Homeownership Rates for Children of Immigrants—Age Matters

by George Masnick
Senior Research Fellow

Analyses of data used in a recent Census Bureau report show that homeownership rates for younger adult children of immigrants are substantially higher than rates for immigrants in the same age cohorts. In addition, while homeownership rates for native-born residents with native-born parents under age 45 are higher than those for the children of immigrants, members of the latter group quickly make up this deficit after the age of 45.

These findings emerge from additional analyses of data used in a first-ever report on the characteristics of three generations of US residents by nativity that was released late last month by the Census Bureau. The report is the first to use a unique question in the Current Population Survey‘s Annual Social and Economic Supplement (CPS/ASEC) asking the birthplace of both the respondent and the respondent’s parents. This allows one to identify people born abroad (1st generation), native-born children of at least one immigrant parent (2nd generation), and those whose parents were both born in the United States (3rd-and-higher generations).

The Census report discusses differences among the three groups in such areas as age, education, labor force participation, income, poverty, occupation, and homeownership. The last section is particularly interesting because other Census Bureau data the Joint Center has used to study homeownership, such as the Decennial Census, the American Community Survey, and the American Housing Survey, do not ask respondents where their parents were born. Moreover, as I have shown in an earlier post that also used CPS/ASEC data, immigrants are an important part of a recovering housing market. Foreign-born people have accounted for about one-third of all net household formations over the past two decades, and slightly under 30 percent of all gains in owner-occupied housing. Fully half of all household growth between 1994 and 2014 by under-30-year-olds came from 2nd generation children of immigrants, and another 35 percent from immigrants themselves.

The Census Bureau report notes that incomes and homeownership rise sharply between the 1st and 2nd generations but tend to level off for the 3rd-and-higher-generations. However, these findings may obscure significant differences between the 2nd and 3rd-plus generations because, as other parts of the Census Bureau report note, the generations have dramatically different age distributions. In particular, the majority of immigrants are middle-aged, and their children are 20 or younger. Adult children of immigrants have their largest percentages in the under-30 age group. Baby boomers dominate the 3rd-and-higher generations at age 50-70 in 2013 (Figure 1).

Source: U.S. Census Bureau, Characteristics of the U.S. Population by Generational Status: 2013, Current Population Survey Reports, Nov. 2016, Figure 9.

Because of these differences in age structure, it is impossible to compare the three generations broadly on any variable that varies with age, such as income or homeownership. For example, as the Census report shows, the median income among all individuals age 15 and over rises dramatically from $36,669 for the 1st generation to $46,764 for the 2nd generation. But, at $46,795, it is virtually unchanged for the 3rd-and-higher generations. However, when the data are broken down by age groups, they tell a somewhat different story. The Census report, which looks at median personal income for four broad age groups, shows significant income advantages for the 2nd generation over the 3rd-and-higher generations for 25-44, 45-64, and 65+ year olds. When median household income (a more relevant definition of income with respect to homeownership) is broken down into 5-year age groups, the 2nd generation can be seen to earn significantly more than their parent’s generation at every age, and importantly, more than the 3rd-and higher-generations as well (Figure 2).

Source: Joint Center for Housing Studies tabulation of 2015 CPS/ASEC data.

The need to control for age is especially important when examining generational differences in homeownership. In four of the five household family types discussed in the Census report, when age is not controlled, 2nd generation homeownership rates are lower than those for the 3rd-and-higher generations (and in the fifth, the difference between the groups is quite small) (Figure 3).

Source: U.S. Census Bureau, Characteristics of the U.S. Population by Generational Status: 2013, Current Population Survey Reports, Nov. 2016, Fig. 28.

If we control for age, would 2nd generation homeownership rates still be lower than those for the 3rd-and-higher generations? Also, since the Census report examined generational differences for a single year (2013), if there are differences by age, how well have they held up over time?

To answer these questions, we examined homeownership rates by age by 5-year age groups for the three generations for each year 1994-2015. These tabulations first can be summarized by examining the trends for two broad age groups (Figures 4 and 5). For households age 25-44, 2nd generation homeownership rates are well above those of their parents’ generation but below those of the later generations. This last pattern is partly explained by the greater concentration of younger 25-34 year olds in the broader 25-44 age group for the 2nd generation, and probably also due to the greater concentration of immigrants and their children in locations that have below average homeownership rates, such as the Los Angeles, San Francisco, New York City, Boston, and Chicago metropolitan areas. There might also be a greater ability of 3rd-and-higher generation parents to help their children financially in buying their first home, and a corresponding need for children of immigrants to save longer for a downpayment.

Source: Joint Center for Housing Studies tabulations of 1994 through 2015 CPS/ASEC data.

Source: Joint Center for Housing Studies tabulations of 1994 through 2015 CPS/ASEC data.

