Tag: statistics

Two apartment buildings under construction in the "North Union" development in the 27th Ward.
Two apartment buildings under construction in the "North Union" development in the 27th Ward.

Fair share: how many new homes were permitted in your Chicago ward?

February 1, 2025 / / 0 Comments

Now that I’ve audited the Chicago building permits for the last four years I can more accurately visualize where new homes were permitted across Chicago’s fifty wards. I was not surprised to see that the 27th Ward carries the team known as City Council, but I was surprised by how big the gap was between the first and second place wards, and the gap between the fewest number of wards where 50 percent of new homes were permitted and the number of wards where the other half were permitted.

In the period 2022-2024…

  • 24.0 percent of new homes were permitted in the 27th Ward
  • 10.6 percent in the 34th Ward
  • 8.1 percent in the 3rd Ward
  • 6.9 percent in the 4th Ward

Those four wards comprise 49.5 percent of new homes permitted, while 46 wards permitted the remaining 50.5 percent. Some of this imbalance is due to how different alderpersons accept new development proposals, and the current zoning capacity of properties in each ward.

Incredibly, when rounding to the tenths place, 24 wards permitted so few new homes in that time period that they round down to 0 percent.

To further illustrate how some wards are where so few new homes are permitted, which may be due to factors beyond the alderperson’s control (local rents not meeting development and construction costs, and racism, to name a couple), consider that six wards permitted fewer than 10 homes each during that three-year period.

While Chicago does not have quotas or goals on how many new homes should be permitted or built either citywide or by ward, the city will maintain a housing shortage if most wards are not facilitating or allowing new housing to be built. The allowance of new housing is heavily influenced by each alderperson’s choices.

The city’s ability to grow and spread the property tax revenue burden fairly depends on new development occurring across the city. This is especially the case in areas where new housing can moderate rising demand housing costs, and transportation infrastructure and amenities are in good supply.

map of Chicago showing the 50 wards. Each ward is labeled with its ward number and the percentage of new homes permitted in that ward for the period 2022-2024.
Map 1. Chicago’s 50 wards and their share of new homes permitted in 2022-2024. Tap or click the map to enlarge it. Open the spreadsheet containing data that powers this map.

Other statistics

Table 1. New construction homes permitted, by year

202220232024Total
7,5744,4984,36016,432

Methodology

Using Chicago Department of Building permits that are imported to Chicago Cityscape’s Building Permits Browser, I review each new construction permit’s description to count the number of units authorized by that permit. Foundation phases of multi-phase permits and most revision permits are excluded. I do my best to catch projects that change scope between two permits, such as a permit originally issued for a two-flat but changed to a single-family house, or a larger multifamily building losing or gaining units in a subsequent permit.

New construction coach house units are also excluded because they are allowed only in five pilot areas in a subset of wards; view ADU statistics on Chicago Cityscape.

The statistics are also shown in Chicago Cityscape’s building permits analysis table, which is updated daily; look for columns with a heading that says the year and the word “audited”. Data for permits in other years are not yet reviewed and corrected.

This is an imperfect comparison of wards because there was a redrawing of ward boundaries and an election in 2023. This means that some alderpersons are new, and that all alderpersons oversaw new development approvals and the capacity of their zoning map in different areas before and after the remap.

On the flip side, the new ward map also means that the number of inhabitants in each ward was roughly equal at the time of the remap. This supports some level of data normalization (i.e. new homes permitted per capita), which can be done in future analysis.

Finding a new way to measure cities’ bike friendliness in the United States

November 3, 2012 / / 8 Comments

A really smart person could come up with a way to measure day-to-day bike friendliness based on how well cities adhere to standards that keep roads clear of obstructions that further frustrate the commute, like construction projects that squeeze bikes and cars together. 

I work at home. There are some days when I only leave my house to get milk from the Mexican grocery store at the end of my block (which makes awesome burritos). That means I ride my bike half as much as people who commute to work. on their bikes. Today I had a bunch of errands to run: drop off stuff, buy stuff, take pictures of stuff for my blog, Grid Chicago.

