Thursday, August 20, 2015

A City Revival? It Depends on Your Definitions

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

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

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

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

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

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

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

Wednesday, August 12, 2015

Despite Declines in Homelessness, Family Homelessness Persists

by Irene Lew
Research Assistant
Since the 2010 release of Opening Doors, the first federal strategic plan to end and prevent homelessness, total homelessness in the US is now down 10 percent, from about 640,500 people in 2010 to 578,400 by 2014 according to HUD’s annual Point-in-Time (PIT) counts. This decline has been driven by a significant ramp-up in federal resources devoted to ending homelessness over the past decade. Although federal investment has resulted in substantial reductions in homelessness among at-risk groups such as veterans and individuals experiencing chronic homelessness, homelessness among families has persisted.  According to HUD’s most recent PIT count, more than a third (37 percent) of the total homeless population in the US is made up of people in families, with children under the age of 18 accounting for nearly 60 percent of this group. In fact, compared to other at-risk groups, homelessness among persons in families has declined at a much slower rate since 2007 (Figure 1).

Source: US Department of Housing and Urban Development, 2014 Annual Homeless Assessment Report to Congress: Part 1- Point-in-Time Estimates of Homelessness.

Most notably, much of the decline in family homelessness in recent years has occurred among the unsheltered population (those living on the streets, in abandoned buildings, vehicles or parks), while the number of sheltered homeless people in families (those living in emergency shelters, transitional housing programs, or safe havens) continues to rise steadily (Figure 2). Nearly nine in ten homeless people in families were staying in shelters in 2014. In New York City, where homelessness has reached historic proportions, the advocacy group Coalition for the Homeless estimates that homeless families make up the majority of homeless shelter residents and that the average number of homeless families in shelters rose by 67 percent between January 2005 and January 2015.

Source: US Department of Housing and Urban Development, 2014 Annual Homeless Assessment Report to Congress: Part 1- Point-in-Time Estimates of Homelessness.

Since the end of the recession, the affordable housing shortage has continued to play a major role in rising rates of family homelessness. Between 2010 and 2014, in high-cost locations where affordable rentals are in short supply, the number of homeless people in families increased substantially: by 50 percent in the District of Columbia, 41 percent in Massachusetts, and 22 percent in New York.  The problem is acute in urban areas across the country. According to the 2014 US Conference of Mayors Hunger and Homelessness Survey, 83 percent of the 25 cities surveyed cited the lack of affordable housing as a leading cause of homelessness among families with children in cities in 2014, with over a third (39 percent) of the 25 survey cities reporting that they expected the number of homeless families to increase moderately in the coming year. Indeed, family homelessness remains concentrated in urban areas, with 45 percent of all homeless people in families living in major cities in 2014. Nearly 20 percent of homeless people in families in the US lived in New York City, which had the largest concentration of homeless people in families in the country (41,633) in 2014, followed by Los Angeles City and County in a distant second (6,229). The concentrations of homeless people in families in New York City and Los Angeles also reflect the rising market rents in these metro areas, which have forced a growing share of households to allocate higher shares of their monthly incomes to housing costs. In 2013, 32 percent of renters in the Los Angeles metro area and 30 percent of renters in the New York metro area spent more than 50 percent of their monthly household income on housing, according to the American Community Survey.

The best  housing and services interventions for assisting homeless families have been a matter of some debate. Because families typically do not face long-term episodes of homelessness—indeed, HUD’s PIT count found that just 7 percent of homeless people in families were chronically homeless in 2014—one strategy often touted as suitable for helping them has been rapid re-housing, which focuses on quickly moving families out of shelters into permanent housing through the use of short-term rental subsidies. According to the National Alliance to End Homelessness, about three-quarters of families entering shelter are able to exit quickly with little or no assistance and never return.  However, results released from HUD’s Family Options study last month found that rapid re-housing was much less effective than a permanent housing subsidy, such as a housing choice voucher, in reducing shelter usage and improving housing stability of homeless families. Rapid re-housing may not work for all families, particularly those who are struggling with a host of long-term issues that may inhibit them from securing stable employment and achieving housing stability once their rental assistance expires.

