{"id":9467,"date":"2024-03-13T09:06:29","date_gmt":"2024-03-13T13:06:29","guid":{"rendered":"https:\/\/montgomeryplanning.org\/blog-design\/?p=9467"},"modified":"2026-03-23T16:25:33","modified_gmt":"2026-03-23T20:25:33","slug":"repositioning-montgomery-county-for-prosperity-part-2-montgomery-countys-income-shifts-in-regional-and-national-contexts","status":"publish","type":"post","link":"https:\/\/montgomeryplanning.org\/blog-design\/2024\/03\/repositioning-montgomery-county-for-prosperity-part-2-montgomery-countys-income-shifts-in-regional-and-national-contexts\/","title":{"rendered":"Repositioning Montgomery County for Prosperity, Part 2: Montgomery County\u2019s Income Shifts in Regional and National Contexts"},"content":{"rendered":"<p class=\"lead\"><!--<img decoding=\"async\" src=\"https:\/\/montgomeryplanning.org\/blog-design\/wp-content\/uploads\/2024\/03\/Screenshot-2024-03-13-at-9.07.11-AM.png\" alt=\"\" \/><span data-mce-type=\"bookmark\" style=\"display: inline-block; width: 0px; overflow: hidden; line-height: 0;\" class=\"mce_SELRES_start\"><\/span>-->The <a href=\"https:\/\/montgomeryplanning.org\/blog-design\/2024\/03\/repositioning-montgomery-county-for-prosperity-part-1-montgomery-countys-income-shifts\/\">previous blog<\/a> in this <a href=\"https:\/\/montgomeryplanning.org\/blog-design\/tag\/repositioning-montgomery-county-for-prosperity\/\">series<\/a> described how income-based population dynamics are shifting within Montgomery County. This blog compares these dynamics with those in Montgomery County\u2019s regional neighbors and other large counties across the nation.<\/p>\n<h2>Income Change in the Washington, DC Region<\/h2>\n<p>The previous blog noted that Montgomery County\u2019s low- and middle-income populations both shifted by five percentage points, in opposite directions, from 2005 to 2022. The low-income share of Montgomery County\u2019s population rose from 25% to 30%, while the middle-income share fell from 23% to 18%.<\/p>\n<p>This shift may not seem significant, but it stands out in the region. Compared with the United States as a whole and the 10 largest jurisdictions near Montgomery County, these compositional changes in low- and middle-income populations were the largest and second largest in their respective directions (orange bar in Figures 1 and 2). Within this region, only Prince William County and Montgomery County failed to increase their high-income shares (Figure 3).<\/p>\n<p><iframe id=\"datawrapper-chart-fCpjP\" style=\"width: 0; min-width: 100% !important; border: none;\" title=\"Figure 1: Change in share of low-income population, 2005-2022\" src=\"https:\/\/datawrapper.dwcdn.net\/fCpjP\/1\/\" height=\"371\" frameborder=\"0\" scrolling=\"no\" aria-label=\"Bar Chart\" data-external=\"1\"><span data-mce-type=\"bookmark\" style=\"display: inline-block; width: 0px; overflow: hidden; line-height: 0;\" class=\"mce_SELRES_start\">?<\/span><\/iframe><script type=\"text\/javascript\">!function(){\"use strict\";window.addEventListener(\"message\",(function(a){if(void 0!==a.data[\"datawrapper-height\"]){var e=document.querySelectorAll(\"iframe\");for(var t in a.data[\"datawrapper-height\"])for(var r=0;r<e.length;r++)if(e[r].contentWindow===a.source){var i=a.data[\"datawrapper-height\"][t]+\"px\";e[r].style.height=i}}}))}();\n<\/script><\/p>\n<p><iframe id=\"datawrapper-chart-KOKaG\" style=\"width: 0; min-width: 100% !important; border: none;\" title=\"Figure 2: Change in share of middle-income population, 2005-2022\" src=\"https:\/\/datawrapper.dwcdn.net\/KOKaG\/2\/\" height=\"371\" frameborder=\"0\" scrolling=\"no\" aria-label=\"Bar Chart\" data-external=\"1\"><\/iframe><script type=\"text\/javascript\">!function(){\"use strict\";window.addEventListener(\"message\",(function(a){if(void 0!==a.data[\"datawrapper-height\"]){var e=document.querySelectorAll(\"iframe\");for(var t in a.data[\"datawrapper-height\"])for(var r=0;r<e.length;r++)if(e[r].contentWindow===a.source){var i=a.data[\"datawrapper-height\"][t]+\"px\";e[r].style.height=i}}}))}();\n<\/script><\/p>\n<p><iframe id=\"datawrapper-chart-k3Xzt\" style=\"width: 0; min-width: 100% !important; border: none;\" title=\"Figure 3: Change in share of high-income population, 2005-2022\" src=\"https:\/\/datawrapper.dwcdn.net\/k3Xzt\/2\/\" height=\"371\" frameborder=\"0\" scrolling=\"no\" aria-label=\"Bar Chart\" data-external=\"1\"><\/iframe><script type=\"text\/javascript\">!function(){\"use strict\";window.addEventListener(\"message\",(function(a){if(void 0!