Human Capital: Confidential Draft – 9/24/11
Market Analysis Guidance for MBP Metro Teams
[Notes on completeness: (1) The tone of the document description section needs a bit of word
editing to be positioned as less definitive/exhaustive; (2) some text editing throughout; (3)
review potential for added citations.]
Document Description
This memo is part of a series providing additional guidance for metro teams during the
development of the Strategic Overview component of their metropolitan business plans. The
purpose of the series is to briefly outline our approach to understanding and analyzing the five
major market levers and suggest a starting point for local analysis. Toward this end, it
identifies: (1) what aspects of each lever are most important to examine; (2) suggested metrics
for analyzing each aspect of regional performance; and, (3) some data sets (or other, more
qualitative sources of information) available nationally and/or locally for each metric. Because
of the inherent overlap in the market levers themselves, some of the metrics listed below will
appear under multiple headings. Ultimately, the information contained herein should be used as
a starting point to frame the market analysis and serve as the foundation of your Metro’s
Strategic Overview. For more detailed information on this and other market levers, please see
the papers developed for the Surdna “Implementing Regionalism” project, the CMAP chapters
and the MBP “Getting Started” PowerPoint.
Introduction: High Human Capital Aligned With Job Pools
Human Capital: The stock of knowledge, skills, expertise, and capacities embedded in the labor
force.
Human capital is the most important factor contributing to economic growth in metropolitan
areas.1 Most fundamentally, this is because the deployment of highly skilled workers into jobs
that fully utilize their talent leads to increases in firm productivity and output, which in turn
generates increased rates of total economic growth2. The underlying logic is that more
1
Weissbourd and Berry, The Changing Dynamics of Urban America, 32. In a statistical analysis examining the
impact of myriad characteristics of Metropolitan Statistical Areas (MSAs) on economic growth through the 1990s,
the effect of the educational attainment variables (a conventional proxy for human capital more broadly) was larger
than for all other independent variables. Roughly, for each 2% increase in the proportion of adults with college
degrees in a MSA in 1990, income growth from 1990-2000 increased by about 1%. See also Randall Eberts, George
Erickcek and Jack Kleinhenz, “Dashboard Indicators for the Northeast Ohio Economy: Prepared for the Fund for
Our Economic Future,” Federal Reserve Bank of Cleveland, Upjohn Institute for Employment Research, and
Kleinhenz and Associates, 2006. In an analysis of 118 metropolitan areas similar in size to those in Northeast Ohio,
having a skilled workforce was found to be the primary driver of economic growth between 1994 and 2004,
correlated most highly with output, per capita income, and productivity.
2
Gottlieb and Fogarty, “Educational Attainment and Metropolitan Growth,” Economic Development Quarterly (17)
(2003): 325-336. See also Pamela Blumenthal, Harold Wolman, and Edward Hill, “Understanding the Economic
1
knowledgeable and experienced individuals are capable of producing better goods and services
more efficiently. They only do so, however, when employed in positions that make use of their
particular knowledge and skills.
High concentrations of human capital are particularly important in modern cities, where several
factors amplify this market lever’s potential to positively affect growth:



Exponential productivity increases resulting from the combination of highly-skilled
workers and new technologies in the “knowledge” economy3;
“Knowledge spillover” effects that arise as smart, experienced workers interact with each
other and move between firms;4 and,
Larger and more efficient labor markets that improve job-sorting and lead to better firmworker matches.5
While recognition of these general effects is important, the goal of analysis for the human capital
market lever is to provide specific detail regarding the role of human capital in your local
economy. This requires the identification of current conditions and trends, as well as the
determination of factors influencing your region’s human capital dynamics over time. Since
human capital yields the greatest positive effects when deployed efficiently, we must assess not
only the level of human capital available, but also the degree to which that human capital is wellmatched to current and future jobs. This means analyzing and understanding the performance of
regional systems that help firms and workers find one another, and searching for ways to
increase the efficiency of these matching mechanisms. Overall, analyzing human capital
dynamics in your metro will help you identify potential policy interventions that build upon
current strengths, address regional challenges, and capitalize on emerging opportunities. Since
higher levels of analytical detail will enable more directly targeted interventions, the rest of this
guidance memo focuses on specific ways to assess the level and types of human capital present
in your region.
