Taking it to the House: Our Most Popular Blogs of 2017

by David Luberoff, Deputy Director

As we turn the calendar to 2018, we took a moment to look back at the past year to see what were the most popular articles in our Housing Perspectives blog.  

The top five articles of 2017 were:

1. When Do Renters Behave Like Homeowners?
   In high-housing cost cities, renters and homeowners both oppose new residential developments proposed for their neighborhoods. (Written by Michael Hankinson, a Joint Center Meyer Doctoral Fellow)


2. Wait... What? Ten Surprising Findings from the 2017 State of the Nation’s Housing Report
   There were a number of surprises in our annual report, including the fact that fewer homes were built over the last 10 years than any 10-year period in recent history and that the homeownership gap between whites and African-Americans widened to its largest disparity since WWII. (Written by Daniel McCue, a Senior Research Associate at the Joint Center)


3. Are Home Prices Really Above Their Pre-Recession Peak?
   While nominal home prices were above their mid-2000s heights in 48 percent of the nation’s 951 local markets, in real dollars, prices reached their peaks in only 15 percent of those markets. (Written by Alexander Hermann, a Research Assistant at the Joint Center)


4. Projection: US Will Add 25 Million Households by 2035
   Revising previous estimates, the Joint Center now predicts that the United States will add 13.6 million households between 2015 and 2025, and another 11.5 million households between 2025 and 2035. (Also written by Daniel McCue)


5. Our Disappearing Supply of Low-Cost Rental Housing
   The number of units renting for $2,000 or more per month (in constant, inflation-adjusted dollars) nearly doubled between 2005 and 2015, while the number of units renting for below $800 fell by 2 percent. (Written by Elizabeth La Jeunesse, a Joint Center Research Analyst)

A Shared Future: Fostering Communities of Inclusion in an Era of Inequality

by Jonathan Spader and
Shannon Rieger

Almost 50 years after the passage of the Fair Housing Act, what would it take to meaningfully reduce residential segregation and/or mitigate its negative consequences in the United States?

Over the next several months, the Joint Center for Housing Studies will publish working papers on various aspects of this question written by a diverse set of scholars, policymakers, and practitioners. The papers will be available on our website and will also be collected into an edited volume to be published next year. The papers were presented at a two-day symposium, A Shared Future: Fostering Communities of Inclusion in an Era of Inequality, that was convened by the Joint Center earlier this year.

At the symposium's seven thematically-focused panels, the authors took stock of the changing patterns of residential segregation by race/ethnicity and income, and examined concrete steps that could achieve meaningful improvements within the next 10-to-15 years. On a monthly basis from this fall until next summer, we will publish those papers on a panel-by-panel basis, along with a series of blogs, many of them by others who attended the symposium, that further engage with the event's central question.

This process begins today with the publication of our framing paper for the symposium, which summarizes existing evidence on three topics: the current patterns of residential segregation by race/ethnicity and income, the causes of residential segregation in the United States, and the consequences for individuals and society. The paper also examines the rationale for government action in these areas as well as the key levers that policymakers could use to change the current situation. Because each of these topics is the subject of a larger and longstanding research literature, our summary is not exhaustive. Rather, we seek to provide a concise overview of existing research, so that the papers which follow can focus on potential solutions.

Our discussion of these topics is a reminder of both what has been accomplished since the passage of the Fair Housing Act (technically Title VII of the Civil Rights Act of 1968) half a century ago and also how far the US remains from the aspirations put forth when it became law. In particular, we note that while the extent and nature of discrimination have changed int he last five decades, the legacies of historical segregation and exclusion by government, private institutions, and individuals have continued to produce stark and stubborn patterns of racial segregation in US metropolitan areas.

At the same time, we note that changes in demography, income distribution, and the geography of American communities are changing the patterns of residential segregation by income and race/ethnicity. The bursting of the housing bubble and the Great Recession exacerbated distress among poor communities—particularly poor communities of color. In many metropolitan regions, job growth in central cities, improved neighborhood amenities, and increased demand for urban living have also fostered rapid increases in housing costs in longstanding low-income and minority communities located in or near those regions' urban cores. While gentrification has been one of the most visible signs of these changes, the suburbanization of lower-income households and the growing self-segregation of high-income households into wealthy enclaves are equally consequential.

The framing paper also documents the severe costs of this separation for all members of society, as well as the disproportionate burdens imposed on residents of neighborhoods with concentrated disadvantage. Residents of such neighborhoods—who are most often members of minority racial and ethnic groups—face elevated risks to their health, safety, and economic mobility. Moreover, at a national scale, there is compelling evidence that these individual costs constrain the economy from reaching its full potential while also increasing levels of prejudice and mistrust within the populace and impairing the functioning of our democracy. These costs, along with the potential benefits of greater integration, highlight the need for continued attention and innovation to these challenges.

The symposium papers, which will be released over the next few months, will present multiple perspectives about how we might address these challenges. Our hope is that they will raise questions, spur discussions, and ultimately contribute to forward progress.

Are Integrated Neighborhoods Becoming More Common in the United States?

by Jonathan Spader and
Shannon Rieger

The share of the population living in racially and ethnically integrated neighborhoods in the US has increased since 2000, according to our new Joint Center research brief. However, most Americans continue to live in non-integrated neighborhoods, and evidence suggests that some of the recent increases in integration may be the temporary byproduct of gentrification and displacement.

The new brief, "Patterns and Trends of Residential Integration in the United States Since 2000," assesses whether the nation's increasingly diverse population is fostering the growth of integrated neighborhoods or whether the choices people make about where to live are reinforcing existing lines of segregation and exclusion. Specifically, we use data from the 2000 Census and the 2011-15 American Community Survey (the most recent data available at the census tract level) to describe the number, stability, and characteristics of integrated neighborhoods.

Because there is no single measure for identifying integrated neighborhoods, our analyses applies two commonly-used definitions to define integration. The first approach—which we refer to as "no-majority neighborhoods"—defines integrated neighborhoods as those where no racial or ethnic group accounts for 50 percent or more of the population. While this definition identifies neighborhoods with a plurality of races and ethnicities, it may exclude some neighborhoods with relatively high levels of integration relative to the median neighborhood in the United States. For example, under this definition, a census tract that is 49 percent black and 51 percent white would be classified as non-integrated.

The second definition—which we refer to as "shared neighborhoods"—uses a broader definition of integration, identifying neighborhoods as integrated if any community of color accounts for at least 20 percent of the tract population AND if the tract is at least 20 percent white. While this definition might be expanded to include neighborhoods in which any two groups account for at least 20 percent of the tract's population, this definition requires that the neighborhood population be at least 20 percent white because of whites' long history of exclusionary practices as well as attitudinal surveys suggesting that, on average, whites are less willing that other groups to live in integrated neighborhoods.

