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The American racial patchwork

Measuring racial diversity across U.S. counties

The U.S. population is a patchwork of all sorts of immigrants and nationalities, which also translates into wide racial diversity. But the degree of diversity isn’t uniform across the country, which we can see if we examine the “racial dissimilarity index” shown on the map.” Here’s the story. The Census Bureau has data from the 3,241 U.S. counties that divide the population into White and Non-White, with a national average of 78% White and 22% Non-White. They create an index that basically depicts how diverse the racial distribution of the population is within each county: They determine the proportion of each group for each county and adjust each county’s score according to the share of its non-Hispanic White population that would have to move from one census tract in that county to another census tract to achieve uniformity across tracts. (Each census tract typically has a few thousand people.) This score appears to vary widely from county to county, showing that even neighboring counties can have very different racial landscapes. Also keep in mind that two counties could have essentially the same score but be mirror images of racial dissimilarity. Take Allamakee County, Iowa, and Bolivar County, Mississippi, for example. Their dissimilarity scores are very close (66.34 and 58.03), but their populations don’t look the same. The United States really is a patchwork.

How this map was created: The original post referenced an interactive map from our now discontinued GeoFRED site. The revised post provides a replacement map from FRED’s new mapping tool. To create FRED maps, go to the data series page in question and look for the green “VIEW MAP” button at the top right of the graph. See this post for instructions to edit a FRED map. Only series with a green map button can be mapped.

Suggested by Christian Zimmermann.

Poverty in America

An analysis of the difficulties of measuring poverty

This map shows, in some way, poverty across U.S. counties. We say “in some way” because poverty isn’t a well-defined or stationary object. Today’s poor in the U.S. could be rich in another country or in another century. So it’s important to understand what is measured when people talk about poverty rates.

The data shown here are based on the American Community Survey from the Census Bureau, which asks families about all their cash income (including social benefits, alimony, dividends, etc.) but before capital gains, non-cash benefits, and taxes. That income is then compared with a standard. The Census Bureau determines a threshold income that depends on the number of family members and that is adjusted for inflation. The map above is for 2015: At that point, the poverty threshold for a family of four with two children under 18 was $24,036. For a single person above 65, the threshold was $11,367. See this link for details.

The map shows the proportion of families in each county who fall below these thresholds. The highest incidence is in Jefferson County, Mississippi, with 48.7%. The lowest is 1.4% in Borden County, Texas. Does this mean that there is 35 times more poverty in Jefferson County than in Borden County? Not necessarily. First, this measure says nothing about the distribution of income below the threshold. Second, the measure does not take into account living expenses. Income in, say, Manhattan, New York, is treated the same as in, say, Harlingen, Texas. Finally, Borden County has a total population of 627. Measurement of poverty with small samples is extra difficult.

How to create this map: The original post referenced an interactive map from our now discontinued GeoFRED site. The revised post provides a replacement map from FRED’s new mapping tool. To create FRED maps, go to the data series page in question and look for the green “VIEW MAP” button at the top right of the graph. See this post for instructions to edit a FRED map. Only series with a green map button can be mapped.

Suggested by Christian Zimmermann.

Are we paying more taxes than before?

Reflections on the aggregate share of taxes in the nation's income

Tax season is upon us, at least for the procrastinators who haven’t filed yet. And filing a tax return may get you wondering if the tax burden just keeps increasing. While FRED can’t address your personal situation, it can look at the big picture. The graph shows aggregate U.S. federal tax receipts as a percentage of national income (GDP). Apart from the run-up during World War II, there’s no clear trend. Of course, income and population have steadily increased over this period and so have tax receipts, but they haven’t increased as a share of GDP.

Now, there are provisions in the tax code that could have led to steady increases in tax receipts. The progressivity of the tax rate is one: As income grows, one has to pay a larger share in taxes. But the thresholds for progressivity have been adjusted over time, thus negating the channel for an automatic tax revenue increase. On the other side, the thresholds for calculating the alternative minimum tax have been left largely unchanged for a long time. Introduced in 1969, when they were applicable to only 155 tax payers, the AMT now applies to several million tax payers. Since 2012, the AMT has been indexed to inflation (but not to general income growth); thus, the effect on the aggregate tax share is supposed to lessen. So what prevented the aggregate tax share from increasing over several decades? Was it more-generous deductions, less progressivity, more exclusions…? These questions are too taxing to answer in this blog post.

How this graph was created: Search for “federal receipts” and click on the series you want displayed.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: FYFRGDA188S


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