What Would it Take to Make Neighborhoods More Equitable and Integrated?

by Katie Gourley, Graduate Research Assistant

How do household decisions about where to live perpetuate residential segregation, and what would it take for such choices to result in more inclusive neighborhoods? Three papers released today by the Joint Center for Housing Studies explore these questions from somewhat different perspectives. The newly released papers, which were presented at A Shared Future: Fostering Communities of Inclusion in an Era of Inequality, a symposium hosted by the Joint Center, include an overview paper by the panel’s moderator and two papers by panelists examining key issues in more detail. The papers are:

Justin Steil &

Reed Jordan,

MIT

Household Neighborhood Decisionmaking and Segregation, an overview paper co-authored by Justin Steil, the panel’s moderator, and Reed Jordan, investigates what we know about households’ decisionmaking processes and explores the ways that technology and other interventions might help create more integrated places. They note that notwithstanding the significance of schools and other local amenities, the racial composition of a neighborhood is a significant determinant in the residential decisionmaking process. Moreover, they add, while homeseekers increasingly rely on the internet, it is not yet clear how that reliance impacts the makeup of neighborhoods. However, they note, it seems clear that different sources of information have implications for segregation and may serve as points of leverage for pro-integration interventions.

Ralph McLaughlin &

Cheryl Young,

Trulia

Data Democratization and Spatial Heterogeneity in the Housing Market, by Ralph McLaughlin and Cheryl Young, argues that improved access to residential real estate data has the potential to affect residential settlement patterns in two countervailing ways. On the one hand, it could expand individuals’ housing search choice to include properties in more diverse neighborhoods. Alternatively, it could increase the demand to live in amenity-rich locations, which might price out existing and future residents (unless the supply of housing in those locations grew at a similar rate). However, they argue, the extent to which households might be priced out of a neighborhood is not primarily influenced by data availability but rather by the ease with which housing supply can be increased to meet demand in those areas. They therefore recommend three policy approaches: reducing exclusionary and restrictive zoning policies in expensive, amenity-laden markets; giving housing choice voucher (HCV) recipients the option to conceal their voucher status from landlords during the application process; and requiring that some available Low Income Housing Tax Credit funds be used in “high-value” Census tracts.

Tarry Hum,
Queens College

Minority Banks, Homeownership, and Prospects for New York City's Multi-Racial Immigrant Neighborhoods, by Tarry Hum, focuses on the role of Asian minority banks in in lending to Asian borrowers for residential property purchases in Queens and Brooklyn. Established to counter financial exclusion resulting from discrimination and linguistic and cultural barriers, these banks historically have been a key source of credit, especially for Asian immigrants who may not qualify for conventional loans. However, using data sets from 2010 and 2015, Hum shows that there was a significant rise in lending by these banks to investors rather than owner-occupants. She concludes by exploring how these changes may be driving up prices, displacing low- and moderate income renters, and spurring illegal conversions – changes that together may be destabilizing many of the neighborhoods where the loans are being made.

The three papers build on previously released papers from the symposium that discuss the nature of residential segregation in the US, its consequences, rationales for public policies to address those consequences, and priorities for action. Over the next several months, the Joint Center will be releasing additional papers from the symposium that will focus on promising strategies in a variety of areas that would help foster more inclusive residential communities. The papers also will be collected into an edited volume that will be published in 2018.

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Additional papers from the A Shared Future symposium are available on the JCHS website. 

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

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.

New Population Data from U.S. Census Reveals Increasing Migration to Sunnier Regions

by Sonali Mathur

Research Assistant

Last week, the U.S Census Bureau released new population estimates and its analysis of components of population change for counties and metro areas. This data includes total population estimates for July 1, 2015, total population change, changes in population due to natural increase, and domestic and international migration between July 1, 2014 and July 1, 2015.

We can see that domestic migration continues on a post-recession path of recovery and with it, long-term patterns of growth and movement to the Sunbelt, slowed by the downturn, are reappearing. Suburban counties in the South are once again attracting the most movers, while northern, largely Midwestern counties are experiencing the greatest population losses.