This analysis also shows that among younger adults the gap between the homeownership rates of the 2nd and 3rd-and-higher generations has widened since the Great Recession. The growing gap might be due to compositional shifts within the broad 20-year age cohort in such factors as age, ethnic composition, household composition and income. Alternatively, tightening credit markets might affect the generations differently. This could be particularly important for undocumented members of the 2nd generation. In any case, both the generational gap for younger adults and their recent trend certainly deserve further investigation.

For the broad adult age group over age 45, the story is quite different. Among older adults, the homeownership rates among the 2nd and 3rd-and-higher generations have been essentially equal for the past two decades except for a few years at the height of the Great Recession. The slower entry into homeownership we noted for younger 2nd generation households appears to have simply reflected the timing of the transition from renting to owning, rather than the effects of any structural differences between these two generations. After age 45, the 2nd generation has consistently closed the gap with the 3rd-and-higher over the past two decades. Another way to look at this homeownership data is to follow different birth cohorts of young adults as they age from the 25-44 age group into the 45-64 group. For each of the five-year 2nd generation cohorts under age 45 in 1995, the homeownership rates are lower than the respective cohorts in the 3rd-and-higher-generations. However, by 2015, when each of these cohorts is 20 years older, the homeownership gap between the generations has been completely eliminated (Figures 6 and 7).

Source: Joint Center for Housing Studies tabulations of 1995 CPS/ASEC data.

Source: Joint Center for Housing Studies tabulations of 1995 CPS/ASEC data.

The higher median income of 2nd generation adults above age 45 perhaps provides just the leverage they needed to make up the lost ground. And it is also likely that the older 2nd generation households are more concentrated in locations that have lower homeownership rates than the national average. If we could control for metropolitan location as well, middle-aged 2nd generation age-specific homeownership might well be higher than for the 3rd-and-higher generations. Unfortunately, the CPS/ASEC sample size does not allow such sub-national trends to be observed.

In sum, it is important to underscore that failing to recognize the important age differences between the three generations can lead to erroneous conclusions about levels and trends in income and homeownership. Because the 2nd generation age structure is so young, comparisons that lump adults of all ages together will result in unduly low incomes and homeownership for this group. As the Census report concludes, most 2nd generation U.S. residents surpass their parents’ generation in many measures, particularly education, income and homeownership. Once proper age controls are introduced, they equal or surpass the 3rd-and-higher generations in these dimensions as well.

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.

New Census Data on Incomes Suggests Growing Demand for Housing

Dan McCue
Senior Research Associate

New data released by the Census Bureau on Tuesday suggests that the demand for housing – particularly among young adults – may be growing.

As many news outlets have reported, the CPS 2016 Annual Social and Economic Supplement with household income data for 2015  showed that real median household income rose 5.2 percent from 2014 to 2015, to $56,516. It was the first annual increase in median household income since 2007. Median household incomes were up for each region of the country, and for non-Hispanic white, black, and Hispanic households, and across all age groups (Figure 1).

Source: JCHS tabulations of US Census Bureau, Current Population Survey Annual Social and Economic Supplements

The data release also showed significant increase in real median earnings at the person level in 2015, which grew 5.0 percent for all adults over age 15. Incomes were up most sharply among younger adult age groups under the age of 40 (Figure 2).

Source: JCHS tabulations of US Census Bureau, Current Population Survey Annual Social and Economic Supplements

For several reasons, this growth is likely to have significant implications for housing markets. First, at the individual level, higher incomes increase demand for housing. For young adults, housing independence is closely linked to income. Those with higher incomes are more likely to be able to rent their own apartment. Analyses in the Joint Center’s 2016 State of the Nation’s Housing report describe this, adding that nearly half of the decline in household formation among young adults aged 25-34 across the Great Recession was due to declines in income suffered by people in this age group. Income growth can therefore work in the reverse, helping enable young adults to move out of their parents’ basement and into their own home.

At the household level, income growth also increases housing demand, particularly for homeownership. As higher income households are more likely to own homes, increases in incomes among households will work against the continued decline in the US homeownership rate. In terms of affordability, the strong association between household income and housing cost burdens also means income growth may help alleviate some people who are stressed with housing costs, but on the affordability front there is still a long way to go.

Finally, it is worth noting that the Current Population Survey Annual Supplement is a relatively small survey with a high degree of annual volatility year to year, so the exact movements of household income and personal earnings measured year to year should be viewed with the wide margin of error they require. That said, the income growth reported in the latest survey is still a good sign that improvement in jobs and the economy is now translating into increased earnings that is likely to lead to growth in households and greater demand for housing.

Reconciling Different Household Counts from Census Bureau Surveys

by Dan McCue
Senior Research Associate

One of the major challenges faced by housing analysts and demographers is the lack of consistency among various Census Bureau surveys.  Particularly troublesome is the persistently wide range of difference reported by surveys in the number of households in the US, a key measure of housing demand.  In 2013, for instance, household counts reported by various Census Bureau surveys ranged from a low of 114.6 million in the Housing Vacancy Survey (HVS), to 116.3 million in the American Community Survey (ACS), to a high of 122.5 million in the Current Population Survey’s March ASEC (CPS/ASEC) - a span of fully 7.8 million households (Figure 1).  Annual surveys also differ widely in their measures of growth in the number of households, confounding efforts to gauge recent trends.  Indeed, household growth measures for 2013 ranged from 0.3 to 1.4 million depending on the survey, leaving data observers unsure whether growth in that year was historically weak or incredibly strong.

