by Chris Marshall, National Housing Conference
NHC’s Center for Housing Policy will begin researching the combined housing and transportation (H+T) costs of low-income households (those at or below 50 percent of area median income (AMI)). To do so, Center staff is capitalizing on data from HUD’s Location Affordability Index (LAI).
The LAI predicts housing and transportation costs for different geographic levels in 942 Core Based Statistical Areas (covering 94 percent of the U.S. population). The cost estimates are for 12 different household types, ranging in estimated income from a two-worker family to a single, very low-income person.
This is not the first time the Center has researched H+T costs. In 2006, we partnered with the Center for Neighborhood Technology (CNT) and the Institute of Transportation Studies at UC-Berkeley to produce A Heavy Load: The Combined Housing and Transportation Burdens of Working Families. The report documented how moderate-income households were making trade-offs between housing and transportation costs. The Center and CNT partnered again in 2012 to produce Losing Ground: The Struggle of Moderate-Income Households to Afford the Rising Costs of Housing and Transportation. This report examined the H+T burdens of moderate-income households in the 25 largest metro areas in the U.S.
Center staff is excited to use data from the relatively new LAI, as it builds on previous housing and transportation cost tools (see CNT’s H+T Affordability Index). Using the data, however, requires that one acknowledge some limitations. Chief among these is that housing data is from the 2006-2010 American Community Survey. A third-party review says that “house prices within and between cities can change drastically over a few years, and using data that is, on average, four years old creates a significant risk that estimates are not accurate.” Related limitations include the use of older mortgage data (thereby not reflecting the true, current cost of newly buying a home in a neighborhood) and the use of imprecise block group data. As the review states, “For every block group… the average margin of error for block group level (selected monthly owner costs) is 37percent of the level.”
These limitations in mind, the LAI remains a helpful tool to at least generally understand H+T costs for low-income (and other) households. Local entities are using the tool to analyze what is happening in their parts of the country. For example, the Chicago Metropolitan Agency for Planning uses the LAI to estimate “that a typical low-income household would need to spend 46… to 145 percent of its income on [H+T] to live in much of the region.” The Metropolitan Washington Council of Governments says “the [LAI] will be another key device in COG’s toolkit to help meet the Regional Forward Target in keeping housing and transportation costs below 45percent of median household income….” And the cities of Minneapolis and Saint Paul link to the LAI from their “Live MSP” homepage to help current and prospective residents “measure the true affordability of a city neighborhood….”
Going forward, we will consider diving into certain research questions, such as:
· What are the H, T, and combined H+T costs for low-income households nationwide and in the largest metro areas?
· If the H+T share of income is relatively higher for low-income households than others, what are the economic and social implications?
· How might H+T costs for low-income households correlate with access to opportunity areas?
· What are the implications of the methodology and data limitations on using LAI data for analyzing H+T costs?
How have you used the LAI to answer your particular research questions?