Use your widget sidebars in the admin Design tab to change this little blurb here. Add the text widget to the Blurb Sidebar!
Home Commentary Metropolitan Spotlights Dashboard Data Maps Blog Subscribe to MetroTrends Blog - RSS RSS icon

Built Environment Archive

Beyond affordability: rental housing problems in Indian Country

Author: Jennifer Biess

| Posted: April 17th, 2014

Last month, we released an interactive map illustrating the pervasive lack of decent and affordable rental housing for extremely low-income (ELI) households in the US. We identified the size of the deficit between the number of decent, affordable units and ELI households for every county. Surprisingly, counties that include Native American tribal lands, which have persistently high poverty and unemployment rates, are some of the places where the shortfall is smaller. But does that mean that housing problems are less severe in Indian Country?

The map below shows the locations of tribal areas throughout the continental US and Alaska where nearly one million American Indians and Alaska Native (AIAN) alone individuals lived in 2010.


Consistent with the affordability map, we found that housing is more affordable for Native American renters living in larger tribal areas (data unavailable for smaller areas) than the national average. About 38 percent of AIAN renter households living on larger tribal areas were cost burdened (paid 30 percent or more of their income for housing) compared to the national renter average of 51 percent.  Further, the average rent for Native American renter households living on larger tribal areas was about half the national average at about $440.

But there’s another way to consider those same numbers. Even though the average rent is very low, nearly 4 in 10 AIAN renter households pay more than 30 percent of their incomes on housing. That’s still a problem – a poverty problem (32 percent of Native Americans live in poverty in tribal areas, more than double the national rate for non-Natives).

And cost isn’t the only issue to consider when thinking about housing problems in Indian Country. While most US housing units have complete kitchen and plumbing facilities – meaning hot and cold running water, a flush toilet, and a tub or shower, a sink with a faucet, a stove or range, and a refrigerator – higher shares of households in Indian Country do not. On larger tribal areas, 3.3 percent of AIAN renter households lacked complete plumbing, four times the national rate. In Arizona and New Mexico 10 percent of all AIAN households lacked complete plumbing, and in Alaska the share was even higher at 18 percent. These shares have gone down over the decade, but remoteness, challenging climates, and lack of infrastructure mean any progress is hard won and difficult to maintain.

AIAN households are also more likely to live in overcrowded housing situations (more than one occupant per room) than households nationally. On tribal areas, 13 percent of AIAN alone renter households are overcrowded, more than double the six percent national rate. We don’t know the extent to which Native Americans choose these living situations because of cultural preferences for intergenerational living arrangements or as an effort to make housing more affordable, but either way the housing units in which they live may not be large enough to comfortably accommodate their residents.

To improve housing conditions on tribal land, we need to better understand housing conditions there as well as these local and cultural factors. We are currently conducting the first study of its kind on Native American housing needs in nearly 20 years, of which this analysis is a part as well as a nationally representative survey of Native American households on tribal land, visits to 24 tribes and other efforts that collectively will shed light on these issues.

More research is available on the Urban Institute’s new Native American Communities landing page

Share this:
Share this page via Email Share this page via Stumble Upon Share this page via Digg this Share this page via Facebook Share this page via Twitter
Filed under: Built Environment |Tags: , , , , ,
Add a Comment »

Keep investing in transit. It’s good for low-income drivers too.

Author: Rolf Pendall

| Posted: April 10th, 2014




With access to cars, many low-income families would live in better neighborhoods, get more stable jobs, and earn more, as my recent study with Evelyn Blumenberg and Casey Dawkins has shown. This is why it’s important to increase the affordability and reliability of car access for low-income households.

But this doesn’t mean we ought to shift our attention and investment away from improving transit, enhancing walkability, and increasing the diversity and density of cities. In fact, all these efforts can help relieve pressure on low-income Americans’ transportation spending even when they own cars.

In 2011, about a third of urban households in the lowest fifth of earners got by without their own car*, according to the Consumer Expenditure Survey. The average household in the poorest fifth spends as much of its income on transportation—32 percent—as the typical American household pays for housing. But the single largest expenditure for the poorest households isn’t a car; it’s gasoline, adding up to 12 percent of the average the average poor household's income*.