Source: JCHS tabulations of US Census Bureau data.

Given their importance to much of our work, the Joint Center has recently released a research note to highlight some of our current thinking on Census Bureau survey counts including: the differences in household counts among annual Census Bureau surveys and their causes; which surveys we believe to have more accurate counts than others and why; how we use different household count data for different analyses at the Joint Center; and how much of a difference using alternative headship rates based on different household counts would have on the current JCHS household projections.

The research note finds that the major source of difference among survey counts of households appears to be whether or not the surveys are person-based or stock-based.  Person-based estimates, which count the number of people who report being heads of households, consistently result in higher numbers of households than stock-based estimates, which count the number of housing units that are occupied.  We don’t exactly know why there is such variance in person-based and stock-based survey results, but the magnitude of difference between these two approaches is big and can be roughly approximated by the difference in household counts of the HVS and CPS/ASEC, because they are essentially stock-based and person-based versions of the same underlying survey sample. 

Among the annual surveys, the person-weighted CPS/ASEC has an advantage in that its household counts have come in closest to decennial census counts, which we take to be the benchmark. It is also a relatively timely survey and has the longest track record of matching census growth over the decades.  However, the CPS/ASEC does have a number of other shortcomings. One of the its major shortcomings, year-to-year volatility, can be reduced by smoothing over the data using rolling averages, but that approach also reduces the timeliness of the survey for measuring short-term trends in household growth. 

The second major annual household survey from which to get household counts, the stock-based HVS, is the most timely measure, providing quarterly results in addition to annual counts, and it also offers a series of annual household counts that use a consistent weighting vintage, which provides a more stable framework for measuring annual household growth trends than surveys that adjust their underlying survey controls year to year.  However, those vintage weighting controls do not eliminate a high amount of annual volatility.  Recent results underscore this fact, for it is highly unlikely that household counts in the HVS jumped fully 1.3 million between the third and fourth quarters of 2014 as reported in the HVS.

Finally, lack of timeliness is also a major disadvantage of using the third major annual census survey, the ACS, for analyzing annual counts of households: while other annual survey results have been out for months, the 2014 ACS is not due out until late 2015.  The ACS also has much lower household counts and appears to be essentially a stock-based survey with slightly higher household counts than HVS that is most likely a result of its more inclusive rules for determining occupancy of a unit.  Still, even with its lower base of counts, as a large and detailed survey the ACS may prove to provide a reliable measure of the growth trend in households, but so far this survey has had only a few years under a consistent weighting methodology in which to judge its reliability.

Overall, there is no satisfying conclusion to which annual survey is best for measuring annual household growth trends and none is perfect. CPS/ASEC is volatile but can be smoothed over at the expense of timeliness; HVS is timely and attractive in that its counts are pinned to stable consistent weighting vintages across years but it is still volatile, and possibly the vintage controls bias growth too low; and ACS is not timely enough to be helpful in measuring recent trends and is a survey without much history in which to judge its accuracy, though it has promise as a large and detailed survey that receives a relatively high amount of resources from the Census Bureau.  In terms of the number of households, however, there is reason to believe that higher counts of the CPS/ASEC, obtained from person-based weighting approaches, do appear to be preferable to lower counts of the HVS and ACS in offering counts closest to that of the official decennial censuses.  It is largely for these reasons we have used household counts from CPS/ASEC as a key input in Joint Center household projections, which apply current headship rates (the ratio of households to people) to population projections to produce household projections that form a baseline for estimating future housing demand.

Some Thoughts on a Surprising Household Growth Estimate

by Dan McCue
Research Manager

Many media outlets and blogs (including our own), have reported on the results of the Housing Vacancy Survey (HVS) for the fourth quarter of 2014, which showed the US homeownership rate had dropped to its lowest point in fully 20 years. But the fourth quarter HVS contained another surprising reading—one that could be even more noteworthy than the continued fall in the homeownership rate. The HVS is one of very few sources of short-term estimates of household growth – an important gauge of housing demand.  And the surprise here was that HVS data show household growth going through the roof in the fourth quarter of 2014, with year-over-year growth in excess of 1.6 million households. This comes after household growth had long been stalled out, averaging less than 600,000 per quarter for much of the previous five years (Figure 1).

The concern and attention surrounding this number breeds from the thick cloud of uncertainty behind trends in household growth. Survey data from the Census Bureau such as the HVS, ACS, and CPS/ASEC give different and sometimes conflicting measures of household growth year-to-year, each with wide margins of error, which makes it difficult for analysts to call out trends with much confidence.  Amidst this lack of clarity is a widely held anticipation, or possibly hope, that household growth, having been ‘pent-up’ after such a long period of weakness, is primed to rebound strongly and this Q4 number from HVS might signal an inflection point.