According to this latest release, the Houston, Dallas, Atlanta, Phoenix and New York metro areas rounded the top five for net population growth. In Texas, the metro areas of Houston and Dallas-Fort Worth saw population growth of 159,000 and 145,000 residents respectively over the past year. Two other metros in Texas—Austin-Round Rock and San Antonio—each grew by 50,000 people, putting them among the top growing metros in the nation. Collectively, these four metros added 412,000 in population. In all, Texas was home to 4 of top 16 metros in terms of population growth, in keeping with state-level data released late last year that showed Texas as the state with the most population growth followed by Florida, California, Georgia, and Washington. Among the top 100 metros, in percentage terms the Cape Coral-Fort Myers, FL Metro Area saw the highest population gain of 3.3%.

In all, 96 metros lost population over the past year. Among the top 100 metros, the biggest net population loss was in the Chicago area where the population dropped by 6,200, followed by Pittsburgh which lost 5,000 people.

The micropolitan areas saw a net growth of 27,000 with more than half (a total of 261) micro areas gaining population, four of which added more than 2000 people.

At the county level, population growth was also skewed to the south and west with the top 30 counties for total population growth being located in either the South or the West. The top three for net population gains were first Harris County, Texas and Maricopa County, Arizona, followed by Los Angeles County, California. Counties with the largest population losses were Cook County, Illinois which had a net negative population change of nearly 10,500, and Wayne County, Michigan, which had a net negative population change of nearly 6,700 people.

In percentage terms, among counties that had a total of more than 100,000 people in 2015, the top counties that gained the most population growth are in Texas, Hays county (5.2%) and Comal County (4.5%), while the counties that lost the most are San Juan County, NM (-4.2%) and Hardin County, KY (-1.8%). Though these counties with highest percentage losses are in the South and West, overall the counties with largest net losses were overwhelmingly in the Midwest and Northeast, and the ones with the biggest net gains were concentrated in the South.

In addition to overall gains and losses in population in metros and counties, the population estimates data also show components of growth in terms of net gains and losses from international immigration as well as domestic migration, which allow us to see what parts of the country are attracting people from around the country and those that are losing population moving to other areas.

As for domestic migration, top ten counties with highest net inflows were in the Sunbelt states of Arizona, Nevada, Florida and Texas. Maricopa County, Arizona saw the highest net domestic inflow, which was 48% of the net population change in the county. Clark County, Nevada saw the second highest net domestic inflow, which was 54% of the net population change in the county. Lee County, Florida moved up to the third spot from the ninth in 2014 for net domestic inflow, which was 92 % of the net population change in the county.

Los Angeles County, California followed by Cook County, Illinois saw the most net domestic outflow for the second year in a row.

In general, counties and metros that were attractive to domestic migrants also had high levels of international immigration. However, some counties that saw high international immigration, such as Los Angeles County, Miami-Dade County, and Queens County, also saw high domestic out migration. Indeed, in many areas gains from international immigration staved off potentially larger population losses due to domestic migration.

The map below shows the changes in population for each county between July 2014 and July 2015. Click on a county to display its data. Select a tab to map percent change in population, net international immigration or net domestic migration. [May take a few seconds to load. Click on the (i) in the upper right to reveal color key information.]




Detailed explanation of the census bureau methodology.

Socialize: http://arcg.is/1pYaNfM

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. 

How Does Geographic Diversity in Age Structures Impact Housing Market Dynamics?

by George Masnick
Senior Research Fellow

As the youngest of the baby boom generation has now turned 50, there is much talk about the overall aging of the U.S. population. But recently released Census Bureau population estimates for states and counties tell a more nuanced story about the diversity in age structures in the U.S.  The census release notes that the oldest county (Sumter County-FL) has a median age of 65.5, while the youngest (Madison-ID) has a median age of 23.1.  Quite a difference!  Other counties among the oldest include Charlotte-FL (57.5), Alcona-MI (56.9), Llano-TX (56.9), and Jefferson-WA (55.9).  The five youngest counties also include Radford City-VA (23.3), Chattahoochee-GA (23.9), and Harrisonburg City-VA (24.2), and Utah County-UT (24.2).  The U.S. median age is 37.6. 

