because they were already designed and had environmental permits in place. But the fact that these projects were so far along in development, yet remained unbuilt, suggests that they were not the highest priorities for the local and state transportation agencies that oversaw their construction.

Though administrations have changed, the disproportionate allocation of federal spending to rural areas over more developed cities – where the majority of needed infrastructure work exists – will likely go unabated. President Trump has proposed various tax incentives to stimulate $1 trillion worth of private investment towards the nation’s infrastructure. While Trump has discussed urban-based projects, such as rebuilding New York City’s poorly-managed airports, the Republican party – which he leads but counts as its base mainly rural voters – will likely exacerbate the overfunding of rural projects even more, if only to get its own representatives and senators re-elected.

Along with project location, setting job creation as an objective of infrastructure spending can also undermine the economic value of projects. At the time of the 2009 stimulus, unemployment was around 10%. With more workers looking for jobs, spending on infrastructure during a recession may arguably bring labor off the sidelines, while also taking advantage of the temporary wage drop due to the joblessness spike. In short, the state can get more infrastructure built for less, and put people to work who would have been otherwise unemployed. Today, however, unemployment is around 4.7%. Competition for labor is up, and with it construction wages. And without slack in the labor market, new projects are more likely to shift employed workers around, not add new jobs to the economy. Worth noting is President Trump’s assertion that his proposed tax breaks will pay for themselves. If these privately-funded projects fail to increase the net number of jobs, the hope for additional revenue to offset tax incentives will never come into reality.

Further complicating the job scenario is the capital-intensive nature of construction today. Macro-economists or policymakers who think of highways and transit lines as engines of job creation are remembering grainy black and white images of Civilian Conservation Corps workers slinging pickaxes as they build roads through national parks. Construction projects are more capital intensive than they were in the 1930s, using heavier machinery and far less labor. As technology advances, and construction equipment becomes increasingly roboticized and automated, jobs will become highly skilled and decrease in number. Most infrastructure construction jobs already require two or three years of apprenticeship and on-the-job training. In the future, infrastructure stimulus may offer little for unemployed people without extensive construction experience.

While the creation of jobs from infrastructure construction is limited, there are potential long-term benefits of constructed infrastructure in terms of jobs. It is worth noting that our current surface transportation system is not just in need of repair. In most parts of the U.S., our system connects everything worth connecting, and does so as cost-effectively as possible. There’s little need for new infrastructure, but great urgency to rehabilitate the infrastructure we already have.

Local and state governments are largely responsible for preserving existing infrastructure. They can use additional federal support. But we should be sure that any support is pushed toward maintenance, not new infrastructure which largely serves as a distraction. We all know that maintenance, repair, and reconstruction are not sexy. They do not result in ribbon cuttings with smiling politicians getting their pictures taken and posted in the local news. Yet on a per-dollar basis, fine-grained maintenance work employs more people than large-scale greenfield construction. Moreover, it is ideal to run the capital equipment required for road construction at a continuous level, thus maximizing its productivity. Continuous utilization is achieved by a steady rate of spending on projects, not stimulus-related spikes or failures to authorize infrastructure expenditures.

Economic activity increases with accessibility – more specifically, the ability for workers to reach jobs and stores, and for firms to easily interact. This occurs with faster and more direct transport, denser land use, and increased access to developed urban areas over less economically active rural areas. That said, it is cheaper to build in rural areas than cities, so the cost-to-benefit ratio is not obvious. This ambiguity is worth noting. While infrastructure policies may aim to even out spatial inequities and “spread the wealth,” that ambition is at direct odds with the desire to maximize the productivity and efficiency of infrastructure.

Public works are justifiable when social benefits exceed costs, not because they create spikes in job growth or score political points. To maximize the amount of infrastructure society gets per dollar, the government needs to be efficient about how infrastructure money is spent. From an infrastructure perspective, if a road project employs some people, that provides a nice rhetorical flourish; but if projects are aimed solely to employ people, the state will be wasting money which in the long run shrinks the economy. The debt borrowed to build said projects ultimately comes due.