Source: US Census Bureau, Housing Vacancy Survey Revised Estimates of the Housing Inventory: 2000 to Present, Table 8a.

One possible explanation for such an abrupt change in the rate of household growth in the fourth quarter HVS would be some change in how the survey is conducted or weighted that caused a discontinuity in the series. But the folks at HVS report that there were no structural or methodological changes to the dataset that would have been behind the sharp rise.

Without any methodological justification for the sudden jump, another factor may be some degree of sampling variation that produced an abnormally high estimate for the quarter. HVS has noted that quarter to quarter variability within the survey has increased and in many respects, this Q4 number is simply a prime example of how erratic quarterly data in the HVS can be and why we prefer not to make much of any one quarter and opt instead to look at rolling averages or other smoothed versions of this data to get a sense of recent trends.  But even averaged over the previous four quarters, Q4 still pulls the annual household growth reading for 2014 up significantly, to 789,000, representing a significant increase from the 524,000 annual growth reported for 2013, although still well below the long-run pace of 1.2 million per year that the Joint Center estimates is the baseline amount to expect given current levels of adult population growth and changes.

Alternatively, this fourth quarter increase could be a sign that the HVS is simply catching up to reality with its household counts after underestimating household growth over the past several years, In fact, prior to the 4th quarter results, the primary concern with HVS estimates was that they were overly low (see previous blogs on the topic here and here), in showing continued weakness in new household formation even as the economic recovery continued to gain steam.

Indeed, there are a variety of other market indicators that would suggest that household growth has been increasing at a modest pace in recent years and more than has been suggested in HVS quarterly releases prior to Q4. Most notably, employment growth has been ratcheting up over the last three years, from 2.3 million in 2012 to 2.4 million in 2013 and 3.1 million last year. Importantly, these gains have also been felt among young adults who are so important to household formation, with the unemployment rate of those age 25-34 dropping from 8.9 to 5.9 percent over this period. The slow rise in housing starts from 550,000 in 2009 to 1.0 million last year, at the same time that vacancy rates have declined, also suggests that household growth has been picking up steadily over this period.

In short, given the nature of survey data, we are not putting too much trust in the accuracy of this one quarter’s estimate of household growth reaching a 1.6 million annual pace, but do believe household formation has been gaining momentum, which bodes well for a stronger housing recovery in 2015. But there are also headwinds. Indeed, rising rents, declining rental affordability, and rising student debt levels remain barriers to household formation for many. Given the lack of clarity, certainly there is good reason to keep an even closer eye on this important measure over the course of the coming year. 

11+ Million Undocumented Immigrants in the U.S. Could Be Important for the Housing Recovery

by George Masnick
Senior Research Fellow

President Obama’s recent announcement that he will take executive action on immigration could be an important step in further supporting the sluggish housing recovery. Immigrants have historically been an important part of housing markets, especially for the past two decades. The foreign born have accounted for about one third of net new household formations since 1994 (Figure 1). Immigrants owned 11.2 percent of all owner occupied units in 2014, up from 6.8 percent in 1994, accounting for 27.5 percent of owner household growth over this period.

Source: Joint Center Tabulations of 1994 and 2014 Current Population Survey Data

For households under age 45, the foreign born have accounted for virtually all household growth over this period, as the aging of Generation X led to a decline in native born households in this age range. Meanwhile, as immigrants accounted for a similar level of household growth among heads over age 45, the overwhelming majority (80.3 percent) of total growth in this age range over the past 20 years is attributable to native-born adults. The particularly high numerical household growth among 45-64 year olds represents the aging of the baby boom generation into this age span during this 20 year period. 

Households headed by those under the age of 45, however, have had a very different mix of growth by nativity of the head. Figure 2 breaks household growth for under-45 year olds into 5-year age groups, and separates the native-born growth into natives with one or both parents being foreign born (second generation immigrants) and natives where both parents were native born. I have separated out the native-born children of immigrants to make the point that immigrant population growth has both an immediate impact on housing markets and a secondary impact (approximately 20-40 years later) through the children they bear in the U.S. As shown, second generation immigrants have accounted for the largest share of growth in under-30 year old households, followed by immigrants themselves. Looking forward, we expect that second generation growth originating from the higher immigration levels of the 1990s and early 2000s will be even larger.

Source: Joint Center Tabulations of 1994 and 2014 Current Population Survey Data

Over the next two decades, native-born cohorts that are third or higher generation immigrants will begin to exercise a more positive influence on household growth as millennials born after 1985 continue to age into young adulthood. And as the smaller Generation X enters middle age, immigrants and their native-born children will continue to bolster households in this age range, just as they did over the past two decades for the under-45 age group.

There is considerable potential for additional household formation and homeownership among the foreign born, particularly for the nation’s estimated 11 million undocumented immigrants, many of whom have been cautious about signing a lease or applying for a mortgage given their status. A recent Pew Research Center report estimates that 61 percent of undocumented immigrants have been here for 10 or more years, and the longer the duration of residence in the U.S., the more likely that immigrants will form independent households and pursue homeownership.  

