Infrastructure grade for Illinois: C-

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The infrastructure of Illinois did not receive a good grade in a recent report from the American Society of Civil Engineers:

The overall Illinois grade was a combination of individual grades for different elements of state infrastructure, including aviation, bridges, drinking water systems and rail.

The card’s lowest individual grade — a D- — went to the care of navigable waterways, noting that the confluence of the Illinois, Mississippi and Ohio rivers are crucial to the country’s navigation system. But this advantage is threatened by deferred maintenance on locks that have “long exceeded” their 50-year design life, the group said.

Illinois’ roads got a D, as they are ranked third worst nationally for travel delay, excess fuel consumed, truck congestion cost and total congestion cost, the engineers’ report found. The report noted that despite the need for maintenance and repair, the state’s 19-cent-per gallon fuel tax has remained the same since 1991. Other states have raised their gas taxes in recent years to fund road programs.

Illinois transit also got a D, because of lack of capital funding, according to the society.

This is not just a concern because Illinois is a populous state where many people rely on the infrastructure. This also matters because Illinois depends on this infrastructure quite a bit for industry and business. Because of the state’s location roughly in the middle of the country plus containing a path from the Great Lakes to the Mississippi River and numerous busy facilities that enable travel and the shipping of freight (railroad lines, O’Hare and Midway Airports, intermodal facilities), Illinois’ infrastructure is particularly important as it helps make many other things happen.

Despite its importance, I’m not sure I hold out much hope that significant efforts will be made to maintain and upgrade the infrastructure in Illinois given the state’s budget and political issues. Illinois could be a fantastic example of a state that builds for the future by comprehensively addressing infrastructure here and now to set up future decades.

New standard and platform for city maps

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Maps are important for many users these days and a new open data standard and platform aims to bring all the street data together:

Using giant GIS databases, cities from Boston to San Diego maintain master street maps to guide their transportation and safety decisions. But there’s no standard format for that data. Where are the intersections? How long are the curbs? Where’s the median? It varies from city to city, and map to map.

That’s a problem as more private transportation services flood the roads. If a city needs to communicate street closures or parking regulations to Uber drivers, or Google Maps users, or new dockless bikesharing services—which all use proprietary digital maps of their own—any confusion could mean the difference between smooth traffic and carpocalypse.

And, perhaps more importantly, it goes the other way too: Cities struggle to obtain and translate the trip data they get from private companies (if they can get their hands on it, which isn’t always the case) when their map formats don’t match up.

A team of street design and transportation data experts believes it has a solution. On Thursday, the National Association of City Transportation Officials and the nonprofit Open Transport Partnership launched a new open data standard and digital platform for mapping and sharing city streets. It might sound wonky, but the implications are big: SharedStreets brings public agencies, private companies, and civic hackers onto the same page, with the collective goal of creating safer, more efficient, and democratic transportation networks.

It will be interesting whether this step forward simply makes what is currently happening easier to manage or whether this will be a catalyst for new opportunities. In a number of domains, having access to data is necessary before creative ideas and new collaborations can emerge.

This also highlights how more of our infrastructure is entering a digital realm. I assume there are at least a few people who are worried about this. For example, what happens if the computers go down or all the data is lost? Does the digital distance from physical realities – streets are tangible things, not just manipulable objects on a screen – remove us from authentic streetlife? Data like this may no be no substitute for a Jane Jacobs-esque immersion in vibrant blocks.

The end of global evangelists?

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The passing of Billy Graham led me to ponder whether another religious leader can rise to a similar stature in today’s world. On one hand, the world is more connected than ever. When Pope Francis and the Dalai Lama are on Twitter, it is not hard to follow religious leaders or to find their words and actions in news sources. An increasingly connected world means that any leader, religious or otherwise, could quickly connect with billions around the globe.

Yet, it strikes me that there were certain conditions in play that helped contribute to the rise of Billy Graham. These would be difficult to duplicate:

  1. The end of World War II and the prosperity of the United States. As an American, Graham emerged from the country that helped end World War II and became the global democratic superpower. Graham could push against communism and project American strength and cool.
  2. The rise of the United States was accompanied by a religious resurgence in the US. As Finke and Stark argue in The Churching of America, church attendance rose through the 1950s before leveling off in the 1960s.
  3. A rising middle-class individualism in the United States that Graham could appeal to. While he often addressed social issues, the path to solving these problems started with changing individual hearts. This individualistic appeal – not new in American religion – now had a broad audience.
  4. A particular evangelistic and global missionary zeal in the United States where fundamentalists and evangelicals had both the resources and energy to try to spread the Gospel. This has cooled off to some degree.
  5. The emergence of evangelicals as a category from the dust heap of fundamentalism which had been pushed to the sidelines of American society in the early 1900s.
  6. The rise of mass media, particularly television, and the regular access billions had to it. Graham was telegenic enough. Yet, this mass media was not the same as today: it had a limited number of outlets so the audience was not as fragmented as later on.