==a.data[\"datawrapper-height\"]){var e=document.querySelectorAll(\"iframe\");for(var t in a.data[\"datawrapper-height\"])for(var r=0;r<e.length;r++)if(e[r].contentWindow===a.source){var i=a.data[\"datawrapper-height\"][t]+\"px\";e[r].style.height=i}}}))}();\n<\/script><\/p>\n<p>Montgomery County gained more low-income residents and lost more middle-income residents than any of the 10 other jurisdictions. Washington, DC, Loudoun County, VA, and Fairfax County, VA all gained more high-income residents during the period than Montgomery County, with DC nearly doubling Montgomery County\u2019s gain. Although Montgomery County had the third largest net gain in high-income population, its percent change\u2014accounting for the initial size of its high-income population\u2014was the lowest of its neighbors at 14%.<\/p>\n<p><span class=\"block-headline datawrapper-k3Xzt-ckuume \" style=\"margin: 5px 0px 0px 0px;\">Table 1: Net and Percent changes of Income-Based Population Groups in Washington, DC Region*, 2005\u20132022, listed in order of net low-income change<\/span><\/p>\n<table style=\"border: 1px black solid;\" width=\"95%\" cellpadding=\"5\">\n<thead>\n<tr>\n<th rowspan=\"2\" valign=\"bottom\">Jurisdiction<\/th>\n<th style=\"text-align: center; border-bottom: 1px solid black; border-left: 1px solid black;\" colspan=\"3\" scope=\"colgroup\" valign=\"bottom\">Net Change<\/th>\n<th style=\"text-align: center; border-bottom: 1px solid black; border-left: 1px solid black;\" colspan=\"3\" scope=\"colgroup\" valign=\"bottom\">Percent Change<\/th>\n<\/tr>\n<tr style=\"text-align: center; border-bottom: 1px solid black;\">\n<th style=\"text-align: center; border-left: 1px solid black;\" scope=\"col\" valign=\"bottom\">Low-income<\/th>\n<th style=\"text-align: center;\" scope=\"col\" valign=\"bottom\">Middle-income<\/th>\n<th style=\"text-align: center; border-right: 1px solid black;\" scope=\"col\" valign=\"bottom\">High-income<\/th>\n<th style=\"text-align: center;\" scope=\"col\" valign=\"bottom\">Low-income<\/th>\n<th style=\"text-align: center;\" scope=\"col\" valign=\"bottom\">Middle-income<\/th>\n<th style=\"text-align: center;\" scope=\"col\" valign=\"bottom\">High-income<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr style=\"background-color: #f8f8f8;\">\n<td style=\"text-align: left; border-right: 1px solid black;\" width=\"25%\">Montgomery County, MD<\/td>\n<td style=\"text-align: center;\" width=\"12.5%\">87,927<\/td>\n<td style=\"text-align: center;\" width=\"12.5%\">-26,279<\/td>\n<td style=\"text-align: center; border-right: 1px solid black;\" width=\"12.5%\">67,177<\/td>\n<td style=\"text-align: center;\" width=\"12.5%\">39%<\/td>\n<td style=\"text-align: center;\" width=\"12.5%\">-12%<\/td>\n<td style=\"text-align: center;\" width=\"12.5%\">14%<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: left; border-right: 1px solid black;\">Prince George's County, MD<\/td>\n<td style=\"text-align: center;\">54,905<\/td>\n<td style=\"text-align: center;\">-1,339<\/td>\n<td style=\"text-align: center; border-right: 1px solid black;\">45,827<\/td>\n<td style=\"text-align: center;\">19%<\/td>\n<td style=\"text-align: center;\">-1%<\/td>\n<td style=\"text-align: center;\">15%<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8;\">\n<td style=\"text-align: left; border-right: 1px solid black;\">Prince William County, VA<\/td>\n<td style=\"text-align: center;\">47,774<\/td>\n<td style=\"text-align: center;\">29,434<\/td>\n<td style=\"text-align: center; border-right: 1px solid black;\">58,697<\/td>\n<td style=\"text-align: center;\">49%<\/td>\n<td style=\"text-align: center;\">35%<\/td>\n<td style=\"text-align: center;\">36%<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: left; border-right: 1px solid black;\">Fairfax County, VA<\/td>\n<td style=\"text-align: center;\">33,341<\/td>\n<td style=\"text-align: center;\">-2,558<\/td>\n<td style=\"text-align: center; border-right: 1px solid black;\">98,771<\/td>\n<td style=\"text-align: center;\">15%<\/td>\n<td style=\"text-align: center;\">-1%<\/td>\n<td style=\"text-align: center;\">17%<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8;\">\n<td style=\"text-align: left; border-right: 1px solid black;\">Loudoun County, VA<\/td>\n<td style=\"text-align: center;\">29,473<\/td>\n<td style=\"text-align: center;\">24,176<\/td>\n<td style=\"text-align: center; border-right: 1px solid black;\">122,362<\/td>\n<td style=\"text-align: center;\">76%<\/td>\n<td style=\"text-align: center;\">41%<\/td>\n<td style=\"text-align: center;\">78%<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: left; border-right: 1px solid black;\">Howard County, MD<\/td>\n<td style=\"text-align: center;\">25,405<\/td>\n<td style=\"text-align: center;\">-4,564<\/td>\n<td style=\"text-align: center; border-right: 1px solid black;\">46,243<\/td>\n<td style=\"text-align: center;\">61%<\/td>\n<td style=\"text-align: center;\">-7%<\/td>\n<td style=\"text-align: center;\">30%<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8;\">\n<td style=\"text-align: left; border-right: 1px solid black;\">Charles County, MD<\/td>\n<td style=\"text-align: center;\">9,940<\/td>\n<td style=\"text-align: center;\">7,316<\/td>\n<td style=\"text-align: center; border-right: 1px solid black;\">14,652<\/td>\n<td style=\"text-align: center;\">26%<\/td>\n<td style=\"text-align: center;\">20%<\/td>\n<td style=\"text-align: center;\">24%<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: left; border-right: 1px solid black;\">Frederick County, MD<\/td>\n<td style=\"text-align: center;\">7,633<\/td>\n<td style=\"text-align: center;\">11,334<\/td>\n<td style=\"text-align: center; border-right: 1px solid black;\">48,715<\/td>\n<td style=\"text-align: center;\">13%<\/td>\n<td style=\"text-align: center;\">17%<\/td>\n<td style=\"text-align: center;\">52%<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8;\">\n<td style=\"text-align: left; border-right: 1px solid black;\">Alexandria City, VA<\/td>\n<td style=\"text-align: center;\">-733<\/td>\n<td style=\"text-align: center;\">-1,680<\/td>\n<td style=\"text-align: center; border-right: 1px solid black;\">23,663<\/td>\n<td style=\"text-align: center;\">-2%<\/td>\n<td style=\"text-align: center;\">-6%<\/td>\n<td style=\"text-align: center;\">37%<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: left; border-right: 1px solid black;\">Arlington County, VA<\/td>\n<td style=\"text-align: center;\">-7,756<\/td>\n<td style=\"text-align: center;\">2,165<\/td>\n<td style=\"text-align: center; border-right: 1px solid black;\">45,341<\/td>\n<td style=\"text-align: center;\">-14%<\/td>\n<td style=\"text-align: center;\">6%<\/td>\n<td style=\"text-align: center;\">44%<\/td>\n<\/tr>\n<tr style=\"border-bottom: 1px solid black; background-color: #f8f8f8;\">\n<td style=\"text-align: left; border-right: 1px solid black;\">District of Columbia<\/td>\n<td style=\"text-align: center;\">-44,938<\/td>\n<td style=\"text-align: center;\">22,097<\/td>\n<td style=\"text-align: center; border-right: 1px solid black;\">152,557<\/td>\n<td style=\"text-align: center;\">-18%<\/td>\n<td style=\"text-align: center;\">24%<\/td>\n<td style=\"text-align: center;\">89%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p class=\"wp-caption-text\">Data: 2005 and 2022 1-year ACS estimates<\/p>\n<p class=\"wp-caption-text\">*Includes the 10 largest jurisdictions in the Washington-Arlington-Alexandria (DC-VA-MD-WV) metropolitan statistical area and Howard County, which is in the neighboring Baltimore-Columbia-Towson (MD) metropolitan statistical area. Fairfax City, Falls Church City, Manassas City, and Manassas Park, all in Virginia, are not included in the data.