Over the past decade, housing costs in the U.S. have risen faster than average incomes. While housing affordability has long been a problem for low-income families, middle-income families are increasingly facing affordability challenges, especially in urban areas with strong labor markets. When housing costs rise, households can respond by adjusting their consumption; for instance, living in smaller spaces or moving farther from city centers. In this paper, I examine middle-class housing stress along four dimensions: affordability, inadequate space, commute times, and homeownership. Using household-level data from the Census Bureau’s Individual Public Use Microdata Sample (IPUMS), I explore how housing stresses vary by income, household type, race, and geography. Results show that, on average, middle-income families are doing well on all four dimensions. However, distinct population groups show stress on several metrics, including affordability, crowding, long commute times, and access to homeownership.

1. Housing can enhance well-being or create distress through several channels.

2. Lower-middle-income households are stretching to afford housing.

If we group households in all three middle income quintiles together, renter households spend just under 30 percent of their income on housing costs. Middle-income homeowners spend 25 percent.[3] These numbers vary considerably across income quintiles, as shown in Figure 2, and to a smaller degree by household type, race, and geography. Housing costs take up a larger share of income for poor and lower-middle-income households than for more affluent households (Figure 2). Most households in the third income quintile spend under 30 percent on income on housing, while households in the fourth quintile spend less than 20 percent. But lower-middle income households (second quintile) spend nearly 40 percent of income on housing, while the poorest households spend on average more than 60 percent. Within income quintiles, housing accounts for similar income shares for both homeowners and renters. While income is the main factor that affects how much households spend on housing, there is some variation by household type, race, and geography (Figure 3). Within each income quintile, families with children spend more of their income on housing than households without children.[4] Asian households have higher housing expenses than white, black, or Hispanic households.[5] Nearly 70 percent of Asian households live in the highest-priced housing markets, compared to forty percent of non-Asian households. Housing costs make up a larger share of income in more expensive metros for all income quintiles. For instance, households in San Francisco spend more on housing than in the other three metros.

3. Middle-income households occupy plenty of space – with one important exception.

Middle-income households occupy homes with an average of one person per bedroom – half the threshold for crowding. The average number of people per bedroom varies somewhat across income quintiles, but more by house price levels in the metropolitan area. Of course, the number of bedrooms is not a perfect measure of space: square footage of housing units with the same bedroom count can vary widely across neighborhoods and cities. The top panel of Figure 4 shows persons per bedroom, with metros divided into quartiles by housing values (1 is the least expensive, 4 is the most expensive). Households of all incomes living in the lowest cost metros have about one person per bedroom. For households living in the most expensive metros, all three income quintiles have slightly more than one person per bedroom. The pattern is even more notable when we look at the share of crowded households (more than two people per bedroom). The lower panel of Figure 4 shows the share of households with more than two persons per bedroom, by metro price tier and income quintile. About three percent of all middle-income households across the U.S. are crowded, but nearly six percent of households in the most expensive metros are crowded. Almost nine percent of lower-middle income households in the most expensive metros are crowded. The amount of space consumed per person is mostly a function of household type: crowding is most acute for families with children. The top panel of Figure 5 shows the frequency of crowding by household type and metro housing prices. Five percent of families with children in the cheapest metros are crowded, rising to about 14 percent of families in the most expensive metros. Crowding is extremely rare among childless households both under and over age 40. One possible explanation is that the size of most housing units is too small to accommodate families. To examine this hypothesis, the lower panel of Figure 5 shows the frequency of “excess” space, defined as households who have fewer than one person per bedroom (e.g. a married couple living in a house with three or more bedrooms). Excess space is much more common than crowding in all price tiers and for most household types. Nationally, more than one in three households has excess space, even in high-priced metros. Childless households over age 40 are the most likely to have excess space; many of these households may be empty nesters who have not downsized after their children left home. For a broader picture of how common crowding is among families with children across the U.S., we can map the relative frequency for the largest 100 metro areas (Figure 6). Crowding is most common among metros in California and Texas. The metros along California’s coast - San Francisco, Los Angeles, San Diego, and Santa Barbara – have some of the highest housing values nationwide, as do other outliers like New York. But the highly crowded metros also include relatively inexpensive markets with high poverty rates, such as McAllen, TX, and Fresno, CA.

4. Long commutes are more common in expensive housing markets

Most middle-income households have commute times close to the national average of 27 minutes. Average commute times vary relatively little by income or household type. Commute times – and especially the frequency of very long commutes – vary substantially by metropolitan area housing prices (Figure 7). Households of all incomes have on average 8 minute longer commutes in the most expensive metros compared to the least expensive metros (top panel of Figure 7).[6] Very long commutes (more than one hour each way) are also more common in expensive metros (lower panel of Figure 7).[7] Only four percent of households in the cheapest metros have hour-long commutes, while more than 10 percent of households in expensive metros commute that long. Differences across metros are much larger than within-metro differences by income or household characteristics.[8] To see geographic patterns in the frequency of hour-long commutes, I mapped the share of households with long commutes across the 100 largest metros (Figure 8). Long commutes are especially prevalent along the Northeast corridor from Washington DC to Boston and in California. Chicago and Atlanta also have very high shares of households with long commutes. There is some overlap between metros with high crowding and long commutes; the correlation between the two metrics is about 0.45.

5. Income, age, and race limit access to homeownership.

Consistent with prior research, the probability of owning one’s home increases with income (Figure 9). More than 70 percent of households in the 4th income quintile are homeowners, compared to 40 percent of lower-middle-income households. Within income quintiles, homeownership rates vary substantially by household type (Figure 10, upper left). Childless households over 40 are the most likely to own their homes, with childless households under 40 the least likely. Families with children are about equally distributed by age, and are more likely to be homeowners than equivalent age households without children. Homeownership rates also vary by race and geography. Black and Hispanic households are least likely to own their homes, with largest gaps in the second income quintile. Black households in the middle income quintile are in fact slightly less likely to own their home than white households in the income quintile below. Homeownership rates for all income quintiles are lower in the most expensive metro areas, like San Francisco; high housing prices make downpayments a substantially larger hurdles in expensive metros. Households in the fourth income quintile in San Francisco are about as likely to own their homes as third quintile households in the other three metros – even though absolute incomes are much higher in San Francisco.

6. Discussion and policy implications