Income Inequality in Major US Metro Areas (I Dream of Gini)

I read a tweet this morning from Planetizen about a recent study by the Brookings Institution. Here are links to the Planetizen post and the Brookings post.

The Brookings Institute study is a clever bit of work. It uses data from the 2014 and 2016 American Community Survey data on household income distribution, for the 100 largest metropolitan areas (Metropolitan Statistical Areas, or MSAs), and their principal (largest) cities.

The measure of “income inequality” in the Brookings study is the ratio of the area’s household income at the 95th percentile (only 5% of the households make more than the 95th), to the household income at the area’s 20th percentile (20% of the household make less than that.)

This data is available from Table B19080 in the Census Bureau’s American FactFinder (AFF). What makes the Brookings study an extra chore (for them, at least) is that the Census Bureau puts a $250,000 cap on the 95th percentile for all data reported in the standard AFF tables. So, the Brookings people examined data from the 2016 ACS Public Use Microdata Sample (PUMS) to calculate a better estimate for about a dozen or so metro areas and their principal cities. That seems like a lot of work!

What puzzles me is why the Brookings Institute researchers didn’t use the most direct index of income inequality in use in the world, and as provided by the Census Bureau, the Gini Coefficient?

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Gimme (Affordable) Shelter (Part 4)

Continuing from yesterday’s blog post, today I look at the opposite extreme: the least housing cost burdened (“most affordable”) large cities in the USA in 2016.

To repeat from yesterday’s post, housing cost burden is calculated as the ratio of rent or mortgage/utilities paid relative to household income. Data is from the one-year 2016 American Community Survey, Tables B25070 and B25091. Here are the four categories of housing cost burden used in this analysis:

  • Low Burden: less than 15 percent of income spent on housing costs;
  • Moderate Burden: 15 to 29.9 percent of income spent on housing costs;
  • High Burden: 30.0 to 49.9 percent of income spent on housing costs; and
  • Severe Burden: 50.0 or more percent of income spend on housing costs.

For this blog post, I’ve further collapsed the burden categories into two:

  • Low-to-Moderate Burden (<30.0%); and
  • High-to-Severe Burden (>= 30.0%).

Low-to-Moderate Housing Cost Burden,  Large Cities, Population 65,000+ (2016)

The three largest cities with the highest high-to-severe housing cost burden are in the midwest:

  1. Carmel, Indiana (82.7% of household with low-to-moderate housing cost burden);
  2. Maple Grove, Minnesota (81.7%); and
  3. Troy, Michigan (81.6%).

Thirty (30) large places in the United States have a low-to-moderate housing cost burden for at least seventy-five percent (75%+) of their households.

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Gimme (Affordable) Shelter (Part 3)

I’m back after a few months respite from blogging!

Today I want to examine the year 2016 housing cost burden by large (65,000+ population) places in the United States. That’s data for 600 of the largest cities/places in the USA and Puerto Rico.

Housing cost burden is calculated as the ratio of rent or mortgage/utilities paid relative to household income. Data is from the one-year 2016 American Community Survey, Tables B25070 and B25091. Here are the four categories of housing cost burden used in this analysis:

  • Low Burden: less than 15 percent of income spent on housing costs;
  • Moderate Burden: 15 to 29.9 percent of income spent on housing costs;
  • High Burden: 30.0 to 49.9 percent of income spent on housing costs; and
  • Severe Burden: 50.0 or more percent of income spend on housing costs.

For this blog post, I’ve further collapsed the burden categories into two:

  • Low-to-Moderate Burden (<30.0%); and
  • High-to-Severe Burden (>= 30.0%).

High-to-Severe Housing Cost Burden,  Large Cities, Population 65,000+ (2016)

The three largest cities with the highest high-to-severe housing cost burden are in northeast New Jersey:

  1. Passaic, NJ (58.3% of households with high-to-severe housing cost burden);
  2. Newark, NJ (56.6%); and
  3. Elizabeth, NJ (55.6%)

Twenty one large places in the United States have a high-to-severe housing cost burden for at least fifty percent of their households.

