Throughout my blogging, I have consistently turned to the Missouri Economic Research and Information Center’s posting of cost-of-living data from the Council for Community and Economic Research (C2ER). Today I find MERIC has posted the 2015 annual average cost of living for all states as compared to the national average.
Mississippi ranks #1, as in having the lowest cost of living, 83.5% of the national average. The next cheapest states are Indiana, Idaho, Oklahoma, and Kentucky. Ranking 46th through 50th are, perhaps predictably, Alaska, California, New York, the District of Columbia, and Hawaii (the last at 168.6% of the national average).
Where’s South Dakota? 30th, as in more costly to live in than 29 other states:
In 2015, it actually cost 2.5% more to pay for groceries, housing, utilities, transportation, health care, and other basic living expenses in South Dakota than the national average. Among our neighbors, only Montana had a higher cost of living. Everyone else in the neighborhood, even Minnesota, has a lower cost of living. Iowa’s the cheapest neighbor, with cost of living 92.0% of the national average.
Yes, yes, the C2ER does not include taxes. But South Dakota’s low tax burden doesn’t make up for South Dakota’s low wages, meaning our higher-than-you-thought cost of living still kicks working folks around as hard as if not harder than the cost of living across most of our borders.
The C2ER index also looks only participating cities. In South Dakota, the only two participating areas are Sioux Falls and Pierre (come on, Rapid City! Fill out that questionnaire!). North Dakota sends data from Bismarck, Fargo, and Minot. Minnesota sends data from Minneapolis, St. Paul, Mankato, and St. Cloud. So if you’re going to argue that the C2ER data is biased toward the high costs in South Dakota’s big towns and leaves out our rural areas, you have to consider that (1) Pierre offers an interesting counter to economic trends in Sioux Falls and perhaps offering a useful proxy for isolated rural communities, and (2) the absence of really-small-town data should equally skew the numbers in North Dakota and Minnesota.