Households in the poorest fifth who had cars also spent about as much on auto insurance—$800 a year—as those in the second-poorest fifth. On a per-car basis, they paid the same amount as everyone else to insure cars with blue-book values a fraction of that of better-off households. Even poor households without cars took about a third of their trips in 2001 either by borrowing a car or riding with a household who had one.

These numbers strengthen the argument that investing in transit and walkability is important for low-income families. Of course many low-income households are carless, and many others need options for family members who can’t drive or can’t get access to the one car they do have. But if we reinforce transit, we support higher-density housing, jobs, and retail.

With these “trip generators” closer and more mixed together, we all drive less—and shorter trips help low-income drivers in the same way they help everyone—but with a much bigger impact on their household finances. Drivers don’t need to buy as much gas or pay as much for insurance (which costs more when you drive more). They’re less likely to get into accidents because their trip speeds are lower, and driving less means spending less on routine maintenance and major repairs.

And then there’s time: almost all the households in our study were single mothers and their kids. Their lives are complicated enough even when they have cars and live close to their destinations. Every additional mile they have to drive is an additional mile where something can go wrong: a missed appointment with a job counselor or a few minutes late to work or day-care pickup.

Investments including transit that support density and land-use diversity not only give these households more options and improve their cities, but also can save time by bringing people closer to the things they need.

Despite all of that, many low-income families could be greatly supported with access to a car. More on that in my next blog post.

Photo by Lionel Foster, Urban Institute. *Amended since posting.

Share this:
Share this page via Email Share this page via Stumble Upon Share this page via Digg this Share this page via Facebook Share this page via Twitter
Filed under: Built Environment, Economy |Tags: , , , , , ,
1 Comment »

Fast pay-off, low down payment loans perform well

Author: Laurie Goodman and Ellen Seidman and Jun Zhu

| Posted: January 30th, 2014


(This post is the first in a series on “Housing the next generation.”)

We’ve heard a good deal recently about how upcoming potential homebuyers will be locked out because of low wealth, high debt, and uncertain, lower incomes. While some potential new homeowners might have all of these characteristics, many will almost certainly fall into just one or two categories.

In particular, we would not be surprised to find potential homeowners who are wealth- and/or credit-constrained, but who have relatively good and steady incomes. Can they be served in a way that meets their needs and is safe and sound for lenders and investors?

We can get some hint of the answer by looking at the performance of 15-year fixed rate loans over the last 15 years. Sure, a disproportionate share of 15-year loans are refinances, but we have a large enough dataset to be able to look at 15-year purchase loans, and also to separate out high loan-to-value (LTV), low FICO score loans—that is, loans to the lower-wealth, poorer-credit borrowers of the past.

The good news is that the faster equity appreciation of a 15-year loan, in comparison to a 30-year loan, makes a huge difference in loan performance. As shown in the chart below, for our entire database of loans (CoreLogic Prime Servicing Data, which includes about 62 percent of outstanding loans), only 1.8 percent of purchase money 15-year fixed rate loans ever went 90 days delinquent, compared with 6.9 percent of purchase money 30-year fixed rate loans. And that’s over the entire boom-and-bust cycle, from before 2000 through 2013.


As illustrated above, significant differences are apparent for purchase loans to borrowers with FICO scores below 700 (2.6 percent versus 10.7 percent) and for loans with LTVs above 90 (4.0 percent versus 8.2 percent). Even more impressive: the 7.5 percent default rate for greater than 90 LTV, less than 700 FICO 15-year mortgages is similar to the 6.9 percent default rate for greater than 90 LTV, 700-750 FICO 30-year borrowers. These differences held when we used a logit model to hold other factors (occupancy, state, issue year) constant.

While there may be multiple reasons for this similarity in performance, the faster equity buildup of a 15- year loan is an important contributing factor. Moreover, and not considered in the chart (which only measures delinquencies), faster equity growth means that when a 15-year loan defaults, the loss severity is likely to be lower.

As shown by comparing the first red bar to the second blue bar, low down payment 15-year purchase loans outperform 30-year purchase loans of all LTVs. Taking that into account could open the door to homeownership to many more low-wealth families, even those without pristine credit, if their incomes allow them to afford a higher monthly payment.