A model of two-destination choice in trip chains with GPS data

Recently published:

Studying trip chaining behavior has been a challenging endeavor which requires the support of microscopic travel data. New insights into trip chaining can be gained from real-time GPS travel data. This research introduces a framework that considers two-des- tination choice in the context of home-based trip chains. We propose and empirically compare three alternatives of building choice sets where we consider various relation- ships of the two destinations (such as major–minor destinations, selecting one first, and selecting two concurrently). Our choice set formation alternatives use survival models to determine the selection probability of a destination. Our results reveal that trip chaining behavior is shaped by the features of retail clusters, spatial patterns of clusters, trans- portation networks, and the axis of travel. This research reveals that not only the spatial relationship but also the land use relationship of the destinations in a trip chain affect the decision making process.

Justice, Exclusion, and Equity: An Analysis of 48 U.S. Metropolitan Areas

Recent working paper

Injustice in transportation services experienced by disadvantaged demographic groups account for much of these groups’ social exclusion.

HoustonOppUnfortunately, there is little agreement in the field about what theoretical foundation should be the basis of measures of the justice of transportation services, limiting the ability of transportation professionals to remedy the issues. Accordingly, there is a need for an improved measure of the justice of the distribution of transportation services, which relates to the effectiveness of transportation services for all members of disadvantaged groups rather than for only segregated members of these disadvantaged groups. To this end potential measures of distributive justice, based on the accessibility to jobs provided by various modes, are evaluated in 48 of the top 50 largest metropolitan areas in the United States. The purpose of the study is to inform recommendations for appropriate use of each measure.

Sydney Transport/Urban Twitter/Blogosphere Meetup

Sydney Transport/Urban Twitter/Blogosphere Meetup – Friday Sept, 22 (6pm) at Hotel Sweeney’s 236 Clarence St, Sydney NSW 2000, Australia

Come one, come all.

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Safety in Numbers and Safety in Congestion for Bicyclists and Motorists at Urban Intersections

Recent working paper:

The rate of number of crashes to traffic flow
The rate of number of crashes to traffic flow

This study assesses the estimated crashes per bicyclist and per vehicle as a function of bicyclist and vehicle traffic, and tests whether greater traffic reduces the per-car crash rate. We present a framework for comprehensive bicyclist risk assessment modeling, using estimated bicyclist flow per intersection, observed vehicle flow, and crash records. Using a two-part model of crashes, we reveal that both the annual average daily traffic and daily bicyclist traffic have a diminishing return to scale in crashes. This accentuates the positive role of safety in numbers. Increasing the number of vehicles and cyclists decelerates not only the probability of crashes, but the number of crashes as well. Measuring the elasticity of the variables, it is found that a 1% increase in the annual average daily motor vehicle traffic increases the probability of crashes by 0.14% and the number of crashes by 0.80%. However, a 1% increase in the average daily bicyclist traffic increases the probability of crashes by 0.09% and the number of crashes by 0.50%. The saturation point of the safety in numbers for bicyclists is notably less than for motor vehicles. Extracting the vertex point of the parabola functions examines that the number of crashes starts decreasing when daily vehicle and bicyclist traffic per intersection exceed 29,568 and 1,532, respectively.

Spatiotemporal Short-term Traffic Forecasting using the Network Weight Matrix and Systematic Detrending

Recent working paper:

LookBackWindowsThis study examines the dependency between traffic links using a three-dimensional data detrending algorithm to build a network weight matrix in a real-world example. The network weight matrix reveals how links are spatially dependent in a complex network and detects the competitive and complementary nature of traffic links. We model the traffic flow of 140 traffic links in a sub-network of the Minneapolis – St. Paul highway system for both rush hour and non-rush hour time intervals, and validate the extracted network weight matrix. The results of the modeling indi- cate: (1) the spatial weight matrix is unstable over time-of-day, while the network weight matrix is robust in all cases and (2) the performance of the network weight matrix in non-rush hour traffic regimes is significantly better than rush hour traffic regimes. The results of the validation show the network weight matrix outperforms the traditional way of capturing spatial dependency between traffic links. Averaging over all traffic links and time, this superiority is about 13.2% in rush hour and 15.3% in non-rush hour, when only the 1st -order neighboring links are embedded in modeling. Aside from the superiority in forecasting, a remarkable capability of the network weight matrix is its stability and robustness over time, which is not observed in spatial weight matrix. In addition, this study proposes a naïve two-step algorithm to search and identify the best look-back time win- dow for upstream links. We indicate the best look-back time window depends on the travel time between two study detectors, and it varies by time-of-day and traffic link.