This is not to say that religion is an inert force in today’s world or that new religious leaders could not emerge. Yet, they will do so in different conditions than that experienced by Graham and several generations of world citizens.

Countering gerrymandering in Pennsylvania with numerical models

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Wired highlights a few academics who argued against gerrymandered political districts in Pennsylvania with models showing the low probability that the map is nonpartisan:

Then, Pegden analyzed the partisan slant of each new map compared to the original, using a well-known metric called the median versus mean test. In this case, Pegden compared the Republican vote share in each of Pennsylvania’s 18 districts. For each map, he calculated the difference between the median vote share across all the districts and the mean vote share across all of the districts. The bigger the difference, the more of an advantage the Republicans had in that map.

After conducting his trillion simulations, Pegden found that the 2011 Pennsylvania map exhibited more partisan bias than 99.999999 percent of maps he tested. In other words, making even the tiniest changes in almost any direction to the existing map chiseled away at the Republican advantage…

Like Pegden, Chen uses computer programs to simulate alternative maps. But instead of starting with the original map and making small changes, Chen’s program develops entirely new maps, based on a series of geographic constraints. The maps should be compact in shape, preserve county and municipal boundaries, and have equal populations. They’re drawn, in other words, in some magical world where partisanship doesn’t exist. The only goal, says Chen, is that these maps be “geographically normal.”

Chen generated 500 such maps for Pennsylvania, and analyzed each of them based on how many Republican seats they would yield. He also looked at how many counties and municipalities were split across districts, a practice the Pennsylvania constitution forbids “unless absolutely necessary.” Keeping counties and municipalities together, the thinking goes, keeps communities together. He compared those figures to the disputed map, and presented the results to the court…

Most of the maps gave Republicans nine seats. Just two percent gave them 10 seats. None even came close to the disputed map, which gives Republicans a whopping 13 seats.

It takes a lot of work to develop these models and they are based on particular assumptions as well as methods for calculations. Still, could a political side present a reasonable statistical counterargument?

Given both the innumeracy of the American population and some resistance to experts, I wonder how the public would view such models. On one hand, gerrymandering can be countered by simple arguments: the shapes drawn on the map are pretty strange and can’t truly represent any meaningful community. On the other hand, the models reinforce how unlikely these particular maps are. It isn’t just that the shapes are unusual; they are highly unlikely given various inputs that go into creating meaningful districts. Perhaps any of these argument are meaningless if your side is winning through the maps.

More evidence of discrimination in mortgages by race and ethnicity

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The Center for Investigate Reporting went through 31 million records created by the Home Mortgage Disclosure Act and found disparities:

The analysis – independently reviewed and confirmed by The Associated Press – showed black applicants were turned away at significantly higher rates than whites in 48 cities, Latinos in 25, Asians in nine and Native Americans in three. In Washington, D.C., the nation’s capital, Reveal found all four groups were significantly more likely to be denied a home loan than whites.

Reveal’s analysis included all records publicly available under the Home Mortgage Disclosure Act, covering nearly every time an American tried to buy a home with a conventional mortgage in 2015 and 2016. It controlled for nine economic and social factors, including an applicant’s income, the amount of the loan, the ratio of the size of the loan to the applicant’s income and the type of lender, as well as the racial makeup and median income of the neighborhood where the person wanted to buy property.

Credit score was not included because that information is not publicly available. That’s because lenders have deflected attempts to force them to report that data to the government, arguing it would not be useful in identifying discrimination. 

This is an ongoing pattern. While I was in graduate school, I had a little experience working with the millions of HMDA records since my advisor, Rich Williams, had published on the topic. For example, see his 2005 article in Social Problems.

And lest we think that this is just about applicants of different races or ethnicities with equal standing receiving different treatment (generally the point of audit studies), it was even worse before the housing bubble burst:

In 2006, at the height of the boom, black and Hispanic families making more than $200,000 a year were more likely on average to be given a subprime loan than a white family making less than $30,000 a year…

Relative to comparable white applicants, and controlling for geographic factors, blacks were 2.8 times more likely to be denied for a loan, and Latinos were two times more likely. When they were approved, blacks and Latinos were 2.4 times more likely to receive a subprime loan than white applicants. The higher up the income ladder you compare white applicants and minorities, the wider this subprime disparity grows.

Or another study:

According to the study’s authors, the economists Patrick Bayer, Fernando Ferreira, and Stephen L. Ross, race and ethnicity were among two of the key factors that determined whether or not a borrower would end up with a high-cost loan, when all other variables were held equal. According to them, even after controlling for general risk considerations, such as credit score, loan-to-value ratio, subordinate liens, and debt-to-income ratios, Hispanic Americans are 78 percent more likely to be given a high-cost mortgage, and black Americans are 105 percent more likely.

