Tag Archives: income

Going It Alone on Your Mortgage

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walking alone

WiseBread quoted me in When It Makes Sense to Apply for a Mortgage Loan Without Your Spouse. It opens,

You and your spouse or partner are ready to apply for a mortgage loan. It makes sense to apply for the loan jointly, right? That way, your lender can use your combined incomes when determining how much mortgage money it can lend you.

Surprisingly, this isn’t always the right approach.

If the three-digit credit score of your spouse or partner is too low, it might make sense to apply for a mortgage loan on your own — as long as your income alone is high enough to let you qualify.

That’s because it doesn’t matter how high your credit score is if your spouse’s is low. Your lender will look at your spouse’s score, and not yours, when deciding if you and your partner qualify for a home loan.

“If one spouse has a low credit score, and that credit score is so low that the couple will either have to pay a higher interest rate or might not qualify for every loan product out there, then it might be time to consider dropping that spouse from the loan application,” says Eric Rotner, vice president of mortgage banking at the Scottsdale, Arizona office of Commerce Home Mortgage. “If a score is below a certain point, it can really limit your options.”

How Credit Scores Work

Lenders rely heavily on credit scores today, using them to determine the interest rates they charge borrowers and whether they’ll even approve their clients for a mortgage loan. Lenders consider a FICO score of 740 or higher to be a strong one, and will usually reserve their lowest interest rates for borrowers with such scores.

Borrowers whose scores are too low — say under 640 on the FICO scale — will struggle to qualify for mortgage loans without having to pay higher interest rates. They might not be able to qualify for any loan at all, depending on how low their score is.

Which Score Counts?

When couples apply for a mortgage loan together, lenders don’t consider all scores. Instead, they focus on the borrower who has the lowest credit score.

Every borrower has three FICO credit scores — one each compiled by the three national credit bureaus, TransUnion, Experian, and Equifax. Each of these scores can be slightly different. When couples apply for a mortgage loan, lenders will only consider the lowest middle credit score between the applicants.

Say you have credit scores of 740, 780, and 760 from the three credit bureaus. Your spouse has scores of 640, 620, and 610. Your lender will use that 620 score only when determining how likely you are to make your loan payments on time. Many lenders will consider a score of 620 to be too risky, and won’t approve your loan application. Others will approve you, but only at a high interest rate.

In such a case, it might make sense to drop a spouse from the loan application.

But there are other factors to consider.

“If you are the sole breadwinner, and your spouse’s credit score is low, it usually makes sense to apply in your name only for the mortgage loan,” said Mike Kinane, senior vice president of consumer lending at the Hamilton, New Jersey office of TD Bank. “But your income will need to be enough to support the mortgage you are looking for.”

That’s the tricky part: If you drop a spouse from a loan application, you won’t be penalized for that spouse’s weak credit score. But you also can’t use that spouse’s income. You might need to apply for a smaller mortgage loan, which usually means buying a smaller home, too.

Other Times to Drop a Spouse

There are other times when it makes sense for one spouse to sit out the loan application process.

If one spouse has too much debt and not enough income, it can be smart to leave that spouse out of the loan process. Lenders typically want your total monthly debts — including your estimated new monthly mortgage payment — to equal no more than 43% of your gross monthly income. If your spouse’s debt is high enough to throw this ratio out of whack, applying alone might be the wise choice.

Spouses or partners with past foreclosures, bankruptcies, or short sales on their credit reports might stay away from the loan application, too. Those negative judgments could make it more difficult to qualify for a loan.

Again, it comes down to simple math: Does the benefit of skipping your partner’s low credit score, high debt levels, and negative judgments outweigh the negative of not being able to use that spouse’s income?

“The $64,000 question is whether the spouse with the bad credit score is the breadwinner for the couple,” says David Reiss, professor of law with Brooklyn Law School in Brooklyn, New York. “The best case scenario would be a couple where the breadwinner is also the one with the good credit score. Dropping the other spouse from the application is likely a no-brainer in that circumstance. And of course, there will be a gray area for a couple where both spouses bring in a significant share of the income. In that case, the couple should definitely shop around for lenders that can work with them.”

Salary Needed for a House in 27 Cities

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HSH.com has posted a study to answer the question — How much salary do you need to earn in order to afford the principal, interest, taxes and insurance payments on a median-priced home in your metro area? The study opens,

HSH.com took the National Association of Realtors’ fourth-quarter data for median-home prices and HSH.com’s fourth-quarter average interest rate for 30-year, fixed-rate mortgages to determine how much of your salary it would take to afford the base cost of owning a home — the principal, interest, taxes and insurance — in 27 metro areas.

We used standard 28 percent “front-end” debt ratios and a 20 percent down payment subtracted from the NAR’s median-home-price data to arrive at our figures. We’ve incorporated available information on property taxes and homeowner’s insurance costs to more accurately reflect the income needed in a given market. Read more about the methodology and inputs on the final slide of this slideshow.

The theme during the fourth quarter was increased affordability.

Home prices declined from the third to the fourth quarter in all of the metro areas on our list but one. But on a year-over-year basis, home prices have continued to trend upward.

