# The Cheapest State

There have been a lot of attempts to rank the 50 states by affordability, and different methodologies have come up with different answers for which state is the cheapest (Mississippi, Iowa, West Virginia). As enticing as it may be to come up with one definitive answer for the cheapest state to live in, the usefulness of these rankings is a bit dubious. Moving to Mississippi will not necessarily improve your financial situation.

In reality, the “cheapest” state for a person to live in depends on their family size, their occupation, and their financial goals. To illustrate this point, let’s consider a few examples.

Tom is a single middle school teacher without any kids. Rather than save up his leftover income after paying for his living expenses, he wants to put his money toward living in a nicer house. The “cheapest” state for Tom is going to be the one where his basic living expenses make up the lowest percentage of his overall salary. To estimate the percent of Tom’s annual income that would go toward living expenses in a given state, we take the typical annual living expenses for a single adult in that state, divide it by the average annual salary for middle school teachers in that state, and multiply the result by 100 to get a percent (percent of income used on living expenses = (living expenses/income)*100). For example, in Idaho, the typical annual living expenses for a single adult are $34,348, and the average annual salary for middle school teachers is $53,060. So, the percent of a middle school teacher’s income that would go toward living expenses is ($34,348/$53,060)*100 = 64.7%. When we do this calculation for all 50 states, we find that the “cheapest” state for single middle school teachers who want to use their leftover income on better living conditions is Michigan (where only 50.9% of their income would go toward living expenses), and the most “expensive” state is Arizona (where 85% of their income would go toward living expenses).

Next let’s consider Maria, a married mechanical engineer with 3 kids. Maria’s husband does not work, and her goal is to maximize retirement savings after paying her family’s living expenses. The “cheapest” state for Maria is going to be the one where she has the most leftover savings after paying for her family’s basic living expenses. To estimate Maria’s leftover savings in a given state, we take the average annual salary for a mechanical engineer in that state and we subtract the typical annual expenses for a household with 2 adults and 3 children (leftover savings = income – living expenses). For example, in Tennessee, the average annual salary for mechanical engineers is $87,390, and the typical annual living expenses for a household with 2 adults and 3 children is $86,322. So, the leftover savings for a mechanical engineer with a spouse and 3 children is $87,390 - $86,322 = $1,068. When we do this calculation for all 50 states, we find that the “cheapest” state for married mechanical engineers with 3 children who want to save their leftover income is New Mexico (where their leftover savings would be $21,381), and the most “expensive” state is Hawaii (where their family’s living expenses would exceed their income by $62,655).

Finally, let’s consider Sayid and Sara, a married couple with 2 children. Sayid works as a dentist, and Sara works as a web developer. They, like Maria, want to save up all of their leftover income after paying for their family’s living expenses. To estimate Sayid and Sara’s leftover savings in a given state, we take the sum of the average annual salary for a dentist and the average annual salary for a web developer in that state and we subtract the typical annual expenses for a household with 2 adults and 2 children (leftover savings = (income1 + income2) – living expenses). For example, in Maine, the average annual salary for dentists is $179,920, the average annual salary for web developers is $62,390, and the typical annual living expenses for a household with 2 adults and 3 children is $97,454. So, the leftover savings for a dentist and a web developer with 2 children is ($179,920 + $62,390) - $97,454 = $144,856. When we do this calculation for all 50 states, we find that the “cheapest” state for a family made up of a dentist, a web developer, and 2 kids that wants to save its leftover income is Delaware (where its leftover savings would be $222,643), and the most “expensive” state is Louisiana (where its leftover savings would be $85,494).

Use the visualization below to find your own “cheapest” state based on your family size, your profession, and your financial goals. Keep in mind that while both the “percent of income” method and the “leftover savings” method account for how family size and profession change cost of living comparisons across states, they measure slightly different things. Use the leftover savings method if your goal is to maximize the amount of money you can save after living expenses. Use the percent of income method if you want to get the most bang for your buck spending your excess income on things other than basic living expenses. The percent of income method accounts for the fact that $5,000 of excess income goes further in a state like Wyoming than in a state like New York. Under the leftover savings method, two states with the same excess income would get the same rank. Under the percent expenses method, if two states had the same excess income, the state with lower living expenses would be ranked as less expensive than the state with higher living expenses.

The typical annual living expenses estimates for this visualization come from the Economic Policy Institute’s Family Budget Fact Sheets. These estimates factor in the cost of housing, food, childcare, transportation, health care, other necessities, and taxes. This data has estimates by county. To get state-level estimates, I calculated a weighted mean for each state based on the population of each county in the state. The average annual salaries for this visualization come from the U.S. Bureau of Labor Statistics. All the data for this visualization is based on values from the year 2017.

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