{"id":7748,"date":"2021-07-27T10:42:12","date_gmt":"2021-07-27T14:42:12","guid":{"rendered":"https:\/\/montgomeryplanning.org\/blog-design\/?p=7748"},"modified":"2021-08-12T10:13:39","modified_gmt":"2021-08-12T14:13:39","slug":"the-opportunity-insights-project-and-economic-mobility-in-montgomery-county","status":"publish","type":"post","link":"https:\/\/montgomeryplanning.org\/blog-design\/2021\/07\/the-opportunity-insights-project-and-economic-mobility-in-montgomery-county\/","title":{"rendered":"The Opportunity Insights Project and Economic Mobility in Montgomery County"},"content":{"rendered":"<p class=\"lead\"><img decoding=\"async\" width=\"1365\" height=\"768\" class=\"alignnone size-full wp-image-7769\" src=\"https:\/\/montgomeryplanning.org\/blog-design\/wp-content\/uploads\/2021\/07\/lab-face-coverings.jpg\" alt=\"Genetic engineering concept. Medical science. Scientific Laboratory.\" srcset=\"https:\/\/montgomeryplanning.org\/blog-design\/wp-content\/uploads\/2021\/07\/lab-face-coverings.jpg 1365w, https:\/\/montgomeryplanning.org\/blog-design\/wp-content\/uploads\/2021\/07\/lab-face-coverings-300x169.jpg 300w, https:\/\/montgomeryplanning.org\/blog-design\/wp-content\/uploads\/2021\/07\/lab-face-coverings-1024x576.jpg 1024w, https:\/\/montgomeryplanning.org\/blog-design\/wp-content\/uploads\/2021\/07\/lab-face-coverings-768x432.jpg 768w\" sizes=\"(max-width: 1365px) 100vw, 1365px\" \/><br \/>\nMontgomery County Planning works to create thriving places across the county. This goal is reflected in our proposed General Plan update, <a href=\"https:\/\/montgomeryplanning.org\/planning\/master-plan-list\/general-plans\/thrive-montgomery-2050\/\">Thrive Montgomery 2050<\/a>, master plans, functional plans, and other special studies.<\/p>\n<p>But how do we know if a place is indeed thriving? \u00a0We often use publicly available data from agencies like the U.S. Census Bureau and the U.S. Bureau of Labor Statistics to analyze shifts in key indicators of an area\u2019s economic vitality.<\/p>\n<p>Now let\u2019s zoom in on the map and ask a deeper question: do thriving neighborhoods help the people living in them to thrive? Put another way, do neighborhoods thrive because the people living in them improved their economic status, or because people of higher economic status moved in? Unfortunately, this question has been difficult to answer because there have been no large, public datasets that capture changes in individuals\u2019 lives over time.<\/p>\n<p>That\u2019s where the <a href=\"https:\/\/opportunityinsights.org\/\">Opportunity Insights<\/a> project comes in. It tracks changes in individuals\u2019 incomes from childhood to adulthood, enabling us to ask whether children who grew up in specific neighborhoods have experienced improvements in their own economic circumstances that are on par with improvements in the neighborhood. The Opportunity Insights dataset also allows us to track differences in outcomes for people based on race and ethnicity. Additionally, since Opportunity Insights data cover the entire U.S., we can assess economic mobility in Montgomery County against other places in the country.<\/p>\n<p>This blog is the first of a two-part series that uses data from Opportunity Insights to describe economic mobility for people in Montgomery County, and how geography, race, and ethnicity impact mobility. As the first in the series, this blog focuses on the Opportunity Insights mobility metric and discusses overall trends in mobility for people who grew up in Montgomery County. Part 2 will look more closely at Montgomery County\u2019s neighborhoods and compare our traditional indicators of neighborhood prosperity to those available from Opportunity Insights.<\/p>\n<h3>The Opportunity Insights Approach to Measuring Economic Mobility<\/h3>\n<p>The Opportunity Insights project is an expansive multi-year investigation conducted by a team of economists and other social scientists, led by Raj Chetty of Harvard University, to assess the state of economic mobility in the United States and to determine policies that may improve mobility. The project is important because it provides comprehensive longitudinal and causal evidence about economic mobility, as well as differences based on race, ethnicity, sex, and even neighborhood.