Metro Atlanta Housing Data Explorer

<p style='box-sizing:border-box; margin-top:0px; margin-bottom:20px; color:rgb(54, 56, 57); font-family:Arial, Helvetica, sans-serif; font-size:14px;'>The Atlanta Regional Commission (ARC), in collaboration with several internal departments and external contracting, recently published a new tool for assessing housing market dynamics around the metro area. The <a href='https://metroatlhousing.org/' target='_blank' rel='nofollow ugc noopener noreferrer'>Metro Atlanta Housing Strategy Toolkit</a><u> </u>includes a mapping component displaying ten distinct submarkets in the 11-county Atlanta region. The submarkets are defined by identifying similar patterns of demographic and economic factors. The toolkit also features recommendations for possible housing policy strategies by area, such as preserving affordable units, increasing supply, and promoting housing stability.</p><p style='box-sizing:border-box; margin-top:0px; margin-bottom:20px; color:rgb(54, 56, 57); font-family:Arial, Helvetica, sans-serif; font-size:14px;'>ARC developed the toolkit to equip local governments and civic organizations with (1) data to understand factors impacting barriers to affordable housing and the dynamic forces at play presenting challenges for potential homeowners, and (2) initial strategy options to consider in addressing the barriers and challenges.</p><p style='box-sizing:border-box; margin-top:0px; margin-bottom:20px; color:rgb(54, 56, 57); font-family:Arial, Helvetica, sans-serif; font-size:14px;'>The submarkets shown in the mapping tool were built up out of Census tracts, by using a supervised learning technique to categorize each tract as urban or suburban based on land use. The research also incorporates home sales data from <span style='box-sizing:border-box;'><a href='https://www.attomdata.com/sem/property-data/?creative=615885122373&amp;keyword=attom%20data%20solutions&amp;matchtype=p&amp;network=g&amp;device=c&amp;gad_source=1&amp;gclid=CjwKCAiAhP67BhAVEiwA2E_9g7_1Vxbfw4Y8hlK0tpzyqIpDwYt_RFyxCt_nRClS_ABP4UYve-He8xoC0twQAvD_BwE' style='box-sizing:border-box; text-decoration:none; color:var(--link_color);' target='_blank' rel='nofollow ugc noopener noreferrer'>ATTOM Data Solutions</a></span> aggregated to the tract level as well as several Census variables. For more detail on the methodology, including a template of the Python notebook used in the analysis, see our <a href='https://github.com/arc-research-analytics/MAHS_update_2024' target='_blank' rel='nofollow ugc noopener noreferrer'>GitHub repo</a>.</p>