It was a very frustrating experience. I don’t need to go into details about how I was harassed by people who the state so graciously awarded a license to drive. But it happened. And it happens a hundred times a day to people cycle commuting in Chicago. I got to thinking about “bike friendly” cities. Is there a way to incorporate driver attitudes in there? I tweeted:

[tweet_embed id=264575958374305792]

Later I had the idea to use some very simple but objective measurements to create a new bike friendliness metric. It would help ensure that “Silver” (a ranking the League of American Bicyclists [LAB] uses) in one city means the same as “Silver”. It can expand from here but basically it works like this:

  • The share of people going to work who go by bike is a proxy for how “friendly” a city is to biking.
  • If a city has a lot of people biking to work, it must be friendly.
  • If a city has a few people biking to work, it must be non-friendly.
  • Cities are compared to each other to determine friendly and non-friendly.
  • The metric uses standard deviation to score cities.

Stop me if this has already been done.

I created a spreadsheet that lists the top 10 populous cities in the United States. I then added 10 more cities: Austin, Boston, Davis, Madison, Minneapolis, Portland, San Francisco, Seattle, and Washington, D.C. In the next column I listed their bike commute share from the American Community Survey 2006-2010 5-year estimates. I calculated the standard deviation and mean of these shares and then in another column used Apple Numbers’s STANDARDIZE function:

The STANDARDIZE function returns a normalized value from a distribution characterized by a given mean and standard deviation.

I think that’s what I want. And the output is close to what I expected. I then found the LAB ranking for each city and found the variance of each ranking to see how far apart each city within one ranking was from another city in the same ranking. The results were interesting: the higher the ranking, the more variance there was.

Hurricane Sandy prompted a lot of New Yorkers to bike. It made headlines, even. Photo by Doug Gordon. 

I wanted to add another metric of bike friendliness, and that’s density. To me, a higher density of people would mean a higher density of places to go (shop, eat, learn, enjoy) and friends and family would be closer, too. Or the possibility of meeting new people nearby would be higher. Yeah, I’m making a lot of assumptions here. So I applied the STANDARDIZE function there as well. I added this number to the previous STANDARDIZE result and that became the city’s score.

So, in this new, weird ranking system, the most bicycle friendly cities are…drum roll please…

  1. Davis, California (Platinum)
  2. New York City (Silver) *
  3. San Francisco (Gold) *
  4. Boulder (Platinum)
  5. Boston (Silver)
  6. Philadelphia (Silver)
  7. Tie: Chicago*, Washington, D.C. (Silver)
  8. Tie: Portland* (Platinum), Minneapolis* (Gold)

Remember, I said above that any author of a list should spend at least a day cycling in each city. I’ve starred the cities where I’ve done that – I’ve cycled in 5 cities for at least a day.

I only calculated 20 cities. Ideally I’d calculate it for the top 50 most populous cities AND for every city that’s been ranked by LAB.

LAB cities list (PDF). My spreadsheet (XLS).

Stats from the OECD: Comparing traffic injuries of the United States and Netherlands

May 21, 2012 / / 0 Comments

For an article I’m writing for Architect’s Newspaper about the Chicago Forward CDOT Action Agenda, I wanted to know about traffic injuries and fatalities in the United States, but compared to the Netherlands and Denmark and other places with a Vision Zero campaign (to have 0 traffic deaths each year).

I already knew the OECD had a good statistics database and web application. With a few clicks, I can quickly get a table of traffic injuries (casualties) listing just the countries I want. I can easily select the years I want, too.

In one more click the web application will show a time animated bar chart. A feature I’d like to see added is dividing the figure (in this case traffic injuries) by the population. Check out the video to see what it looks like. The United States looks to be in terrible shape, but our country has several times more residents.

I had trouble downloading and opening the CSV file of the data table I created. The XLS file was damaged, also. The built-in Mac OS X Archive Utility app couldn’t open the .gz file, but I used The Unarchiver app successfully.

My calculations, based on data from OECD (national population and traffic fatalities), Illinois Department of Transportation (IDOT), and the American Community Survey:

Fatalities per 100,000 in 2009

  • United States: 11.02472
  • Denmark: 5.48969
  • Netherlands: 4.35561
  • Sweden: 3.84988
  • Chicago: 16.74891
  • United Kingdom: 3.83555

Chicago’s fatality rate per 100,000 citizens in 2009 was 16.75 (473 deaths on the roads). The fatality rate dropped in 2010: just 11.65 deaths per 100,000 residents (315 deaths on the roads; the population also decreased).

Updated September 28, 2012, to add the United Kingdom. 

Frequency of Chicago women riding their bikes to work is down

November 9, 2010 / / 50 Comments

UPDATE: I added data from years 2005-2007 to complement existing 2008-2009 data in Table 1 as well as a visual representation. I have also added data from the 3-year estimates to Table 2.

