Why is Moving to a New Home Worse for African-American and Hispanic Children than for White Children?

by Kristin Perkins
Postdoctoral Fellow

Compared to children who do not move to a new home, children who move are more likely to do worse in school, have more physical and mental health problems, and are more likely to be delinquent and use alcohol and drugs. In recent research that uses detailed data from the Project on Human Development in Chicago Neighborhoods, I find that African-American and Hispanic children showed more signs of anxiety and depression after they moved. I also find that, on average, Hispanic children demonstrated more aggressive behavior after they moved (Figure 1). White children in this sample, however, did not appear to be negatively affected by a move.
Figure 1.  

Why might moving be worse for African-American and Hispanic children than it is for white children? Perhaps non-white children are more likely to be exposed to violence or have fewer social supports in their homes and neighborhoods, which would make them more susceptible to the disruptive effects of a move? Neither of those factors, however, explained the negative effect of moving for African-American and Hispanic children (as measured by the Child Behavior Checklist, well-established scales that are frequently used as indicators of child behavior). A variety of other factors, such as being renters instead of homeowners and, for Hispanic children, their immigration history, also failed to explain the differences.

Another factor could be the differences between the types of neighborhoods that people are leaving and those they are entering. In general, most of the children in my sample whose families left their neighborhoods moved to a new neighborhood with similar characteristics. This is consistent with other research showing that it is uncommon for families to move to new neighborhoods that are radically different (in terms of poverty level and other characteristics) from the neighborhoods they are leaving. Given this, it's not surprising that among those moving to similar (or worse) neighborhoods, African-American and Hispanic children showed more signs of anxiety and depression, on average, after they moved.

I do, however, have suggestive findings that indicate that African-American children who moved to much better neighborhoods, within or beyond the city of Chicago, did not experience increases in anxiety and depression, unlike African-American children who moved to similar or worse neighborhoods. This finding is consistent with research on the Moving to Opportunity program showing better outcomes in some domains for children who moved from neighborhoods characterized by concentrated poverty to lower poverty neighborhoods.

These and similar findings from other studies of residential mobility and neighborhood effects have several possible implications for policymakers. The data suggest that the children most likely to experience negative effects of moves seem to be similar to children that Matthew Desmond's work on evictions shows are more likely to experience forced moves. If this is the case, the findings underscore the importance of efforts to prevent and reduce evictions and other forced moves.

The findings also suggest that policymakers pursuing programs that aim to improve neighborhood contexts by relocating families need to acknowledge the potential disruptive effects of residential mobility that could undermine the benefits of those moves. If further research confirm the suggestive results showing that the disruptive effects of residential mobility may differ depending on the characteristics of the destination neighborhood, then mobility programs should be designed to focus on efforts to move families to more advantaged neighborhoods.

Beyond mobility programs, policymakers might consider the extent to which other programs and policies unintentionally increase the number of moves that children make and thus increase the possibility of negative outcomes. As one example, it would be useful to determine if the Housing Choice Voucher Program's time limits for finding a unit to rent with a voucher unnecessarily result in temporary moves before a household finds a permanent unit.

Taken as a whole, such measures could potentially reduce negative outcomes among African-American and Hispanic children whose families have to move, particularly those who have to move frequently.

We're Finally Building More Small Homes, but Construction Remains at Historically Low Levels

by Alexander Hermann
Research Assistant

Census data released last month show that after years of stagnation, construction of smaller homes grew appreciably in 2016. New completions for homes under 1,800 square feet increased nearly 20 percent in 2016 to 163,000 units, the first significant growth since 2004 and the largest rise since the data series began in 1999.

This growth is significant because many first-time and lower-income homebuyers hope to purchase smaller homes, which are generally less expensive than larger ones. Moreover, historically-low levels of home construction over the last decade have led to declining inventories, decreasing vacancy rates, and increasing prices, as discussed in our latest State of the Nation's Housing report (Figure 1).

Even with the uptick in 2016, though, small-home construction remains 65 percent below the 464,000 units completed annually between 1999 and 2006, and comprises a much smaller share of newly-built housing than in the past. In 2016, small homes were 22 percent of single-family completions, well below their 37 percent market-share in 1999. In contrast, the share of large homes built grew from 17 percent in 1999 to 30 percent in 2016, while moderately-sized homes, which have consistently been the largest share of the market, have annually been 43-to-48 percent of all new single-family homes.

Construction of condos and townhouses, possible alternatives to smaller single-family housing, also remains low. Builders of multifamily properties continue to focus on the rental market where demand remains strong. Consequently, only 28,000 condos were started in 2016, a modest increase from the 26,000 starts in 2015 but much lower than the 53,000 starts averaged annually in the 1990s (Figure 2). Similarly, townhouse starts grew from 86,000 units in 2015 to 98,000 units in 2016. While this is more than double the number of starts from 2009 and comparable to the 95,000 units started annually in the 1990s, it is less than half the number started in 2005.

