Update: For an additional map that breaks the data down by metropolitan statistical areas, click here.

This week’s tax map shows the real value of $100 in each state. Because average prices for similar goods are much higher in California or New York than in Mississippi or South Dakota, the same amount of dollars will buy you comparatively less in the high-price states, or comparatively more in low-price states. Using data from the Bureau of Economic Analysis that we’ve written about previously, we adjust the value of $100 to reflect how prices are different in each state.

For example, Tennessee is a low-price state, where $100 will buy what would cost $110.25 in another state that is closer to the national average. You can think of this as meaning that Tennesseans are about ten percent richer than their nominal incomes suggest.

The states where $100 is worth the least are the District of Columbia ($84.60), Hawaii ($85.32), New York ($86.66), New Jersey ($87.64), and California ($88.57). That same money goes the furthest in Mississippi ($115.74), Arkansas ($114.16), Missouri ($113.51), Alabama (113.51), and South Dakota ($113.38).

Regional price differences are strikingly large, and have serious policy implications. The same amount of dollars are worth almost 40 percent more in Mississippi than in DC, and the differences become even larger if metro area prices are considered instead of statewide averages. A person who makes $40,000 a year after tax in Kentucky would need to have after-tax earnings of $53,000 in Washington, DC just in order to have an equal standard of living, let alone feel richer.

As it happens, states with high incomes tend to have high price levels. This is hardly surprising, as both high incomes and high prices can correlate with high levels of economic activity. However, this relationship isn’t strictly linear: for example, some states, like North Dakota, have high incomes without high prices. Adjusting for prices can substantially change our perceptions of which states are truly poor or rich.

As we showed in an example in our recent paper on income data, adjusting for prices reveals average real incomes in Kansas to be higher than in New York, despite New York having much higher incomes as measured in dollars.

The tax policy consequences of this data are significant. For example, because taxes must be calculated based on nominal income, the average New York resident pays significantly more in taxes than the average Kansas resident. But the Kansas resident actually has higher purchasing power, meaning that they get to pay lower taxes despite getting to have a richer amount of consumption.

Furthermore, this affects means-tested federal welfare programs. A poor person in a high cost area – like Brooklyn or Queens – may be artificially boosted out of the range of income where they are eligible for welfare programs, despite still being very poor. At the same time, many people in low-price states may be eligible for welfare programs despite actually being much richer than they appear. If the same dollar value program is offered in New York City and rural South Dakota, it may be too small to help anyone in New York City, and yet so big it discourages work in South Dakota.

We’ve explained elsewhere how taxes have a role to play in urban gentrification, which in turn increases the cost of living and the local price level. As we also pointed out when the BEA data was first released, adjusting state incomes for price levels helps solve several statistical problems related to taxes and migration as well.

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