We should perhaps not be surprised that the county with the oldest population is in Florida, or that Idaho and Utah, with their Mormon influences, should have the counties with the youngest populations. But what is going on in Michigan, Texas, and Washington counties to rank among the oldest, and in Georgia and Virginia to produce places with the youngest populations?

There are three main demographic factors that influence the age structure of a population: 

1. Domestic migration patterns of both young adults and the elderly; 
2. Settlement patterns of international immigrants; 
3. Levels of fertility of both the immigrant and native born populations.  

Differences in life expectancy could also influence age structures if those differences are large.  For states and counties in the U.S., however, mortality differences are not sufficient to affect differences in median age. 

Places with net domestic out-migration of young adults, and/or in-migration of elderly will be older (younger if these migration patterns are reversed).  Florida is a destination state for retirement migration, as are North Carolina, Arizona, and other warm weather and low-tax states in the south and west.  Maine, West Virginia and many rust belt and Great Plains states lose young adults on net, so places in these states will also have an older age structure.

Immigrants tend to be young and have higher fertility compared to the native-born, so places that are immigrant destinations will be younger.  While states on the coasts and along our southern border still attract the majority of immigrants, states in the interior have increasingly become immigrant destinations as immigrant networks have spread beyond gateway states. 

Finally, fertility levels are the primary determinant of a population’s age structure.  When fertility is above replacement (more children born than reproductive-age adults in a family) the population pyramid is broader at the base, and median age is lower. The pyramid becomes more mushroom-shaped when fertility is below replacement, and median age is higher. 

When the population unit is relatively small, as with most of the counties listed above, these demographic factors can reinforce one another and create extreme values.  For larger units of population, such as large counties, metropolitan areas and states, differences should be less extreme, but they can still be significant. 

The population estimates from which median ages were calculated contain detail by race/Hispanic origin and sex, allowing us to examine the percent minority as a surrogate for the influence of immigration and the boost to overall fertility levels that immigrants and native-born minorities provide.  We can also look at a measure of recent total fertility by calculating the ratio of children age 0-4 to women in the primary reproductive ages of 20-44.  We cannot get a direct estimate of net domestic migration by age group from the published population estimates, however.  

The table at the bottom of this post, constructed from the 2013 population estimates, ranks states on median age, percent minority, and fertility.  While Florida has the county with the highest median age, the state as a whole is only the 5^th oldest, surpassed by Maine, Vermont, New Hampshire and West Virginia.  The lower the percentage minority in a state, the higher the median age (Figure 1). The oldest states are those where young immigrants and native-born minorities with higher fertility have not settled.  Maine, Vermont, West Virginia and New Hampshire rank the lowest on percent minority. In addition, the lower the total fertility rate, the higher the median age (Figure 2). This second relationship is the stronger of the two that are graphed, and the relationship holds fairly well across the entire range of fertility (discounting DC as an outlier).  The New England states collectively are also near the bottom of the ranking on total fertility.

Source: U.S. Census Bureau Population Estimates

Older states may be destination states for retirement migration, but can also have lost young adults from out-migration to states with bigger cities and more job opportunities.  For example, according to the 2012 American Community Survey, Maine gained 27,500 residents from other states during the previous year, but lost 38,500.  If most of the out-migration from Maine were young adults, the effect would be to increase the median age.

The youngest states, however, are more of a mixed bag.  Utah’s very high fertility level – the highest in the nation – is sufficient to secure its ranking as the state with the youngest median age. Utah is not completely lacking in diversity - its percent minority (20.3%) is just the 18^th lowest, but the total fertility rate in Utah is primarily driven by its non-Hispanic white population’s high rate of childbearing.  Alaska, the second youngest state, has a large minority population (mostly native Alaskans), as well as levels of fertility that are well above the U.S. average.  Its young ranking, however, is likely also determined by in-migration of young adults to work in energy and nature oriented jobs, and out-migration of the elderly to warmer climates.  The District of Columbia has achieved its ranking as the third youngest in all likelihood because of in-migration of young adults to work in Washington for a spell.  These adults are largely single, as suggested by DC’s extremely low fertility. But also contributing to DC’s young age structure is the fact that the percent minority is the highest on the mainland (64.2%).  Texas is the 4^th youngest state, both due to its high percent minority (56%) and high fertility.  Texas has received consistent growth from both immigrants and young domestic migrants in recent years.  The final state among the top five youngest is North Dakota, which has been the beneficiary of considerable in-migration of young adults to work in the booming energy sector in the western part of the state.  North Dakota’s fertility rate is also among the highest, attesting to the impact of a favorable economy on family formation.   