<\/p>\n<p>The key metric produced by Opportunity Insights tracks how an individual\u2019s position in the national household income distribution changes from childhood\u2014when the person\u2019s parents were the main earners\u2014to adulthood. Specifically, it looks at the more than 20 million children born in the U.S. between 1978 and 1983<a href=\"#_ftn1\" name=\"_ftnref1\"><sup>1<\/sup><\/a> at two points in time: 1) when they were about 16 years old\u2014in the mid- to late-1990s\u2014and 2) when they were in their mid-thirties (around the years 2014 and 2015). For example, a child whose parents\u2019 combined income was in the 25<sup>th<\/sup> percentile of the national income distribution (the bottom quarter, about $30,000 in 2014 dollars) when they are 16 may ultimately wind up in the 51<sup>st<\/sup> percentile (the top half, compared only to people of their age) by the time they reache their mid-30s. By virtue of moving up in the national income distribution, this person would be considered upwardly mobile. This blog will use the term \u201cchildhood household income\u201d to reflect the initial measure and \u201cadult household income\u201d to indicate the outcome.<\/p>\n<p>There are two important points to keep in mind about the adult household income metric. First, it reflects <em>household<\/em> rather than individual incomes, so it introduces a bit of bias by comparing people who live alone to households with two or more working adults. Nevertheless, this bias is likely minimized by comparing people at the same stages of life: They compare 35-year-olds to 35-year-olds; not for example 35-year-olds to 55-year-olds, the latter of whom on average earn much more. Second, being \u201cfrom\u201d a tract only applies to a person\u2019s childhood years. Adult household incomes are counted regardless of whether they stayed in the same tract or moved anywhere else in the nation.<br \/>\n<img decoding=\"async\" width=\"1254\" height=\"836\" class=\"alignnone size-full wp-image-7770\" src=\"https:\/\/montgomeryplanning.org\/blog-design\/wp-content\/uploads\/2021\/07\/Office_facecoverings.jpg\" alt=\"Corporate meeting and group work in modern company in office interior. African american woman manager in protective mask holding tablet, talking to workers keeping social distance during epidemic\" srcset=\"https:\/\/montgomeryplanning.org\/blog-design\/wp-content\/uploads\/2021\/07\/Office_facecoverings.jpg 1254w, https:\/\/montgomeryplanning.org\/blog-design\/wp-content\/uploads\/2021\/07\/Office_facecoverings-300x200.jpg 300w, https:\/\/montgomeryplanning.org\/blog-design\/wp-content\/uploads\/2021\/07\/Office_facecoverings-1024x683.jpg 1024w, https:\/\/montgomeryplanning.org\/blog-design\/wp-content\/uploads\/2021\/07\/Office_facecoverings-768x512.jpg 768w\" sizes=\"(max-width: 1254px) 100vw, 1254px\" \/><\/p>\n<h3>Mobility in the U.S. and in Montgomery County<\/h3>\n<p>Mobility levels across the country have fallen significantly over the last century. According to Chetty and the co-authors, while \u201cmore than 90% of children born in the 1940s grew up to earn more than their parents\u2026today only half of children\u201d reach this milestone.<a href=\"#_ftn2\" name=\"_ftnref2\"><sup>2<\/sup><\/a> This nationwide decline in economic mobility is due to many factors, including economic policy, industrial restructuring, technological change, and the legacy of racism and discrimination.