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Gimme (Affordable) Shelter (Part 2)

Today’s question: What US congressional districts have the highest share of households with a severe housing cost burden? By “severe housing cost burden” I’m using the 50 percent-plus share of household income spent on monthly ownership or rental costs.

In the United States, 14.3 percent of households have a severe housing cost burden, as of 2016. The median household income in the United States was $57,617 in 2016. And the median monthly housing costs in the United States was $1,022 in 2016. The median annual housing costs (the monthly multiplied by 12!) is $12,264. (Data on median household income and median housing costs is from the Census Bureau’s American Factfinder, Table S25003.)

The top ten congressional districts with the highest share of households with severe housing cost burdens are all in New York City and Los Angeles City.

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Gimme (Affordable) Shelter (Part 1)

Housing affordability. It’s a really big and really important topic for all of us! This is my first post on this topic, and hopefully I’ll lay the foundation for subsequent posts on how housing affordability has changed over the years.

Housing affordability is typically based on the percentage of a household’s monthly income spent on housing costs. If the percentage exceeds a certain level, say, 30 percent, then that household has a moderate-to-severe “housing-cost burden.”

Housing costs are assessed based on the household’s tenure, that is, are they an owner-occupied household, or a renter occupied household.

Renter households have “Gross Rent” (GR). This includes contract rent plus utilities.

Owner households have “Selected Monthly Owner Costs” (SMOC). This includes mortgages, real estate taxes, utilities, and condo association fees. Oftentimes (but not always) the owner-occupied households are split into households-with-mortgages and households-without-mortgages. As you could imagine, there’s a significant difference in affordability for owner households with or without a mortgage!!

Why the 30 percent of income standard for housing affordability? It’s a relevant question, and there’s a comprehensive answer in a must read article on the Census Bureau’s website: “Who Can Afford to Live in a Home?: A look at data from the 2006 American Community Survey” by Mary Schwartz and Ellen Wilson of the US Census Bureau. The above link is to PDF document squirreled away on the Bureau’s web site. I can’t find a corresponding web page that refers to this important article! Oh well.

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How Big is the American Community Survey?

Really big! Over 49.9 million people have been surveyed in the American Community Survey over the past ten years, 2007-2016.

The American Community Survey (ACS) collected by the US Census Bureau is the replacement for the “long form census” conducted on April 1st of years ending in “0”. The last traditional “long form census” was in year 2000.

The American Community Survey was introduced to my professional community in the mid-1990s as the Continuous Measurement (CM) program. That name didn’t stick or click, and the Census Bureau renamed it the American Community Survey in the late 1990s.

The first, fully functional, nationwide implementation of the ACS was in 2005, though that year excluded group quarters (dormitories, prisons, hospitals, etc) persons. Group quarters were introduced in the 2006 ACS, so 2006 is sometimes considered the first year of full implementation. (If you’re just interested in household and housing characteristics, then don’t overlook the 2005 ACS!)

Well, is the ACS the same sample size, in general, as the older long form data?

Yes, if you look at ten years worth of ACS data.

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Health Insurance in the USA (Part 4)

The Census Bureau released data from the 2016 American Community Survey last week (September 12-14).

Here is the Bureau web page related to 2016 Health Insurance Coverage. The report P60-260 (pdf format) includes abundant information related to changes in health insurance status of the American population between 2008 and 2016. It is a must read in the current era of amending and/or repealing the US Affordable Care Act.

This blog post is an update to my June 17, 2017 post. That post used data from the 2015 American Community Survey. I’m updating this with data from the 2016 American Community Survey, Table GCT-2701.

(I’ll be out of the country for the next two weeks, exploring Mayan ruins and current cultures in Central America, so don’t expect blog posts in the near future!)

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