Analytical Framework
Since human capital is a broad concept, it may be helpful to unpack and identify the specific
components of this lever that are most important in a regional labor market. To aid in this
process, we have organized the metrics in this memo into three categories: (1) Local Human
Performance of Metropolitan Areas in the United States,” Urban Studies 46 (3): (2007) 605-627. From 1990 to
2000, initial-year human capital (share of population with bachelor degrees or higher) is positively and significantly
related to GMP and employment growth.
3
Christopher Berry, Riccardo Bodini and Robert Weissbourd, Grads and Fads: The Dynamics of Human Capital
Location (Chicago: CEOs for Cities, August 2005), 4.
See Gottlieb and Fogarty, “Educational Attainment and Metropolitan Growth,” 326; and Glaeser and Gottlieb,
“The Wealth of Cities: Agglomeration Economies and Spatial Equilibrium in the United States,” 983, 1012.
4
See Christopher H. Wheeler, “Cities and the Growth of Wages Among Young Workers: Evidence from the
NLSY,” Working Paper 2005-055A, The Federal Reserve Bank of St. Louis, 2005; and Christopher Wheeler,
“Search, Sorting, and Urban Agglomeration,” Journal of Labor Economics 19 (4) (2001): 879-99.
5
2
Capital; (2) Labor Market Dynamics; and (3) Job Structure and Opportunity Richness. The first
category analyzes the presence of human capital in your metro, while the others focus on the
deployment of that capital in your regional economy. All three categories are described in more
detail below.

Local Human Capital [rename?]: Assessing the local supply of human capital involves
research in three primary areas of interest. First, the level of local human capital is
determined by demographic features such as average educational attainment and
individual work experience. These factors help determine a region’s capacity to support
different industries and occupations and innovate over time. Second, a region’s
production of human capital measures the degree to which it is preparing for the future
by investing in education and workforce development. Finally, examining
attraction/retention patterns allows metros to identify the direction of the flow of human
capital in their region. If they are attracting highly skilled workers, then there is room for
knowledge- and skill-intensive industries to grow, but if they are witnessing a net loss
over time, it may be necessary to design an intervention.

Labor Market Dynamics: An effective and efficient labor market helps a region take full
advantage of its human capital supply. In order to highlight the most important aspects of
labor market dynamics, we divide this category into two broad dimensions: (1) Alignment
of Supply and Demand; and, (2) Market Efficiency. Understanding the alignment of
supply and demand for human capital in your region’s economy means comparing
current and projected employment patterns to the educational attainment levels and soft
skills of the local workforce. Such analysis helps identify what types of workers the
region needs to focus on producing, attracting, and retaining in order to meet demand in
various industries and occupations. Examining market efficiency, on the other hand,
means understanding the function and performance of systems that facilitate firm-worker
pairing. High levels of efficiency enable firms and workers to easily find and evaluate
each other to form productive matches. This might result in low unemployment and an
ability for employers to fill positions quickly with high-quality workers.

Job Structure and Opportunity Richness: Opportunity richness encourages growth by
alleviating concentrated poverty and increasing middle-class buying power6. Evaluating
your region’s performance in this area requires an assessment of both the existing
structure of the regional job market and the ease with which workers can move between
firms and occupations, especially when they are transitioning in order to gain new skills,
become more productive or advance along a particular career path. Practitioners can
further evaluate regional strengths and weaknesses in this area by examining factors such
as the level of income/wealth inequality and the opportunity-richness of the labor market,
characterized by the presence of middle-skill and middle-wage jobs. Analyzing and
understanding workers’ opportunities for professional and economic advancement within
a region also requires an assessment of the presence and performance of occupation-
See Summers, “Rescuing and Rebuilding the U.S. Economy: A Progress Report;” “Remarks by the President in
the State of the Union Address;” Katz, “The Next Economy: Transforming Energy and Infrastructure Investment”;
and “Strengthening the American Labor Force” in The Economic Report of the President.
6
3
specific training, credentialing programs and other mechanisms that aim to facilitate
workers’ upward mobility.
The remainder of this memo is organized around the presentation of specific metrics for
understanding performance in these three categories. Again, the goal here is simply to suggest a
starting point for local analysis and provide initial guidance for how to think about and interpret
findings. The rest is up to you!
