This article was originally published in the November/December 1995 issue of Home Energy Magazine. Some formatting inconsistencies may be evident in older archive content.



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Home Energy Magazine Online November/December 1995


in energy

Computing Commuting Into Mortgages

City dwellers have long known that they spend less on transportation than do suburbanites. Now conservation organizations are studying how these savings might translate into higher qualifying ratios for home mortgages. Just as home buyers or owners who invest in energy efficiency can use their savings on utility bills to qualify for higher mortgages, those who live in dense urban areas may soon be able to use transportation savings in a similar manner.

Planners, transit agencies, and conservation groups throughout the country have been studying the factors determining urban auto dependence. One of the most comprehensive studies was conducted in 1994 by the Natural Resources Defense Council (NRDC) and funded by California Home Energy Efficiency Rating Systems (CHEERS). This study found that residential density and transit accessibility had the strongest influence on driving. Neighborhood shopping and pedestrian accessibility also affect how much people drive, but these factors are closely linked to density and transit.

A 1991 NRDC study of five communities in San Francisco had found that as residential density increases, trip destinations, such as markets, jobs, restaurants, friends, and relatives are nearer, allowing for shorter trips. As density doubles, per capita vehicle miles traveled (VMT) decreases by 25% to 30%. To compare two extremes in the San Francisco region, northeast San Francisco had about 100 households per residential acre, with driving averaging 5,519 miles per year, while Danville-San Ramon, 20 miles southeast of Oakland and Berkeley, had approximately 3.2 households per residential acre, each driving an average of 28,153 miles per year. Other communities in the area fell between these extremes--those with higher density having lower VMT.

The 1991 study was expanded in 1994 to include other areas in California. This study found that increased density generally correlates with improvement in transit accessibility, neighborhood shopping, and pedestrian accessibility. In northeast San Francisco, 90 buses per hour pass within 1/2 mile of the average household, while in San Ramon only 1 does. Northeast San Francisco has a high neighborhood shopping index, meaning that all households are located within a 1/4-mile walk of five key local businesses; in San Ramon, none is. Pedestrians also have an easier time in northeast San Francisco. Despite its famous hills, the area was given a rating of 0.66 for the pedestrian accessibility index, which measures the completeness of the pedestrian grid, the availability of sidewalks, hilliness, and threats from traffic; San Ramon scored 0.08.

A Short Trip to the Bank

Most significant to lenders is the amount urban dwellers save by driving less. The average household in northeast San Francisco spent $4,200 on driving costs annually, while the average household in Danville-San Ramon spent $17,800. The San Francisco households saved $13,600 annually, or $1,130 per month. If banks will consider Energy Efficiency Mortgages for people spending less on utility bills, why not allow a Location Efficient Mortgage (LEM)?

When determining the mortgage a buyer can afford, banks currently do not take variations in transportation expenses into account. Yet housing costs decrease as transportation expenses increase in metropolitan areas, creating a bias toward urban sprawl. As David Goldstein at NRDC put it, location efficient mortgages would level the playing field.

According to Goldstein, two things are needed to make LEMs a reality: a data base of evidence that living in denser areas saves people money on transportation, and a means to assess these savings, just as Home Energy Rating Systems assess the energy efficiency of houses. John Holtzclaw, who conducted both studies for NRDC, has devised a formula for calculating location efficiency, which may serve as a model for lending institutions. Lenders would divide the urban dweller's transportion savings by 12 months and add the savings to the standard PITI (principal, interest, taxes, and insurance) mortgage qualification formula.

Holtzclaw will have the opportunity to refine this formula after gathering new data with an expanded study conducted by NRDC, the Center for Neighborhood Technology in Chicago, and the Surface Transportation Policy Project, a Washington, D.C.-based educational and advocacy group for transportation reform. Holtzclaw hopes to have collected the data by the end of this year, and Goldstein speculates that a rating system and a market for LEMs might also be in place by that time.

--Nancy Hurrelbrinck


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