Should everyone be required to have a 15-year loan? No. The advantage of the 30-year mortgage has always been lower monthly payments, and for many borrowers, those are key to being able to purchase a home. Moreover, good underwriting, which often was not the case during part of the period at issue but that will be required by the ability to pay rules under the Dodd-Frank Act, will enhance the quality of all loans. But this analysis provides one illustration that a higher down payment isn’t the only road to good performance.

Follow Ellen Seidman on Twitter at @esseidman.

Share this:
Share this page via Email Share this page via Stumble Upon Share this page via Digg this Share this page via Facebook Share this page via Twitter
Filed under: Built Environment, Economy |Tags: , , , , , ,

Extending the HARP cutoff date is no silver bullet

Author: Bing Bai and Taz George

| Posted: January 28th, 2014

The Home Affordable Refinance Program (HARP) stands out as one of the Obama administration’s most successful interventions to help borrowers hit by the housing market crash. The program is aimed at borrowers who took out mortgages backed by Fannie Mae and Freddie Mac (the GSEs) prior to June 1, 2009, and enables them to refinance their loans even if the loans did not meet the GSEs’ normal requirements for refinancing.

Since 2009, HARP has allowed over 3 million homeowners to refinance their mortgages, securing lower monthly payments. Given this success, senior US Treasury official Michael Stegman’s declaration in a speech last week that there would be no extension of the cutoff date limiting the program’s reach came as a surprise to many.

In the Housing Finance Policy Center’s January edition of our monthly chartbook (page 24), we investigated a key claim behind Stegman’s statement: that extending the June 2009 cutoff date—loans made after that date cannot qualify for HARP—would affect a small number of borrowers.

To determine how many borrowers would potentially benefit from a later cutoff date, we took a look at the other requirements for HARP eligibility. First, a borrower must have a record of making their payments on time: no late payments in the past six months, and no more than one late payment in the past year. Second, the homeowner must have limited equity in the home, with the marked-to-market loan-to-value (LTV) ratio (the ratio of the unpaid mortgage balance to the current market value of the house) above 80 percent. Finally, the loan must be “in the money,” meaning that the refinance would be economical for the borrower—that is, the current interest rate must be enough lower than the rate the borrower is paying to cover the costs of the refinancing.


The chart above sorts the universe of GSE loans by these HARP eligibility rules. Out of approximately 25 million active Freddie and Fannie loans, there are 14 million originated after the cut-off date that meet the pay history requirement. That seems like a large number that could potentially benefit from a change in the cutoff, but only about 2.4 million of these meet the LTV ratio minimum of 80 percent, because since 2009, well over half of the loans purchased by the GSEs have been refinances, and most of those have LTVs under 80 percent.

Of those 2.4 million, only 11 percent (249,932; see the tiny overlap in the middle of the chart) are “in the money.” Why so few? Because post-June 2009 borrowers took out their mortgages at a time of historically low interest rates, making it unlikely that they could obtain a lower rate today. And some of these borrowers HARPed once, early in the process, and the rules prohibit them from a further HARP refinance.

When we further divided the group of 249,932 who could potentially benefit from an extension by their origination dates, we tallied 113,998 borrowers that could benefit from a one-year extension of the cut-off date, and 200,632 that could benefit from a two-year extension. These numbers are dwarfed by the 846,677 pre-June 2009 borrowers that remain eligible without an extension, and over 3 million who have already benefited from a HARP refinance.

There has been little question of HARP’s effectiveness in providing relief to homeowners since the housing crisis, but Stegman is correct that tweaking the cutoff date will do little to extend the program’s reach.

Share this:
Share this page via Email Share this page via Stumble Upon Share this page via Digg this Share this page via Facebook Share this page via Twitter
Filed under: Built Environment, Economy |Tags: , , , , ,
Add a Comment »

How homelessness continues to decline despite the affordable housing crisis

Author: Josh Leopold

| Posted: January 14th, 2014

Later this month, the Department of Housing and Urban Development (HUD) will conduct its yearly Point-in-Time count to determine how many Americans are homeless on a single night. The most recent count found 610,042 people experiencing homelessness on that night in January 2013, four percent fewer than in 2012.

This decline was widespread. Overall homelessness decreased by 9 percent between 2012 and 2013, and is down among all reported subpopulations. The number of military veterans experiencing homelessness decreased by eight percent, from 62,619 to 57,849, and the number of homeless families decreased by eight percent, from 77,157 to 70,960. These figures continue a downward trend that has been apparent since 2007, the first year with reliable national data.