Market Analysis: Measuring Human Capital
This section presents a recommended (though non-exclusive) set of metrics useful in evaluating
a region’s performance on the human capital market lever. It is organized according to the three
categories described above, with each metric being accompanied by a brief explanation of its
importance and, when available, suggested data sources. Some of the metrics listed below are
included in the Brookings-compiled dataset for the largest 100 metro areas and should therefore
require no additional data collection efforts. These appear in bold text. Others have not been
provided, but can be obtained and analyzed locally to supplement the Brookings dataset and gain
a more nuanced picture of overall performance. Note that some metrics appear in more than one
category or are cross-listed as part of another market lever. This occurrence underlines the
interconnectedness of the five major market levers and suggests that multiple meanings may be
extracted from a single statistic.
Of course, understanding a region’s performance on any market lever is a complex task, and the
metrics listed below are not sufficient on their own. Moving forward, it is important for each
metro team to develop a customized analysis designed to more effectively capture its particular
assets, challenges and opportunities. Once established, this analysis should be used to inform the
development of a meaningful strategic overview and comprehensive metropolitan business plan.
A table summarizing recommended indicators and potential data sources listed in this section is
included in Appendix 1 (page 11).
A. Local Human Capital [rename?]
Assessing the local supply of human capital allows metro teams to gauge their region’s capacity
for supporting particular jobs and industries. To meet this task, we recommend an organization
around three primary areas of focus: (1) Levels; (2) Production; and, (3) Attraction/Retention.
Taken together, the following metrics enable a baseline assessment of both the current stock of
human capital in your region, as well as the direction in which that stock appears to over time.

Levels
1. Working Age Population and Change (2000-2009)
The working age population is the total number of potential workers in a region. As a
fundamental input to production, changes in this metric have the potential to greatly affect the
local economy. We expect this to be a significant area of focus and concern in the coming years
as the first members of the baby boom generation begin to retire.
4
2. Educational Attainment
Research has identified educational attainment levels as a primary determinant of regional
economic performance7. The implication is that a more highly educated population is better
positioned to enjoy increases in productivity and standard of living. This metric is limited,
however, in that it only accounts for formal education. Much of the value embedded in human
capital lies in work experience and knowledge derived from on-the-job training, and therefore
isn’t captured by this metric.
3. Percent of Population with Bachelor’s Degree or Higher by Age Cohort
The age distribution of individuals with a bachelor’s degree or higher is important in that it
reflects the future availability of human capital in the region8. Metros with a high number of
young college graduates are better positioned to adapt to the mass retirement of the baby boom
generation. The importance of young college graduates is further underlined by their association
with higher levels of innovation and entrepreneurship.
4. Technical and Trade Certifications awarded
Technical and trade certifications are an increasingly prevalent way for individuals to signal
possession of specific knowledge and skills to potential employers. Determining the number of
individuals who have received or are pursuing certification is therefore a way to further assess
the level of human capital present in a region. Data on technical and trade certifications may be
available through local institutions including universities and community colleges.
5. Soft Skills and Experience
Understanding the level of soft skills and experience embedded in the local working population
is challenging to the extent that such characteristics are often difficult to quantify. It is
important, however, for metro teams to determine certain core strengths in the working
population to help identify opportunities for attracting and supporting new and growing
See both R. Lucas, “On the Mechanics of Economic Development,” Journal of Monetary Economics 22 (July
1988): 3-42 and J. Rauch, “Productivity Gains from Geographic Concentration of Human Capital: Evidence from
Cities,” Journal of Urban Economics 34 (1993): 380-400.
7
Between 2006 and 2016, jobs that require either an associate’s degree or a post-secondary vocational award are
projected to grow faster than jobs that require no postsecondary training and slightly faster than occupations
requiring a bachelor’s degree or more. See Preparing the Workers of Today for the Jobs of Tomorrow (Washington,
DC: Executive Office of the President, Council of Economic Advisers, 2009).