Both definitions suggest that the number of integrated neighborhoods—and the share of the US population living in integrated neighborhoods—increased between 2000 and 2011-15 (a time when the white, non-Hispanic share of the population fell from 69.1 percent to 62.3 percent). The number of "no-majority neighborhoods" increased from 5,423 census tract in 2000 to 8,378 in 2011-15, and the share of the US population residing in such tracts increased from 8.0 percent in 2000 to 12.6 percent in 2011-15 (Figure 1).

Similarly, the number of "shared neighborhoods" increased from 16,862 tracts in 2000 to 21,104 tracts in 2011-15, and the share of the US population residing in "shared" tracts increased from 23.9 percent in 2000 to 30.3 percent in 2011-15. These figures are higher than the estimates for "no-majority" tracts, reflecting the broader definition of integration used to define "shared neighborhoods." Nonetheless, both definitions show increases in integration between the 2000 Census and the 2011-15 ACS.

Notes: "No-majority neighborhoods" are census tracts in which no racial or ethnic group accounts for 50 percent or more of the population. "Share d neighborhoods" are census tracts in which whites account for 20 percent or more of the population and any community of color accounts for 20 percent or more of the population. 
N=71,806 Census tracts.

While the share of the population living in integrated neighborhoods has increased since 2000, most Americans continue to live in non-integrated areas, with white individuals the least likely to live in integrated areas. While 12.6 percent of the total US population lives in one of the 8,378 "no-majority" tracts, these neighborhoods include just 7.2 percent of the nation's whites, compared to 20.3 percent of blacks, 20.3 percent of Hispanics, 30.9 percent of Asians, and 19.5 percent of individuals of other races and ethnicities (Figure 2).

A similar pattern is present within "shared neighborhoods." While 30.3 percent of the total US population lives in one of the 21,104 "shared neighborhoods," these neighborhoods include just 22.9 percent of the nation's whites, compared to 43.0 percent of blacks, 42.8 percent of Hispanics, 44.8 percent of Asians, and 36.5 percent of individuals of other races and ethnicities.

Note: Estimates show the percent of each group that live in integrated neighborhoods. White, black, Asian, and Other are non-Hispanic.

The research brief provides more specific details about the relative composition of integrated and non-integrated neighborhoods by race, ethnicity, and other demographic characteristics. Additionally, it describes the stability of integrated neighborhoods between 2000 and 2011-15, as well as the geographic distribution of integrated neighborhoods across central cities, suburbs, and non-metropolitan areas.

Taken together, this evidence offers support for the conclusion that the number of integrated neighborhoods has increased in recent years. However, it also highlights that this conclusion is subject to two important caveats. First, some portion of the increase in integration reflects neighborhood change processes associated with the gentrification and displacement pressures affecting the central areas of many cities. While some of these neighborhoods may become stably integrated areas, it is not yet clear how many of the newly integrated neighborhoods will become stably integrated and how many will eventually become non-integrated areas.

Second, integrated neighborhoods remain the exception rather than the rule in the United States. The 2011-15 ACS shows that fewer than one in three Americans lives in a shared neighborhood, with just 12.6 percent living in "no-majority neighborhoods." As the country moves toward a population in which people of color are projected to be a majority by the middle of the century, further growth will be necessary for such changes to produce a more inclusive society.

Growing Demand and Tight Supply are Lifting Home Prices and Rents, Fueling Concerns about Housing Affordability

A decade after the onset of the Great Recession, the national housing market has, by many measures, returned to normal, according to the 2017 State of the Nation’s Housing report, being released today by live webcast from the National League of Cities. Housing demand, home prices, and construction volumes are all on the rise, and the number of distressed homeowners has fallen sharply. However, along with strengthening demand, extremely tight supplies of both for-sale and for-rent homes are pushing up housing costs and adding to ongoing concerns about affordability (map + data tables). At last count in 2015, the report notes, nearly 19 million US households paid more than half of their incomes for housing (map + data tables).

National home prices hit an important milestone in 2016, finally surpassing the pre-recession peak. Drawing on newly available metro-level data, the Harvard researchers found that nominal prices in real prices were up last year in 97 of the nation’s 100 largest metropolitan areas. At the same time, though, the longer-term gains varied widely across the country, with some markets experiencing home price appreciation of more than 50 percent since 2000, while others posted only modest gains or even declines. These differences have added to the already substantial gap between home prices in the nation’s most and least expensive housing markets (map).

“While the recovery in home prices reflects a welcome pickup in demand, it is also being driven by very tight supply,” says Chris Herbert, the Center’s managing director. Even after seven straight years of  construction growth, the US added less new housing over the last decade than in any other ten-year period going back to at least the 1970s. The rebound in single-family construction has been particularly weak. According to Herbert, “Any excess housing that may have been built during the boom years has been absorbed, and a stronger supply response is going to be needed to keep pace with demand—particularly for moderately priced homes.”

Meanwhile, the national homeownership rate appears to be leveling off. Last year’s growth in homeowners was the largest increase since 2006, and early indications are that homebuying activity continued to gain traction in 2017. “Although the homeownership rate did edge down again in 2016, the decline was the smallest in years. We may be finding the bottom,” says Daniel McCue, a senior research associate at the Center.

Affordability is, of course, key. The report finds that, on average, 45 percent of renters in the nation’s metro areas could afford the monthly payments on a median-priced home in their market area. But in several high-cost metros of the Pacific Coast, Florida, and the Northeast, that share is under 25 percent. Among other factors, the future of US homeownership depends on broadening the access to mortgage financing, which remains restricted primarily to those with pristine credit.

Despite a strong rebound in multifamily construction in recent years, the rental vacancy rate hit a 30-year low in 2016. As a result, rent increases continued to outpace inflation in most markets last year. Although rent growth did slow in a few large metros—notably San Francisco and New York—there is little evidence that additions to rental supply are outstripping demand. In contrast, with most new construction at the high end and ongoing losses at the low end (interactive chart), there is a growing mismatch between the rental stock and growing demand from low- and moderate-income households.

Income growth did, however, pick up last year, reducing the number of US households paying more than 30 percent of income for housing—the standard measure of affordability—for the fifth straight year. But coming on the heels of substantial increases during the housing boom and bust, the number of households with housing cost burdens remains much higher today than at the start of last decade. Moreover, almost all of the improvement has been on the owner side. “The problem is most acute for renters. More than 11 million renter households paid more than half their incomes for housing in 2015, leaving little room to pay for life’s other necessities,” says Herbert.