<\/p>\n<p>While declining overall economic mobility is a deeply entrenched nationwide problem that requires comprehensive solutions, the good news for Montgomery County is that its residents have been more economically mobile than residents of other similarly sized counties. Opportunity Insight\u2019s mobility metrics show that in Montgomery County, a teen living in a household with an income at the 25<sup>th<\/sup> percentile nationally in the mid- to late-1990s\u2014not technically in poverty but close to it depending on household size\u2014can expect on average to have made it to about the 48<sup>th<\/sup> percentile of household income by their early thirties. This level of mobility\u2014moving from the bottom quarter of the national household income distribution to just short of the top half\u2014ranks 10<sup>th<\/sup> out of the 125 largest counties in the U.S.<a href=\"#_ftn3\" name=\"_ftnref3\"><sup>3<\/sup><\/a> Montgomery retains this 10<sup>th<\/sup> place ranking in adult income levels when considering all child income levels together, including those raised below the 50<sup>th<\/sup> percentile and those raised above it.<\/p>\n<p>Table 1 shows both the childhood and adult percentiles and their corresponding earnings for children raised at the 25<sup>th<\/sup>, 50<sup>th<\/sup>, and 75<sup>th<\/sup> percentiles of household incomes, as well as the overall average adult (mid-thirties) household incomes for all children raised in Montgomery County.<\/p>\n<h6>Table 1: Average Mobility Outcomes for Children Growing Up in Montgomery County born between 1978 and 1983<\/h6>\n<table>\n<tbody>\n<tr style=\"border-bottom: 1pt solid black;\">\n<th style=\"padding: 10px 5px 0px 0px;\" width=\"25%\">Childhood Income Percentile<\/th>\n<th style=\"padding: 10px 5px 0px 0px;\" width=\"25%\">Childhood Income Level (2015 dollars)<\/th>\n<th style=\"padding: 10px 5px 0px 0px;\" width=\"25%\">Adult Income Percentile<\/th>\n<th style=\"padding: 10px 5px 0px 0px;\" width=\"25%\">Adult Income Level (2015 dollars)<\/th>\n<\/tr>\n<tr>\n<td width=\"25%\">25<sup>th<\/sup><\/td>\n<td width=\"25%\">$27,044<\/td>\n<td width=\"25%\">48<sup>th<\/sup><\/td>\n<td width=\"25%\">$39,924<\/td>\n<\/tr>\n<tr>\n<td width=\"25%\">50<sup>th<\/sup><\/td>\n<td width=\"25%\">$55,802<\/td>\n<td width=\"25%\">55<sup>th<\/sup><\/td>\n<td width=\"25%\">$48,749<\/td>\n<\/tr>\n<tr>\n<td width=\"25%\">75<sup>th<\/sup><\/td>\n<td width=\"25%\">$94,252<\/td>\n<td width=\"25%\">62<sup>nd<\/sup><\/td>\n<td width=\"25%\">$59,128<a href=\"#_ftn4\" name=\"_ftnref4\"><sup>4<\/sup><\/a><\/td>\n<\/tr>\n<tr>\n<td width=\"25%\">All levels<\/td>\n<td width=\"25%\">N\/A<\/td>\n<td width=\"25%\">61<sup>st<\/sup><\/td>\n<td width=\"25%\">$57,533<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<p>Using the first row as an example, the table shows that children raised in Montgomery County in a household at the 25<sup>th<\/sup> percentile of household income in the mid-1990s would have had parents earning the equivalent of $27,044 (in 2015 dollars). On average these children would have gone on to earn\u2014either individually or with a partner \u2013 about $39,924 by 2015, putting them in the 48<sup>th<\/sup> percentile among people the same age nationally.<\/p>\n<h3>The Racial and Ethnic Mobility Gap<\/h3>\n<p>For Black and Hispanic residents, Montgomery County offers high mobility relative to other places. Looking once again at children raised in relatively poor households (the 25<sup>th<\/sup> percentile), Montgomery County ranks 5<sup>th<\/sup> in the nation in Black economic mobility and 3<sup>rd<\/sup> in the nation for Hispanic economic mobility.<\/p>\n<p>These promising statistics are in line with the county\u2019s reputation as a diverse and welcoming community. It certainly seems that Montgomery County is a better place than most\u2014at least statistically and economically\u2014for people of color to grow up.<\/p>\n<p>However, a deeper inspection reveals that Montgomery County has not\u00a0 overcome the racial inequities and wealth disparities that plague the rest of the nation; Montgomery ranks highly not because its own racial and ethnic income gap is small, but rather because the gap almost everywhere else is so large.