It is an understatement to say that real estate has been turbulent in the last three years. But it’s also true to say it’s been more turbulent in some places than in others. What is the best way to measure the turbulence of a market? You can’t just compare median prices and sales volume from 2007 and 2010 because you could miss some drama in the mean time.
Probably the best way to measure it is with a coefficient of variation, which measures the ups and downs, and normalizes it so you can compare neighborhood to neighborhood (more on this below). Click the table headings to sort:
Chicago's Most Stable Neighborhoods
Low values represent stability; the composite column is a mix of all metrics. Sort by individual metrics to find the neighborhoods with the lowest variation in that metric.
CITY 0.203 0.157 0.066 0.300 0.726
ALBANY PARK 0.215 0.194 0.112 0.360 0.880
BEVERLY 0.129 0.160 0.518 0.643 1.449
BRIDGEPORT 0.194 0.214 0.078 0.496 0.982
EDGEWATER 0.212 0.313 0.126 0.236 0.887
HUMBOLDT PARK 0.583 0.162 0.224 0.545 1.513
HYDE PARK 0.209 0.276 0.135 0.376 0.996
IRVING PARK 0.233 0.178 0.122 0.385 0.918
JEFFERSON PARK 0.172 0.180 0.289 0.462 1.103
LAKEVIEW 0.171 0.276 0.050 0.312 0.809
LINCOLN PARK 0.107 0.265 0.061 0.347 0.780
LINCOLN SQUARE 0.167 0.196 0.091 0.333 0.786
LOGAN SQUARE 0.285 0.162 0.097 0.361 0.905
LOOP 0.225 0.667 0.121 0.273 1.286
NEAR NORTH SIDE 0.146 0.338 0.105 0.215 0.805
NEAR SOUTH SIDE 0.165 0.439 0.112 0.290 1.006
NEAR WEST SIDE 0.139 0.354 0.072 0.398 0.964
NORTH CENTER 0.080 0.284 0.092 0.384 0.839
ROGERS PARK 0.153 0.333 0.163 0.315 0.965
UPTOWN 0.223 0.272 0.051 0.314 0.860
WEST TOWN 0.155 0.217 0.062 0.333 0.767
The table shows the 20 neighborhoods I track on a quarterly basis, along with their coefficient of variation. The smaller the number, the more stable the market. Taking condos and single family homes, sales volume and median prices all into account, West Town, Lincoln Park, and Lincoln Square have been the most stable neighborhoods (the composite column). But you can sort the chart by any individual metric to explore the data yourself.
For example, if you click on “SF median,” you’ll see that North Center is the lowest value (the most stable), along with Lincoln Park, Beverly, and Near West Side. If you click twice on “Condo median” you’ll see that the highest values (the least stable) have been Beverly, Jefferson Park, and Humboldt Park. By following the links in this post, you can verify that these neighborhoods have flat or spiky charts in the neighborhood reports.
For data junkies, the metric in the chart is the coefficient of variation. For non-junkies, this is a two-step calculation. First, we calculated the standard deviation, which measures how far the individual data points differ from the average. So a metric that goes way up and way down will have a high standard deviation.
The second step is to divide by the average, so that we get a coefficient (a number between 0 and 1) that can be compared across many different data points. The result is that a low coefficient of variation means that a given metric has stayed relatively flat; a high coefficient means it’s changed a lot–either way up, way down, or up and down.
You’ll generally see high coefficients of variation in instances where there are very few sales–condos in Beverly, for example, and single family homes in the South Loop.
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