The Measure of America (and Herkimer and Oneida Counties): 2013-2014

In the era of “big data,” it would seem that policymakers and regular people alike would have the information they need at their fingertips to understand their world and make it better. Unfortunately, that’s far from the case. Though we know the country’s gross domestic product quarterly, its retail sales monthly, and stock market numbers minute-by-minute, we rarely hear statistics on our country’s people. How long can a baby born today in Missouri, New Mexico, or Minnesota expect to live? What proportion of adults have completed high school in Houston as compared to Dallas? What wages and salaries are typical of Latinos in the United States, and how do they compare to those of whites or African Americans?

The people at MeasureofAmerica.com have released their 2013-2014 report on exactly those items. Using what is called the Human Development Index, Measure of America looks specifically at three vital areas of human development — health, education, and earnings — and their impact on the opportunities available to us and how they enable people to invest in their families and live to their full potential. The Measure of America 2013–2014 contains American Human Development Index rankings for the 50 U.S. states and the District of Columbia, the 25 largest metropolitan areas, and racial and ethnic groups within those states and metro areas. It also looks at changes in well-being in states since 2000 and in metro areas before and after the Great Recession. Below is a screen shot of how each state (and the D of C) rank overall and with each of the three areas of human development.

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If you visit their mapping page, you can see some of these data mapped on the county level for the country, and of course, for New York as well. If you change you geographic level to county...

 
...and proceed despite the warning that pops up...

...you can look at any number of pieces of information on the county level.

In the end, you get access to a spatial graphic that looks like this (in this case for the income related index data):

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So play around a little and see how we measure up !