UPDATE 01/20/11: Added the most recent 3-year estimate that the Census Bureau released in January 2011 to Table 2.

In September 2009, I wrote about “what the Census tells us about bicycle commuting” and a couple of days ago I compared Chicago to Minneapolis and St. Paul.

I want to update readers on the changes between the 1-year estimate data reported in that article (from 2008) and the most recent 1-year estimate data (from 2009). Percentages represent workers in the City of Chicago aged 16 and older riding bicycles to work.

Table 1 – Bicycling to work, 16 and older, 1-year estimates

Year Total MOE Male MOE Female MOE
2005 0.7% +/-0.1 0.9% of 621,537 +/-0.2 0.4% of 541,013 +/-0.1
2006 0.9% +/-0.2 1.2% of 645,903 +/-0.3 0.7% of 563,219 +/-0.2
2007 1.1% +/-0.2 1.4% of 656,288 +/-0.3 0.7% of 574,645 +/-0.2
2008 1.0% +/-0.2 1.5% of 657,101 +/-0.3 0.5% of 603,640 +/-0.2
2009 1.1% +/-0.2 1.8% of 651,394 +/-0.3 0.4% of 620,350 +/-0.1

View graph of Table 1. MOE = margin of error, in percentage points.

We should be concerned about the possible decrease in the percentage of women riding bicycles to work, especially as the population size increased. The margin of error also decreased, thus suggesting an improvement in the accuracy of the data. There have already been many discussions (mine, others) as to why it is important to encourage women to ride bicycles and also what the woman cycling rate tells us about our cities and policies. If the decrease continues we must discover the causes.

But Table 1 doesn’t tell the full story.

As Matt points out in the comments below, the number of surveys returned for 1-year estimates is smaller than that from the Decennial Census. Therefore, I took a look at the two 3-year estimates available, each having a larger sample size than the 1-year estimates (see Table 2). The data below seem to show the opposite change than seen in Table 1: that the number of women bicycling to work has increased. The crux of our quandary is sample size. The sample size is the number of people who are asked, “How did this person usually get to work LAST WEEK?”

Table 2 – Bicycling to work, 16 and older, 3-year estimates

Click header for data source 2005-2007 2006-2008 2007-2009
Total workers 1,203,063 1,230,809 (+2.31%) 1,291,709 (+4.71%)
Males bicycling to work 7,549 9,014 (+19.41%) 11,014 (+18.16%)
Females bicycling to work 3,474 3,741 (+7.69%) 3,542 (-5.62%)

The number of discrete females who bike to work has decreased in the most recent survey (2007-2009) while the total number of workers 16 and older has increased, giving females bicycling to work a smaller share than the previous survey (2006-2008). We must be careful to also note the margin of error for females bicycling to work is ±499.

Matt suggested that sustainable transportation advocates “push for higher sampling” to reduce “data noise” and increase the accuracy of how this data represents actual conditions. I agree – I’d also like more data on all trips, and not just those made to go to work. Household travel surveys attempt to reveal more information about a region’s transportation.

One of the two overall goals of the Bike 2015 Plan is “to increase bicycle use, so that 5 percent of all trips less than five miles are by bicycle.” Unfortunately, the Plan doesn’t provide baseline data for this metric, but we can make some inferences (there will probably be no data for this in 2015, either). The CMAP Household Travel Survey summary from 2008 says that the mean trip distance (for all trips) for Cook County households is 4.38 miles (under five miles). The same survey says that for all trips, 1.3% were taken by bike. These can be our metrics. *See below for men/women breakdown. Note that no data for “all trips” exists for the City of Chicago.

We will not achieve the Bike 2015 Plan goal unless we do something about the conditions that promote and increase bicycling. Achieving the goals in the Bike 2015 Plan is not one group or agency’s responsibility. The Plan should be seen as a manifestation of what can and should be done for bicycling in Chicago and we all have a duty to promote its objectives.

Please leave a comment below for why you think the rate of women who bike to work has stayed flat and decreased, or what you think we can do to change this. Does it have to do with the urban environment, or are the reasons closer to home?

*The same survey also said: Cook County males used the bike for 1.9% of all trips. Cook County females used the bike for 0.8% of all trips.

Table 1 data comes from the 1-year estimates from the American Community survey, table S0801, Commuting Characteristics by Sex for the City of Chicago (permalink), which is a summary table of data in table B08006. Table 2 data directly from American Community Survey table B08006.