Because the data in the above charts are national in scope, and because undocumented immigrants are more concentrated in some parts of the country than in others, their impact at a local level can be much more pronounced. While there are obviously a number of factors to weigh in deciding whether and how to offer a path to citizenship for undocumented immigrants, a greater appreciation of the role that immigrants play in our housing markets—and  through housing in the health of the overall national economy—should be a part of the discussion of immigration reform. Granting undocumented immigrants who have been working here for an extended period of time, especially those with children born in the U.S., the opportunity to remain in this country under the law will certainly be an important boost to the housing sector of the economy. 

Pent-Up Demand for Additional Household Formation is Fraught with Uncertainties

by George Masnick
Fellow

In early 2011, economists at the National Association of Home Builders (NAHB) reported that the slowdown in household formation that started in 2007 with the advent of the Great Recession had produced a 2.1 million household formation shortfall by 2010. The authors concluded that the demand for new housing should accelerate dramatically once the economic recovery releases this “pent-up” demand. Another pent-up demand calculation, by Jed Kolko at Trulia, estimated 2.6 million “missing households” in 2010. After three additional years in which the economy has improved on many fronts – albeit at a slow pace – the 2013 Trulia deficit in the household count was still estimated at 2.4 million. But how solid are these estimates and how likely is it that household formation rates will return to pre-recession levels?

One difficulty in making these calculations is that actual household growth estimates since 2007 vary considerably from year to year and are inconsistent among data sets (Figure 1). There is good reason to believe that the most widely used data to track household growth, the Housing Vacancy Survey (HVS, used in the NAHB calculation), has seriously underestimated the number of US households – and as a result household growth – since a revision in methodology in 2003.  The HVS’s average annual estimate of household growth since 2007 of 550-600,000 contrasts with the American Community Survey’s (ACS) estimate of 700-800,000 new households annually and the higher Current Population Survey (CPS) growth numbers of over 1 million new households annually since 2010. Without agreement on actual levels of household growth since 2007, it is quite impossible to gauge the shortfall in growth, and therefore the probable level of pent-up demand. 

Notes: 2013 ACS not available.  2010-2013 growth for the ACS a two-year average of 2010-2011 and 2011-2012 data.

The method used to estimate the “normal” level of household growth also matters. The NAHB number was based on a simple difference between “actual” household growth estimates for the 2007-2010 period, and a straight line trending of HVS household growth prior to 2007. Over the very short run this approach may be appropriate, but would not be expected to hold up over a longer period.

Kolko’s calculations are more sophisticated. Using CPS data, he computes the change in age-specific headship rates (the share of persons in an age group that head an independent household) from the average 2000-07 pre-recession levels. This change, when multiplied by the official annual population estimates for each year, gives the deficit in number of household formations in each age group due to changes in the propensity to form households. This method corrects for the effects on household formation of simple changes in the size and age structure of the adult population, which the NAHB method does not take into account. But what Kolko’s calculation does not control for is the increasing share of minorities in the population. And since Hispanics and Asians have lower headship rates than non-Hispanic whites this oversight is not trivial (Figure 2). In fact, a certain amount of the decline in household formation is due to the changing race/Hispanic origin composition of the population and not to the recent economic downturn.

This issue is exacerbated by an undercounting of growth in Hispanics and Asians over the past decade, as revealed by the results of the 2010 Census. The underestimating of Hispanic and Asian shares of the population in the CPS during the 2000s also means that pre-2010 CPS headship values are biased upward by overcounting the white share, due to incorrect population weights in the CPS survey, making the 2000-2007 benchmark headship rates too high, and exaggerating the decline in age-specific headship pre-versus-post recession.  

Even controlling for both age and race/Hispanic origin in the different surveys, we know that household formations have slowed relative to pre-recession levels, we just do not know by how much given concerns just discussed. We also know that the slowdown is likely a consequence of the recession. But, we are uncertain about whether the reduced level of household formation has been primarily driven by economic factors, or whether it is the result of more fundamental changes in attitudes and behavior regarding independent living by today’s young adults that might be partly recession-driven, but may also have deeper roots.

Lower rates of labor force participation, lower incomes of those in the labor force, rising rents, greater student loan debt and tight mortgage lending conditions are economic factors that could partly explain low levels of independent household formation. But we do not know whether these effects are likely to be short-term or long-term as an improving economy and governmental initiatives could reverse many of these factors quite quickly. 

But trends in college and graduate school enrollment, the structure of the labor force, the timing of marriage and childbearing, and attitudes about co-residence might lead millennials to form independent households according to a different timetable than the generations that preceded them, regardless of economic conditions. Going back to school for retraining is becoming increasingly necessary for technology oriented jobs in a rapidly changing economy. Employment in start-ups, freelance work, and spells of temporarily working long hours in different jobs and on various projects, followed by periods of downtime, are increasingly common. The timing and sequence of important life-course decisions such as co-habitation, marriage, and childbearing have become more fluid. Intergenerational interdependency at various life-course stages has also changed, with parents playing a larger role in financially supporting their children as young adults, in helping to raise grandchildren, and in opening their homes for spells of co-residence when their children ask. These factors may have inertia that will make them less responsive to economic changes.  

