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Humanizing Data: Area Median Income (AMI) and Affordable Housing Policy

January 8, 2020 Andy Marzo

Although much of the analytic work that we do is data driven and metric focused, our analytics team tries to add a human element to these figures to give a more holistic picture of a community’s unique situations. Uniting the human element with metrics and data results in tailored solutions and policies that address particular issues for our clients.

One metric that can be confusing to many and important to humanize is Area Median Income (AMI) and the associated AMI levels determined by the US Department of Housing and Urban Development (HUD) every year. Since AMI is used in determining eligibility for affordable housing programs at the federal and sometimes local levels, its particularly important that decision makers and community members understand this metric, and who the people are that may be impacted by any policies that leverage AMI or AMI levels.

Area Median Income – A Quick Overview

Each year, HUD calculates the area median income (AMI) for every geographic region in the country by using data from the US Census based American Community Survey. The area median income is the midpoint of a region’s income distribution, meaning that half of households in a region earn more than the median and half earn less than the median. A household’s income is calculated by its gross income, which is the total income received before taxes and other payroll deductions.

In addition to calculating AMI, HUD defines and calculates different levels of AMI for geographic areas across the country by household size. Households less than 80% of the AMI are considered low-income households, households earning less than 50% of the AMI are considered to be very low-income, and households earning less than 30% of AMI are considered to be extremely low-income households. These income levels set relative to AMI identify households that may be eligible for certain housing assistance programs administered through HUD (however, the number of tiers used, and percentage of AMI used for qualification varies by each housing program).

AMI Thresholds and HUD’s Housing Choice Voucher Program

A good example of how these thresholds are used at the federal level is HUD’s Housing Choice Voucher Program. The housing choice voucher program is the federal government’s major program for assisting very low-income families, the elderly, and the disabled to afford decent, safe, and sanitary housing in the private market. To be eligible for a Housing Choice Voucher, household income must be at or below 50% of AMI.

As displayed in the table below, which outlines a portion of the AMI levels for the City of San Francisco region, this means that a one-person household would need to have a household income at or below $43,100 to be eligible, a two-person household (which may include a child) would have to have an annual household income at or below $49,250 to be eligible, and so on.

Humanizing AMI to Help Inform Communities and Housing Policies

In addition to HUD, many local housing programs use AMI levels to govern eligibility for affordable housing programs. However, when initial housing policies are being contemplated – community leaders, decision makers, and other stakeholders can be left confused and wondering who exactly resides in these AMI levels, and in turn who they may be helping through their housing policies. To overcome this, it can be helpful to add context and create graphics that humanize AMI metrics so that decision makers know who they may be assisting and/or targeting through their respective programs.

Below is an example of how this can be done using the data from the table above. In this figure, we take AMI level data and turn it into a figure that overlays various occupational median earnings data for the area. By doing this and aligning it with the individual household income level figures along the axis, it is easier to tell who resides in these AMI levels and who programs might target once implemented.

For example, if you wanted to establish a localized affordable housing voucher program with eligibility requirements outlining that households must be below 50% AMI to qualify, you can now see that a family of four (two adults and two children) where one parent is a fast-food cook and the other is a paramedic would not qualify because the combined household income ($63,000) is above the 50% AMI threshold for a family of four ($61,600).

Looking at the data and metrics in this light brings more human context to the reader or decision maker, which in turn helps inform them on who programs can assist based on the eligibility requirements being contemplated. With more and more aspects of our lives and local policies focusing on data and metrics, it is important to continue to use the human context to make the data more impactful and meaningful.

Image Source: Camoin 310