Breaking Down the Financial Impact of Self-Driving Cars
They would be mostly -- but not all -- good for state and local revenues.
The expectations over driverless cars are stratospherically high. For one, there’s the fascination with the technology and the presumption of an easier commute: The self-driving car will take us to work while we surf the Internet, read files and review emails. Once it drops us off, it returns home where others in our household can use it -- until it’s time to call it to pick us up and take us home again.
There’s more to this futuristic concept than creature comforts, though. With self-driving cars anticipated to be in wider use on our roads within four years, there are promises of extraordinary impacts on state and local finances -- most of them positive; a few not. Several reports from some of the biggest names in banking put startling numbers on the effects wrought by a changeover to driverless driving.
Let’s start with Morgan Stanley. Its new report, Autonomous Vehicles & Municipal Bonds, puts the net positive impact on municipal budgets in excess of half a trillion dollars. That number takes into account more efficient roadway use and a dramatic reduction in parking garages and parking spaces. With parking facilities no longer needed, those properties can be turned into higher-level development, which would provide municipalities with a boost in property taxes. Offsetting those gains, Morgan Stanley foresees losses of roughly $1.3 billion from such revenue sources as fuel taxes, license fees, parking fees, speeding tickets and personal property taxes.
Barclays, the British banking and financial services company, notes that transportation in the U.S. is the second highest average household expenditure and that the average car is parked 95 percent of the time. It estimates that the average U.S. household will reduce its car ownership from today’s 2.1 vehicles to 1.2. (A figure also cited in a University of Michigan Transportation Research Institute study.) For states and localities, such a reduction could signal an end to what Barclays calls “the fretting” about investing in additional highway lanes or new roads.
That lack of fretting would have quite an effect on infrastructure and the municipal bonds that finance it. The impact starts with this forecast from several researchers: A single self-driving car could replace up to 12 regular vehicles. If that happens, it would affect some of the existing $3 billion in dedicated tax-exempt state and local parking revenue bonds. It would also affect airport revenue bonds. Airports currently generate 28 percent of their operating revenue from rental cars, parking and ground transportation -- revenue that could be at risk from the cascading parking effects of self-driving cars.
The influence on general obligation bonds would be significant in a more positive way. The greater efficiency of self-driving cars and the ability to fit triple the amount of traffic in existing lanes could sharply reduce current projected needs for infrastructure and therefore the need to borrow money to build new roads.
There are other revenue savings. Self-driving cars are predicted by the National Transportation Safety Board to save “many, if not most, of the 33,000 lives lost to traffic fatalities every year on our streets and highways.” If true, this would lead to a major benefit via the $18 billion annual health-care costs from emergency room visits related to motor vehicle injuries, injuries that currently average 15 percent of hospitalized injuries -- not to mention the costs to local emergency responders.
Then there’s this: For many police departments, 42 percent of police contacts are initiated during a traffic stop -- with driving under the influence of alcohol being the second highest cause. Self-driving cars would render DUIs virtually obsolete. That would be a signal benefit not only -- and most important -- on innocent lives saved, but also in a diminution of emergency medical and police costs.
No wonder Morgan Stanley came up with a half-a-trillion dollar figure.
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