<\/p>\n<p>To illustrate this gap within Montgomery County, the chart below shows average adult incomes for white, Black, and Hispanic people broken down by the percentile of household income of their parents. Montgomery\u2019s average overall adult household income for white children is $67,657, while for Black children it is only $38,759 (far right set of bars)\u2014an almost $30,000 difference. On average, white children who grow up in Montgomery County go on to form households that earn $1.75 for every $1.00 earned by households formed by Black children, and $1.43 for every $1.00 earned by households formed by Hispanic children. The size of the racial gap in adult earnings is largest for children raised at higher levels of the income distribution, meaning that while children end up out-earning their Black peers from all levels of childhood income, they tend to pull farthest ahead of their high-income Black childhood peers.<\/p>\n<h6>Adult incomes for white, Hispanic, and Black children living in Montgomery County, born between 1978 and 1983, by childhood household income percentile (2015 dollars)<\/h6>\n<p><iframe id=\"datawrapper-chart-9Cp5q\" style=\"width: 0; min-width: 100% !important; border: none;\" title=\"Adult incomes for white, Hispanic, and Black children living in Montgomery County, born between 1978 and 1983, by childhood household income percentile (2015 dollars)\" src=\"https:\/\/datawrapper.dwcdn.net\/9Cp5q\/2\/\" height=\"474\" frameborder=\"0\" scrolling=\"no\" aria-label=\"Grouped Column Chart\"><\/iframe><script type=\"text\/javascript\">!function(){\"use strict\";window.addEventListener(\"message\",(function(e){if(void 0!==e.data[\"datawrapper-height\"]){var t=document.querySelectorAll(\"iframe\");for(var a in e.data[\"datawrapper-height\"])for(var r=0;r<t.length;r++){if(t[r].contentWindow===e.source)t[r].style.height=e.data[\"datawrapper-height\"][a]+\"px\"}}}))}();\n<\/script><\/p>\n<p>As noted above, Montgomery County\u2019s racial and ethnic economic mobility gap is significant, but ranks favorably because it pales in comparison to other similarly large counties in the U.S. For example, Fulton County, GA (where Atlanta is located), ranks near the bottom in the nation for Black economic mobility (116<sup>th<\/sup> out of the 125 largest counties). In Fulton County, the average Black child grew up to have a household income just under $24,000 per year, while the average white child grew up to have a household income of just under $64,000 per year. This means that the average white child from Fulton goes on to earn $2.67 for every dollar earned by the average Black child (at the household level), which is the largest black-white mobility gap in the nation. While Montgomery County fares well in Black economic mobility compared to other similar counties, this achievement is only relative, and it has certainly not conquered the problem.<\/p>\n<h3>Opportunity and Mobility in Perspective<\/h3>\n<p>Opportunity Insights mobility data show mixed results for Montgomery County. On one hand, many people who grew up in the county have been quite upwardly mobile over the last several decades even though the county\u2019s median income slightly declined.\u00a0 Black and Hispanic people who grew up in Montgomery County have some of the highest mobility levels in the nation. These are hopeful trends upon which we can build.<\/p>\n<p>On the other hand, the significant racial disparity in mobility levels in Montgomery County belies its apparent success as a springboard to prosperity. The main reason Montgomery County ranks so highly in Black and Hispanic mobility is because most other places have even larger racial and ethnic mobility disparities.<\/p>\n<p>While these metrics from Opportunity Insights are helpful in determining who is likely to achieve economic mobility, they should not be considered the definitive source of information on the topic. First, the cohort studied has long since grown up, so outcomes may be different for younger groups. The study also looks at <em>income<\/em> as opposed to <em>wealth<\/em>\u2014two related but distinct concepts that have different implications for mobility. Ultimately, prosperity and quality of life are influenced by many factors, some of which are difficult or impossible to quantify. We all likely know people who have come out ahead of or behind these generalized mobility outcomes, and even on an individual level the factors contributing to one\u2019s ultimate position on the economic ladder are complex and difficult to disentangle.