The low levels of new construction have resulted in historically-low housing inventories, especially entry-level housing. According to data from CoreLogic, the supply of modestly-priced homes – those selling for 75-to-100 percent of the area's median list price – was below three months at the end of 2016, about half of the six months that generally represents a balanced market (Figure 3). Indeed, according to data compiled by Zillow, only a quarter of the homes for sale at the end of last year were in the bottom one-third of area homes by price, while half were in the top one-third.



Increased demand for entry-level housing and the corresponding uptick in smaller housing construction have already contributed to the growing number of first-time homebuyers in 2016. According to the National Association of Realtors, first-time homebuyers comprised 35 percent of home sales in 2016, up from 32 percent in 2015 but still below long-term historical rates, which are close to 40 percent of all buyers. Looking forward, increases in the supply of smaller homes, townhouses, and possibly condos could help address the growing demand for lower priced homes for first-time and low-income homebuyers.

Steady Gains in Remodeling Activity Moving into 2018

by Abbe Will
Research Associate

Healthy and stable growth in home improvement and repair spending is anticipated for the remainder of the year and into the first half of 2018, according to our latest Leading Indicator of Remodeling Activity (LIRA), released today. The LIRA projects that annual increases in remodeling expenditures will soften somewhat moving forward, but still remain at or above 6.0 percent through the second quarter of 2018.

The remodeling market continues to benefit from a stronger housing market and, in particular, solid gains in house prices, which are encouraging owners to make larger investments in their homes. Yet, weak gains in home sales activity due to tight inventories in many parts of the country is constraining opportunities for more robust remodeling growth given that significant investments often occur around the time of a sale.

Even with some easing this year, the remodeling market is still expected to grow above its long-term average. Over the coming 12 months, national spending on improvements and repairs to the owner-occupied housing stock is projected to reach fully $324 billion.

For more information about the LIRA, including how it is calculated, visit the JCHS website.

The Effect of Debt on Default and Consumption: Evidence from Housing Policy During the Great Recession

by Peter Ganong and
Pascal Noel, Meyer Fellows

What is the effect of mortgage debt reductions that reduce payments in the long-term but not in the short-term? In a new paper using data from a recent government mortgage modification program, we find that substantial mortgage principal reductions that left short-term payments unchanged had no effect on default or consumption for "underwater" borrowers who owed more on their home than their homes were worth.

This finding is significant because the design of mortgage modification programs was a key question facing policymakers attempting to help struggling households during the Great Recession. Policymakers faced a choice between debt reductions that focused on borrower liquidity by temporarily reducing mortgage payments or debt reductions that focused on borrower solvency by permanently forgiving mortgage debt.

This normative policy debate hinged on fundamental economic questions about the effect of long-term debt obligations on borrowers' default and consumption decisions. While a large academic literature has examined the effect debt reductions that mix both short and long-term payment reductions, little is known about the specific effects of long-term debt obligations.

To help fill this gap, we compared underwater borrowers who received two types of modifications in the federal government's Home Affordable Modification Program (HAMP). Both modification types resulted in identical payment reductions for the first five years. However, one group also received $70,000 in mortgage principal reduction, which translated into increased home equity and substantial long-term payment relief. By comparing borrowers in each of these modification types, we were able to isolate the effects of long-run debt levels holding fixed short-run payments. An important feature of the policy we studied was that borrowers remained underwater even after substantial debt forgiveness.

To compare these borrowers, we built two new datasets with information on borrower outcomes and HAMP participation. Our first dataset matched administrative data on HAMP participants to monthly consumer credit bureau records from Transunion. Our second dataset used de-identified data assembled by the JPMorgan Chase Institute (JPMCI) that included mortgage, credit card, and checking account information for borrowers who received HAMP modification from Chase.

Using an empirical strategy called a regression discontinuity design, we found that principal reduction has no effect on default. The analysis exploited a cutoff rule in a model used by mortgage servicers to assign borrowers between the two modification types. While borrowers just above the cutoff were 41 percentage points more likely to receive principal reduction than those just below the cutoff, default rates were smooth at the cutoff, which indicates that principal reduction had little effect on default (Figures 1 and 2). We also estimated that even at the upper bound of our confidence interval, the government spent $800,000 per avoided foreclosure. This is over an order of magnitude greater than estimates of the social cost of foreclosures.

Figure 1.  

Figure 2.  

In the second part of our empirical analysis, we examined the effect of principal reduction on consumption by comparing the monthly spending of the two groups of borrowers over time. We showed that these two groups of borrowers were similar before modification on a broad range of observable characteristics, and that their credit card and auto spending measures were trending similarly in the months before modification. This means that the payment reduction group could be used as a valid counterfactual control group for the principal reduction group.

