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Data Tools for Dynamic Communities
More than ever, primary data and data tools are accessible for all types of consumers, from statisticians to novices. Large and complex "big data" has become an area ripe for exploration, and even run-of-the-mill data are being used in novel and interesting ways. Infographics and data visualization tools are increasingly available from many sources, such as an interactive map accompanying a news article or a graph of expenditures analyzing an online credit card statement. These types of tools enrich our understanding of concepts and trends. Accordingly, many data tools have been developed that have significant applications in community and economic development.
Two very useful and well-established tools in this field include the H+T® Index created by the Center for Neighborhood Technology (CNT) and the Location Affordability Index (LAI), developed by the U.S. Department of Housing and Urban Development (HUD) and Department of Transportation, in collaboration with Manhattan Strategy Group and with support from CNT. Both tools aim to capture the real variation between housing and transportation costs between and within regions, and therefore the relative affordability for households of varying income levels. While both were built on CNT's original model, there are several differences between the two tools, with the most significant being the current models used.
The H+T tool allows users to determine an area's average percentage of household income spent on housing and transportation, among other metrics, for three different types of households: those earning the median income at the national and regional levels, and those earning 80 percent of the regional median income. The LAI tool provides the percentage of household income spent on housing and transportation for eight different types of households, including (in order of income level) very low-income individuals, single-parent families, working individuals, retired couples, moderate-income families, median-income families, single professionals, and dual-professional families, with between zero and two commuters per household.
Both tools provide data at various levels of granularity: U.S. Census block groups, tracts, places, counties, and metropolitan areas (core-based statistical areas, or CBSAs), for example. The H+T offers 94 percent coverage of the United States at the block group level or larger, while the LAI offers 100 percent coverage for block groups in CBSAs and for counties in nonmetro areas. Both use relatively recent Census demographic, employment, transportation, and geographic feature data. The model used in the LAI (called a simultaneous equation model, or SEM) accounts for interrelationships between various inputs, and many variables have been refined or replaced in the latest iteration (version 2). The H+T methodology is an ordinary least squares (OLS) regression analysis that predicts the transportation costs of automobile and transit. The advantage of the SEM model is that it is able to handle greater interaction of relationships, making it a good fit for this type of application. The OLS model is perhaps more easily understood and interpretable.
The H+T tool was created in 2006 for planners, housing stakeholders, policymakers, and researchers to better understand the cost burden of housing and transportation in their regions in order to promote more location efficient development. It has been used by HUD, the state of Illinois, the city of El Paso, and other jurisdictions to benchmark and evaluate potential developments. It was recently highlighted in a Forbes article, "The Best and Worst Cities for Finding a Job in 2016." The original LAI tool portal was launched in 2013 and updated in 2014. HUD provides a searchable resource library with dozens of documents on research and development, analysis, commentary, and educational materials related to housing and transportation affordability.
It should also be noted that CNT has created a number of additional tools, such as the comprehensive transit mapping tool All Transit™ and the National TOD Database for evaluating transit stations and regions (in collaboration with Reconnecting America and Strategic Economics and other entities). In 10 years of providing data, the H+T Index has had a significant influence on policy and on the state of the art in mapping and data visualization tools. The LAI has refined the H+T model and allows for greater differentiation between household types. These tools each provide a deeper understanding of the cost of living in U.S. communities and are meant to influence development and policy that will reduce the household cost burden of housing and transportation.
By Ann Carpenter, Atlanta Fed CED adviser