<\/p>\n<p>With these caveats in mind, the second blog in this series will look at this issue at the neighborhood level and show how the economic success of places is not always shared by the people who live in them.<\/p>\n<hr \/>\n<p><a href=\"#_ftnref1\" name=\"_ftn1\">[1]<\/a> These records are kept anonymous, and data are not reported whenever there is a remote possibility of identifying someone.<\/p>\n<p><a href=\"#_ftnref2\" name=\"_ftn2\">[2]<\/a> https:\/\/opportunityinsights.org\/national_trends\/<\/p>\n<p><a href=\"#_ftnref3\" name=\"_ftn3\">[3]<\/a> Size determined by total population in the 2010 Decennial Census.<\/p>\n<p><a href=\"#_ftnref4\" name=\"_ftn4\">[4]<\/a> Although children raised at the 75<sup>th<\/sup> percentile of household income in Montgomery County appear to be downwardly mobile (ending up in the 63<sup>rd<\/sup> percentile on average in their thirties), this is a normal, expected, and in fact desirable phenomenon: For economic mobility to be possible at all, those who start out life higher on the economic ladder must on average concede some status to those who start out at the lower rungs. Additionally, as is evident on the Opportunity Insights web-based map, many rural and agricultural counties in the upper Midwest (i.e. the Dakotas, Minnesota, Iowa, and Nebraska) offer very high household incomes to people in their thirties in the agricultural and natural resource industries, but these earnings may not increase as much over careers as those in metropolitan areas.<\/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\/2021\/07\/BKraft_Headshot.jpg\" alt=\"Ben Kraft\" width=\"220\" \/><br \/>\n<strong>About the author<\/strong><br \/>\nBen Kraft is a research planner in the Research and Strategic Projects Division. His research and planning work focuses 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\"> Montgomery County Planning works to create thriving places across the county. This goal is reflected in our proposed General Plan update, Thrive Montgomery 2050, master plans, functional plans, and other special studies.<\/p>\n<p>But how do we know if a place is indeed thriving? \u00a0We often use publicly available data from agencies like the U.S. Census Bureau and the U.S. Bureau of Labor Statistics to analyze shifts in key indicators of an area\u2019s economic vitality.<\/p>\n<p>Now let\u2019s zoom in on the map and ask a deeper question: do thriving neighborhoods help the people living in them to thrive? Put another way, do neighborhoods thrive because the people living in them improved their economic status, or because people of higher &#8230; <a href=\"https:\/\/montgomeryplanning.org\/blog-design\/2021\/07\/the-opportunity-insights-project-and-economic-mobility-in-montgomery-county\/\" 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":[5],"tags":[644,42,515,649,643],"class_list":["post-7748","post","type-post","status-publish","format-standard","hentry","category-planning","tag-economic-mobility","tag-economy","tag-employment","tag-opportunity-insights","tag-work"],"_links":{"self":[{"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/posts\/7748","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=7748"}],"version-history":[{"count":19,"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/posts\/7748\/revisions"}],"predecessor-version":[{"id":7878,"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/posts\/7748\/revisions\/7878"}],"wp:attachment":[{"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/media?parent=7748"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/categories?post=7748"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/montgomeryplanning.org\/blog-design\/wp-json\/wp\/v2\/tags?post=7748"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}