Geographic diversity in age structures has direct implications for housing market dynamics.  Places with younger age structures will require new construction to house young adults, both now and in the future.  If the young age structure is created by higher fertility, homes will need to be larger to accommodate larger families.  If the younger age is created by in-migration of singles, a different housing mix is required, at least in the short run. 

Places with older populations are expected to show a greater balance between supply and demand for existing housing.  An older age structure brought about by low fertility and out-migration of young adults will have less need for new construction.  This is especially true if the existing housing is located in places where young adults want to and can afford to live.  However, if future demand for existing housing by young adults or older in-migrants is not there, older adults may be less able to sell their homes, and we can expect higher rates of aging in place. In these places there would be a greater need for modification and upgrading of existing housing to help the elderly safely stay in their homes.  On the other hand, if the older age structure is primarily the result of in-migration of retirees, and if that in-migration is sustained, there will be more opportunities for new construction and for the elderly to sell their homes in order to adjust their housing needs.  

Source: 2013 Census Bureau population estimates for states and counties.

*Fertility Rate is the number of children age 0-4 per 1000 women age 20-44. 

Fertility Rates and Age Structures – The Underpinnings of Replacement Fertility in the U.S.

by George Masnick
Fellow

The U.S. fertility rate is at near replacement level, where a woman bears two children over her lifetime (just enough to ‘replace’ herself and her partner).  The Total Fertility Rate (TFR), which is how many children the average woman in the U.S. will have if she survives through the reproductive ages and bears children at each age at rates U.S. women are currently experiencing, is just below this level.  Replacement fertility leads to a “pillar” like age structure, where the base of the pillar (children) contains about the same number of people per five-year age group as the middle of the pillar (parents).  For the U.S., that number is currently about 20 million (Exhibit 1).

Source: http//www.census.gov/population/international/data/idb/informationGateway.php

This situation can be contrasted with fertility rates and age structures in most other industrialized countries.  Below-replacement fertility in much of Europe and in a number of Asian countries has created “mushroom cloud” shaped age structures where the numbers of children are just fractions of the size of the parents’ generations.  In Germany, for example, the 0-4 and 5-9 age groups are only about half the size of the 40-44 and 45-49 age groups (Exhibit 1).  Age structures for other countries with TFRs of 1.6 or less are broadly similar to Germany’s (Table 1).  Such an imbalance in age structures has the potential to create enormous problems for these societies in areas such as institutional stability (e.g. schools), labor force succession, housing market dynamics, and old-age social security.  Shrinking class sizes, workforce shortages, declining demand for larger homes that prevent older households from downsizing, and payroll tax collections that are insufficient to pay for retirement benefits are all consequences of long periods of below-replacement fertility.

Source: http://www.oecd.org/berlin/47570005.pdf

So why is the U.S. such an outlier compared to other industrialized countries in having experienced recent near replacement-level fertility and a relatively healthy age structure?  And, is the U.S. likely to retain this advantage in the future?  The answers to these questions point to the importance of immigration in shaping the present demography of the U.S., and to uncertainty about future levels of immigration and the role it will play in the future.

Decomposing the U.S. age structure into immigrants (first generation), the children of immigrants born in the U.S. (second generation), and third or higher generations (parents born in the U.S.), illustrates the importance of immigration in both backfilling the smaller baby bust cohorts born between the mid-1960s and mid-1980s and in increasing the cohort size of children born here in the past 20 years (Exhibit 2).  According to a recent Pew Research Center report, immigrant fertility rates are about 50 percent higher than native-born rates.    While in 2010, only 17 percent of women of reproductive age were immigrants, immigrant women bore a quarter of all children born in the 2000s. Replacement level fertility in the 2000s was achieved by above-replacement immigrant fertility counter balancing below-replacement native fertility.