Link found at
http://www.whitehouse.gov/assets/documents/Jobs_of_the_Future.pdf. See also Anthony Carnevale and Donna
Desrochers, “The Missing Middle: Aligning Education and the Knowledge Economy,” paper prepared by the
Educational Testing Service for the Office of Vocational Education, U.S. Department of Education, 2002; and
Thomas L. Hungerford and Robert W. Wassmer, K-12 Education in the U.S. Economy: Its Impact on Economic
Development, Earnings, and Housing Values (Washington, DC: National Education Association, September 2003).
See also Jesse Shapiro, “Smart Cities: Quality of Life, Productivity, and the Growth Effects of Human Capital,”
Working Paper No. 11615, National Bureau of Economic Research, September 2005.
8
5
industries9. This process can and should be organized around a combination of approaches. On
the quantitative side, it is possible to use BLS occupational data and information from O*NET to
determine the kinds of skills possessed by major cohorts of the working population.10 The
information gleaned from these efforts could be further fleshed-out through targeted interviews
with both employers and workers alike.

Production
6. New Graduates with STEM (Science, Technology, Engineering & Mathematics) Degrees
The number of new graduates with STEM degrees coming out of local universities is a good
measure of a region’s preparedness for competition, and consequently potential for growth, in
the knowledge economy11. Data on this and similar subjects is available online at the state and
institution levels through the NSF’s integrated database service, WebCASPAR. It is important
to note, however, that these numbers do not reflect how many local graduates are actually
staying to work in the area. This information would likely have to be collected through
coordination with local schools.
7. Workforce Development and Continued Education
The number of new graduates coming out of local colleges and universities does not provide a
full account of a region’s human capital production. Production levels are also affected by the
amount of time and money being invested in workforce development and continued education
projects. Such investments can generate significant returns by adding value to the knowledge
and skills already possessed by experienced workers and facilitating mid-career transitions into
new industries. Information on investment and participation in these activities could be collected
through collaboration with local education agencies and HR directors.
8. K-12 School Quality: Math and Verbal Scores for 4th, 8th, and 12th Grades
K-12 school quality is a major determinant of local human capital production. For those entering
the workforce before or immediately after graduation, such education is a main source of
important knowledge and skills. For those enrolling in colleges and universities, a high quality
K-12 education paves the way for future educational attainment. In a less direct manner, K-12
. See James Heckman, JoraStixrud and Sergio Urzua, “The Effects of Cognitive and Noncognitive Abilities on
Labor Market Outcomes and Social Behavior,” Journal of Labor Economics 24(3) (2006): 411-482. Heckman et al.
find that except for male 4-year college graduates, the labor market values noncognitive skills (as measured by
increased wages) as much as or more than cognitive skills. The magnitude of the effect depends on the specific
population of workers in question (i.e., high school graduates, drop outs, some college, female, male, etc.). See also
Marigee Bacolod, Bernardo Blum and William Strange, “Skills in the City,” Journal of Urban Economics 65(2)
(2009): 136-153; and Robert Lerman, Are Skills the Problem? Reforming the Education and Training System in the
United States (Kalamazoo, MI: Upjohn Institute for Employment Researchat the Urban Institute, 2008).
9
10
[Link to Iowa Skillshed analysis document?]
See Louis Jacobson and Christine Mokher, “Pathways to Boosting the Earnings of Low-Income students by
Increasing Their Educational Attainment,” prepared for the Bill & Melinda Gates Foundation by the Hudson
Institute for Employment Policy and CNA Analysis and Solutions, 2009.
11
6
school quality also influences human capital attraction/retention, as highly skilled workers desire
better opportunities for their children. While data on Math and Verbal scores is available for 18
of the largest American cities through the “NAEP data explorer” and displayed in city profiles on
the NCES website, it is likely better to coordinate data collection efforts with state and local
school districts.
9. High School Graduation Rates
Graduation rates are a basic measure of human capital production that affect both the number of
students entering the workforce with a diploma and the number going on to pursue higher
education. Without a good high school graduation rate, regions may not be able to produce
enough skilled workers to meet current and future demand by industries and occupations.

Attraction/Retention
10. Immigration and Immigrant Skills
Although there is much variation in education and skill levels in the immigrant population, each
new addition to the labor pool represents an opportunity for increased regional productivity.