The decline in homelessness despite the housing crisis, the Great Recession, sequestration, and a weak recovery is regarded as a “public policy triumph,” and the fanfare is warranted. Opening Doors, the first national plan to prevent and end homelessness, has helped sharpen focus and increase accountability among federal agencies. The Housing First model, which prioritizes immediate placement into permanent housing instead of making housing contingent upon substance abuse treatment, sobriety, or other milestones, has emerged as a best practice for ending homelessness for even the hardest cases.

Supportive housing for those facing challenges like mental illness, addiction, and HIV/AIDS has become more widely available since 2007. Congress has funded more than 50,000 new HUD-Veterans Affairs Supportive Housing units for veterans since 2008 and created the Supportive Services for Veteran Families, a $300 million annual homeless prevention and rapid re-housing program.

These policies have focused primarily on veterans and the chronically homeless, people with disabilities that have been homeless a year or more or four or more times in the last three years, nearly all of whom are individuals. So it is more difficult to explain the decline in family homelessness, particularly since the affordable housing crisis has gotten worse.

Congress has not authorized significant new investment in family homelessness programs since 2011. That year, the number of families with worst-case needs— that is, paying more than half their income on rent or living in severely inadequate housing—reached 8.5 million, up 44 percent from 2007. And 21.8 million households were living “doubled up” with family and friends, an 11-percent jump from 2007. The Department of Education’s report on homeless students, which, unlike HUD’s figures, includes doubling up, reported 1.1 million homeless students using public schools in the 2011-2012 school year, a 72 percent increase from pre-recession levels.

Meanwhile, rental assistance, one of the best antidotes to homelessness, has become scarcer because of sequestration.

But a few factors may help explain the decline.

First, the stimulus-funded Homeless Prevention and Rapid Re-Housing Program expired in 2012. The three-year, $1.5 billion program provided assistance to more than a million people, and helped prevent homelessness from surging following the recession. But it has not been replaced by any new federal prevention or rapid re-housing program of a similar size.

Secondly, some programs that provide temporary rental assistance for homeless families have been re-classified from transitional housing programs to rapid re-housing programs. Because families receiving rapid re-housing assistance are living in their own homes and can continue living there after program assistance ends, HUD does not consider them homeless and they are not counted as such. It is unknown how many families were affected by this re-classification, but communities did report 11,860 fewer transitional housing beds in 2013 than in 2012.

Finally, the count of homeless families and, by extension, the accuracy of that count, is constrained by the availability of shelter. Families are much less likely than individuals to sleep on the streets, even under the most dire circumstances. Only a handful of areas, including the state of Massachusetts; New York City; Hennepin County, MN; Columbus, OH, Montgomery County, MD, and Washington, DC (during hypothermia season), guarantee homeless families a right to shelter. Since 2007, the number of homeless families in these right-to-shelter areas has increased 34 percent. In the rest of the country it has decreased by 24 percent.

This decline does not necessarily reflect a reduced need for shelter. The 2013 U.S. Conference of Mayors Report on Hunger and Homelessness found that in 17 of the 21 cities included in its survey, emergency shelters had to turn away families with children because there were no available beds. So, paradoxically, unless they happen to be outside during an annual Point-in-Time count, families who are turned away from a shelter are denied not only a bed but inclusion in official statistics.


There are many reasons to cheer the steady decline in chronic homelessness and homelessness among veterans. However, the reported decrease in family homelessness appears to underestimate the need for shelter in many communities. The solution is not necessarily to build more shelters, but to build more affordable housing and make it more accessible for families that are homeless or at risk of homelessness.

Chart by Tim Meko, Urban Institute

Share this:
Share this page via Email Share this page via Stumble Upon Share this page via Digg this Share this page via Facebook Share this page via Twitter
Filed under: Built Environment, People, Quality of Life |Tags: , , ,

Are we in another housing bubble?

Author: Taz George and Bing Bai

| Posted: January 10th, 2014

As we gradually recover from the housing crisis, extra caution must be taken to prevent future real estate bubbles. But merely detecting a bubble is a tricky and contentious matter.