Source: Joint Center tabulations of CPS data.  Average of 2011, 2012 and 2013 values.

And even if market forces are the primary reasons for depressed rates of household formation, geographic variations in job and income growth and housing costs and availability mean that the magnitude and pace with which pent-up household formation is released should vary in different parts of the country. For all these reasons calculations about the extent of pent-up demand for housing and speculation about its causes, when demand will be released, and what kind of housing will be required to meet future demand are fraught with uncertainties. The latest Joint Center household projections hold household formation rates constant at average 2011-2013 levels, making no allowance for the future release of pent-up demand, and should therefore be considered conservative.   

JCHS Releases New Household Projections

by Dan McCue
Research Manager

Today, the Joint Center for Housing Studies posted its latest household projections. These new projections incorporate several updates to data that were made since our last projections in 2010. The 2013 projections use the Census Bureau 2012 Population Projections (released in late 2012 and early 2013), and also use more recent data to derive headship rates (ratios of households per person), specifically using data from the 2011-2013 Current Population Estimates and Current Population Survey March Supplements.   

Aside from the new data, the JCHS projection methodology remains largely unchanged from that used to create the 2010 series. The most notable change is that unlike in 2010 we do not make any adjustment to the Census Bureau’s population projections, as our concerns about what seemed to be overly high estimates of future immigration levels have now been addressed in the latest projections from Census. Since we are using the 2012 Census population projections as published, the 2013 JCHS household projections now contain high, middle, and low series, whereas the 2010 projections only had a high and a low series. The projections are also carried out an additional ten years, and so now extend to 2035.

The 2013 JCHS household projections are consistent with those from 2010.  In the near term (2015-2025), they call for annual household growth rates ranging from 1.16 million in the low series to 1.32 million in the high series, not far from the span of 1.15–1.36 million per year in our 2010 projections.  Differences between the 2013 and 2010 series largely follow differences in the underlying population projections (Figure 1).  Some difference is also due to updated headship rates, which are calculated for every 5-year age group by race and averaged across the years 2011, 2012, and 2013.  These are now slightly lower overall than those from 2007, 2008, and 2009 used in the 2010 projections (Figure 2).  (Click to enlarge.)

Sources: 2008 and 2012 Census Bureau Population Projections and 2010 JCHS Household Projections.

Note: Adult headship rates use CPS/ASEC household counts and Census July 1 Estimates of the population age 15 and older.  Source: JCHS tabulations of Census Bureau data.

Like the 2010 projections, our 2013 household projections also anticipate substantial growth in minority, senior, and single-person households in the coming decades (Figure 3).  In the 2015-2025 period for instance, minorities are projected to account for just over 76 percent of all household growth in each of the low-, middle-, and high- projections, with Hispanics alone accounting for 40 percent of total household growth. Additionally, growth in the number of households age 65 or older during this period is also expected to be 91 percent of the net change in households under the low projection and 81 percent in the high projection. As a result of the growth in senior households, single-person (4.4-4.7 million) and married-without-children households (4.0-4.3 million), two of the largest groups that comprise senior households, will together comprise nearly three quarters of all household growth in 2015-2025, but the number of married with children households will also see some growth as millennials age.

Source: 2013 JCHS Household Projections.

Tenure Scenarios Presented as Well

The report also includes a simple homeowner and renter projection scenario.  Under a steady-state scenario of constant homeownership rates by age, race, and household type, this analysis offers one look at how demographic changes in the composition of households may influence future homeownership rates. In this scenario, changing demographics are expected to be a positive influence on the overall homeownership rate through about 2025 (Figure 4).  After that time, the upward influence of the aging of the population gives way to greater downward pressure from young adult and minority household growth.  Figure 4 shows how downward pressure on homeownership rates is steepest in the high projections which, unlike the middle- and low-projections, expects no demographically driven growth in homeownership rates through 2025.

Note: Homeownership rates by age, race/ethnicity, and household-type are held constant. 

Source: Joint Center for Housing Studies tabulations of 2013 JCHS Household Projections.

Users of these estimates are cautioned that that they should be considered baseline projections and not a growth forecast. Actual household growth could deviate dramatically over short periods of time, as the projections reflect long-run, demographically driven trends and do not allow for any adjustments either upward or downward in response to changing economic conditions or cyclical factors.  Indeed, favorable economic conditions could increase headship rates above levels assumed in the projection and increase household growth, while a variety of factors could weigh down economic opportunities and result in lower household formation rates that depress future household growth.  

