More 2016 Commuting Data

People who earn more than $75,000 a year are more likely to ride transit than people in any other income bracket. Most of those high-income transit riders live not in big cities like New York or Chicago but in suburbs of those cities.

That information is from table B08119 from the 2016 American Community Survey. I’ve downloaded the table for the nation, states, counties, cities, and urbanized areas and posted it with calculations showing what percentage of people in each income bracket use each form of transportation. The calculations don’t show this, but you can calculate it for yourself, but about 18.5 percent of people earn more than $75,000 a year, but a full 24 percent of people riding transit earn more than that amount.

I was surprised to discover that New York City was not one of the places where people earning more than $75,000 were the most likely to take transit, so I added a column, EB, that flags those areas where the $75,000 bracket is the most likely to take transit. On a state level, this included Idaho, Illinois, Massachusetts, New Jersey, Virginia, and Wyoming. Continue reading

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Housing Affordability in 2015

Today the Antiplanner continues reviewing 2016 American Community Survey data by looking at housing affordability, a common measure of which is median house prices divided by median family incomes, or value-to-income ratio. Median family incomes are in ACS table B19113, while median home prices are in table B25077.

To save you time, I’ve downloaded these tables, pasted the value and income data into one table, and calculated the ratio for the nation, states, counties, cities, and urban areas. For comparison, I have the same data for 2015, 2010, and 2006. As noted yesterday, only some counties, cities, and urban areas are used each year and the list varies from year to year so the rows are not identical each year. The states don’t vary from year to year, so I’ve also provided a spreadsheet comparing value-to-income ratios for the nation and each state for all four years.

All of the numbers, by the way, are actually for the previous year, as the surveys asked people how much they earned and how much their homes were worth the year before the survey. So the number shown as the 2016 value-to-income ratio is actually the ratio in 2015, etc. That means the data are a couple of years behind the current state of housing affordability. Zillow shows that prices in some areas have dramatically increased in the last couple of years to the point where many Silicon Valley homes are selling for 50 percent above their asking prices. Continue reading

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Commuting Data for 2016

Last week, the Census Bureau posted 2016 data from the American Community Survey, including population, income, housing, employment, and commuting data among many other categories. The survey is based on data from more than 3.5 million households. Today, the Antiplanner will look at commuting data: how people got to work in 2016 compared with previous years.

To save you time, I’ve downloaded and posted 2016’s table B08301, “Means of Transportation to Work,” for the nation, states, counties, cities, and urbanized areas. I’ve also posted similar tables for 2006, 2010, and 2015.

In columns Z through AE, I’ve calculated the shares of commuters (excluding people who work at home) who traveled to work by driving alone, carpooling, transit, rail transit, bicycling, and walking. (These won’t quite add up to 100 percent as are other categories such as taxi and motorcycle.) Only some cities, counties, and urban areas are included because others were too small for the sample size to be valid. Since the places that are included may vary from year to year, the rows of the various spreadsheets do not line up below the state level.

The data show that, nationwide, transit’s share of travel grew from 5.03 percent in 2006 to 5.49 percent in 2015. This growth was at the expense of carpooling, as driving alone’s share also grew. In 2016, however, transit’s share fell to 5.36 percent while both driving alone and carpooling grew. Continue reading

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Denver’s Immobility Plan

Denver’s Mayor Michael Hancock has issued what he calls a Mobility Plan. But if carried out, it will actually reduce the mobility of the residents of America’s nineteenth-largest city. Instead of doing anything to relieve congestion, the number one listed goal of the plan is to increase the share of commuters walking, cycling, or taking transit to work to 30 percent. Such a 146-percent increase over the current 12.2 percent is unattainable, so the plan ends up devoting most of the city’s transportation funds to forms of transportation that are either insignificant or obsolete.

Click image to download a 5.5-MB PDF of this plan.

The centerpiece of the Mayor’s plan is dedicated bus lanes on Colfax, Denver’s most important east-west street. Currently, buses carry about 22,000 people a day, more than any other corridor in Denver. But, as the Antiplanner noted recently, dedicated bus lanes can move than many people per hour, and even the 50,000 people per day that the city optimistically projects for Colfax isn’t enough to justify dedicating that much street space to buses. Continue reading

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Reversible Lanes, Not Trains

Predictably, in the aftermath of Hurricane Irma, some people are saying that Florida would have been better off trying to evacuate people with passenger trains than over the highways. No one knows exactly how many people did evacuate south Florida, but after the state ordered 6.3 million people to leave their homes, photos of bumper-to-bumper cars on Interstates 75 and 95 became a staple of hurricane reporting.