Earlier this week, Peter Wallison of the American Enterprise Institute warned that a new bubble is forming. His evidence? Home prices have increased more quickly than rental rates in the past year, according to data from the U.S Bureau of Labor Statistics and the Case-Shiller national home price index. This divergence should not occur under healthy market conditions, Wallison argues, because families should prefer to rent when home prices climb, bringing the costs of renting and owning back to equilibrium.

The story is not that simple, though. A bubble is a situation in which instruments trade in high volumes at prices that are at odds with intrinsic value. A differential rate of increase between home prices and rents does not necessarily mean that the average mortgage payment, a more precise measure of the cost of homeownership, is growing faster than the cost of renting. While a mortgage payment does not capture all of the benefits of homeownership over renting, such as tax incentives and accrued wealth, it is a better estimate of the cost of owning a home than home prices alone.

For example, when mortgage rates were high in the 1980s, the typical mortgage payment on a new loan was far higher than home prices alone would suggest. For a bubble to occur, the mortgage payment relative to rent must be historically high—a sign that families are continuing to purchase homes even though renting is more economical.

To create a more accurate picture of whether a housing bubble is currently forming, we computed two ratios, illustrated below. The light blue line compares the home price index to the rent index, the relationship Wallison cites as evidence of a bubble. It depicts a large increase in the housing boom years, the subsequent drop, and a significant amount of volatility since 2009, including a slight uptick in the past two years.


Evidence of a bubble becomes even less compelling when one looks at mortgage payments versus rent payments, represented by the solid dark blue line. The trend is similar, but the darker solid line remains far below its average (dotted dark blue line). This suggests that recent gains in housing prices are not indicative of a bubble, in which families continue to buy homes even though renting is more economical. Instead, we see a market that is somewhat skewed in the other direction—more economical for new owners than renters, compared to a typical period, largely because of low interest rates.

What’s more, the housing bubble we just experienced was associated with easy access to credit, even for borrowers with low FICO scores, the standard credit score used in most lending decisions. The 10th percentile FICO score of all borrowers with new loans is a good representative of the lower bound of creditworthiness needed to attain a mortgage at any given time.

December’s At A Glance, the Housing Finance Policy Center’s monthly chartbook, shows that this lower bound hovered near 600 between 2001 and 2006, but by 2013 had crossed 650, and it continues to rise. An increase of this magnitude means that the millions of borrowers who qualified for mortgages with credit scores below 650 during the boom years would struggle to be approved for a loan today.

The increase is even sharper in some regions, such as the San Francisco and New York City metropolitan areas, where the average FICO score on new loans now exceeds 750. Credit availability today is far more limited than it was during the bubble years, and it is becoming more, not less, limited.

In short, a historically high bar for creditworthiness and a below average ratio of mortgage payments to rents does not seem like a bubble. It is reflective of a tight credit box, low mortgage rates, and a gradual recovery in the housing market.



Share this:
Share this page via Email Share this page via Stumble Upon Share this page via Digg this Share this page via Facebook Share this page via Twitter
Filed under: Built Environment, Economy |Tags: , , ,
1 Comment »

Paying our nation's home utility bills this winter

Author: Carlos Martin

| Posted: December 19th, 2013




As the temperature drops, most of us brace ourselves and accept that winter means spending more on home energy costs. But, sadly, this seasonal price shock uptick can literally leave many low-income households in the cold. For many reasons, the utility bills of families in publicly assisted housing should worry us all.

At last count, annual spending on utilities in all US public and assisted housing totaled $7.1 billion, the equivalent of one-sixth of the annual budget for the US Department of Housing and Urban Development (HUD). $2 billion of that sum are annual utility bills for public housing units alone, and these costs are largely covered by the federal government. At the same time, there is a backlog of over $20 billion in outstanding repairs and improvements in public housing units. That price tag will only increase as this housing continues to age.

These are enormous sums, but we can chip away at them. Energy-related investments give money back over the long run by reducing energy bills from 10 to even 50 percent. For example, investments of about $4 billion in basic energy and water improvements in public housing units now could pay for themselves in just 12 years.

The best option for decreasing our national home energy bill is simply to invest in energy efficient retrofits, but funds to support capital and operating costs have been slashed. Without capital funding for these investments, there can be no savings to housing authorities and developers and US taxpayers down the road.