<\/p>\n<h2>Income Change in the United States Overall and in Other Large Counties<\/h2>\n<p>The yellow bar in Figures 1 through 3, representing the entire United States, shows that Montgomery County\u2019s compositional shift in population by income level runs counter not only to its neighbors\u2019 trends, but also to the shifts occurring nationwide. To gauge where Montgomery County stands relative to similarly large counties across the country, we ranked its low-, middle-, and high-income changes against the 50 largest counties by population in 2005 (Montgomery was the 40<sup>th<\/sup> largest county; see the <a href=\"https:\/\/montgomeryplanning.org\/wp-content\/uploads\/2024\/03\/Income-Shifts-Research-Brief-Final.pdf\" target=\"_blank\" rel=\"noopener\">Navigating Income Shifts in Montgomery County: Towards Shared Prosperity<\/a> research brief for the full list).<\/p>\n<p>While Montgomery County began the study period with a proportionally small low-income population, ranking 49<sup>th<\/sup> out of these 50 counties, its rapid net growth in this group ranked 9<sup>th<\/sup> out of these 50 counties (see Table 2). To put this growth in perspective, Montgomery County added more low-income people over this period than several counties whose total populations were more than twice its size in 2005. These include Dallas County, TX; Miami-Dade County, FL; and San Bernardino County, CA.<\/p>\n<p><span class=\"block-headline datawrapper-k3Xzt-ckuume \" style=\"margin: 5px 0px 0px 0px;\">Table 2: Montgomery County\u2019s Rank among the 50 Largest Counties in Net Change of Income-Based Population Groups, 2005\u20132022<\/span><\/p>\n<table style=\"border: 1px black solid;\" width=\"95%\" cellpadding=\"5\">\n<thead>\n<tr>\n<th rowspan=\"2\"><\/th>\n<th style=\"text-align: center; border-left: 1px black solid; border-right: 1px black solid;\" rowspan=\"2\" valign=\"bottom\">Total Population 2005<\/th>\n<th style=\"text-align: center; border-bottom: 1px black solid;\" colspan=\"3\" scope=\"colspan\">Population group net change<\/th>\n<\/tr>\n<tr style=\"border-bottom: 1px black solid;\">\n<th style=\"text-align: center; border-left: 1px solid black;\" scope=\"col\">Low-income<\/th>\n<th style=\"text-align: center; border-left: 1px solid black;\" scope=\"col\">Middle-income<\/th>\n<th style=\"text-align: center; border-left: 1px solid black;\" scope=\"col\">High-income<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th style=\"text-align: left; width: 8%;\"><strong>Rank<\/strong><\/th>\n<td style=\"text-align: center; width: 23%; border-left: 1px solid black;\">40<\/td>\n<td style=\"text-align: center; width: 23%; border-left: 1px solid black;\">9<\/td>\n<td style=\"text-align: center; width: 23%; border-left: 1px solid black;\">40<\/td>\n<td style=\"text-align: center; width: 23%; border-left: 1px solid black;\">36<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p class=\"wp-caption-text\">Data: 2005 and 2022 1-year ACS estimates<\/p>\n<p>Montgomery County again contrasts with its neighbors and the nation regarding compositional change. Its five-percentage-point increase in low-income population was not only the highest in the region, but it was also the highest among these 50 large counties. Likewise, it ranked third-to-last in change in share of both middle- and high-income populations.<\/p>\n<p><span class=\"block-headline datawrapper-k3Xzt-ckuume \" style=\"margin: 5px 0px 0px 0px;\">Table 3: Montgomery County\u2019s Rank among the 50 Largest Counties in Change in Share of Income-Based Population Groups, 2005\u20132022<\/span><\/p>\n<table style=\"border: 1px black solid;\" width=\"95%\" cellpadding=\"5\">\n<thead>\n<tr>\n<th rowspan=\"2\"><\/th>\n<th style=\"text-align: center; border-left: 1px solid black;\" rowspan=\"2\" valign=\"bottom\">Total Population 2005<\/th>\n<th style=\"text-align: center; border-bottom: 1px black solid; border-left: 1px solid black;\" colspan=\"3\" scope=\"colspan\">Population group net change<\/th>\n<\/tr>\n<tr style=\"border-bottom: 1px black solid;\">\n<th style=\"text-align: center; border-left: 1px solid black;\" scope=\"col\">Low-income<\/th>\n<th style=\"text-align: center; border-left: 1px solid black;\" scope=\"col\">Middle-income<\/th>\n<th style=\"text-align: center; border-left: 1px solid black;\" scope=\"col\">High-income<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th style=\"text-align: left; width: 8%;\"><strong>Rank<\/strong><\/th>\n<td style=\"text-align: center; width: 23%; border-left: 1px solid black;\">40<\/td>\n<td style=\"text-align: center; width: 23%; border-left: 1px solid black;\">1<\/td>\n<td