Here you can see the overall results of the 2015 Localism Index by metro area, where red corresponds to highest scores and yellow corresponds to lowest. Find the interactive version of this map here.
In an age in which data is used ubiquitously to measure and analyze society (it’s what I do here regularly), it is important to recognize that numbers and metrics are always infused with implicit values. This is something we must remember when we are faced with facts or rankings of any sort; even simple statistics can rarely be presented without any sort of bias or narrative. This isn’t exactly a bad thing; narratives help us derive meaning from the world, but narratives and biases can become dangerous when we grow so accustomed to them that we approach them with thoughtless acceptance. I would even go so far as to assert that every metric and every piece of data is flawed; it is not the metrics which are most flawed of which we should be wary, but the ones with flaws we’ve ceased to recognize (GDP is one of these metrics. For further discussion about this, see my post on my senior thesis). Because of these issues, I strive in my work to constantly assess and shape the values implicit in data for the benefit of human well-being. In this vein, I have worked off and on for the past year to produce a new sort of ranking system for American cities. I’d like to introduce it to you now: the 2015 Localism Index. Continue reading
A friend of mine snaps a photo of our reflections in the window as we wait for an elevator on the campus of Purdue University, 12/1/2010
I was once in a course on economic thinking, and the class was posed the following question:
“Workers in a high-rise office building are complaining about having to wait too long for elevators. The level of discontent seems to be rising. What might be done? Some suggestions are offered. These include:
- add more elevators;
- increase the size of the elevators;
- speed up the elevators;
- stagger the working hours of different groups in the building;
- make some of the elevators go non-stop to the higher floors, while others cover the lower floors stopping at each floor as needed; or,
- use a differential charge for using the elevator, with higher price at peak-use times.”
After being given time to argue the merits of these possible solutions and put forth alternative options, we were surprised to learn the often implemented real-world solution: leaving the elevators themselves the same, and simply putting mirrors in elevator lobbies. Even though we had all waited in elevator lobbies that were walled with mirrors (they were all over campus), this idea had not occurred to any of us because we were attacking an entirely different problem than the one mirrors address.
We don’t always need to move more quickly. If we experience each moment as meaningful, then the pace of our actions becomes insignificant and the idea of “waiting” vanishes altogether.
The first three solutions try to fix the problem through brute force, attempting to increase elevator capacity or capability in a single stroke. The next three start to get a little more creative, attempting to cut down on demand or increase the efficiency of the elevator set-up, but they still approach the problem as one of insufficient elevator space to meet the demands of all the workers wanting to use them. Continue reading
Continuing the Conversation on Diversity in American Cities
Four years ago, my introduction to the field of community development was accompanied by a few disparaging words about gentrification. In the four years that I have spent in the field, gentrification has been an unending source of conversation and, often, confrontation. It is often decried and lamented as a scourge on our cities and accompanied by insults of racism and classism. Lately, however, pundits and journalists have been questioning its evils. Today, as I continue my discussion of diversity in American cities, I’d like to take a look at one recent study which is attempting to adjust the focus of our conversation around poverty away from the issue of gentrification and towards the issue of concentration.
City Observatory’s report can be found here.
First, for those who are unacquainted with the topic, gentrification is a term used to describe the rapid transformation of a neighborhood, from low-income (and typically racially diverse) to somewhat-affluent (and if we follow the cliche, white and hipster). The argument goes that when rich white kids start moving into a poor neighborhood, it is immediately flooded with development money and its long-time poorer residents are driven out by the rising costs of living. If this story is true, it certainly presents a problem for low-income residents of cities everywhere. However, if a recent study by Joe Cortright and Dillon Mahmoudi of City Observatory is to be believed, gentrification really isn’t the issue we should be talking so much about. Instead, concentrated poverty represents a much larger challenge for American cities. Continue reading
Diversity in the Real World, Following Up on the Parable of the Polygons
In December, I introduced the Parable of the Polygons, an incredibly engaging and revealing bit of computer-generated game theory (read: fancy graphics with shapes that move based on laws of social behavior), designed to illustrate how segregation can happen in our cities.
This got me curious about how segregation happens in our cities today, and what it might look like to find a neighborhood that was truly diverse. In this vein, I’ve compiled data from all U.S. Census Tracts with populations larger than 500 and created an index* which ranks each by its level of diversity. Above, you can see a map of the top ten most diverse (green stars) and top ten least diverse (red teardrops) tracts in the U.S.