Looking at the decade ahead, the report notes that as the members of the millennial generation move into their late 20s and early 30s, the demand for both rental housing and entry-level homeownership is set to soar. The most racially and ethnically diverse generation in the nation’s history, these young households will propel demand for a broad range of housing in cities, suburbs, and beyond. The baby-boom generation will also continue to play a strong role in housing markets, driving up investment in both existing and new homes to meet their changing needs as they age. “Meeting this growing and diverse demand will require concerted efforts by the public, private, and nonprofit sectors to expand the range of housing options available,” says McCue.

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Live Webcast Today @ Noon ET

Tune into today's live webcast from the National League of Cities in Washington, DC, featuring:

Kriston Capps, Staff Writer, CityLab (panel moderator)
Chris Herbert, Managing Director, Joint Center for Housing Studies
Robert C. Kettler, Chairman & CEO, Kettler
Terri Ludwig, President & CEO, Enterprise Community Partners
Mayor Catherine E. Pugh, City of Baltimore, Maryland

Tweet questions & join the conversation on Twitter with #harvardhousingreport

New Report: Aging Homeowners Drive Growth in Remodeling as Millennials Begin to Gain Footing

Homeowner spending on remodeling is expected to see healthy growth through 2025, according to Demographic Change and the Remodeling Outlook, the latest biennial report in our Improving America’s Housing series. Demographically based projections suggest that older owners will account for the majority of spending gains over the coming years as they adapt their homes to changing accessibility needs. Although slower to move into homeownership than previous generations, millennials are poised to enter the remodeling market in greater force, buying up older, more affordable homes in need of renovations.

The residential remodeling market includes spending on improvements and repairs by both homeowners and rental property owners, and reached an all-time high of $340 billion in 2015, surpassing the prior peak in 2007. [See our Interactive Infographic.] Spending by owners on improvements is expected to increase 2.0 percent per year on average through 2025 after adjusting for inflation, just below the pace of growth posted over the past two decades, and about on par with expected growth in the broader economy.

The large baby boom generation has led home improvement spending for the past twenty years, and its influence shows no signs of waning. Older homeowners will continue to dominate the remodeling market, as they make investments to age in place safely and comfortably. Expenditures by homeowners age 55 and over are expected to grow by nearly 33 percent by 2025, accounting for more than three-quarters of total gains over the decade. The share of market spending by homeowners age 55 and over is projected to reach 56 percent by 2025, up from only 31 percent in 2005.

Gen-Xers are now in their prime remodeling years, and while some are still recovering from home equity losses after the housing crash, many in this generation will undertake discretionary projects deferred during the downturn. And as younger households move into homeownership, they will supplement the already thriving improvement market.

Try the Interactive Infographic

“With national house prices rising sufficiently to help owners rebuild home equity lost during the downturn, and with both household incomes and existing home sales on the rise, we expect to see continued growth in the home improvement market,” says Kermit Baker, director of the Remodeling Futures Program at the Joint Center for Housing Studies.

Even though increasing house prices are encouraging homeowners to reinvest in their homes, they also are raising housing affordability concerns among younger buyers. Climbing mortgage interest rates and rising house prices not only make homeownership more difficult for younger households, but leave those who are able to buy with fewer resources to make improvements and repairs. And while high rents may provide an incentive to buy homes, they also make it difficult for first-time buyers to save for a downpayment.

Some demographic trends are also presenting challenges to a healthier remodeling market outlook. A disproportionate share of growth over the coming decade will be among older owners, minority owners, and households without young children; groups that traditionally spend less on home improvements.

“Despite these challenges, the remodeling industry should see numerous growth opportunities over the next decade,” says Chris Herbert, managing director of the Joint Center for Housing Studies. “Strong demand for rental housing has opened up that segment to a new wave of capital investment, and the shortage of affordable housing in much of the country makes the stock of older homes an attractive option for buyers willing to in invest in upgrades.”

Finally, as a new generation of homeowners enters the remodeling market, specialty niches focused on energy-efficiency, environmental sustainability, and healthy homes are likely to see significant growth. Home automation—encompassing everything from entertainment systems to home energy management, lighting, appliance control, and security—is also emerging as a strong growth market, particularly among younger households.

Looking ahead, there are several opportunities for further growth in the remodeling industry. The retiring baby boom generation is already boosting demand for accessibility improvements that will enable owners to remain safely in their homes as they age. Additionally, growing environmental awareness holds out promise that sustainable home improvements and energy-efficienct upgrades will continue to be among the fastest growing market segments.

Read the full report, try the Interactive Infographic, or join the conversation on Twitter with #HarvardRemodeling.

Defining the Generations Redux

by George Masnick
Senior Research Fellow

How should we define the baby boom, Generation X, and the millennial generation?

In a Joint Center blog published in 2012, I argued that using 20-year age spans for each generation would make it easier to compare them. Since many researchers still use generational definitions that span different and inconsistent age ranges, particularly for millennials, it is perhaps timely to reframe and restate my case.

In keeping with my recommendations, the Joint Center has long identified the cohort born between 1945 and 1964 as baby boomers.Those born between 1965 and 1984 are Generation X, and the cohort born between 1985 and 2004 are millennials (Figure 1). 

However, other analysts use several different earlier dates to usher in the millennial generation, apparently because they want to ensure that the oldest member of this cohort were considered adults at the dawn of the new millennium (i.e. they had turned 18 or 20 in the year 2000). This definition meant that by 2015, the oldest millennials were in their mid-30s, old enough to prompt compelling stories about how many 30-somethings were still living with parents, living in cities, forsaking marriage and childbearing, and delaying homeownership. In contrast, under my recommended cut-off dates, the oldest millennials turned age 20 in 2005 and didn’t start entering their 30s until 2015.

Besides making it easier to compare generations, there are several reasons why the millennial generation should start with those born in 1985 and turning 20 in 2005. As I noted in my 2012 blog, 1985 was the year that U.S. births once again exceeded 3.7 million, the approximate number that demarcated the beginning and the end of the baby boom, as well as the beginning and the end of the “baby bust” that defines Generation X.

Three other big changes occurred shortly after 2005 that significantly altered the way young adults live. First, social media participation skyrocketed. Facebook became available to everyone age 13 and older with a valid e-mail address in September 2006. Twitter became public in 2006. The first iPhone was released in June of 2007. As a result of these and other changes, the share of adults using social media rose from five percent in 2005 to 69 percent in 2016, according to a recent Pew Research publication.

Second, student loan debt outstanding more than tripled between 2005 and 2016, rising from $400 billion to over $1.3 trillion. This high level of debt is thought to affect everything from leaving the parental home, to getting married and starting a family, and purchasing a first home. 