style=\"text-align: center; width: 23%; border-left: 1px solid black;\">48<\/td>\n<td style=\"text-align: center; width: 23%; border-left: 1px solid black;\">48<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p class=\"wp-caption-text\">Data: 2005 and 2022 1-year ACS estimates<\/p>\n<p>Most counties on this list, as well as the nation overall, saw a decline in the middle-income population, as incomes have generally improved relative to the poverty level since 2005. In this sense, Montgomery County is no different. What sets Montgomery County apart is the combination of its middle-income loss with its significant low-income gain. These shifts have contributed to Montgomery County\u2019s rapid compositional change in population and its stagnation in overall income metrics. While there is no single factor underlying these income trends, the dramatic decline in middle-income population suggests there\u2019s not enough housing in the county that this group can afford.<\/p>\n<p>The <a href=\"https:\/\/montgomeryplanning.org\/blog-design\/2024\/03\/repositioning-montgomery-county-for-prosperity-part-3-abundant-housing-for-inclusive-growth\/\">last blog in this series<\/a> takes a deeper dive into how housing relates to these population shifts and what Montgomery County can do to encourage more inclusive and sustainable growth.<\/p>\n<hr \/>\n<div style=\"clear: right; width: 100%;\"><img decoding=\"async\" class=\"alignleft\" style=\"clear: left; padding: 15px;\" src=\"https:\/\/montgomeryplanning.org\/blog-design\/wp-content\/uploads\/2023\/07\/ben-kraft.jpg\" alt=\"Ben Kraft\" width=\"220\" \/><br \/>\n<strong>About the author<\/strong><br \/>\nBenjamin Kraft is a research planner in Montgomery Planning\u2019s Research and Strategic Projects Division. His research and planning work focus on topics related to the economy and employment. Ben has a Ph.D. in city and regional planning from Georgia Tech and a master\u2019s degree in urban planning from the University of Michigan.<\/div>\n","protected":false},"excerpt":{"rendered":"<p class=\"lead\">The previous blog in this series described how income-based population dynamics are shifting within Montgomery County. This blog compares these dynamics with those in Montgomery County\u2019s regional neighbors and other large counties across the nation.<\/p>\n<p> Income Change in the Washington, DC Region <\/p>\n<p>The previous blog noted that Montgomery County\u2019s low- and middle-income populations both shifted by five percentage points, in opposite directions, from 2005 to 2022. The low-income share of Montgomery County\u2019s population rose from 25% to 30%, while the middle-income share fell from 23% to 18%.<\/p>\n<p>This shift may not seem significant, but it stands out in the region. Compared with the United States as a whole and the 10 largest jurisdictions near Montgomery County, these compositional changes &#8230; <a href=\"https:\/\/montgomeryplanning.org\/blog-design\/2024\/03\/repositioning-montgomery-county-for-prosperity-part-2-montgomery-countys-income-shifts-in-regional-and-national-contexts\/\" class=\"read-more\">Continue reading<\/a><\/p>\n","protected":false},"author":35,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[519],"tags":[714,693],"class_list":["post-9467","post","type-post","status-publish","format-standard","hentry","category-research","tag-economy-research","tag-repositioning-montgomery-county-for-prosperity"],"_links":{"self":[{"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/posts\/9467","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/users\/35"}],"replies":[{"embeddable":true,"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/comments?post=9467"}],"version-history":[{"count":30,"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/posts\/9467\/revisions"}],"predecessor-version":[{"id":11189,"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/posts\/9467\/revisions\/11189"}],"wp:attachment":[{"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/media?parent=9467"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/categories?post=9467"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/tags?post=9467"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}