Tag Archives: Southern California

Decreasing congestion with driverless cars

Traffic is aggravating. Especially for San Francisco residents. According to Texas A&M Transportation Institute, traffic congestion in the San Francisco-Oakland CA area costs the average auto commuter 78 hours per year in extra travel time, $1,675 for their travel time delays, and an extra 33 gallons of gas compared to free-flow traffic conditions. That means the average commuter spends more than three full days stuck in traffic each year. Unfortunately for these commuters, a potential solution to their problems just left town.

Last month, after California officials told Uber to stop its pilot self-driving car program because it lacked the necessary state permits for autonomous driving, Uber decided to relocate the program from San Francisco to Phoenix, Arizona. In an attempt to alleviate safety concerns, these self-driving cars are not yet driverless, but they do have the potential to reduce the number of cars on the road. Other companies like Google, Tesla, and Ford have expressed plans to develop similar technologies, and some experts predict that completely driverless cars will be on the road by 2021.

Until then, however, cities like San Francisco will continue to suffer from the most severe congestion in the country. Commuters in these cities experience serious delays, higher gasoline usage, and lost time behind the wheel. If you live in any of these areas, you are probably very familiar with the mind-numbing effect of sitting through sluggish traffic.

It shouldn’t be surprising then that these costs could culminate into a larger problem for economic growth. New Mercatus research finds that traffic congestion can significantly harm economic growth and concludes with optimistic predictions for how autonomous vehicle usage could help.

Brookings Senior Fellow Clifford Winston and Yale JD candidate Quentin Karpilow find significant negative effects of traffic congestion on the growth rates of California counties’ gross domestic product (GDP), employment, wages, and commodity freight flows. They find that a 10% reduction in congestion in a California urban area increases both job and GDP growth by roughly 0.25% and wage growth to increase by approximately 0.18%.

This is the first comprehensive model built to understand how traffic harms the economy, and it builds on past research that has found that highway congestion leads to slower job growth. Similarly, congestion in West Coast ports, which occurs while dockworkers and marine terminal employers negotiate contracts, has caused perishable commodities to go bad, resulting in a 0.2 percentage point reduction in GDP during the first quarter of 2015.

There are two main ways to solve the congestion problem; either by reducing the number of cars on the road or by increasing road capacity. Economists have found that the “build more roads” method in application has actually been quite wasteful and usually only induces additional highway traffic that quickly fills the new road capacity.

A common proposal for the alternative method of reducing the number of cars on the road is to implement congestion pricing, or highway tolls that change based on the number of drivers using the road. Increasing the cost of travel during peak travel times incentivizes drivers to think more strategically about when they plan their trips; usually shifting less essential trips to a different time or by carpooling. Another Mercatus study finds that different forms of congestion pricing have been effective at reducing traffic congestion internationally in London and Stockholm as well as for cities in Southern California.

The main drawback of this proposal, however, is the political difficulty of implementation, especially with interstate highways that involve more than one jurisdiction to approve it. Even though surveys show that drivers generally change their mind towards supporting congestion pricing after they experience the lower congestion that results from tolling, getting them on board in the first place can be difficult.

Those skeptical of congestion pricing, or merely looking for a less challenging policy to implement, should look forward to the new growing technology of driverless cars. The authors of the recent Mercatus study, Winston and Karpilow, find that the adoption of autonomous vehicles could have large macroeconomic stimulative effects.

For California specifically, even if just half of vehicles became driverless, this would create nearly 350,000 additional jobs, increase the state’s GDP by $35 billion, and raise workers’ earnings nearly $15 billion. Extrapolating this to the whole country, this could add at least 3 million jobs, raise the nation’s annual growth rate 1.8 percentage points, and raise annual labor earnings more than $100 billion.

What would this mean for the most congested cities? Using Winston and Karpilow’s estimates, I calculated how reduced congestion from increased autonomous car usage could affect Metropolitan Statistical Areas (MSAs) that include New York City, Los Angeles, Boston, San Francisco, and the DC area. The first chart shows the number of jobs that would have been added in 2011 if 50% of motor vehicles had been driverless. The second chart shows how this would affect real GDP per capita, revealing that the San Francisco MSA would have the most to gain, but with the others following close behind.

jobsadd_autonomousvehicles realgdp_autonomousvehicles

As with any new technology, there is uncertainty with how exactly autonomous cars will be fully developed and integrated into cities. But with pilot programs already being implemented by Uber in Pittsburgh and nuTonomy in Singapore, it is becoming clear that the technology’s efficacy is growing.

With approximately $1,332 GDP per capita and 45,318 potential jobs on the table for the San Francisco Metropolitan Statistical Area, it is a shame that San Francisco just missed a chance to realize some of these gains and to be at the forefront of driving progress in autonomous vehicle implementation.

City population dynamics since 1850

The reason why some cities grow and some cities shrink is a heavily debated topic in economics, sociology, urban planning, and public administration. In truth, there is no single reason why a city declines. Often exogenous factors – new modes of transportation, increased globalization, institutional changes, and federal policies – initiate the decline while subsequent poor political management can exacerbate it. This post focuses on the population trends of America’s largest cities since 1850 and how changes in these factors affected the distribution of people within the US.