Third, and perhaps most importantly, the economic changes that led to the Great Recession hit hardest among young adults who were in their 20s shortly after 2005. The unemployment rate of adults older than 25 without a high school degree rose from below six percent in late 2006 to 15 percent in mid-2009. (Those with a high school degree or more followed this trend within a year.) Unemployment rates of those with a high school degree or more have slowly improved, but still remain above pre-recession levels. Unemployment rates for those with less than a high school degree have returned to their pre-recession elevated levels, but people in this group generally are making less money and receiving fewer benefits than they did before the recession. Meanwhile, housing costs have returned to, or now exceed, their pre-recession levels.

Using equally broad 20-year age spans produces several important findings about the different generations. To start with, the millennial generation has been larger than the baby boom generation, now or at any other previous time since the boomers were age 10-29 in 1975 (Figure 2). Millennials now number almost 87 million compared to less than 79 million for baby boomers at the same age. This is in contrast to findings of a 2016 Pew Research study that compared generations using millennials with a smaller age range and found roughly equal numbers between these two generations in 2015 (75 million).

Source: Census Bureau Population Estimates 1975-2015

Using consistent age spans also shows the changing ways that immigration has affected the number of people in each generation. In 1995, when Generation X was age 10-29, it was smaller than the baby boom generation was in 1955, when it was the same age. However, because of immigration, by 2005, when Generation X was age 20-39, it already exceeded the number of baby boomers at the same age. 

Immigrants also make up a small but growing share of millennials. In 2015, 9.6 percent of millennials were foreign born compared to 21.4 percent of Generation X, and 15.3 percent of baby boomers (Figure 3). However, according to the latest Census Bureau population projections, the share of millennials who are foreign born is expected to rise to 20.9 percent in 2035 when they are age 30-49, which will boost the number of millennials to 97.3 million (Figure 4).  

Source: Census Bureau Population Projections for 2015

* Data do not allow 85-89 year olds from 85+ age group

Source: Census Bureau Population Projections for 2035

Finally, the constant-age-span approach allows us to identify significant generational differences in race and ethnicity. Overall, in 2015, 45.4 percent of millennials, 41 percent of Generation X, and 28.6 percent of baby boomers were minorities (i.e. non-Hispanic Blacks, non-Hispanic Asian/Others, or Hispanics of any race). Moreover, because of continued immigration, the share of millennials who are minorities is projected to rise to almost 50 percent in 2035 and the share of Generation X is projected to rise slightly to 42.4 percent. In contrast, the share of baby boomers who are minorities is projected to hold constant at 28.6 percent. 

These differences reflect changes for both foreign-born and native-born members of each generation. In 2015, fully 85 percent of both foreign-born millennials and foreign-born members of Generation X were minorities.  In contrast, only 78.5 percent of foreign-born baby boomers were minorities. Moreover, while 41.2 percent of native-born millennials were minorities, only 29 percent of native-born members of Generation X and 19.6 percent of native-born baby boomers were minorities (Figure 5).

* Data do not allow 85-89 year olds from 85+ age group

Source: Census Bureau Population Projections

Looking forward to 2035, the size of the baby boom cohort will drop to about 60 million people because a growing number of baby boomers will pass away. Many millennials and members of Generation X will want to live in the housing units formerly occupied by those baby boomers. Their ability to do so will not only be shaped by the fundamental economic and social changes discussed above but also by whether the large numbers of racial and ethnic minorities in these two generations will have full access to those housing markets, and with it, the ability to achieve the American dream. 

New Report: Number of Older Adults in the US Expected to Surge, Highlighting Need for Accessible Housing and Policy Improvements

Download the Report

By 2035, more than one in five people in the US will be aged 65 and older and one in three households will be headed by someone in that age group, according to our new report, Projections and Implications for Housing a Growing Population: Older Adults 2015-2035, released today. This growth will increase the demand for affordable, accessible housing that is well connected to services beyond what current supply can meet.

As the baby boom generation ages, the US population aged 65 and over is expected to grow from 48 million to 79 million, and the number of households headed by someone over 65 will increase by 66 percent, to nearly 50 million. This growth will increase the demand for housing units with universal design elements such as zero-step entrances, single-floor living, and wide halls and doorways.  However, only 3.5 percent of homes offer all three of these features.

“The housing implications of this surge in the older adult population are many,” says Chris Herbert, managing director of the Joint Center. “and call for innovative approaches to respond to growing need for housing that is affordable, accessible and linked to supportive services that will grow exponentially over the next two decades.”

In the coming years, many older adults will have the financial means to pay for appropriate housing and supportive services that allow them to live longer in their own homes. However, many others will face financial hardships, particularly because their incomes will decline in retirement. Low-income renters are particularly vulnerable, notes the report, which projects that nearly 6.4 million low-income renters will be paying more than 30 percent of their income for housing by 2035. The report adds that 11 million homeowners will be also be in this position by that time. In total, the report estimates, 8.6 million people will be paying more than half their income for housing by 2035. The report also projects that 7.6 million older adults will have incomes that would qualify them for federal rental subsidies by 2035, an increase of 90 percent from 2013. “Today, however, we only serve one-third of those who qualify for assistance,” says Jennifer Molinsky, a senior research associate at the Joint Center and lead author of the report. “Just continuing at this rate—which would be a stretch—would leave 4.9 million people to find affordable housing in the private market.”

The report notes that in many surveys, older adults express a strong desire to live at home for as long as possible. Achieving that goal will require public and private action to support modifications to existing homes, take steps to address the affordability challenges facing both owners and renters, and adapting the health care system to enhance service delivery in the home. There is also a need to expand the range of housing options available to better meet the needs of an aging population and improve options for older adults to remain in their community when their current home is no longer suitable. 

“The implications of our aging US population on the housing industry are unambiguous,” says Lisa Marsh Ryerson, President of AARP Foundation, which provided funding for the report. “It will be imperative, in the coming years, that the housing industry, policymakers, and individuals take action to address the need for housing that will enable millions of older adults in this country to live with security, dignity, and independence.”

Read the full report

Join the conversation on Twitter: #harvardhousingreport

Have Recent Demographic Trends Contributed to the Rise and Fall of the Homeownership Rate?

by Jonathan Spader
Senior Research Associate

What has caused the ongoing, decade-long decline in homeownership in the United States? And which factors are most likely to influence homeownership rates in the future?