“Home prices in metro areas throughout the country continue to show solid price growth, up 25 percent over the past three years on average,” said Lawrence Yun, NAR chief economist.

Along with affordable home prices, mortgage rates fell across the board which caused the required salaries for our metro areas to decline (again, except for one).

“Low interest rates helped preserve affordability last quarter, but it’ll take stronger income gains and more housing supply to help meet the pent-up demand for buying,” said Yun.

On a national scale, with 20 percent down, a buyer would need to earn a salary of $48,603.82 to afford the median-priced home. However, it’s possible to buy a home with less than a 20 percent down payment. Of course, the larger loan amount when financing 90 percent of the property price, plus the need for Private Mortgage Insurance (PMI), raises the income needed considerably. In the national example above, a purchase of a median-priced home with only 10 percent down (and including the cost of PMI) increases the income needed to $56,140.44 – just over $7,500 more.

This sounds like a pretty reasonable methodology, but there are a lot of assumptions built into the ultimate conclusions. They are generally conservative assumptions — buyers will get a 30 year fixed rate mortgage instead of an ARM, buyers will have 28% debt ratios. I would have liked to see some accounting for location affordability, because transportation costs can vary quite a bit among metro areas, but you can’t have everything.

As always, I am particularly interested in NYC, the 24th most expensive of the 27 cities.  NYC requires an income of $87,535.60 to buy a median home for  $390,000. By way of of contrast, the cheapest metro is Pittsburgh, which requires an income of $31,716.32 to buy a median home for $135,000 and the most expensive was San Francisco, which requires an income of $142,448.33 to buy a median home for $742,900.

Economic Segregation in NYC and the USA

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Richard Florida and Charlotta Mellander have released Segregated City: The Geography of Economic Segregation in America’s Metros. The executive summary reads,

Americans have become increasingly sorted over the past couple of decades by income, education, and class. A large body of research has focused on the dual migrations of more affluent and skilled people and the less advantaged across the United States. Increasingly, Americans are sorting not just between cities and metro areas, but within them as well.
This study examines the geography of economic segregation in America. While most previous studies of economic segregation have generally focused on income, this report examines three dimensions of economic segregation: by income, education, and occupation. It develops individual and combined measures of income, educational, and occupational segregation, as well as an Overall Economic Segregation Index, and maps them across the more than 70,000 Census tracts that make up America’s 350-plus metros. In addition, it examines the key economic, social, and demographic factors that are associated with them. (8)
Although it reads like a jeremiad at times, there is a lot of thought-provoking information in this report. For instance, it examines “the segregation of the three major occupational classes—the creative class of knowledge workers, the even faster growing but lower-paid service class, and the declining blue-collar working class.” (36) It shows that there is a lot of segregation of these classes. This is unsurprising given the correlation between occupational class and income.
As a New Yorker, I immediately focused on the findings relevant to NYC. The report finds that the New York Metro area exhibits a high degree of economic segregation. This is not surprising, but it is interesting to learn where it stands vis a vis other large metro areas — it is sixth highest in the country.
I am not sure what the policy implications are of this report, but it does tell a tale of two cities in one place, one rich and one poor.

Nation of Renters

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NYU’s Furman Center and Capital One have produced an interesting graphic, Renting in America’s Largest Cities. The graphic highlights the growing trend of renting in urban communities, but also the increasing expense of doing so. The press release about this study provides some highlights:

  • In 2006, the majority of the population in just five of the largest 11 U.S. cities lived in rental housing; in 2013, that number increased to nine.
  • As demand for rental housing grew faster than available supply, rental vacancy rates declined in all but two of the 11 cities, making it harder to find units for rent.
  • Rents outpaced inflation in almost all of the 11 cities. Rents Increased most in DC, with a 21 percent increase in inflation-adjusted median gross rent, and least in Houston, where rents were stable.
  • In all 11 cities, an overwhelming majority of low-income renters were severely rent-burdened, facing rents and utility costs equal to at least half of their income.
  • Even In the most affordable cities in the study, low-income renters could afford no more than 11 percent of recently available units.
  • In five major cities, including New York, Los Angeles, San Francisco, Boston and Miami, moderate-Income renters could afford less than a third of recently available units in 2013.

Rental housing clearly has an important role to play in providing stable homes for American households, particularly in big cities. While rental housing has been the stepchild of federal housing policy for far too long, it is good that it is finally get some attention and resources.

I look forward to the Furman Center’s follow-up report, which will provide more detail than the graphic does. I am particularly curious about whether the researchers have addressed the difference between housing affordability and location affordability in the longer study. I would guess that the relative affordability of the cities in this study is greatly impacted by households’ transportation costs.

The Secret to Financial Well-Being?

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The Consumer Financial Protection Bureau has issued a report, Financial Well-Being:  The Goal of Financial Education. I have been somewhat critical of the CFPB’s approach to financial literacy education, but I think that this report sets forth a pretty reasonable baseline for future research. It states,

A growing consensus is emerging that the ultimate measure of success for financial literacy efforts should be improvement in individual financial well-being. But financial well-being has never been explicitly defined, nor is there a standard way to measure it. Overall, the literature paints a picture of nuanced, complex interactions between financial knowledge, understanding, and actions taken. However, rigorously identified links between these factors and financial outcomes have yet to be established.

