Family Instability... It's Not Just Mom and Dad

by Kristin Perkins
Postdoctoral Fellow

Children experience many changes in their households while they are growing up. But while we often think about divorcing and remarrying parents as common changes in household composition that affect many children, in new research, I show that changes involving extended family members and nonrelatives are far more common than changes involving a parent. This finding is significant because prior research suggests that it is likely that instability involving nonparental household members affects children's outcomes. It is therefore relevant to assess the extent to which children are exposed to these transitions and how exposure varies by race and family structure.

To gauge the extent of household changes, I used the nationally representative Survey of Income and Program Participation (SIPP) to track a sample of more than 72,000 children and their households over approximately two years. The SIPP interviews households every four months and documents the set of household members at each interview. This allowed me to identify the relationship between each child and each other household member and to determine who exited or entered the households between interviews.

Overall, by the end of two years (after six interviews), about one percent of children experienced a change in household composition involving their mother and five percent experience a change involving their father. In contrast, more than 10 percent experienced a change involving a grandparent, aunt, uncle, cousin, or other extended family member. In addition, more than four percent of children experienced a change involving a nonrelative. This means that if we think only about divorcing and remarrying parents, we miss changes that affect 14 percent of children over a period of about two years.

These rates vary significantly by type of household, by race, and by ethnicity. For example, 18 percent of children living with a single parent and 29 percent of children living with no parents had an extended family member enter or exit their households compared to only seven percent of children who live with two parents. Similarly, over 10 percent of children living with a single parent or no parent experienced a change involving a nonrelative compared to two percent of children living with two parents (Figure 1).

Moreover, 17 percent of black children and 18 percent of Hispanic children experienced a change in household composition involving extended family members compared to only six percent of white children. There is not as much difference by race and ethnicity, however, for changes involving nonrelatives. Rather, the rate clustered around five percent for all three groups (Figure 2).

Taken together, these findings mean that considering only instability involving parents may not uncover differences by family structure, race, and ethnicity that a broader conceptualization of household instability would reveal. This is important because many studies find that divorce has negative effects on children's well-being. My research showing the much more widespread exposure to changes in household composition highlights the need for future research that assesses whether these other changes in household composition are detrimental—or beneficial—for children. For example: do the distraction and stress from instability involving relatives and nonfamily members mean children perform less well in school or have more behavior problems? Or do some types of changes reflect closer relationships with extended kin that are beneficial for children? Such questions, which were beyond the scope of my analysis, clearly merit further attention.

These descriptive findings and future work on the consequences of household instability for children could also have implications for housing policy. If high housing cost burdens and a lack of affordable options contribute to changes in household composition and if those changes are detrimental to children, then expanding the supply of affordable housing and targeting it to specific households and/or specific high-cost or low-income geographies could greatly help those children. Moreover, such policies could have meaningful spillover effects because providing housing assistance to families not only might benefit children in the family that receives the assistance, but could also help children in the households their families otherwise would have joined when they doubled up with extended family members or nonrelatives.

How Do Funding and Review Processes Shape the Design of Affordable Housing?

by David Luberoff
Deputy Director

How do the notoriously complicated funding and approval processes for affordable housing shape the design of those projects? In particular, are these elements so complex that they make it difficult, if not impossible, to incorporate high-quality design into the planning and execution of affordable housing?

In a new paper, jointly published by the Joint Center and Enterprise Community Partners, Inc., and being presented at a Research Seminar tomorrow (Friday, March 23), Donald Taylor-Patterson, a second year Master of Urban Planning student at the Harvard Graduate School of Design and former Joint Center student research assistant, and I examine these questions as they pertain to Massachusetts in general, and to greater Boston in particular.

One Beach apartments, Revere, MA. Photo by Flagship Photos.

To do so, we drew on three sources of information. First, we carefully reviewed the state's Qualified Allocation Plan, which are the guidelines the state uses to allocate its annual allotment of federal Low-Income Housing Tax Credits (LIHTC), a key funding source for affordable housing. Second, Taylor-Patterson interviewed 18 leading experts in the field and we reviewed the insights that came from those discussions. Finally, Taylor-Patterson spoke with participants at Enterprise's 2017 Affordable Housing Design Leadership Institute (AHDLI), an annual event that brings together non-profit developers and design professionals to discuss how to improve the design of proposed affordable housing projects. (The research, it bears mention, did not attempt to define "design excellence," which can be subjective. Instead, the research focused on whether and how key actors and processes assessed the design quality of affordable housing developments.)

Four key findings emerged from this research. First, the LIHTC process in Massachusetts generally encourages design excellence for "invisible" project elements, particularly those that can be measured such as energy efficiency or accessibility. Second, the harder-to-measure "visible" or "aesthetic" design elements are often the product of the informal and formal ways that community groups and local governments review proposed affordable housing developments.