Discussions of the declining homeownership rate—which fell from 69 percent at its mid-2000s peak to below 64 percent in 2015—frequently point to demographic trends, such as delayed marriage and childbirth, an increasingly diverse U.S. population, and changing attitudes and preferences among both Millennials and retiring baby boomers, as the primary source of the decline. However, non-demographic factors like high foreclosure rates, tightening credit standards, and falling household incomes probably also contributed to the recent declines. To better understand the relative importance of the demographic changes, I used data from the Current Population Survey’s Annual Social and Economic Supplement (CPS/ASEC) for 1985-2015 to examine the extent to which changes in the distribution of U.S. households by age, race/ethnicity, and family type contributed to both the rise and fall in the homeownership rate over the past two decades.

I found that while there have been significant demographic changes in the last 30 years, these changes alone do not explain the last decade’s drop in homeownership rates. Nor do demographic trends explain why the homeownership rate rose from about 64 percent in 1990 to 69 percent in 2005. Rather, changes in the demographic profile of U.S. households suggest that the homeownership rate should have steadily declined by about 1-2 percentage points between 1985 and 2015. This, in turn, suggests that the rise and fall in the homeownership rate between 1985 and 2015 reflects changes in the broader economy, home price appreciation, mortgage credit conditions, and possibly household preferences for owning versus renting that alter the likelihood that demographically-similar households are homeowners.

Several demographic trends are reshaping the profile of U.S. households. First, the aging of the baby boomer generation has increased the number of households in older age cohorts. For example, the number of households headed by an individual age 55-59 hovered near 6.5 million from 1985 to 1995 before increasing to 9.8 million in 2005 and 12.3 million in 2015. (Figure 1) This shift has put upward pressure on the homeownership rate by increasing the number of households in older age cohorts, which have higher homeownership rates than younger age cohorts. (Figure 2) In coming years, the baby boom generation will continue to reshape the profile of U.S. households as they reach the oldest age groups.

Second, the racial and ethnic makeup of U.S. households is changing. The share of white non-Hispanic households declined from 81.3 percent in 1985 to 67.6 percent in 2015. Over the same period, the share of black households increased from 10.8 percent to 12.5 percent, the share of Hispanic households more than doubled from 5.6 percent in 1985 to 13.0 percent in 2015, and the share of Asian and all other households more than tripled from 2.2 percent in 1985 to 6.8 percent in 2015. (Figure 3) The implications of these trends for the homeownership rate depend on whether historical differences in homeownership rates across groups will persist in coming years. Historical CPS data suggest that the Hispanic-White and Asian/Other-White gaps in homeownership rates narrowed only slightly between 1985 and 2015, whereas the Black-White gap increased from 24.6 percentage points in 1985 to 28.8 percentage points in 2015. (Figure 4)

Third, larger numbers of young households are delaying marriage and childbirth until later in life, or forgoing them entirely. The share of households headed by a married couple decreased steadily from 58.9 percent in 1985 to 49.9 percent in 2015. The reduction is due entirely to decreases in the share of married couples with children, as the share of married couples without children remained approximately constant during this period. The decline is offset by increases in the share of single person households, unmarried households with children, and other unmarried households. (Figure 5) While homeownership rates for all groups have declined in recent years, the rates are consistently highest for married couples with children. (Figure 6)

To estimate the cumulative effect of these trends, I conducted shift-share analyses using the CPS/ASEC data. These analyses hold constant homeownership rates at their levels in various years to reveal the extent to which changes in the homeownership rate are driven by changes in the number of households in each age, race/ethnicity, and family type group. For example, using the 1985 sample, I calculated the 1985 homeownership rates associated with each combination of the 13 age groups, 4 racial/ethnic groups, and 5 family type groups shown in the figures above—creating 260 categories in total. For each of the years from 1986-2015, we can then calculate what the U.S. homeownership rate would have been if the homeownership rates for each group remained at the 1985 level. (Readers seeking a more detailed description of the methodology for this analysis can consult a forthcoming JCHS working paper.)

Figure 7 displays the results of such calculations when rates are held constant at their levels in 1985, 1990, 1995, 2000, 2005, 2010, and 2015. The projected homeownership rates suggest that changes in the profile of U.S. households by age, race/ethnicity, and family type do not explain the boom and bust trends in homeownership rates since the early 1990s. Rather, these factors predicted a modest decline in the homeownership rate of about 1-2 percentage points between 1995 and 2015. However, the overall predicted homeownership level varies sharply across the various years, which is the result of unmeasured changes across time in the broader economy, home price appreciation, mortgage credit conditions, and possibly household preferences for owning versus renting that alter the likelihood that demographically-similar households were homeowners in different years.

For a second analysis, I added additional variables to the shift-share analysis using a regression model to calculate the homeownership rates associated with each variable. (Again, more detail about the methodology can be found in the forthcoming working paper.) Specifically, the second analysis adds information on household income, employment status of the head and spouse, educational achievement, veteran status, and more detailed measures of marital status and the presence of children in the household. The projected homeownership rates from this analysis show that while these factors produce more volatile projections, they explain very little of the rise and fall in the actual homeownership rate between 1985 and 2015. The one possible exception is the period from 1996 to 2000, when rising incomes and employment help to explain a portion of the rise in the homeownership rate at that time. However, these factors are not able to explain the continued rise of the homeownership rate following the 2001 recession or the subsequent bust in the latter part of the decade. (Figure 8)

Taken together, these findings suggest that demographic factors explain very little of the rise and fall in the homeownership rate from 1985-2015. Rather, changes in the profile of U.S. households during this period have placed competing pressures on the homeownership rate and largely offset one another. Looking forward, the aging of the baby boom generation and the coming of age of the Millennial generation are similarly unlikely to substantially alter the homeownership rate in the near future. Instead, the trajectory of the homeownership rate depends more heavily on how quickly the foreclosure backlog clears, how many people who lost their homes to foreclosure buy homes in the future, how long mortgage credit conditions remain tight, and whether young households’ slowed rates of homeownership entry persist in future years. Additionally, any major changes in the broader economy, housing finance system, or attitudes toward homeownership may also influence future homeownership rates to the extent that they alter households’ demand or access to homeownership.

Are Renters and Homeowners in Rural Areas Cost-Burdened?

by Sonali Mathur
Research Assistant

As our latest report and interactive map illustrate, housing affordability is one of the biggest challenges faced by owner and renter households in most metro areas across the US. However, maps that use metro areas to display the local-level story miss the fact that cost burdens are also a major concern in non-metro/rural areas and are severely high for millions of low-income rural households. To address this gap in visibility, we created a set of interactive maps (Figure 1) using 2010-2014 American Community Survey (ACS) estimates. In doing so, we found that housing cost burden rates in some rural counties are significant. We also learned that rural counties of the Northeast and west, that are adjacent to high-cost metros, have even higher cost burden rates than those in parts of the Midwest.

 (Click to launch interactive map; may take a moment to load.)