Recent programs like HUD’s Green Retrofit Program for Multifamily Housing, the Multifamily Energy Innovation Fund, and Public Housing Capital Fund Competitive Grants were a good start. Public housing authorities and assisted housing developers put these funds to great use, from basic weatherization to full-scale energy retrofits and, in some cases, the installation of solar and other renewable sources.

For example, the Cambridge Housing Authority is shaving off $1 million a year—or half­­–of its electricity bill because of these federal resources. Campaigns to increase residents’ energy-conserving behaviors are helping, too. But future capital funding must be strengthened, especially in public housing, to match current needs and reduce future demand.

Earlier this month, HUD and the US Department of Energy (DOE) announced an expansion of the Better Buildings Challenge to include partners in the multifamily residential sector. These partners have committed to reducing energy consumption by at least 20 percent over 10 years. Programs like this mean landlords, tenants, and taxpayers save money. It’s a win-win-win.

It’s clear that assisted housing developers and managers know what it means to do more with less, but they have hit a wall. They must be given the resources to “do more” now—like pay for energy-efficient capital improvements—to make do with increasingly scarce public funding. The need for these investments will exist well beyond this winter.

The Assisted Housing Initiative is a project of the Urban Institute, made possible by support from Housing Authority Insurance, Inc.  (HAI, Inc.), to provide fact-based analysis about public and assisted housing. The Urban Institute is a non-profit, nonpartisan research organization and retains independent and exclusive control over substance and quality of any Assisted Housing Initiative products. The views expressed in this and other Assisted Housing Initiative commentaries are those of the authors and should not be attributed to the Urban Institute or HAI, Inc.

Photo by Flickr user Vansgirl12, used under Creative Commons license (CC BY-NC-SA 2.0)

Share this:
Share this page via Email Share this page via Stumble Upon Share this page via Digg this Share this page via Facebook Share this page via Twitter
Filed under: Built Environment |Tags: , , , ,
1 Comment »

Use our tools to tell your own stories about a decade of change in DC

Author: Lionel Foster

| Posted: December 10th, 2013




You see it in the scaffolding and “Now Leasing” signs and brand new restaurants, the infill housing, bike-share stations, and rising property values. Washington, DC, is changing—rapidly—so rapidly that it can be hard to put it all into words.

So maybe images can help.

Today, the Urban Institute presents Our Changing City, a project we hope will help quantify and personalize DC’s development. In this multi-part, online, interactive series, we use words, data, and visualizations to describe this change and help residents see where they fall within it.

Chapter one focuses on shifting demographics, from the District’s founding in the late 18th century to the riots in the sixties up until 2010, with a special focus on the decade between the last two census counts when DC’s population grew for the first time in 50 years. Subsequent chapters will cover housing, education, crime, and more.

Detailed maps illustrate what happened. Scan back and forth between 2000 and 2010 and you’ll see entire blocks populated seemingly in an instant, young adults speckling Northwest, and a marked decline in the number of African American residents.

Each dot represents a person. Which one are you? If you now live or once lived here, what’s the perspective from your place on the map? Use our tools to tell your story about our changing city.

Share this:
Share this page via Email Share this page via Stumble Upon Share this page via Digg this Share this page via Facebook Share this page via Twitter
Filed under: Built Environment |Tags: , , , , , , ,
Add a Comment »

What HMDA data say about the state of the mortgage market

Author: Ellen Seidman

| Posted: October 1st, 2013



Autumn brings crisper nights, apple cider, and the annual release of the prior year’s Home Mortgage Disclosure Act (HMDA) data.

HMDA requires the vast majority of home mortgage lenders to disclose critical information about each loan application, such as whether the loan was approved or denied, and information about the loans and applicants—including the race, gender, and income of the borrower and the mortgage’s location.

While regulatory use of HMDA focuses heavily on each lender’s service to its community (for banks, performance under the Community Reinvestment Act or CRA; for all lenders, concerns about discrimination), HMDA’s vast dataset—2012’s included 9.8 million loans reported by 7,400 lenders— provides important insight into the state of the mortgage market.