Or see the $175 million fine leveled at Wells Fargo for steering minorities to worse loans.

This reminds of the conclusion of American Apartheid where the sociologists Doug Massey and Nancy Denton argue that Americans lack the will to enforce existing laws about housing discrimination. Even with a variety of laws and regulations intended to eliminate discrimination in housing, there is not a completely level playing level field.

Patterns across the ten metro areas with the most big homes

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While the article I discussed yesterday did not provide a helpful definition of a McMansion, it did provide five trends regarding which metropolitan areas had the largest homes:

Supersize trend No. 1: Outdoorsy types need plenty of space

Supersize trend No. 2: Seeking space in the suburbs

Supersize trend No. 3: Southern cities are churning out jobs and big homes

Supersize trend No. 4: Big homes are all that’s left in tight Midwestern markets

Supersize trend No. 5: Tech hubs + deep pocked buyers = more McMansions available

And, like the McMansion definition, another important caveat:

And if it wasn’t for the fact that we limited our ranking to one housing market per state, Colorado and Utah would’ve had all five top metros.

And a third caveat: this is based on only homes that are on the market.

Even with these significant limitations, I wonder if an analysis could reveal some underlying patterns behind these noteworthy metropolitan areas:

  1. They have a growing population and thus a growing stock of larger, new homes, particularly in suburbs.
  2. They have relatively low housing prices paired with enough higher income jobs. (Seattle and Portland are the ones that stick out here but perhaps this is relative: those same buyers could find higher prices in the Bay Area, LA, Vancouver, etc.)
  3. These places have looser zoning restrictions on the whole that allows for more and/or quick construction. (I imagine there is some variation in these top 10 places. Portland and Bridgeport, for example, likely have some tight restrictions compared to an Indianopolis or Provo.)

This could be worth pursuing though the data needs to provide a more complete picture of the housing stock.

List of cities with the most McMansions does not actually look at McMansions

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Realtor.com asks an intriguing question involving McMansions – “So which are America’s housing markets with the biggest cribs, and why?” – but then does not follow through because of a limited definition of which homes count as McMansions:

We sifted through realtor.com listings to figure out which of the 150 largest metros had the highest percentage of homes on the market that are 3,000 square feet and above. (The average square footage of a new single family home is 2,627, according to the National Association of Home Builders’ analysis of U.S. Census Bureau data.) Sure, this includes some tasteful, large homes and legit mansions. But it was impossible to separate those from the McMansions—it’s rare to see the word “tacky” in a home listing.

There are plenty of big homes in the United States – the median square footage of a new home is over 2,400 square feet – but not all big homes are McMansions. The article provides a different definition for McMansions than the one they actually use with the data:

The imposing, ostentatious structures looming over surprisingly wee plots of land. The crazily mismatched architectural styles. The hipped roofs, gabled roofs, and pyramidal roofs—all on the same house! The bank columns. The front yard Romanesque fountains. The puzzling profusion of window sizes and types. The gigantic, two-story front doors.

I can understand how the real estate listings do not easily allow for the easy categorization of homes as McMansions. Few, if any, homeowners and realtors want to advertise their homes using such a pejorative term. Yet, if you are going to use a headline involving McMansions and then talk about the poor architecture of McMansions, then your measure should take these features into account.

How might this be done? A few ideas:

  1. Take random samples within each metropolitan area and look for specific features.
  2. Do a survey of realtors, architects, and others who might be able to identify McMansions to get their sense of how many McMansions are in particular areas.
  3. Train a computer program to scan thousands of images of homes for sale and determine whether the homes are McMansions or not. (The coding scheme would be very similar to the one used in #1.)

These approaches are not necessarily easy but would be essential for actually getting at which AMerican cities have teh most McMansions.

For a more complete definition of a McMansion – including but also beyond their size and architecture, see my summary here.

Dating and the coming and going of parlors

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Skimming through a conservative take on dating in the modern era, I ran into a part involving the physical spaces where couples interact:

As a result, courtship morphed into dating, with couples venturing from family parlors and front porches to dance halls and, yes, the proverbial back seat. The parlor courtship rituals had been, of course, dependent on one’s family actually having a home with a parlor. As a result of the industrial revolution, families increasingly lived in tenements and apartments that lacked such amenities, so the shift was as much forced by the demographic shifts in the U.S. as by changes in cultural mores.

I could quibble with the details and take interest in the larger issue. Regarding the parlor, I would guess that many Americans in the 1800s into the 1900s did not have access to a parlor. This formal living room was part of a larger home of a wealthier family. Until then, many people lived in a single room or a limited number of rooms where it would be a waste to have a formal entertaining space that could have only a single use. This was true in rural settings – think of the first dwellings in the Little House on the Prairie books – and cities – apartments and limited space. The parlor/living room was linked to the middle-class and the single-family home, something that became part of a consistent American Dream in the early 1900s and became more accessible to more Americans in the 1920s and then the 1950s. And the parlor lasted only so long: living rooms are on the way out with more emphasis on using kitchens and great rooms for social spaces.