Lower-skilled immigrants can fill in important gaps in the labor force, whereas higher-skilled
immigrants bring much needed knowledge and entrepreneurial talent. This means immigration
can serve as a valuable source of both human capital and innovation.
11. Change in Percent of Population with a Bachelor’s Degree or Higher
Using annual data from the ACS, it might be helpful to examine regional trends in educational
attainment. If the percentage of the population with a bachelor’s degree or higher has increased
significantly during a given time period, then it may be said that the region is effectively
attracting and retaining human capital. If, on the other hand, there has been a significant
decrease over time, then it may signal the need for targeted interventions.
12. In- and Out-flows of Recent Graduates
Recent graduates are important both because they possess vital knowledge and skills, and
because they represent a measureable source of human capital in the future. Without a sustained
in-flow of recent graduates, a region may eventually be unable to meet demand in important
industries and occupations. Although detailed MSA-level immigration data on recent graduates
may be available through other sources, percent changes in ACS estimates of educational
attainment by age cohort (ages 24-34 in this case) could be used as a proxy.
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13. “Livability” Measures
In recent years there has been an increase in the use of ‘livability’ indices as a means of
explaining the migration patterns of highly skilled workers and recent college graduates. These
indices range in focus from regional weather patterns and nearby natural amenities to available
sources of entertainment and coffee shops per capita. Research has shown, however, that such
measures have only marginal effects (if any at all) on the number of educated individuals
relocating to a specific region. Instead, location patterns are most influenced by key economic
factors such as wages, unemployment, and the presence of knowledge-intensive industries and
occupations.12 If your team decides to include such measures in your market analysis, then it
may be helpful to begin with one of the indices created by Richard Florida as part of his ongoing
research on the “creative class.”
B. Labor Market Dynamics
Human capital only benefits the regional economy when deployed effectively in the labor
market. It is therefore important for metro teams to examine the degree to which workers are
efficiently matched with local firms. In order to do this, we recommend organizing your analysis
around two areas of focus: (1) Alignment of Supply and Demand; and, (2) Market Efficiency.

Alignment of Supply and Demand
1. Skill Gap Index
The Skill Gap Index provides a simple measure of the alignment of supply and demand for
skilled workers in a region13. A skills gap arises when workers are relatively more or less skilled
than is required by jobs in the region. A “skill surplus” means that many of the region’s workers
are ‘overeducated’ relative to their job requirements, whereas a “skill deficit” denotes an
12
Christopher Berry, Riccardo Bodini and Robert Weissbourd, Grads and Fads: The Dynamics of Human Capital
Location (Chicago: CEOs for Cities, August 2005).See also Michael Storper and Allen Scott, “Rethinking Human
Capital, Creativity and Urban Growth,” Journal of Economic Geography 9 (2009): 147-167; Gottlieb and Joseph,
“College-to-Work Migration of Technology Graduates and Holders of Doctorates within the United States,” Journal
of Regional Science 46(4) (2006): 627-659; Randall Eberts, George Erickcek and Jack Kleinhenz, “Dashboard
Indicators for the Northeast Ohio Economy: Prepared for the Fund for Our Economic Future,”Federal Reserve Bank
of Cleveland, Upjohn Institute for Employment Research and Kleinhenz and Associates, 2006; Paul Gottlieb,
“Economy Versus Lifestyle in the Inter-Metropolitan Migration of the Young,” International Journal of Economic
Development 5(3) (June 2003); Steven Malanga, “The Creative Clash,” Governing Magazine (June 2004); Louis G.
Tornatzky et al., Where Have All the Students Gone? Interstate Migration of Recent Science and Engineering
Graduates (Research Triangle Park, NC: Southern Growth Policies Board, Southern Technology Council, February
1998); and Graduate Migration from Indiana’s Post-Secondary Institutions (Indianapolis: Indiana’s Human Capital
Retention Project, Indiana Fiscal Policy Institute (March 1999).
13
In the 2005 Skills Gap Survey conducted by Deloitte Consulting and the National Association of Manufacturers,
nearly half of responding employers reported that current employees have inadequate basic employability skills such
as attendance, timeliness, and work ethic, and 36 percent indicated insufficient reading, writing, and communication
skills. See “2005 Skills Gap Report-A Survey of the American Manufacturing Workforce,” report produced by
Deloitte Consulting, National Association of Manufacturers, and the Manufacturing Institute.
