In "Rating the ’Burbs," The Kansas City Star set out to measure the quality of life of local suburbs as places to live.
The analysis includes every suburb in metro Kansas City larger than 3,500 residents in 2003. That comes out to 40 cities. In addition, we divided Overland Park in half, by north and south of Interstate 435, because the city is larger than any other suburb and its two halves are distinctly different in age and character.
Our scoring system was based on a carefully constructed set of polls, statistics and computations. We went several steps further than ratings done by magazines in other major metro areas, broadening the range of topics and data in our analysis.
To evaluate livability, we first had to determine what local suburbanites considered important. The Star conducted an opinion poll earlier this year, asking suburban residents what they valued in their communities. It found safety and schools topped the list, mirroring a similar poll done for the Mid-America Regional Council earlier this decade.
Next, we looked for statistics that measured the performance of a place. Some suggestions were made by city managers. We were limited to a degree by what was available on a citywide basis and what was quantifiable. There’s no apparent way, for instance, to statistically assess the level of leadership.
So after consulting with regional council staffers, city government officials, plus local professors, architects and demographers, we ended up with 23 statistical measures grouped into nine general categories:
Crime: violent crimes per capita; property crimes per capita; overall trend of violent and property crimes.
Education: elementary school math scores; elementary school reading/communications scores; average high school ACT score; percent of high school graduates going to college. These represented student achievement more than school funding numbers or pupil-teacher ratios.
Housing: change in resale home prices this decade; new single-family building permits; balance of housing offerings computed by how close a city’s range of home prices matched the suburban norm. These statistics were chosen as indicators of desirability, new housing stock and affordability, respectively.
Government: property taxes on a $150,000 house; city government efficiency as calculated by operations expenditures per capita. These reflected how well local governments were holding their spending in check, with lower being better.
Neighborhoods: percent of residents staying in their homes at least five years; the likelihood that whites will see or interact with a minority, as expressed by a mathematical formula called an "exposure index" favored by sociologists studying race relations. These statistics gave a sense of residential stability and diversity.
Sense of community: voter turnout rates in contested city and school elections this decade; an evaluation of a city’s charm, determined by Realty Executives real estate agents rating such features as tree coverage, architectural style and the upkeep of properties. These statistics conveyed community engagement and attractiveness.
Lifestyle: tally of important cultural, recreational and health offerings, ranging from outdoor concerts to seniors programs; per capita acreage of parks in and adjacent to a city.
Services: number of retail and service businesses per capita; retail sales per capita; city government capital improvement spending per capita, with higher being better. These illustrated the extent of public and private investment to make suburban life more convenient.
The automobile: average commute time; traffic accidents per capita. These provided a snapshot of how well the transportation network works in suburbs.
Once we gathered these statistics, some were sent to cities to review. Then the Mid-America Regional Council’s research services division converted the raw numbers into points on a 1-to-100 scale. The points were based on how close a suburb was to the suburban norm in each statistical measure; the more a city was better than the suburban norm, the more points it got.
Cities’ points were then averaged within each of the nine categories and multiplied by a "weight" based on how important the category was, based on polling results. For example, in The Star’s poll about quality-of-life factors, respondents gave safety a level of importance that was nearly twice as high as commute times.
These were the weights assigned to the categories: crime, 1.963; education, 1.469; housing, 1.415; government, 1.229; sense of community, 1.224; lifestyle, 1.162; services, 1.133; neighborhoods, 1.131; and the automobile, 1.00.
Many of the decisions that went into this analysis - from the selection of statistics to the selection of poll results to apply to weights - represent judgment calls. As Frank Lenk, director of MARC’s research services, puts it: "There’s no such thing as judgment-free data analysis."
In the end, the top-rated places earned just over half the total possible points. No suburb was close to "having it all." And small degrees of differentiation put one suburb above another. In fact, the spread between cities finishing next to each other in the rankings was usually about 1 percent.
Above all, the rankings are merely a snapshot in time. Improvements that various cities are currently undertaking could change the rankings in future years.
- Jeffrey Spivak/The Star