A Disappointing Report on Recent Household Growth Leads to More Questions than Answers

by Dan McCue
Research Manager

Although household growth is the major driver of housing demand, getting an accurate picture of recent trends in this measure is difficult, especially when Census surveys show conflicting trends.   On January 31, the most recent Housing Vacancy Survey (HVS) was released with Q4 numbers and some annual data for 2013.  As one of the few surveys that provide timely measures of household growth, the release was much anticipated in hopes that it would shed more light on trends of a recovery seen elsewhere in the housing market, but the results were disappointing, if not somewhat confusing. 

In its recent release, the HVS reported annual household growth of just 448,800 in 2013.  This represents a 48 percent drop in household growth relative to that from 2012 and marked the lowest annual household growth measure since 2008, in the depths of the Great Recession (Figure 1).

Source: US Census Bureau, Housing Vacancy Survey

In September we noted that the HVS was showing a disconcerting slowdown in household growth after finally having picked up in 2012.  With the annual number now in, this low measure of household growth in the HVS is puzzling, at odds with an assortment of other housing market indicators that have been painting a more positive picture for housing overall.  In particular, the drop in household growth did not mesh with several other trends:

• The much higher 1.375 million annual growth reported in the 2013 Current Population Survey Annual Social and Economic Supplement (CPS/ASEC);
• The same, steady increase in jobs in 2013 as during the previous year; and
• Increased momentum in the housing market, including a further decline in vacancy rates, an increase in new home sales, and an increase in housing construction during the year.

The divergent measure of household growth from the HVS is also troubling because while the HVS is known to have a downward bias in its estimated count of households, it has been useful in tracking short-term trends in that it provides more timely estimates than other sources and has generally been subject to less sampling error.  Indeed, while the CPS/ASEC and HVS both originate from monthly CPS surveys, the HVS annual household growth number is a 12-month rolling average of year over year growth, whereas annual growth in the CPS/ASEC is year over year growth for the single March survey, making it more volatile and less reflective of trends throughout the entire year.

But this is not the only—or most important—source of difference between HVS and CPS/ASEC household counts.  These two surveys differ more fundamentally in that CPS/ASEC arrives at its estimate of households based on weights derived from estimates of the total population and the share who are heads of household, while the HVS estimates households using weights that add up to estimates of the total housing units in the country, with the household count derived as the number of housing units that are not vacant (see Note on Table 3).  During census years, the CPS/ASEC head-counting method has generally produced totals much closer to the decennial Census –the Census Bureau’s benchmark survey of people and housing--while the HVS stock-controlled method has generally produced estimates that are lower by around 3-4 million households. This suggests the HVS household estimates are generally biased lower to begin with.

With its household estimates pinned to estimates of the housing stock, the surprisingly low HVS household growth estimate may be at least in part due to overly low estimates of growth in the total housing stock.  As shown in Figure 2, over the past few years, the total housing stock estimate used by the HVS has been growing slowly and very steadily since 2011, gaining around 350,000 units a year.  At the same time the Census Bureau’s New Residential Construction surveys show a significant upturn in the number of new housing units completed in 2012 and 2013, reaching 762,000 units.  In order for the HVS estimates of changes in the housing stock to be accurate, this would suggest a surge in demolitions that roughly offset the recent surge in new construction, which seems unlikely. 

Source: JCHS tabulations of US Census Bureau, Housing Vacancy Survey and New Residential Construction data.

There is a third census survey from which household growth can be measured, the American Community Survey (ACS), that might shed more light on the recent trend. The ACS is not as timely, however, and the results for 2013 are not due to be released until late 2014.  Still, for 2012 the ACS reported household growth levels in between the HVS and CPS counts (978,000), suggesting it might prove a moderate and viable tie-breaker between the other two surveys on the direction of the recent trend. But since the ACS household estimates are linked to the same housing stock estimates as the HVS chances are the ACS, too, will be subject to a downward bias.

Overall, the discrepancies in these surveys are troubling given the importance of household growth as an indicator of the health of the economy and the housing market.  For the time being, housing analysts are flying in the dark on this key metric.

Although the Population is Rapidly Aging, Young Adults Will Still Drive the Demand for New Housing

by George Masnick
Fellow

Hardly a day goes by when we are not reminded about how rapidly our population will age over the next several decades as the baby boom crosses the 65+ threshold.  For housing analysts, an aging population is often thought of as the key demographic trend that will drive housing consumption over the next 20 years.  This shift in age structure does not, however, mean that elderly population growth will be the primary driver of the demand for newly built housing.  While most of the population growth will take place among the elderly, that increase, for the most part, does not represent people active in the housing market. Younger age groups will not experience much population growth, but this is because, among those under 35, large cohorts are replacing other large cohorts – sometimes a bit smaller and sometimes a bit bigger.  But most of the members of these large younger cohorts will enter the housing market for the first time in their 20s and 30s.  They will consume most of the newly built housing.  Here are the details.