We found that $70,000 in principal reduction had no significant impact on underwater borrowers' credit card or auto expenditure (Figure 3). Although the spending of both groups stabilized after modification (consistent with the idea that short-term payment reductions helped borrowers), the group that received the additional principal forgiveness showed no differential effect. Rather, we estimated for each $1 of principal reduction received by borrowers, their total spending increased by only 0.2 cents. This is an order of magnitude smaller than the consumption response for average homeowners examined in prior studies, which typically have found spending increases between 4 and 9 cents per $1 of wealth increase.

Figure 3.

The inability of underwater borrowers to borrow against the housing wealth gains from principal reduction may explain why they were far less sensitive to housing wealth changes than borrowers in other economic conditions. Typically, housing wealth gains expand borrowers' credit access--in fact, prior research has found that equity withdrawal through increased borrowing may account for the entire effect of housing wealth on spending between 2002 and 2006. But if homeowners need positive home equity in order to borrow against their house, then principal reduction that still leaves borrowers underwater or nearly underwater will fail to free up collateral that can be used to finance new consumption. This limitation helps explain why policies to lower current mortgage payments were more effective than principal reductions at increasing consumer spending during the Great Recession.

The Rise of Poverty in Suburban and Outlying Areas

by Elizabeth La Jeunesse
Research Analyst

A key takeaway from our latest State of the Nation’s Housing report is that poverty is both increasing and becoming more concentrated across the country. Moreover, while a third of the poor live in high-density urban neighborhoods, the number of poor people and poor neighborhoods grew particularly rapidly in the “exurbs,” low-density neighborhoods on the fringe of the nation’s metro areas (Figures 1 and 2).

Figure 1. The Number of People Living in Poverty Has Increased Most in Suburban and Exurban Communities

Figure 2. Much of the Growth in High-Poverty Neighborhoods Has Been in Suburban and Outlying Areas

According to the report, from 2000 to 2015, the number of people living below the federal poverty line rose by 41 percent, from about 33.8 million to 47.7 million. Additionally, the number of high-poverty neighborhoods (census tracts where the poverty rate is 20 percent or more) rose by 59 percent, and the poor population living in these areas increased by 76 percent to 25.4 million. As a result, 54 percent of the nation’s poor now live in high-poverty neighborhoods, up from 43 percent in 2000.

The growth in high-poverty neighborhoods was widespread, occurring in all but three of the nation’s largest 100 metros (Honolulu, El Paso, and McAllen, TX). Moreover, the rise of poverty was particularly rapid in the exurbs, where the number of high-poverty neighborhoods more than doubled between 2000 and 2015, and the number of poor people living in these neighborhoods grew by 164 percent, rising from 1.5 million in 2000 to 3.9 million in 2015. Such growth presumably was due to the fact that housing generally is less expensive in these areas, but the savings in housing costs are often offset by higher transportation costs and more time spent travelling to work and other activities.

Our new interactive chart shows that these changes were not uniform in the nation’s 100 largest metropolitan areas. To begin with, two-thirds of these metros underwent a rise in concentrated exurban poverty from 2000-2015. Moreover, the magnitude of the increase varied. For example, the number of high-poverty, exurban tracts increased more than tenfold in the Detroit, Greensboro, and Cape Coral, FL metros, and increased by a factor of five or more in 11 other metros, including Atlanta, Denver, Charlotte, Cincinnati, Kansas City, Las Vegas, Nashville and Orlando. Other large metros where the number of high-poverty, exurban neighborhoods more than tripled included Baltimore, Philadelphia, Pittsburgh, Portland, St. Louis, and Tampa.

For example, in the Atlanta metro, the number of low-density, high-poverty, exurban tracts rose from only 11 in 2000 to 72 in 2015 (Figure 3). Meanwhile, in the St. Louis metro, there were 28 high-poverty, exurban neighborhoods in 2015, up from 8 such areas just 15 years earlier (Figure 4).

Figure 3. Atlanta

Figure 4. St. Louis

While poverty remains highly concentrated in dense urban areas, several large metros now have unusually large shares of high-poverty, exurban neighborhoods. In the Atlanta, Charlotte, and Nashville metro areas, for example, nearly a quarter or more of all high-poverty neighborhoods are located in low-density, exurban areas. Poverty’s shift to lower-density areas was especially pronounced in the Charlotte area, where 41 percent of high-poverty tracts are now situated in low-density, exurban areas, up from just 15 percent in 2000 (Figure 5).