Current Population Survey Annual Socialand Economic Supplement, 2010, Table 26

The future stability of the age structure of the U.S. will depend on levels of immigration and on fertility trends of both the native born and of immigrants.  The Pew report cited above documents how dramatically fertility rates have fallen since the Great Recession, with the largest percentage declines occurring among immigrants.  Between 2007 and 2010 the number of births per 1,000 women age 15-44 (the General Fertility Rate) fell for native-born women by 6 percent while for foreign-born women the decline was 14 percent. Whether fertility declines have been mostly driven by high unemployment and low wages and so will rebound with an improving economy is too soon to tell.  Any rebound could still leave fertility levels below the replacement rate.  But in any case, it is unlikely that U.S. women will soon adopt the very low levels of childbearing that characterize much of the developed world.  The influence on fertility of “pro-family” fundamentalist religions in the U.S. and the not-unrelated political hostility to birth control and abortion in many parts of the country continue to support higher levels of U.S. childbearing. 

However, the size and composition of future streams of immigration are very much in question.  Immigration reform has been slow to gain traction in the U.S. Congress, and the outcome of any new legislation on future immigration levels remains uncertain.  More to the point, perhaps, is the fact that several important sending countries are undergoing fundamental transformations in both their economies and demographics that will diminish their propensities to send immigrants.  For example, Mexico accounts for about 30 percent of all foreign-born living in the U.S., and immigration from Mexico has long been a safety valve to release excess population growth in that country.  But Mexico has reduced its fertility by over one-half since 1985, with much of the reduction occurring in the past decade.  In the future, as long as Mexico’s economy continues to prosper, we can expect fewer will need to leave Mexico to find work.  Similar transformations are occurring in other sending countries such as India and China. Age structures in these countries have begun to transform from “pyramid” to “pillar” shapes.

Before closing, I want to say a few words about one industrialized country, Sweden, which has succeeded in maintaining near replacement fertility without depending on high fertility immigrants.  There are indeed immigrants to Sweden who are needed to fill certain jobs, but they mostly come from other low fertility countries in Europe, especially the Balkans, and the immigrants retain the low fertility of their countries of origin.  Sweden has a long history of low native-born fertility going back to the 1970s, and has gradually adopted strong social policies to encourage its citizens to voluntarily become parents, including generous maternity/paternity leaves, significant health care and housing benefits, and low-cost, high quality, and readily available daycare. But even with such strong pro-natalist policies, Sweden can barely keep its fertility at near-replacement levels.

We should be thankful that our recent history of high-fertility immigration has helped create an age structure that will lead to far fewer problems in the near future compared to those facing other industrialized countries.  Whether we continue to retain this advantage will depend on future levels of both immigration and fertility (of both the native-born and the newly arrived).  To avoid the U.S. moving toward a mushroom cloud like age structure, absent widespread pro-natalist programs and policies as in the case of Sweden, the depressed immigration levels and declining fertility trends of recent years will need to be reversed.  

A Word of Caution about Census Bureau Projections

by George Masnick
Fellow

The Census Bureau recently released its high and low immigration series population projections going out to 2060, complementing its middle series released in December 2012.  Among the talking points in the press release announcing the projections was the assertion that the high immigration series “projects that the U.S. resident population will become majority-minority by 2041, two years earlier than the December (middle series) projection of 2043.”

The point is well taken that the growth of the minority population depends upon future levels of immigration, and higher immigration means an earlier date at which the country becomes majority-minority. But between now and the 2040s there is a great deal more uncertainty about immigration trends than is captured in the Census Bureau’s latest assumptions, including uncertainty about how attitudes and norms will affect who is counted as minority.  In addition, all three of the Census Bureau’s population projections use the same assumption about projected fertility levels of each race/Hispanic origin group.  Not only are fertility trends difficult to predict over many decades, but different immigration levels will surely affect fertility rates.

The new middle series immigration assumptions trend from 725,000 per year in 2012 to 1.2 million in 2050. Low assumptions trend from 702,000 to 808,000, and high assumptions from 747,000 to 1.6 million annually.  All three immigration assumptions are well below those of the previous Census Bureau population projections released in 2008 and 2009, with the new high immigration series even projecting fewer immigrants in 2050 than the previous low immigration assumption (Figure 1). Such a wide range of uncertainty about future levels of immigration should make one wary about the reliability of projections that reach almost 50 years into the future.