For homeless families that require more intensive psychosocial support, permanent supportive housing, which pairs affordable housing with supportive services in order to achieve long-term housing stability, may be a more appropriate strategy. Through on-site services, permanent supportive housing can address the often complex causes of homelessness among families, such as histories of domestic violence, mental illness, and substance abuse. Yet the current inventory of permanent supportive housing largely targets single adults, especially those with chronic patterns of homelessness. Although the number of permanent supportive housing beds has increased significantly since 2007, a substantial share of permanent supportive housing beds are set aside for individuals rather than families (Figure 3).  The limited availability of subsidies for the services component, as well as higher operating expenses compared to affordable housing, present challenges for expanding the supply of permanent supportive housing. However, given the rising number of homeless families, it is important for policymakers, local communities, and practitioners to collaborate on interventions that address the continuum of needs that homeless families face, whether they be in the form of short-term rental subsidies, a housing voucher or permanent supportive housing. 

Source: US Department of Housing and Urban Development, 2014 Annual Homeless Assessment Report
to Congress: Part 1.

Thursday, July 30, 2015

New Multifamily Construction is Out of Reach for Most Renters

by Elizabeth La Jeunesse
Research Analyst
A major theme of the Joint Center’s 2015 State of the Nation’s Housing Report is the record growth in demand for rental units in recent years.  From 2010-14, the pace of renter household growth accelerated to 900,000 per year on average.  This puts the 2010s on track to be the strongest decade for renter growth in history (Figure 1).

Relative to this surge in demand for rental housing, both the quantity and the pricing of new rental construction has been inadequate.  Annual rental unit completions have ramped up over the past four years, but as of 2014 totaled only 280,000 new units—falling far short of annual growth in renters.  In addition, the rising costs of development pushed the median asking rent for newly constructed multifamily units up to approximately $1,290 per month as of 2013, an increase of $180 in real terms compared to 2012 according to data from the US Census Bureau’s Survey of Market Absorption of New Multifamily Units.

Source: JCHS tabulations of US Census Bureau, Decennial Censuses and Housing Vacancy Surveys.

Meanwhile, typical renter incomes increased by less than half as much, or $60 a month, from $32,000 in 2012 to $32,700 in 2013 according to data from the American Community Survey.  According to the standard definition of housing affordability, where rent should be equal to no more than 30 percent of income, the median or typical renter household could afford a maximum rent of just $820 per month in 2013.  In other words, newly constructed units are truly out of reach for the typical renter household, with the cost of a typical new multifamily unit eating up 47 percent, or almost half, of its total income.

To afford a typical new multifamily unit, a household would need to earn at least $51,440, but less than a third of renters earn this much.  In 2013, the gap between the price of a typical new multifamily unit and what a typical renter could afford was large across all regions of the US, ranging from a difference of around $390 in in the Midwest and South to as much as $475 in the Northeast (Figure 2).  The Northeast and West saw the highest typical asking rents, of $1,350 or more per month.

Notes: *Reported median asking rent was top-coded at $1,350, so the actual median asking rent in the Northeast and West was even higher.  Asking rent data are for privately financed, nonsubsidized units.  Affordable housing is defined as costing no more than 30 percent of gross household income. Source: JCHS tabulations of US Census Bureau, Survey of Market Absorption of New Multifamily Units, and 2013 American Community Survey.

Unfortunately, reported rent data from the Survey of Market of Absorption is top-coded at $1,350, meaning that the actual median asking rent for units completed in these regions was even higher.  For example, results from the American Community Survey suggest that among all units built in 2012-13 that rented at $1,350 or more, well over a third rented for at least $2,000 per month.  This rent would require an annual salary of at least $80,000, placing such units even further out of reach of the typical renter.  Fully 84 percent of new multifamily units in the Northeast and 67 percent of those in the West were priced at a monthly rate of $1,350 or above in 2013.  In the South and Midwest, by comparison, new units in the $1,350+ rent range made up only about a third of growth, suggesting a more even regional supply of new units by price. 