The larger issue is worth pondering: how do physical spaces shape relationships and vice versa? Spaces matter for relationships to form and develop. The ideal that developed in the 1800s emphasized a nuclear family dwelling in a private home. Additionally, the middle-class private home was viewed as the domain of women. Thus, intimate relationships moved to this setting. With the invention and then spread of the automobile, people could pursue relationships in cars as well as more easily access other locations. Urbanization likely had a similar effect: by putting people into close proximity with more people and more spaces, couples could easily access more than just the family dwelling. Today, dating can take place in an online realm and the privacy of bedrooms, possibly bypassing any public settings.

Defining a social problem: “transit gaps” or “transit deserts”

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One skeptic of the concept of transit gaps explains his concerns:

The Chicago-based nonprofit Center for Neighborhood Technology recently unveiled its AllTransit Gap Finder—an online mapping tool designed to point out areas with “inadequate” transit service. It’s a good effort, and it’s certainly good that we have more tools for understanding transit demand…

A transit gap is some kind of difference between transit service and transit need or demand. But need and demand are different things. A need means that there are people whose lives would be better if they had transit. A demand is an indication that transit service, if it were provided, would achieve high ridership.

These terms correspond to the two opposing goals of transit service. If the goal of service is ridership, then it should provide excellent service where there is demand. On the other hand, many people who need transit wouldn’t be served if transit agencies ran only high-ridership service. So transit agencies run a certain amount of service for the non-ridership goal of coverage, which responds to need. In other words, they spread service out so that everyone has a little bit, even though low ridership is the predictable outcome. This critical distinction is explained more fully here. It’s a difficult budgetary choice about dividing resources between competing goals, one that local governments need to think about…

Although AllTransit’s claims are framed in misleading terms, the idea of being able to accurately see exactly how well any given neighborhood is served by transit is a laudable one. Over the years I’ve written about other efforts to get this right. An especially important idea, buried deep in the overly complex methodology, is that a transit quality index should be about where you can get to in a given amount of time, rather than what transit is available. In my own work I routinely use this measure to describe the human benefits of transit service changes, because getting to destinations, and having a choice of more destinations, is what makes for a great life.

There seems to be two issues here: separating community values from possibilities as well as how to best measure transportation options. No city has an endless pot of money with which to fund mass transit. Yet, I imagine proponents of transit deserts would note that the general American orientation is toward driving and roads while mass transit has to regularly scrap for money. The measurement issue is hopefully an ongoing conversation as researchers with different decisions and aims work to find measures that both reflect the social realities as well as provide helpful information for residents and local governments.

But, I also suspect that this is critique is missing a key concern of some of those working in the food/transit/grocery stores/parks/medical care desert literature: the key is which groups are most affected by these deserts or have less access to these necessities. Many of the deserts – however defined and regardless of the goals of the community – seem to affect lower class and non-white residents. One could argue that a community might not have the resources or vision to extend mass transit to a particular area but this does not necessarily address the issue of residential segregation that is alive and well in the United States.

The double-edged sword of record home prices in many American metro areas

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The housing bubble of the late 2000s may be long gone as housing prices continue to rise:

Prices for single-family homes, which climbed 5.3 percent from a year earlier nationally, reached a peak in 64 percent of metropolitan areas measured, the National Association of Realtors said Tuesday. Of the 177 regions in the group’s survey, 15 percent had double-digit price growth, up from 11 percent in the third quarter.

Home values have grown steadily as the improving job market drives demand for a scarcity of properties on the market. While prices jumped 48 percent since 2011, incomes have climbed only 15 percent, putting purchases out of reach for many would-be buyers.

The consistent price gains “have certainly been great news for homeowners, and especially for those who were at one time in a negative equity situation,” Lawrence Yun, the Realtors group’s chief economist, said in a statement. “However, the shortage of new homes being built over the past decade is really burdening local markets and making homebuying less affordable.”

Having read a number of stories like this, I wonder if there is a better way to distinguish between economic indicators that are good all around versus one like this that may appear good – home values are going up! – but really mask significant issues – the values may be going up because many buyers cannot afford more costly homes. The news story includes this information but I suspect many will just see the headline and assume things are good. Another example that has been in a lot of partisan commentaries in recent years (with supporters of both sides suggesting this when their party was not president): the unemployment rate is down but it does not account for the people who have stopped looking for work.

In the long run, we need (1) better measures that can encompass more dimensions of particular issues, (2) better reporting on economic indicators, and (3) a better understanding among the general populace about what these statistics are and what they mean.