Housing cost burdens are particularly stark for rural renters. Indeed, fully 41 percent of all rural renters are cost-burdened (meaning they spend 30 percent or more of their income on housing), including 21 percent who are severely cost-burdened (spending 50 percent or more of their income on housing). Among owners, 22 percent are cost-burdened including nearly 9 percent who are severely cost-burdened. Overall, nearly 5 million rural households pay more than 30 percent of their monthly income toward housing and more than 2.1 million rural households spend more than half of their income on housing.

And cost burdens have been growing in rural areas (Figure 2). Since 2000, housing costs in rural areas have increased over 5 percent and one in every four rural households is now cost-burdened. Comparing burden rates from 2014 to those from 2000 in the maps above shows the increasing cost burdens in many rural areas over the last decade, including areas in and around the traditional Black Belt counties of the Southeast and areas in the west and Northeast that are contiguous to areas that had high cost burdens in 2000.

Source: JCHS tabulations of US Census Bureau, American Community Survey 2010-2014 and census 2000 for all non-metropolitan census tracts. 

Rural affordability issues tend to receive less attention due to a perception that housing costs are lower in rural areas, which is true as compared to metro areas. According to the 2013 American Housing Survey (AHS) the median monthly rent in metro areas is $800, while the median monthly rent in non-metro areas is $530. Monthly owner costs are also fully 43 percent lower in non-metro areas than in metro areas. However, low incomes and poverty are prevalent in rural areas. According to estimates from the American Community Survey, fully 15 percent of all households in non-metro area census tracts earn less than $15,000 annually and nearly 36 percent earn less than $30,000. Poverty is a widespread problem in rural areas, with 18 percent of population living in poverty compared to 15 percent in metro areas.

In addition to poverty and affordability, rural areas face several other major housing challenges. The share of housing stock that would be considered inadequate, as measured by the number of units lacking complete plumbing or a complete kitchen, is higher in non-metro areas. The share of units lacking complete plumbing is 4 percent in non-metro areas, compared to 2 percent nationally.

Among units in non-metro areas that lack complete plumbing facilities, 10.3 percent also have more than one occupant per room (compared to 8.2 percent in metro areas). This suggests that in non-metro areas there is likely to be overcrowding in the same units that lack adequacy. It is probable that the households facing affordability problems are dealing with it alongside other issues.

While it is true that cost burdens are high and a growing problem in most metro areas across the country, it is important to remember that non-metro areas also face increasing housing affordability issues, in addition to other housing-related challenges and should not be forgotten in policy discussions of a comprehensive approach to the escalating housing affordability problem.

The Impact of Student Loan Debt on the Housing Decisions of Young Renters

by Irene Lew
Research Analyst

In the last several presidential debates, both Democratic and Republican candidates have referenced the mounting costs associated with a college education, which have contributed to the dramatic growth in student loan debt over the past decade. Two weeks ago, the nonprofit Institute for College Access and Success released their tenth annual report which showed that students' average debt at graduation rose 56 percent, from $18,550 in 2004 to $28,950 in 2014. Aggregate outstanding student loan balances more than tripled in real value over the same timeframe, rising from an average of $380 billion in 2004 to $1.1 trillion in 2014, according to data from the Federal Reserve Bank of New York’s Consumer Credit Panel. In fact, student loan debt was the only type of consumer debt to rise steadily during the Great Recession, even as households shed other types of non-housing-related debt such as credit card debt.

Many in the housing industry are concerned that unmanageable student debt is holding back Millenials from becoming first-time homebuyers. Households aged 25 to 34 typically account for just over half of all first-time buyers, but homeownership rates among this group have dropped by more than 9 percentage points since 2004. A 2014 survey conducted by the National Association of Realtors found that only a third of 2014 homebuyers were first-time purchasers—the lowest share since 1987—and that among the 23 percent of first-time homebuyers who reported difficulties with saving for a down payment, over half (57 percent) cited student loans as a factor. In a new research brief I analyze the extent to which young renter households in their 20s and 30s are burdened by their student loan payments and explore the potential implications of these payment burdens on future decisions to pursue homeownership. I also build on the findings described in an earlier blog post to further describe the growth and prevalence of student loan debt among various demographic groups, especially among minority households and those without a four-year college degree.

My analysis draws on cross-sectional data from the Federal Reserve Board’s triennial Survey of Consumer Finances (SCF), which describes changes in debt, wealth, and assets at the household level. My brief utilizes the thresholds for student loan debt burdens outlined by the Consumer Financial Protection Bureau, which define burden according to percentage of monthly income made up by each monthly payment: for low, medium and high burdens, respectively, this percentage is less than 8, between 8 and 14, and more than 14. Reflecting both increases in student loan payment amounts and income declines among young renters, I find that the prevalence of young renters with medium or high student debt burdens accelerated following the Great Recession. Between 2007 and 2013, the share of young renters with high student loan burdens nearly quadrupled, from 5 percent to 19 percent (Figure 1).

Young renters at the lower end of the income distribution are more likely to bear the brunt of student debt payment burdens. When factoring in other non-housing debt payments on top of student loan payments, the mean payment-to-income ratios increase to 22 percent for young renters in the bottom quartile and to 8 percent for those in the top quartile (Figure 2). Yet although the lowest-income renters are faced with the highest payment burdens, even the lower payment burdens among renters in the top quartile are large enough to be factored into the ability to purchase a home.

While a causal relationship among student loan debt, housing consumption, and the tenure decisions of young renters cannot be drawn without additional analysis that disentangles other economic factors such as local employment and housing market conditions, student loan payment burdens are likely contributing to downward pressure on the homeownership rates of young households. Indeed, homeownership rates have been consistently lower among households with medium and high payment burdens relative to those with low burdens (Figure 3).

My analysis of student debt burdens excludes households that have not begun making payments on this debt due to deferral or forbearance, suggesting that the number of young renter households with student debt payment burdens is likely to increase in coming years as this group enters the repayment cycle. Indeed, as of 2013, nearly half of the $711 billion in student debt observed in the SCF data was held by households that have at least one student loan in deferral—and 45 percent of renter households aged 20-39 with student loan debt have not yet made any payments toward their outstanding student loan balances (Figure 4).

Another concern is rising student loan default rates, which reflect a growing share of borrowers struggling to pay down their debt. According to the U.S. Department of Education’s Federal Student Aid Data Center, 3.2 million borrowers are in default as of the third quarter of 2015, up by more than half (52 percent) from the same quarter two years ago. Federal student loan borrowers faced with unexpectedly low earnings can take advantage of several income-driven repayment plans that reduce monthly payments and can help minimize payment burdens, but most do not, instead opting for standard repayment plans, not based on current income, where monthly payments are amortized over a 10-year period. Unlike income-driven repayment plans, standard repayment plans do not account for reductions in a borrower’s income and do not establish timelines for forgiveness of any remaining loan balances.