Seminar: The End of Traffic and the Future of Access: A Roadmap for the New Transport Landscape

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I am giving at talk at ITLS on Tuesday, September 19, 2017 at 14:00

Title: The End of Traffic and the Future of Access: A Roadmap for the New Transport Landscape

Venue : Abercrombie Building (H70) Level 5 – Room 5050 , Corner Abercrombie Street and Codrington Street, The University of Sydney

The University of Sydney: Click here for directions

RSVP is required if you wish to attend

Abstract:

Less than two decades into the new millennium, transport is becoming interesting again. Revolutionary technical advances are taking root; evolutionary social forces are responding; together, these phenomena are changing how people access and exchange goods. Transport and planning discussions are now being reshaped, prompting even seasoned transport professionals to appear as neophytes. This talk reframes the evolving nature of debates about transport and to shape perspectives about the future of transport in cities. It discusses the implications of automation, electrification, sharing, and demassification on travel demands and transport policy.

Bio:

Prof. David Levinson teaches at the School of Civil Engineering at the University of Sydney, where he leads the Network Design Lab and the Transport Engineering group. He is an honorary affiliate of the Institute of Transport and Logistics Studies, where he is also a member of the Board of Advice. From 1999 to 2016, he served on the faculty of the University of Minnesota where he held the Richard P. Braun/CTS Chair in Transportation (2006-2016).  Levinson has authored or edited several books, including Spontaneous Access,  The Transportation Experience, and Planning for Place and Plexus, as well as numerous peer reviewed articles. He is the editor of the Journal of Transport and Land Use.

Traffic Flow Variation and Network Structure

Recent working paper

Figure4This study defines and detects competitive and complementary links in a complex network and constructs theories illustrating how the variation of traffic flow is interconnected with network structure. To test the hypotheses, we extract a grid-like sub-network containing 140 traffic links from the Minneapolis – St. Paul highway system. We reveal a real-world traffic network comprises both competitive and complementary links, and there is a negative network dependency between a competitive link pair and a positive network dependency between a complementary link pair. We validate a robust linear relationship between standard deviation of flow in a link and its number of competitive links, its link correlation with competitive links, and its network dependency with both competitive and complementary links. The results indicate the number of competitive links in a traffic network is negatively correlated with the variation of traffic flow in congested regimes as drivers are able to take alternative paths. The results also signify that the more the traffic flow of a link is correlated to the traffic flow of its competitive links, the more the flow variation is in the link. Considering the network dependency, however, it is corroborated that the more the network dependency between a link and its competitive links, the more the flow variation in the link. This is also true for complementary links.

Accessibility Oriented Development

Recent working paper:

AoDMunicipal governments worldwide have been pursuing transit-oriented development (TOD) strategies in order to increase transit ridership, curb traffic congestion, and rejuvenate urban neighborhoods. In many cities, however, development of planned sites around transit stations has been close to non-existent, due to, among other reasons, a lack of coordination between transit investments and land use at the regional scale. Furthermore, the ability to access transit differs from the ability to access destinations that people care about. Reframing transit-oriented development as accessibility-oriented development (AOD) can aid the process of creating functional connections between neighborhoods and the rest of the region, and maximize benefits from transport investments. AOD is a strategy that balances accessibility to employment and the labor force in order to foster an environment conducive to development. AOD areas are thus defined as having higher than average accessibility to employment opportunities and/or the labor force; such accessibility levels are expected to increase the quality of life of residents living in these areas by reducing their commute time and encouraging faster economic development. To quantify the benefits of AOD, accessibility to employment and the labor force are calculated in the Greater Toronto and Hamilton Area, Canada in 2001 and 2011. Cross-sectional and temporal regressions are then performed to predict average commute times and development occurring in AOD areas and across the region. Results show that AOD neighborhoods with high accessibility to jobs and low accessibility to the labor force have the lowest commute times in the region, while the relationship also holds for changes in average commute time between the studied time periods. In addition, both accessibility to jobs and accessibility to the labor force are associated with changes in development, as areas with high accessibility to jobs and the labor force attract more development. In order to realize the full benefits of planned transit investments, planning professionals and policy makers alike should therefore leverage accessibility as a tool to direct development in their cities, and concentrate on developing neighbourhoods with an AOD approach in mind.