The aging of the United States population is dramatically shown in Figure 1.  Between 1970 and 2010, most adult population growth took place in the under 65 age groups.  Starting in 2010, aging baby boomers begin to shift most of the population growth to the over 65 age groups.  Each decade during the past 40 years (the leading edge of the baby boom, those born 1946-1955) has provided the biggest share of population growth of any 10-year age group (lower panel of Table 1 cells highlighted in yellow).  In the 1970s, baby boomers created growth among young adults, gradually shifting the growth to older and older age groups in successive decades.  The dominance of baby boomers in the population growth equation will persist until sometime after 2030 when they begin to reach the end of their lives in large numbers.

Source: Decennial Census data and Census Bureau 2012 Middle Series Population Projections.

Notes: Shaded cells represent largest 10-year cohort in each decade (green) and largest growth (yellow).
Source: Decennial Census counts and 2012 Census Bureau middle series population projections.

Many are quick to conclude that, since population growth drives most of the demand for new housing construction, we must primarily build for the elderly.  The problem with this logic is that elderly population growth does not represent new additions to the population, and most elderly are already housed quite comfortably and show little inclination to move to a different residence. Strong elderly population growth is simply the aging of a large cohort replacing the smaller cohort that came before them - they are not new people entering the housing market.  As I’ve discussed in a previous post, for the remainder of this decade and the next, elderly baby boomers will largely age in place.  Fewer than 4 percent of the population over the age of 65 changed residence in 2012-13.  Over 80 percent of the elderly live in owner-occupied housing.  For those 65+ living in owner-occupied housing, the annual mobility rate is now about 2 percent.

Source: 2013 Current Population Survey, Table 7.

As I mentioned earlier, movers can be thought of as driving the demand for new housing since non-movers by definition stay in their current homes.  While the number of people over age 65 is growing rapidly, given the very low mobility rates of this population the number of movers that are elderly will still be small.  Multiplying the average size of each 10-year age group of adults (upper panel of Table 1) by the average percentage who change residence each year will give the annual number or persons in each age group that are expected to move over the decade.  In the 2000-2010 decade, these movers, or recent occupants, were clearly dominated by young adults age 25-34 (Figure 3).  This cohort does not have the largest population; it is about 5 million less in number compared to the baby boomers age 45-54 in 2010 (upper panel of Table 1). But at over 40 million, its size is substantial.  Having the highest rate of geographic mobility, 25-34 year olds accounted for almost three times as many recent occupants during the 2000-2010 decade as the largest baby boom cohort.  Each year during that decade, persons over the age of 65 averaged only 6.2 percent of total moves (8.5 percent in 2013).  Such low representation of the elderly among movers will persist for the foreseeable future. That share is projected to increase only slightly during the next two decades to an average of about 10 percent in 2020-2030 in spite of the large projected growth in the 65+ population.  Note that these projections likely bias upward the estimates of demand for new market housing by the elderly because the resident population used as a base in the projections include the elderly living in nursing homes and prisons.

Notes: Recent Occupancy numbers = average number of persons in age group during decade x average annual age-specific annual mobility rate.  Number of persons is average of numbers at beginning and end of decade.  Average annual mobility rate is the mean of the age-specific rates at the beginning and end of decade. Projections hold mobility rates constant at 2013 levels.

Source: see Table 1 and Figure 2.

In keeping with their lower mobility rates, older adults are underrepresented in newly built housing.  Households over the age of 65 in 2011 accounted for 22.1 percent of all households, but just 14.4 percent of occupants of units built since 2000 (Figure 4).  Among all owner heads of households, 26.9 percent were over the age of 65, but just 14.7 percent were heads in owner units built since 2000.  However, older households do account for a larger share of heads of households living in new rental units: 13.4 percent of renter heads are elderly, nearly equal to their 13.6 percent share of occupied rental units built since 2000.  This greater parity in representation of the elderly in newer rental units is consistent with the higher mobility rates of older renters compared to older owners.

                                                          

Source: Joint Center tabulations of 2011 American Housing Survey.

As the large baby boom cohorts age into the 65+ age groups, will they increase the share of elderly who live in newer housing?  An increase proportional to their growing share of the adult population (adjusted for their lower mobility rates) is certainly expected.  For example, according to recent Joint Center household projections, the elderly accounted for 23.3 percent of all households in 2014, increasing to 26.4 percent in 2020 and to 31.5 percent in 2030 when all baby boomers are over the age of 65.  If the elderly maintain their share of households living in newer units at current levels, about 20 percent of newly built units in 2030 will be occupied by heads over the age of 65.  But to increase the share of newly built housing occupied by the elderly significantly above that figure, tomorrow’s elderly will need to relocate out of older housing at higher rates than we now observe. 

For the next 15+ years, helping the elderly achieve a better fit with their housing will largely involve initiatives to support aging in place. The need for assisted living facilities and nursing homes will gradually increase as the baby boom ages, but the greatest increases will take place after 2030. Whether the elderly are likely to increase their mobility rates within market housing in the near-term future is worth considering.  Public and private efforts to provide housing that better serves the needs of an aging population could spur greater mobility among those ages 65+.  However, there are a host of demographic, social and economic characteristics of baby boomers that argue for less, not more, geographic mobility among the next generation of elderly. This topic will be the subject of a future blog post.