Rising student debt levels and payment burdens among young renters are likely to impact this group’s long-term finances and their decisions to transition to homeownership. Delinquency and default can harm the ability of young renters to access low-cost credit and qualify for a home-purchase mortgage. Furthermore, student loan payments reduce young renters’ discretionary income and can delay the accumulation of savings toward a down payment on a home. Indeed, according to the SCF, college-educated renters in their 20s and 30s with student loan debt had just $3,500 in cash savings and negative net wealth of -$9,640 at the median, compared to $27,000 in net wealth and more than double the amount of cash savings ($7,500) among those without student debt. With lower incomes, wealth, and savings, young renters with student debt may face challenges qualifying for a mortgage to purchase their first home or setting aside a sufficient financial cushion for a down payment on a home.

A City Revival? It Depends on Your Definitions

by Rachel Bogardus Drew
Post-Doctoral Fellow

Every spring, the Census Bureau publishes estimates of the population as of the prior July 1st at the sub-county level (i.e., individual municipalities, incorporated places, and non-incorporated county balances). Recent releases of these estimates suggest that cities have been expanding faster than their suburbs, with annual average population growth of 0.91 percent in 2010-2014 in the former, versus 0.77 percent average annual growth in the latter (Figure 1). Non-metropolitan areas, meanwhile, have recently seen their populations decline, by an average of more than 0.25 percent annually over the last four years.

Notes: Metropolitan areas and principal cities are defined as of 2013 by the Office of Management and Budget (http://www.census.gov/population/metro). Suburbs are all parts of a metro area not designated as a principal city. 
Source: JCHS tabulations of the U.S. Census Bureau’s Vintage 2014 Postcensal Population Estimates.

This recent trend of city populations growing faster than those of suburbs is a dramatic departure from prior decades, when suburban population growth significantly outpaced that of cities. Indeed, analyses by the Brookings Institution, using slightly different data and definitions of cities and suburbs but reaching the same general conclusions, suggest that between 2000 and 2010 the suburbs of large metropolitan areas grew by 1.38 percent per year, while the primary cities of large metro areas expanded by only 0.42 percent annually.

Some commentators herald this trend as a long-awaited sign of a grand urban revival, attributable to the combination of recent market events and long-running demographic trends. They posit that cities are becoming more popular in the wake of the late-2000s recession and downturn in housing markets, which exposed many of the downsides to suburban living. Either unable or unwilling to purchase homes in suburbs, the argument goes, more households are opting instead to live in urban neighborhoods with their mix of affordable housing options and lifestyle amenities. At the same time, some subsets of the population that are traditionally more likely to live in cities, including young adults, minorities, and childless households, have been increasing as a share of all households. Even if all households continued to live in cities and suburbs at the same rates as in the past, these demographic shifts alone would elevate the populations of cities more than those of suburbs.

Not everyone agrees with the urban revival hypothesis, however. Researchers point out that the suburbs are still home to about half of the U.S. population, and remain the location of choice for most households, including young families and retirees. Proponents of this position further argue that the cities that are growing the most do not resemble the dense cores that urbanists favor, but are instead places with lower densities and auto-centric commuting patterns more akin to close-in suburbs.

The disparity in these viewpoints exists in part because of the way that most analysts define cities and suburbs. Figure 1 above, for example, uses the federal Office of Management and Budget’s (OMB) classification of metropolitan areas and principal cities, and assumes that a principal city is effectively the ‘urban’ portion of the metro area, with the balance comprised only of ‘suburban’ places. This delineation, however, leaves no room for judgments about individual communities that blur the lines between urban and suburban areas. Some principal cities are themselves former suburbs that changed their status by making themselves more appealing to certain residents and/or by attracting a particularly large employer or industry, but that nonetheless retain many of their former suburban characteristics, such as neighborhoods with mostly single-family housing. Some suburbs, meanwhile, have developed dense centers with walkable amenities akin to cities, giving residents a taste of urban lifestyles in their small communities. The definitions used by OMB, however, group such places together with low-density bedroom communities under the broad umbrella category of suburbs. Indeed, even within a particular municipality there can be neighborhoods that have a more urban or suburban feel to them, so that classifying the entire municipality as either a city or suburb ignores the diversity that attracts residents to it in the first place.    

An alternative to the dichotomous definitions of city and suburb is to categorize places on one or more spectrums that take into account the different features of each type of community most significant to residents. These features can include everything from population density to type of housing stock, transportation usage, presence of retail establishments and cultural amenities, and walkability. Some researchers have already developed different classification schemes that take such characteristics into account, using density and commuting statistics to identify cities that are more or less urban in their character, or considering the degree of urbanization of suburban counties outside of large cities. Yet even these approaches still rely on assigned administrative boundaries of cities, counties, and metro areas that ignore the variations within them. A better option for those studying population shifts would thus be to see past political geography in favor of descriptive categories that better capture the diverse qualities sought by people as they choose where to live; researchers should define a spectrum of community types that represent this diversity. Such classifications will not only allow for richer analyses, but will better reflect the reality of where Americans live – not in cities or suburbs, but places that offer the best combinations of amenities to meet the needs of modern households.

For Housing Demographers It’s All About the Data – But Sometimes the Data Come Up Woefully Short

by George Masnick
Senior Research Fellow

Housing demographers are often frustrated by data that range from inconsistent to totally unavailable when attempting to research demographic and housing trends. The inconsistencies between various data sources on estimates of household numbers and household growth, vacancy rates, and homeownership rates are well documented and continue to be dissected and discussed, but there are other metrics that have been even more elusive to pin down that would help enormously to better understand today’s demographic/economic trends and their housing implications.

Two broad areas of housing consumption are particularly difficult to measure.  The first concerns the doubling up of generations living in a single residence.  The second is the opposite – when a single household lives in more than one housing unit on a regular basis. 

We would like to be able to answer many questions about the increasing trend of young adults who live with their parents. We have also identified a growing trend of grandparents who live with their grandchildren (and in many cases the grandchildren’s parent or parents as well) but we cannot identify grandparents who might not live with their grandchildren but live close by and provide support in childrearing.  We would like to know more about how delayed marriage/partnering, and divorce/remarriage, affect housing consumption of multiple units.

For the most part, existing data cannot tell us what actually takes place in the housing history of specific households over time as individuals age and change their household configurations, marital/partnership status, and employment/income profiles.  Most difficult to measure are the linkages between generations in structuring patterns of geographic mobility (affecting both those who move and those who do not move in order to be close to family), young adult household formation, and housing consumption across the age spectrum.