The Federal Reserve Board of Governors’ annual HMDA analysis, authored by Neil Bhutta and Glenn Canner. “Mortgage Market Conditions and Borrower Outcomes: Evidence from the 2012 HMDA Data and Matched HMDA-Credit Record Data” is especially notable this year because it includes analysis of the performance through 2012 of 300,000 loans made in 2006 (at the height of the bubble and of sloppy underwriting) and in 2010 (when mortgage credit was extremely tight).

This ability to follow a mortgage is an important innovation, attributable to an ongoing project called the National Mortgage Database (NMDB), a joint effort of the Federal Housing Finance Administration and Freddie Mac.  (The NMDB was featured at the June data lunch sponsored by the Urban Institute’s new Housing Finance Policy Center.)

Here’s what we learn from the basic 2012 HMDA analysis:

  • New mortgage loans increased 38 percent from 2011 to 2012, but that was largely driven by a 54 percent increase in refinancing loans, compared to only a 13 percent increase in home purchase loans.
  • Government financing—Federal Housing Agency (FHA), Veterans Administration (VA), and Rural Housing Service (RHS)—accounted for 45 percent of the home purchase loans for owner-occupants, with VA and RHS lending particularly strong. The median income of borrowers who got home purchase loans from the FHA was about 40 percent lower than the median for conventional (non-government) home purchase loans, suggesting a bifurcated market.
  • While loans to all groups of borrowers increased, high-income borrowers, non-Hispanic whites, and Asians showed significantly larger increases than other groups. Denial rates for black and white-Hispanic applicants continued at rates significantly higher than denials for other groups. The big reasons for denial related to too high loan-to-value or debt-to-income ratios.
  • Looking at census tracts rather than individual borrowers, lending was weakest in low-income and minority census tracts.
  • High-cost lending (a proxy for subprime lending) remained low, at 3 percent (compared to 28 percent in 2006), but black and white-Hispanic borrowers were more likely to have higher-priced loans.

The matched data enabled Bhutta and Canner to add credit scores—missing from HMDA but scheduled to be included under the Dodd-Frank Act—to their analysis, as well as performance. Some important findings:

  • Confirming the existence of a tight “credit box,” average credit scores rose significantly from 2006 to 2010, from 701 to 728 for home-purchase loans and 682 to 772 for refinances (or “refi”). The inversion of the comparative credit scores for purchase and refi likely reflects the changing shares in origination channels, with FHA, VA, and RHS having a vastly increased portion of the home purchase market, whereas loans banks held in portfolio or sold to Fannie Mae and Freddie Mac were largely refis.
  • In 2010, 22 percent of home purchase borrowers had back-end (i.e., both housing and non-housing) debt payment to income ratios above 43 percent, the bright-line standard for a “Qualified Mortgage” (QM) under the Consumer Financial Protection Bureau’s (CFPB) new rules. However, 70 percent of that 22 percent were FHA, VA, or RHS. On September 30, the FHA released its version of the QM rule; it does not have a 43 percent debt-to-income cutoff.
  • In both 2006 and 2010, loans made by institutions subject to the CRA in their CRA assessment areas had higher credit scores and lower debt–to-income ratios than loans originated outside assessment areas. CRA assessment area loans made in 2006 to low- or moderate-income borrowers had significantly lower delinquency rates than the universe as a whole, and one-fourth the delinquency rate of higher-priced loans. Bhutta and Canner conclude that “the relatively low delinquency rate of loans encouraged by the CRA is inconsistent with the notion that the CRA was a principal driver of the mortgage and financial crisis."

Starting this year, important improvements spurred by work at the CFPB will make the data more accessible. The data on the website of the Federal Financial Institutions Examination Council are easier for researchers to retrieve and use. In addition, the CFPB’s own website now has graphs of loan originations by loan use (purchase, refinance, home improvement) and loan type (conventional, FHA, VA, RHS) for 2010, 2011, and 2012, as well as information about changes in mortgage applications and originations.

CFPB will shortly release a far more robust query tool as well as an API to help developers access HMDA data and design their own applications and visualizations. The Urban Institute’s own Data Dashboard and National Data Repository will also be updated shortly with 2012 HMDA data.

Image from Shutterstock

Share this:
Share this page via Email Share this page via Stumble Upon Share this page via Digg this Share this page via Facebook Share this page via Twitter
Filed under: Built Environment |Tags: , , ,
Add a Comment »