In virtually every major urban real estate market, a major determinant of rent and housing prices is accessibility. If you live in a dense, walkable urban neighborhood, you might manage to live quite comfortably not owning a car, or having just one car for a two-worker family. If you live on the exurban edge, in a low-density subdivision, you might need to own multiple cars just to manage the daily chores of school, shopping and play, as well as commuting to work. It turns out that the value of accessibility gets priced in to the cost of walkable, well-located housing; and conversely, rental and for-sale housing that’s located at a distance from everything is priced at a discount to the market.

What this means as a practical matter that you can’t judge whether an individual household’s living situation is affordable just by looking at whether they spend less than 30 percent of their income directly on housing. Consider this example: two otherwise identical households. One lives in a suburb, owns two cars, and drives most places. They spend 30 percent of their income on housing and 20 percent of their income on transportation. The second household lives in a city and owns one car. Their house is more expensive than the suburban one, so they spend 40 percent of their income on housing, and just 10 percent on transportation. Is it really accurate to describe the second (city) household as any more “cost-burdened” than its suburban peer?

This is the essential insight behind the Center for Neighborhood Technology’s “H+T” Housing and Transportation Index, which quantifies the approximate costs associated with housing and transportation in different neighborhoods. They’ve used census data on income and housing costs, and estimates of commuting patterns, transit available and car ownership to estimate what fraction of a household’s income gets spent on housing and transportation in different locations. They show that some neighborhoods with high housing costs are actually more affordable than lower rent areas, once you add in the savings in transportation costs.

A recent report from the Joint Center on Housing Studies at Harvard shines a slightly different light on this question, by revealing differences in spending patterns among households. This report examines data from the Bureau of Labor Statistics Consumer Expenditure Survey, which is constructed from spending diaries completed by a random sample of American households. We’ve taken their analysis from Table W-6, and reformatted it slightly, computing the share of total spending on housing and transportation for each income group. We’ve also truncated the table to exclude a detailed breakout of other types of spending (food, apparel, etc).