Data sets that do have information about life-course household transitions and some information about relationships between generations rarely have any data on housing.  Data sets that have housing information lack information about life-course changes preceding and during current occupancy.  Information about extended family members that do not reside in the household being interviewed is generally totally lacking.

We would like to know not only how many adult children presently live with their parents, but how many have boomeranged and the type of housing boomerang children moved out of when they moved back home.  How often does moving back home occur for specific households, and how long does it last?  Short spells of returning home presumably have much different consequences than long ones.  Chronic returns might have very different causes and consequences than one-off situations.  Returns to large houses with higher-income parents have different consequences than returns to small homes having low household income. 

We would like to know more about the background details of children when they leave a parental household – reasons for leaving, characteristics of housing (on both ends of the move), and, household size and composition (again on both ends of the move).  Are boomerang kids and their household/housing characteristics different from those who leave and do not return?  This information would be immensely helpful in better understanding the present and future housing consumption of those Millennials who have been slow to form independent households and become homeowners.  

Ideally, answers to the kinds of questions just raised require panel data that track individuals and their housing over time.  The few nationally representative panel surveys with public use micro data, such as the Panel Study of Income Dynamics (PSID) or the National Longitudinal Survey of Youth (NLSY), have limited housing data.  And even these surveys have historically been deficient on the collection of data on individuals and their extended families: the PSID has collected data at regular intervals since 1968, but only in 2013 added a Family Roster and Transfer Module in which respondents and their spouses are asked to enumerate all living parents and children over 18 and to report about recent and long-term transfers of time and money to these individuals.  The new PSID module is the first to fully enumerate all biological, adopted, and step-relationships of parents, parents-in-law, and adult children, and it is the first major data collection effort on transfers of time and money in the PSID since 1988.

Other efforts to assemble panel data to directly study co-residence patterns between adult children and parents, such as in a recent Federal Reserve Bank of New York Report (utilizing its own Consumer Credit Panel (CCP)) are neither a nationally representative sample of all households nor available to other researchers, raising concerns about the reliability of the data. For example, the CCP data set reports a much higher rate of co-residence than other data sources such as the Current Population Survey.  Still, because of the scarcity of panel data to answer some of our questions, data sets the FRBNY CCP cannot be entirely dismissed.

Another reason for growing inter-generational co-residence is the need to support and take care of grandchildren.  Increasing grandparent-grandchild co-residence certainly has important consequences for housing choices, further postponing independent household formation among some Millennials, and perhaps delaying downsizing among the Baby Boomer grandparents.  We would like to know if older Americans who live close to their grandchildren are different from grandparents who live with their grandchildren.  Do they also play financial and childcare roles with respect to their grandchildren?  Are retirees more likely to move to be close to their children if their grandchildren are young?  Does the existence of young grandchildren make retirement moves that put greater distance between them and their grandchildren, or that are to age restricted communities, less probable?  Do older empty nesters with young grandchildren actually downsize less than those with older grandchildren? 

Available data on the rise of co-resident grandparents and their grandchildren are mostly from cross-sectional surveys, like the Current Population Survey, and are biased toward intergenerational families where those in the first wave of Millennials had their children relatively quickly, often while teenagers or still in school, or when not yet absorbed into the labor force.  Such early births are more likely to be to parents without a college education and to be non-marital.  The large and growing share of Millennials who pursue higher education are more likely to postpone childbearing (thus postponing grandparenthood for many Baby Boomers) and their births are more likely to be marital.  Will first grandchildren who come along later in life, when their parents are older and more economically secure and their grandparents are more likely to be retired, be more or less likely live with grandparents?  Live close to their grandparents?   

Unfortunately, nationally representative data that allow us to identify who is even a non-coresident grandparent are practically non-existent.  The sole exception is from the Survey of Income and Program Participation (SIPP), a longitudinal survey following panels of households for 2½-to-4 years, which for three of its panels has asked if a person has any biological children and if those children, in turn, have any biological or adopted children.  The SIPP data overlook persons who are not biological grandparents but are grandparents through marriage, either as stepparents themselves or who became a grandparent when their children partnered with someone who already has children, but has not adopted them.

Analyses of SIPP data on grandparents have been published for the 2001 panel, the 2004 panel, and the 2008 panel.  A 2014 panel is now in the process of data collection.  These data estimate that there were 64 million grandparents in 2009 (second wave questionnaire of the 2008 panel), of which one-in-ten lived with their grandchildren. According to these data, only 22 percent of co-resident grandparents were over the age of 70 compared to 34 percent of grandparents who did not live with grandchildren. We have little insight into proximity of these non-coresident grandparents to their children and the housing choices they have made if they have recently moved.

One additional panel survey that collects data to answer questions about grandparents is the University ofMichigan’s Health and Retirement Study (HRS).  It does allow identification of all grandparents, co-resident grandparents, reasons for moving, and does have some housing data, but it is somewhat limited by a sample design that selects particular birth cohorts.  Still, more analysis of these data, collected annually from 1992 to 1996 and on alternate years since, can help us better answer some of our questions.  

Shifting gears, how people utilize multiple housing units (their own and/or other’s) at different times during the week, month, or year is almost a complete mystery.  We would like to know more about middle-aged and older people who sometimes dwell in two or more housing units while maintaining control of each.  There is a catch-all category of households in some data sets identifying people who have a primary or usual residence elsewhere, and this category has been growing in recent years.  However, households interviewed at their primary residence are not asked if they sometimes live in another home, and data are not collected about the characteristics of that home and the reasons for living in it.  Are grandparents spending some time living with their grandchildren on a regular basis, or buying or renting a residence that they occupy occasionally to be close to their young grandchildren?  Are retirees who once lived close by their young grandchildren retaining a previous residence for a longer period of time to facilitate occasional visiting after retirement migration?  Are more adult children still living in retirees’ previous homes after they retire and move elsewhere?

We would also like to know how long individuals maintain an active consumption of multiple housing units when they change jobs or form new relationships.  Is “living together” increasingly less a status and more a process that could involve two or more housing units over an extended period of time?  Is the rise of long-distance telecommuting predicated on being able to spend some time in two or more locations, and is it the case that housing units in multiple places are owned or rented to facilitate this?  If people are now better able to rent out or share housing with others on a part-time basis (for example, through VRBO and Airbnb), are they more likely to maintain multiple units for their own occasional use? 

  

Until panel surveys from nationally representative samples collect data on life-course transitions, on intergenerational relationships, and on housing consumption more broadly defined, analysts will continue to try to research trends with data that are usually inadequate to the task, and to have questions that simply cannot be answered.