If renters were simply upgrading from lower- to higher-cost housing, the concentration of growth in multifamily construction at the high end would not be a problem.  But available evidence suggests that this is not the case.  According to Joint Center analysis of Housing Vacancy Survey data, more than 90 percent of the decline in rental vacancies over 2013-14 was driven by the 12 percent decrease in the number of vacant, low-rent (i.e., less than $800 per month) units.  And among professionally managed properties, higher occupancy rates were typically found among older units with lower rent levels.  Data from MPF Research also suggest that as of Q4 2014, rents were increasing fastest among older, lower-rent units, further signaling rising demand for a shrinking pool of affordable units.

Other analysis supplied by MPF Research indicates lease renewal rates have been rising over the past five years, as renters increasingly delayed the move to homeownership, leaving even fewer units to filter down to incoming renter households.  Renters’ declining mobility is likely due to a mixture of several factors, including increased difficulty of qualifying for a mortgage, uncertainty about wage growth, debt burdens, and possibly even the difficulty of affording search costs (realtor fees, moving costs, etc.) for an increasingly small number of low-rent units.  As of 2013, nearly half of renters were paying more than 30 percent of their income on housing, indicating that a significant share of renters have already hit a budget ceiling and are likely strapped in their efforts to find other affordable housing options.

The result is that while new multifamily construction is easing some of the demand for new units, it is currently not sufficient to ease the broader affordability problems facing renters. Closing the gap between what it costs to produce this housing, and what economically disadvantaged households can afford to pay, requires the persistent efforts of both the public and private sectors.  For more information on residential construction trends and the affordability challenges renters face, see our full report.

Wednesday, July 22, 2015

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

We would also like to know how long individuals maintain an active consumption of multiple housing units when they change jobs or form new relationships.  Is “living together” increasingly less a status and more a process that could involve two or more housing units over an extended period of time?  Is the rise of long-distance telecommuting predicated on being able to spend some time in two or more locations, and is it the case that housing units in multiple places are owned or rented to facilitate this?  If people are now better able to rent out or share housing with others on a part-time basis (for example, through VRBO and Airbnb), are they more likely to maintain multiple units for their own occasional use? 
Until panel surveys from nationally representative samples collect data on life-course transitions, on intergenerational relationships, and on housing consumption more broadly defined, analysts will continue to try to research trends with data that are usually inadequate to the task, and to have questions that simply cannot be answered.

Thursday, July 16, 2015

Pick-Up Projected in Home Improvement Activity Moving into 2016

by Abbe Will
Research Analyst
The extended easing of gains in residential improvement spending is expected to change course by early next year, according to the Leading Indicator of Remodeling Activity (LIRA) released today by the Remodeling Futures Program at the Joint Center for Housing Studies. The LIRA projects annual spending growth for home improvements will accelerate to 4.0% by the first quarter of 2016 (Figure 1). 

Notes: (e) – estimated; (p) – projected.  Historical data from the second quarter 2014 onward is estimated using the LIRA. Source: Joint Center for Housing Studies of Harvard University.  

One strong signal of a pick-up in home improvement activity is the recent rise in home sales activity, since recent homebuyers typically spend about a third more on home improvements than non-movers, even after controlling for any age or income differences. In addition, rising home prices across the country mean rising equity, which should encourage improvement spending by homeowners.

The Leading Indicator of Remodeling Activity (LIRA) is designed to estimate national homeowner spending on improvements for the current quarter and subsequent three quarters. For more information about the LIRA, including how it is calculated, please visit the LIRA page on the Joint Center’s website. The LIRA is released by the Remodeling Futures Program at the Joint Center for Housing Studies in the third week after each quarter’s closing.