Rail advocates like to claim that rail lines have much higher capacities for moving people than roads, but that’s simply not true. After the San Francisco earthquake of 1906, the Southern Pacific Railroad moved 300,000 people–free of charge–out of the city in what was probably the largest mass transit evacuation in American history. While impressive, it took the railroad five days to move all of those people. Even accounting for improvements in rail capacities in the last century, moving 6 million people out of south Florida by rail would take weeks, not the four days available between Florida’s first evacuation orders and the arrival of Hurricane Irma.

Certainly, the state of Florida could have done more to relieve congestion on major evacuation routes. As near as I can tell, the most it did was to allow vehicles to use the left shoulder lane on part of I-75 and part of I-4 (which isn’t even a north-south route), but not, so far as I can tell, on I-95. What the state should have done, since there was very little southbound traffic, was to open up all but one of the southbound lanes of I-75 and I-75 to northbound traffic. Continue reading

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Driverless Car Update

The National Transportation Safety Board has issued its report about the 2016 crash that killed a Tesla driver. This has been billed as the “first self-driving car fatality,” but the truth is that the Tesla wasn’t designed to be a self-driving car. Instead, it is what is technically known as an SAE level 2 autonomous car, which is defined as “driver assistance systems of both steering and acceleration/ deceleration using information about the driving environment and with the expectation that the human driver perform all remaining aspects of the dynamic driving task.”

Instead of treating it this way, the driver acted as if it were a level 3 car, meaning a car capable of performing “all aspects of the dynamic driving task with the expectation that the human driver will respond appropriately to a request to intervene.” The Tesla was not designed to deal with all aspects of driving nor was it capable of making a request for the driver to intervene.

In this case, the car was going the legal speed limit on a highway and failed to slow or stop when a truck illegally entered the right of way to cross the highway. The Tesla was designed to detect another car in its lane but not a vehicle crossing the lane. The truck driver–who, the NTSB notes, had been smoking marijuana–cross the highway in violation of the Tesla’s right of way. An alert driver would have slowed down, but the Tesla driver was relying on his car to do things it wasn’t designed to do. Continue reading

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Bike Share Programs: Why?

After less than a year of operation, Baltimore is shutting down its bike share program for a month because so many of its bikes were stolen or are heavily damaged. The program began last November with a 175 bikes–40 percent of which had electric boosters–available for rent from 20 different locations, soon increased to 200 bikes and 20 stations.

One cyclist spent a day recently visiting all 25 stations and found only four bikes available to potential renters. The city says the private partner that is running the operation is upgrading the locks to reduce theft. In the meantime, the city has two full-time employees tracking down the GPS-equipped bikes so that other people can repair them and put them back into service.

Baltimore is far from the first city to have problems with its bike-share program. Seattle’s is attracting only half as many riders as expected. Bike share programs in New York, San Francisco and many other cities have also had problems. Continue reading

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DC Metro More Reliable But Riders Are Not

The Washington Metropolitan Area Transit Authority (WMATA) has blamed much of the rail system’s ridership declines on the system’s reliability problems and all of the track work it did in 2016 and early 2017 to fix those problems. Now, the system has become more reliable, but riders don’t seem to be returning.

The Federal Transit Administration has published month-by-month ridership data for all transit systems through June, 2017. The numbers show that Metro rail ridership in February, March, and April of this year were all about 10 percent less than in the same months last year. In May, however, it was only 1.5 percent less, while June 2017 ridership was actually more than in June 2016–though only by 0.6 percent.

While that’s grounds for a bit of optimism, Metro rail ridership still has a long way to go before it returns to its 2009 peak, which was 28 percent higher than the year ending June 2017. I don’t like making predictions because there are too many unknown variables, but I suspect ridership will never return to those levels partly because many former riders have lost faith in the system and partly because the band-aid work done on the system in the last year won’t solve its long-term reliability problems. Time will tell.

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Not Subprimes, But Not Flippers Either

As most readers know, the Antiplanner never bought in to the story that subprime loans were responsible for the 2008 financial crisis. “Low interest rates, the Community Reinvestment Act, and subprime lending were equally available in all 50 states,” I wrote in American Nightmare, “but bubbles occurred in only some of those states,” namely those that were practicing growth management or had some other artificial land-use restrictions.

Several research papers have confirmed the Antiplanner’s view that subprime loans were not the problem. Unfortunately, some have interpreted these papers to place blame on another class of borrowers: flippers, that is, people who bought homes simply to resell them at higher prices. Yet they are no more responsible for triggering the financial crisis than subprime borrowers.

A paper from Wharton’s Business School argues for “a reinterpretation of the U.S. foreclosure crisis as more of a prime, rather than a subprime, borrower issue,” say Wharton economists Fernando Ferreira and Joseph Gyourko. “Housing traits, race, initial income, and speculators did not play a meaningful role.” This absolves subprime borrowers, but also flippers (“speculators”).

A Federal Reserve Bank of New York staff report may be the one that supposedly places the blame on flippers. “In states that experienced the largest housing booms and busts, at the peak of the market almost half of purchase mortgage originations were associated with investors,” the report concluded. That may be true, but that doesn’t mean that flippers triggered the financial crisis.

