In the ongoing effort to view everything geographically, I couldn’t help thinking about how to visualize the proposed tax “cuts” that the House passed last Friday. Paul Krugman’s Thursday article had a link to the data I needed — Congress’s Joint Committee on Taxation’s analysis of the bill’s impact on different incomes. It’s a bit of a stretch, but combined with county data on median household income (last 12 months based on 2015 Census data), the data allows a look at the geographic impact of the bill across the US and through the life of the bill from 2019 to 2027. Note: these maps show changing tax rates for the median household income for each county — they don’t represent rate changes for all income brackets within a given county.

Here’s a quick look and comments for 2019 and 2027 (click on for full size):

The 2019 shows tax breaks for all median incomes across the contiguous 48 states — as promised by Republicans. The breaks are smaller for poorer counties visible across the Appalachians, the rural South, and a spattering of western counties. The “bait” of the tax breaks is real, but — interestingly — is least impactful for many of the poorer regions that voted for Trump. Many of the tax breaks for families are temporary, though, and along with changes in the inflation measure, lead to a substantial “switch” after 2022. By 2023, the average tax rate change for median household incomes looks like this:

Less of a tax break for most median households and some increases for counties with lower median household incomes. By 2027, most median households see a tax increase on par with the earlier breaks:

Only a few of the wealthier counties in the country are projected to have median incomes high enough for most of them to still be receiving tax breaks. Most poorer- and middle-income counties will experience higher taxes.

Interactive version with rates for each two-year period:

Methods and details: First, the county boundaries were combined with media household income data to yield a map of median household income across the country:

Next, the change in rates were calculated from each biennial table within the JCT report (example for 2019):

Rate changes for each county and year were assigned based on the county’s median income.


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