Figure 5. Charlotte, NC

Moreover, in several smaller metros across the South – such as Columbia, SC; McAllen, TX; Greenville, SC; Jackson, MS, and Knoxville, TN – well over half of all high-poverty neighborhoods are located in low-density, outlying regions (Figure 6).

Figure 6. McAllen, TX 

Use our interactive tool to see the change in high-poverty neighborhoods in the nation’s 100 largest metro areas between 2000 and 2015.

Download Excel files for additional data on high-poverty neighborhoods. (W-1 and W-15)

Download Chapter 3 of our State of theNation’s Housing 2017 report, which contains additional discussions on the growth of poverty and the spread of high-poverty neighborhoods.

Are Home Prices Really Above Their Pre-Recession Peak?

by Alexander Hermann
Research Assistant

In 2016, national home prices not only rose for the fifth year in a row, they finally surpassed their pre-recession peak in nominal dollars, according to most national measures of home prices. However, as our new State of the Nation’s Housing report notes, when adjusted for inflation, home prices were still 9 to 16 percent below peak, depending on the measure used (Figure 1).



Figure 1. National Home Prices Now Exceed Their Previous Peak in Nominal Terms, But Not in Real Dollars

Note: Prices are adjusted for inflation using the CPI-U for All Items less shelter.

Source: JCHS tabulations of S&P CoreLogic Case-Shiller Home Price Index data.

Moreover, as our interactive maps show, changes in home price vary widely across the country and often exhibit strong regional patterns (Figure 2).

Figure 2. How Much Have Home Prices Changed?

Our interactive maps give users the ability to view price changes in 951 markets across the country over two time periods—since 2000 and since each area’s mid-2000 peak. Viewable markets include 371 Metropolitan Statistical Areas and 31 Metropolitan Divisions (derived from 11 additional metro areas), which together contain about 85 percent of that nation’s population, as well as 549 smaller Micropolitan Statistical Areas, which are home to another nine percent of the population.

The data indicate that nominal home prices were above their mid-2000s heights in 48 percent of all markets (454 total). These markets were largely concentrated in the middle of the country, the Pacific Northwest, and Texas.

However, in real dollars, prices reached their peaks in only 138 (15 percent) of all markets. Furthermore, while prices were above peak in only 10 percent of Metropolitan Statistical Areas and Metropolitan Divisions, they topped their peak in 17 percent of the smaller micro areas, which experienced less home price volatility over the last decade.

In contrast, real prices were still 20 percent below peak in about one-third of all markets, most located in areas hardest hit by the housing crisis, including Florida and large parts of the Southwest, Northeast, and parts of the Midwest.

There were notable differences in long-term patterns in areas where real prices remained well below their pre-recession peak. In many markets on both coasts—such as Miami, Washington, DC, and Sacramento—prices have risen significantly over the last several years and, in real terms, are now well above their levels in 2000. However, because prices in these areas rose significantly during the boom years and fell so sharply during the recession, the recent gains have left prices far below what they were in the mid-2000s.

In contrast, in some Midwestern and Southern markets—such as Detroit, Chicago, and Montgomery, Alabama—prices rose only modestly in the 2000s, dropped significantly during the recession, and have grown only slightly in recent years. Consequently, real prices in these areas were not only well below their peak levels from the mid-2000s, but remained below 2000 levels in many cases.

The uneven growth in home prices over the past two decades has led to increasing differences in housing costs. Illustratively, in 2000 the inflation-adjusted median home value in the 10 most expensive metros (of the country’s 100 largest metros) was about $350,000, about three times higher than the median value of homes in the 10 least expensive metros. But between January 2000 and December 2016, real home values in the ten highest-cost housing markets rose by 64 percent to about $574,000, more than five times the value of homes in the least expensive areas, which grew by only 3 percent, to $113,000.

A broader look at home prices further highlights these stark disparities. Nationally, real home prices rose 32 percent between 2000 and 2016. But home prices in 30 percent of markets (290 total) actually declined in real terms, including 28 percent of metro and 33 percent of micro areas, most of them in the Midwest and South. In the Detroit metro area, home prices declined 26 percent, the largest decrease among large metros. Prices also fell significantly in the Cleveland (22 percent decline), Memphis (15 percent decline), and Indianapolis (13 percent decline) markets.

At the opposite end of the spectrum, between 2000 and 2016 real median home prices rose by more than 40 percent in 153 markets (16 percent), most of them on the East and West Coasts. In fact, prices doubled in twelve markets, including the Honolulu metro areas, which saw 104 percent growth. Home prices also rose considerably in the Los Angeles (97 percent), San Francisco (84 percent), Miami (73 percent), and Washington, DC (62 percent) markets. While micro areas were more likely to be past their previous peak, the lower price volatility also meant they experienced less price growth since 2000, with only 12 percent of micros exceeding 40 percent growth.