As a paper by MIT finance professor Antoinette Shoar and two of her former graduate students found, “homebuyers and lenders bought into increasing house values and borrowers defaulted after prices dropped.” In other words, prices began dropping before flippers defaulted. After all, as long as prices were rising, why would speculators default?

So what did trigger the crisis? As chapter 13 of American Nightmare shows, the trigger was pulled by the bond ratings agencies: Standard & Poor’s, Moody’s, and Fitch. Up until January, 2007, these companies had been giving AAA ratings to bonds made up of individual mortgage loans. This was because, as one writer observes, “never in history [had] prices for housing market gone down nationally.” Because of this, the ratings companies believed that, even if individuals defaulted on their loans, the banks could resell the homes to someone else without losing money.

What the ratings companies failed to realize, however, was that growth management had made housing prices far more volatile, and such growth management had extended from three or four states in the previous recession to nearly 20 in the mid-2000s–and those 20 states contained close to 45 percent of American housing.

It only took a very small decline in housing prices to wake the companies up to their mistake. Between the third quarter of 2006 and the second quarter of 2007, prices in key markets such as Los Angeles and the San Francisco Bay Area fell by about 1 percent. One percent doesn’t sound like much, but prices had grown in those markets without interruption since 1994.

Starting in June, 2007, the bond ratings companies responded by downgrading bonds issued in 2002 through 2004 from AAA to AA- or A; bonds issued in 2005 from AAA to BBB-; and bonds issued in 2006 from AAA to as low as CCC+. Anything below BBB- is considered junk. More important, reduced ratings increased the cash reserves banks were required to keep.

Buying a bond is the same as lending money, and banks are required to keep cash reserves when they lend money in case their depositors want some of their money back. A bank buying $1 billion of AAA bonds had to keep $16 million in cash. When the grade of those bonds was reduced, that reserve requirement might grow to $80 million. Since all of these bonds totaled to trillions of dollars in value, the banks that owned billions of dollars worth of bonds had to scramble to come up with billions of dollars in cash overnight. Some banks–Bear Stearns, Lehman Brothers, Washington Mutual–went out of business; others, notably Citibank and AIG, were deemed “too big to fail,” so the federal government stepped in. With or without federal involvement, the credit market tightened, leading to financial problems nationwide.

If the banks had not gotten in trouble, credit wouldn’t have tightened and defaults would not have been a problem. If the ratings agencies had correctly rated the bonds in the first place, the banks would not have gotten trouble. If growth management had not made housing more volatile, the original ratings on the bonds would have been correct.

This sidesteps the question of what triggered that 1 percent decline in housing prices in 2006. One story is that builders responded to high prices by oversupplying the market, leading prices to fall. That might have happened in Arizona where it was easy to subdivide land and built new homes, but I doubt that it happened in California, where it can take many years to get permits to build new homes.

Instead, I think homebuyers, whether speculators or not, were spooked by rising prices and fears that a bubble would soon burst. In 2005, The Economist predicted that the bubble would inevitably collapse. “The whole world economy is at risk,” the magazine-that-calls-itself-a-newspaper accurately noted. “It is not going to be pretty.” By early 2006, there were whole websites devoted to monitoring the housing bubble and to debunking those who claimed there was no bubble.

Remember that in the early 2000s, California home buyers routinely bid 20 percent or more above the asking price for homes. It wouldn’t take much publicity about the bubble to lead some potential buyers to say, “Maybe we should wait until after prices fall before we buy.” That in turn would cool the market just enough to get the bond ratings agencies to take notice.

Today, home prices in the San Francisco Bay Area are a third higher than they were during the peak of the 2006 bubble. Even after adjusting for inflation, they are 12 percent higher. Clearly, we are in another bubble. The inevitable collapse of that bubble will cause many local hardships, but should not result in a major financial crisis because the ratings agencies and banks have presumably learned their lessons.

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Bringing Soviet Planning to New York City

New York City Mayor Bill de Blasio wants to bring the same policies that worked so well in the Soviet Union, and more recently in Venezuela, to New York City. “If I had my druthers, the city government would determine every single plot of land, how development would proceed,” he says. “And there would be very stringent requirements around income levels and rents.”

As shown in the urban planning classic, The Ideal Communist City, soviet planners also believed they were smart enough to know how every single plot of land in their cities should be used. The cities built on their planning principles were appallingly ugly and unlivable. They were environmentally sustainable only so long as communism kept people too poor to afford cars and larger homes.

If de Blasio believes in this planning system so much, why doesn’t he implement it in New York City? The biggest obstacle, he says, is “the way our legal system is structured to favor private property.” He blames housing affordability problems on greedy developers who only build for millionaires. Continue reading

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