When water transportation, water power, and proximity to natural resources such as coal were the most important factors driving industrial productivity, businesses and people congregated in locations near major waterways for power and shipping purposes. The graph below shows the top 10 cities* by population in 1850 and follows them until 1900. The rank of the city is on the left axis.

top cities 1850-1900


* The 9th, 11th, and 12th ranked cities in 1850 were all incorporated into Philadelphia by 1860. Pittsburgh was the next highest ranked city (13th) that was not incorporated so I used it in the graph instead.

All of the largest cities were located on heavily traveled rivers (New Orleans, Cincinnati, Pittsburgh, and St. Louis) or on the coast and had busy ports (New York, Boston, Philadelphia, Brooklyn, and Baltimore). Albany, NY may seem like an outlier but it was the starting point of the Erie Canal.

As economist Ed Glaeser (2005) notes “…almost every large northern city in the US as of 1860 became an industrial powerhouse over the next 60 years as factories started in central locations where they could save transport costs and make use of large urban labor forces.”

Along with waterways, railroads were an important mode of transportation from 1850 – 1900 and many of these cities had important railroads running through them, such as the B&O through Balitmore and the Erie Railroad in New York. The increasing importance of railroads impacted the list of top 10 cities in 1900 as shown below.

top cities 1900-1950

A similar but not identical set of cities dominated the urban landscape over the next 50 years. By 1900, New Orleans, Brooklyn (merged with New York) Albany, and Pittsburgh were replaced by Chicago, Cleveland, Buffalo, and San Francisco. Chicago, Cleveland, and Buffalo are all located on the Great Lakes and thus had water access, but it was the increasing importance of railroad shipping and travel that helped their populations grow. Buffalo was on the B&O railroad and was also the terminal point of the Erie Canal. San Francisco became much more accessible after the completion of the Pacific Railroad in 1869, but the California Gold Rush in the late 1840s got its population growth started.

As rail and eventually automobile/truck transportation became more important during the early 1900s, cities that relied on strategic river locations began to decline. New Orleans was already out of the top 10 by 1900 (falling from 5th to 12th) and Cincinnati went from 10th in 1900 to 18th by 1950. Buffalo also fell out of the top 10 during this time period, declining from 8th to 15th. But despite some changes in the rankings, there was only one warm-weather city in the top 10 as late as 1950 (Los Angeles). However, as the next graphs shows there was a surge in the populations of warm-weather cities during the period from 1950 to 2010 that caused many of the older Midwestern cities to fall out of the rankings.

top cities 1950-2010

The largest shakeup in the population rankings occurred during this period. Out of the top 10 cities in 1950, only 4 (Philadelphia, Los Angeles, Chicago, and New York) were still in the top 10 in 2010 (All were in the top 5, with Houston – 4th in 2010 – being the only city not already ranked in the top 10 in 1950, when it was 14th). The cities ranked 6 – 10 fell out of the top 20 while Detroit declined from 5th to 18th. The large change in the rankings during this time period is striking when compared to the relative stability of the earlier time periods.

Economic changes due to globalization and the prevalence of right-to-work laws in the southern states, combined with preferences for warm weather and other factors have resulted in both population and economic decline in many major Midwestern and Northeastern cities. All of the new cities in the top ten in 2010 have relatively warm weather: Phoenix, San Antonio, San Diego, Dallas, and San Jose. Some large cities missing from the 2010 list – particularly San Francisco and perhaps Washington D.C. and Boston as well – would probably be ranked higher if not for restrictive land-use regulations that artificially increase housing prices and limit population growth. In those cities and other smaller cities – primarily located in Southern California – low population growth is a goal rather than a result of outside forces.

The only cold-weather cities that were in the top 15 in 2014 that were not in the top 5 in 1950 were Indianapolis, IN (14th) and Columbus, OH (15th). These two cities not only avoided the fate of nearby Detroit and Cleveland, they thrived. From 1950 to 2014 Columbus’ population grew by 122% and Indianapolis’ grew by 99%. This is striking compared to the 57% decline in Cleveland and the 63% decline in Detroit during the same time period.

So why have Columbus and Indianapolis grown since 1950 while every other large city in the Midwest has declined? There isn’t an obvious answer. One thing among many that both Columbus and Indianapolis have in common is that they are both state capitals. State spending as a percentage of Gross State Product (GSP) has been increasing since 1970 across the country as shown in the graph below.

OH, IN state spending as per GSP

In Ohio state spending growth as a percentage of GSP has outpaced the nation since 1970. It is possible that increased state spending in Ohio and Indiana is crowding out private investment in other parts of those states. And since much of the money collected by the state ends up being spent in the capital via government wages, both Columbus and Indianapolis grow relative to other cities in their respective states.

There has also been an increase in state level regulation over time. As state governments become larger players in the economy business leaders will find it more and more beneficial to be near state legislators and governors in order to lobby for regulations that help their company or for exemptions from rules that harm it. Company executives who fail to get a seat at the table when regulations are being drafted may find that their competitors have helped draft rules that put them at a competitive disadvantage. The decline of manufacturing in the Midwest may have created an urban reset that presented firms and workers with an opportunity to migrate to areas that have a relative abundance of an increasingly important factor of production – government.