Third, while funding and approval processes sometimes crowd out efforts to improve design, key actors can bring design back into the picture, particularly if they can create (or take advantage of) well-timed processes that bring together developers, designers, and others for design-focused discussions that take funding and other constraints into account. Finally, although there is widespread agreement on some aspect of design excellence, the fact that each project's physical, political, and financial context is unique makes it almost impossible to use as regulatory process to specify what design excellence entails.

Taken together, these findings underscore how the complex interplay of funding, design, regulatory processes, and local politics creates both challenges and opportunities to ensure that affordable housing projects are designed and built in ways most likely to benefit both residents and neighborhoods. They also suggest that realizing design excellence for affordable housing projects is difficult but achievable. This is particularly true if the work plan for project development encourages and incentivizes processes that allow project designs to be challenged and pushed to a higher standard.

On the Road Again? After Long-Term Decline, Interstate Migration May be Recovering

by Riordan Frost
Research Assistant

For the first time in decades, the number and share of Americans moving to another state may be rising. Moreover, as our new interactive tools show, the increases are due in large measure to the growing number of millennials and baby boomers who are moving from places like California and New York to places like Colorado, Washington, and Florida.

If these trends continue, they would represent a marked shift in domestic migration patterns within the United States. While the Great Recession brought new attention to the decline in residential migration, this decline began well before the latest economic downturn. The share of US residents moving between states has generally declined since we started measuring these trends in 1948, while the total number of such movers has fallen since the mid-1980s.

The three major data sources for residential mobility—the Current Population Survey (CPS), the American Community Survey (ACS), and the IRS Population Migration data (IRS)—all show notable drops in domestic migration during the Great Recession. After 2010, however, they diverge, with the ACS and IRS data showing an uptick in the number of interstate migrants while the CPS data show a stabilization after a long-term decline (Figure 1). The Census Bureau's Population Estimates Program data on migration is limited to net migration flows, but it's regional net flows corroborate these findings by showing some recover since the recession.

Figure 1. Interstate Migration May Be Recovering for the First Time in Decades (Interactive)

The ACS data show that the numerical uptick in interstate moves appears to be driven in particular by 25-34 year olds, 55-64 year olds, and those over 65. While some of this increase is due to the fact that these age groups encompass the nation's two largest generational cohorts (millennials and baby boomers), some of the increase is driven by the fact that rates of migration have increased overall since 2010, though they declined slightly in 2016 (Figure 2). 

Figure 2. Migration Trends are Stabilizing in All Age Groups (Interactive)

The CPS data, which generally show lower migration numbers and rates than the ACS and the IRS, indicate a stabilization in migration across the board for all age groups after 2010. However, even in the CPS there was noticeable growth in the number and rates of moves among younger people in 2016, particularly 25-34 year olds.

While the IRS data does not include age data before 2012, the post-2012 data offer insights into where people in different age groups leave and where they moved. As one of the new interactive tools shows, states that are attracting individuals across age groups include Arizona, Florida, Nevada, North Carolina, and South Carolina. States particularly attractive to younger people include Colorado, Washington, Georgia, and Texas. Only a few states, notably Delaware and South Dakota, are attracting older individuals in particular (Figure 3).

Figure 3. Many States are Experiencing Age-Specific Trends in Migration (Interactive)

Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming 2016 2014 2012

Moreover, as another interactive tool depicting gross migration flows by year and state shows, overall flows have changed dramatically in the last six years. Many states with positive in-migration in 2012, such as Florida, Arizona, and South Carolina, saw even greater in-migration in 2016. In contrast, several states – notably California, New York, and Massachusetts – that had negative flows in 2012 had even greater negative flows in 2016 (Figure 4).

Figure 4. Migration Flows Have Changed for Most States in the Past Six Years (Interactive)

Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming

While some trends – such as migration to Sunbelt states – are consistent with patterns over the last several decades, there are some notable changes in the flows as well. In the wake of declining oil prices, North Dakota, Oklahoma, and Wyoming, all of which have energy-production-based economies and all of which had been growing, saw net out-migration in 2016. In contrast, Utah was the only state that went from losing residents in 2012 to gaining them in 2016. Indeed, Utah was the fastest growing state in 2016, due in large part to their high birth rate and growing domestic and international immigration.

Looking forward, the question is whether the rise in interstate migration is a short-term change or a long-term fundamental shift that marks the end of the decades-long trend of declining mobility. If it is the latter, the changes could have important implications, from increased labor mobility to changes in housing demand, for the states that are gaining – or losing – residents overall.