Source: U.S. Census Bureau 2009 National Population Projections

However, the projected level of immigration is not the only area of uncertainty that will affect the projected white-minority tipping point.  Predicting a specific year when the population actually becomes majority-minority sometime three decades ahead will also require assumptions about how Americans in the future will identify themselves in terms of race and ancestry.

Perhaps the most important wild card is the growing rate of inter-ethnic/race marriages, particularly when one parent is non-Hispanic white and the other is not, both because the rates of intermarriage will help determine the future minority composition of the population and because it is unclear how the children of such unions will be classified in future censuses and how they will self-identify as adults.  According to a Pew Research Center report, among all newlyweds in 2010, 9% of whites, 17% of blacks, 26% of Hispanics and 28% of Asians “married out."  Most of these marriages involved one partner who was non-Hispanic white. The same report notes that during the past 25 years, public sentiment about inter-marriage has changed markedly: in 2010, nearly two-thirds of Americans said it “would be fine” with them if a member of their own family were to marry someone outside their own racial or ethnic group, while in 1986, two thirds of the population held the opposite view.  During the next 25 years, marrying out is likely to become even more common and more widely accepted.

Such trends in inter-marriage tell only part of the story regarding inter-racial childbearing, however. The percentage of births that are non-marital has been increasing steadily since the 1940s, and the greatest increases have taken place in recent years.  Today, 36 percent of all births taking place in the U.S. are non-marital, with much higher percentages among teens (86 percent) and women in their early 20s (62 percent). Given that younger cohorts are more favorably disposed to inter-racial relationships, many of which result in childbearing outside of marriage, the statistics on inter-marriages in the Pew report could well underestimate the implications for future inter-racial/ethnic childbearing.

The number of inter-marriage/partnerships taking place over the next 30 years, the number of children born to these relationships, and how the race/ethnicity of these children get classified in censuses and surveys will fundamentally affect the share of the population that is identified as minority.  More importantly, how these children will self-identify as adults in 2040 is basically unknown.  Census Bureau population projections tacitly assume that this variable is held constant at today’s levels, and that young adults will self-identify in the future the same way that they were identified as children by their parents.

A strong argument has been made that racial and ethnic identity is highly variable over time and depends upon social and political conditions. In 1970, the question on Hispanic origin was added to the Decennial Census, and in 1980 the question on ancestry, both after concerted political lobbying by Latinos in the case of the former and those of European descent for the latter.  The Asian community successfully lobbied to expand the number of Asian options listed in the 1990 census. However, since then the percentage of the population whose ancestry was not identified by the census has increased, slightly between 1980 and 1990, and dramatically between 1990 and 2000 (increasing from 11 percent to 20 percent).  In 2010 the ancestry question was shifted to the American Community Survey.  In that survey ancestry was unidentifiable or not reported for about 12 percent of the population, but only after a persistent effort with follow-up interviews with respondents having not answered this and other questions. Such follow-up was not conducted for the 2000 census.  

In short, ancestry appears increasingly to be less important in how Americans identify themselves. And if ancestry, and perhaps by extension race and ethnicity, becomes less important in how we self-identify as Americans, it is entirely likely that in 30 years the percent minority will become a statistic that has become less robust.  Specifically, fewer persons of Hispanic origin might check that box. Likewise, fewer of mixed-race ancestry might identify as such.

A third way that the majority-minority tipping date might be influenced are the apparently arbitrary definitions of whom the Census Bureau counts as minority.  For example, immigrants from Brazil are not counted as minority (Hispanic/Latino) because of Portuguese ancestry, even though most Brazilians also have some indigenous South American native ancestry.  Persons with ancestry in the Middle East and in North Africa are also categorized as white. But a future OMB directive could require that these persons be counted as minorities.

Finally, it has already been demonstrated that such simple factors as questionnaire wording, order of asking questions about nativity, race and ethnicity, and examples used as prompts to questions, will all influence responses.  It is very unlikely that current questionnaire protocols for these items will be used decades in the future.