Here are the most diverse:
||Airport Heights North, Anchorage
||Russian Jack Springs Park North, Anchorage
||Portland Avenue Park Area, Tacoma
||South Ozone Park, Queens
||South Ozone Park, Queens
||South Ozone Park, Queens
||South Ozone Park, Queens
||South Ozone Park, Queens
||E. Jamaica Estates, Queens
Here are the least diverse:
||N Buchanan County
||Maverick County, near Eagle Pass
||Central Cambria County/Beaverdale
||NE Holmes County
||Western McDowell County
||SW Breathitt County
||SW Buchanan County
||SW Yuma County, near San Luis
||NW Claiborne County/Clairfield
||East Midwood, Brooklyn
More analysis will be following, but in the meantime I’ll let you do your own analysis of these results.
*Index is based on an entropy index as described in academic literature. My method grouped U.S. Census data into 6 racial/ethnic groups: White, Black, Native American, Asian/Pacific, Other/Multiple, and Hispanic. The proportion of each of these groups per tract is then put into the following formula:
I realize that this is not a perfect representation of diversity, but perfection must be balanced with ease of use.
Do Energy Efficiency Improvements Make Us Use More Energy?
I was quite intrigued this week by the latest podcast offering from Freakonomics. Aside from their somewhat insulting “discovery” that the study of the environment isn’t diametrically opposed to that of economics (a conversation for another day), they put forward an engaging analysis of the effectiveness of energy efficiency. Their discussion centered around the work of Arik Levinson, an economist at Georgetown University. The gist of Freakonomics’ argument, based on Levinson’s work, is that California’s 1978 residential energy efficiency regulations did not result in a decrease in per capita electricity use, and that the differences between energy use in California and other states can be explained by a particular manifestation of the rebound effect: the Jevons paradox.
The podcast chronicles Levinson’s research on the impacts of these building codes, which was recently published in a working paper by the National Bureau of Economic Research. For the study, Levinson analyzed data around California’s housing regulations in three different ways. He says it best in his own words:
First, I compare[d] current electricity use by California homes of different vintages constructed under different standards, controlling for home size, local weather, and tenant characteristics. Second, I examine[d] how electricity in California homes varies with outdoor temperatures for buildings of different vintages. And third, I compare[d] electricity use for buildings of different vintages in California, which has stringent building energy codes, to electricity use for buildings of different vintages in other states. All three approaches yield[d] the same answer: there is no evidence that homes constructed since California instituted its building energy codes use less electricity today than homes built before the codes came into effect.
Why you should always be willing to ask questions about what is presented to you.
I’m currently working on a post around Freakonomics’ latest podcast, “How Efficient is Energy Efficency?” I will have that post up sometime in the next few days, but in my research for the post I ran across an insight that I thought was important to share about how we present and challenge information. The podcast centers around the work of Arik Levinson, an Environmental Economist at Georgetown University. Two of his papers in recent years have focused on energy efficiency regulations for housing in California. The standard narrative is that because California enacted energy efficiency standards for all new houses starting in 1978, it has lead the nation in electricity reduction. This narrative is represented most clearly by the following graph:
Residential Electricity Per Capita. From VoxEU.org. Original Academic Article Here.
Wow! Look at that difference and how dramatically California separated from the rest of the nation right in the 1970s!
People have gotten really excited about this graph. If you want to see how many groups have referenced it, take a look at the Google Image results for searching “California 1970s energy efficiency.” The National Resources Defense Council, Scientific American, and the World Bank (on page 215) are just a few. Each of these organizations has made California and their energy efficiency standards out as some major hero. I am not going to cast doubt on the accuracy of these numbers themselves and so, I believe, they display some useful truths about the nature of California’s energy consumption profile. However, no matter how much truth is represented in this graph, I believe that it serves to cloud the discussion rather than illuminate it. Continue reading
Happy Super Bowl Day, everyone! In honor of one of America’s biggest cultural holidays, I’ve created an infographic which breaks down all you need to know about the big game and its cultural significance. You can watch it today at 6:30PM ET on NBC. Check out the details below:
Then-Senator Barack Obama makes his first visit to Elkhart, IN while campaigning for his presidential run in ’08. From Flickr, CC license.
A few days ago, NPR lead into its coverage of the State of the Union Address by putting up a retrospective on President Obama’s visit six years ago to my high school in Elkhart, IN. It was January, 2009, and Obama chose Elkhart as the first destination of his term in office because the town served as the begrudging poster-boy of the Great Recession. When Obama visited, the unemployment rate in Elkhart was 19.1% and it would go as high as 20.2% a few months later. The title of “Recreational Vehicle Capital of the World” did not do the town much good in an economic climate in which RVs were completely undesirable. Six years later, as NPR chronicles, the economy of Elkhart has rebounded substantially, but is it any less susceptible to economic shocks than it was in 2007? Continue reading