Our project provides a conceptual framework for defining and measuring success in financial education by delivering a proposed definition of financial well-being, and insight into the factors that contribute to it. This framework is grounded in the existing literature, expert opinion, and the experiences and voice of the consumer garnered through in-depth, one-on-one interviews with working-age and older consumers. (4-5)

The CFPB proposes a definition of financial well-being “as a state of being” where people

  • Have control over day-to-day, month-to-month finances;
  • Have the capacity to absorb a financial shock;
  • Are on track to meet your financial goals; and
  • Have the financial freedom to make the choices that allow you to enjoy life.

Because individuals value different things, traditional measures such as income or net worth, while important, do not necessarily or fully capture this last aspect of financial well-being. (5)

 This all seems reasonable to me in the abstract, although I am not sure how you would measure success across a large group of people given the very different ways that people would respond to the prongs of that definition. I would also note that events beyond the control of a financially literate person (illness, structural unemployment etc.) could devastate that person’s financial well-being, much as upright Job was devastated by the tests he had to endure.  Notwithstanding these concerns, I am looking forward to see how the CFPB uses its definition to develop its research agenda and to design its policies.

Who Benefits from the Low Income Housing Tax Credit?

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HUD’s Office of Policy Development and Research has released a report, Understanding  Whom  the  LIHTC  Program  Serves: Tenants  in  LIHTC  Units  as  of  December  31,  2012. By way of background,

The Low-Income Housing Tax Credit (LIHTC) Program provides tax credits to developers of affordable rental housing. The tax credits are provided during the first 10 years of a minimum 30-year compliance period during which rent and income restrictions apply. The LIHTC Program, although established in the U.S. Internal Revenue Code (IRC), is structured such that state-allocating agencies administer most aspects of the program, including income and rent compliance, with the Internal Revenue Service (IRS) providing oversight and guidance. Local administration allows states to address affordable housing needs specific to their populations. (1)

 Here are some findings of note:

  • Approximately three-fourths of reported households include disability status for at least one household member.
  • 36.4 percent of reported LIHTC households had a least one member under 18 years old.
  • Nearly 33 percent of reported LIHTC households have an elderly member, and 28.6 percent of reported LIHTC households have a head of household at least 62 years old.
  • The overall median annual income of households living in LIHTC units was $17,066, ranging from $8,769 in Kentucky to $22,241 in Florida. By comparison, the median income of HUD-assisted tenants was $10,272 in 2012.
  • Approximately 60 percent of reported households nationwide had incomes below $20,000.
  • The study found that approximately 39 percent of all LIHTC households paid more than 30 percent of their income for rent, thus making them housing cost burdened. Ten percent of all LIHTC households faced a severe housing cost burden, paying more than 50 percent of their income towards rent.
  • In 23 states, HUD was able to collect some data on the use of rental assistance in LIHTC units, which can eliminate cost burden for households who have it. Approximately half of reported households receive some form of rental assistance, with the greatest use in Vermont (64 percent) and least use in Nevada (23 percent).

The Housing and Economic Recovery Act of 2008 requires that this information be collected on an ongoing basis. It should be of great value as policymakers formulate federal housing policy for low-income households going forward.

NYC’s Changing Neighborhood Demographics

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The Citizens Housing Planning Council has released a cool interactive map of NYC, Making Neighborhoods.  It “follows change across the city by putting people at the center of analysis. Our work measures and visualizes the movements of groups of New Yorkers who share demographic characteristics.”

The press release continues,

The project uses cluster analysis methodology–common in economic or marketing studies–to form 14 distinct groups, or “population clusters,” and follow their locations in 2000 and 2010. By comparing the two years, we can see which population types grew in number or geographic size, or moved into new areas; if their numbers declined or they retreated from their neighborhoods and were replaced by others; or if groups remained relatively unchanged in a decade. By following groups of people with shared characteristics, we see a different portrait of a changing city. It is one that New Yorkers will recognize, as it reflects the neighborhoods they make for themselves.

Making Neighborhoods stands out among neighborhood-level research being done today in two ways. First, it ignores government-drawn boundary lines like community districts and sub-borough areas, which often obscure important patterns that cross these borders. Second, it captures intersectional change: rather than measuring individual changes in income, race, education type, and so on, this study shows changes in all of those dimensions.

Our work on this project includes three main outputs. First, a full academic paper details the research methods, the cluster traits, their changes over the study period, and policy implications. We also created a report that summarizes and draws out the highlights of the full-length paper. Finally, we created–with help from Van Dam, Inc.–interactive maps that communicate this fairly complex study in a stunning visualization.

In addition to distilling five overarching trends from the population cluster changes, CHPC and lead researcher Raisa Bahchieva performed an analysis of housing distress citywide. By measuring and locating the filing of lis pendens notices and housing code violations, we are able to see which population clusters are experiencing mortgage foreclosure or poor housing, respectively.

This is another cool mapping tool that helps to make sense of NYC’s complex geographic, political and social environment.