While there is a lot of uncertainty about the projections 30-50 years into the future, the new projections for the next 10-20 years are likely to be much more accurate.  And they are extremely valuable for showing the magnitude and importance of different immigration assumptions for relatively near-term trends in population growth and for broadly understanding the changing age, race and ethnic composition of the population. Longer-term trends in race and ethnic composition will depend as much on fertility levels, on rates of intermarriage, and on how we think about others and about ourselves, as it does on actual immigration trends.

Childless Households Have Become the Norm

by George Masnick
Fellow

In 1960 almost half of all households were families with children under 18.  Since then, the number has fallen to under 30 percent (Figure 1).  By definition, the declining share of family households with children exists because households without children have increased more rapidly (Figure 2).  There are many reasons for this trend: delayed age at marriage and later age at childbearing, smaller family sizes, higher divorce rates, and more couples choosing not to have children (Table 1).  The changes in each of these measures over the last few decades are quite striking. In 1960 the median age at first marriage was 22.8 for men and 20.3 for women, compared to 28.6 and 26.6 in 2012.  The share of households with four or more people in 1960 was over 40 percent, falling to just under 23 percent in 2012.  Women who were 25 in 1960 ended their childbearing years in the mid 1980s with only 8.5 percent of them remaining childless. Women born in 1960 finished childbearing in 2010 with nearly twice as many of them childless (16.3 percent). In 1960, only 13 percent of all households were single persons, but by 2012 that percentage had risen to 28. All of these trends result in households having fewer children and fewer households having any children at all. (Click charts to enlarge.)

Source: Current Population Survey March and annual Social and Economic Supplement, 2012 and earlier. Table FM-1.  Minor children numbers from Census Bureau's population estimates for July 1 of each year.

Source: Current Population Survey March and annual Social and Economic Supplement, 2012and earlier. Table FM-1

Source: Census Bureau Current Population Survey historical tables.

The interesting aspect of this long-term trend is that it continued in spite of the strong upswing in the sheer number of American children, which grew after 1990 (also Figure 1).  That increase is due to the largest baby boomers having their own children (the echo boom) and to childbearing by the flood of immigrants who arrived between 1985 and 2005.  (Note that in 2012, fully 87.5 percent of children under the age of 18 who have an immigrant parent were themselves born in this country.) 

To be sure, baby boomer and immigrant childbearing did increase the actual number of households with children.  For example, the number of households with children under the age of 18 increased from 33.3 million in 1985 to 38.6 million in 2012. This 5.3 million increase was far less than the 11.3 million increase in total number of children in the population over this period because many households with children contained two or more children under the age of 18.  More importantly, however, the increase in households without children surpassed the 5.3 million growth of households with children by a considerable margin.

Two key reasons for the recent increase in childless households have been the aging of the population and increasing longevity. The large baby boom generation (age 45-64 in 2010) is now entering the empty nest stage (at least regarding children under 18). Between 2002 and 2012, households with at least one child, headed by today’s 45-64 year old cohort, declined by 12.3 million. There are still 11.5 million 45-64 year old headed households with children, and most will become households without children over the next decade.  Furthermore, empty nest households headed by those over the age of 65 are surviving longer and longer, making it likely that the trend in the decline of households with children will continue well into the future.

Significantly, the decline in the number of households with children accelerated after 2007.  Much of the decline can be explained by the sharp drop in the number of births. Annual births rose from just over 4 million in 2001 to over 4.3 million in 2007, the highest on historical record, but then fell to just below 4 million in 2011.  The total fertility rate (births per 1000 women age 15-44) fell from 69.5  (a 17 year high) to 64.4, a decline of 7.3 percent over this same period. Both the decline in births and the drop in the fertility rate are linked to the decline in immigration that followed the Great Recession. Because newly arrived immigrants are concentrated in the childbearing ages, and because immigrants have higher fertility than the native born, the loss of immigrants has had a disproportional effect on declining fertility.  The effect of the Great Recession on lowering fertility among the native born is also of importance, but this decline could be temporary.  The echo boom generation began to turn 25 in 2010, and has most of its childbearing years yet ahead of it. A return to higher levels of immigration and/or a rebound in fertility could reverse the decline in number of births and ease the long-term decline in the share of households with children, but will not likely reverse it.