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inability of the local labor pool to meet the demands of employers. “Balanced” regions possess
workers that are well-trained for the occupations on offer.
2. Demand Measures
Estimations of the current and future demand for workers in your region should be based on the
analysis your team will perform under the industry and occupational clusters market lever.14
Relevant metrics that should be produced during this process include:
a. Employment Levels and Change by Industry/Occupation;
b. Projected Employment Growth by Industry/Occupation; and,
c. Skills and Education Levels related to High Demand Industries/Occupations.
Once determined, the level of demand for specific kinds of human capital should be analyzed in
comparison to the supply metrics described above in Category A, “Local Human Capital.” This
analysis should be accompanied by an examination of the extent to which production efforts (i.e.
education and training programs) are aligned with the current and anticipated demand in
particular industries and occupations.

Market Efficiency
3. Unemployment Rate
One way of analyzing the efficiency of the regional labor market is to examine the total
unemployment rate. Data are available online through BLS on the total unemployment rate for
372 American MSAs each year. There are other potentially useful measures of unemployment
such as under-employment and discouraged workers, but BLS does not provide these on the
metro level. It may be helpful to contact relevant state and local agencies for estimations of
these rates at smaller geographic units.
4. Unemployment rate by industry
Variations in unemployment rates by industry can help identify specific targets for the
improvement of firm-worker pairing. A high unemployment rate in the construction industry for
example, could be used to indicate the need for a viable system of connecting workers and
construction firms. It could also indicate a need for improvement in the translation of skills from
jobs in one industry to another. BLS reports unemployment rates by industry for approximately
50 selected metropolitan areas around the United States, but locally produced data may also be
available.
5. Average Time Spent on Job Search
The length of time required for an individual to find a job in a region is a function of both job
availability and the quality of worker-firm matching systems. CPS may provide county-level
14
For background information on this lever and detailed descriptions of the metrics within it, please see the Xth
memo in this series. [Need to determine best approach for offering guidance on concentrations market lever.]
9
data on unemployment duration and the number of weeks spent searching for a job, but it would
also be helpful to interview unemployed workers about the tools and strategies they are using to
find work.
6. Jobs Being Left Unfilled
Determining what positions employers are having difficulty filling is important because it
illustrates unmet needs in the local labor market. While there is significant crossover here with
‘demand’ considerations, this indicator may help reveal specific labor market inefficiencies. The
information required for this kind of analysis would probably be best garnered through
interviews with local business people and will likely vary according to industry.
7. Ratio of Job Openings to Unemployed Individuals
If the ratio of job openings to unemployed individuals in a given region is high, then the local
labor market may be doing a fair job of enabling productive firm-worker matches. If it is low,
then there may be inefficiencies in the matching process. This simple metric should not be used
as a basis for policymaking, but could serve as a general gauge of labor market health. It is
difficult to determine the number of job openings in any region, but one approach is to look at
the number of job postings listed on popular websites. Indeed.com is one convenient source
since every city search returns the total number of postings rather than just descriptions of the
jobs themselves. Combined with BLS data, analysts could calculate the approximate ratio of job
openings to unemployed workers. It is important to emphasize that this method would produce
only rough estimates of these dynamics; limitations of this approach include potentially
inconsistent geographic definitions, inaccuracy in regard to the total number of job openings in
the metro (some jobs simply aren’t advertised on indeed.com), and an inability to account for the
number of jobs that would be offered if employers hadn’t already given up on the search.
C. Job Structure and Opportunity Richness
Analyzing and understanding job structure and opportunity richness allows metro teams to
further assess their region’s ability to effectively and efficiently utilize available human capital.
Metrics included in this section are divided into two dimensions: (1) income and wealth
inequality; and (2) job structure.

Income and Wealth Inequality
1. Median Household Income
A region’s median household income is an indicator of the level of affluence enjoyed by the
average family. This affects their ability to purchase goods and services, and is a major
determinant of general quality of life. Since wages exert a significant influence on worker
decisions to relocate, this is a very important measure of opportunity richness in any regional
economy.
2. Low-to-High Wage Ratio
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The Brookings-compiled dataset for the 100 largest American metros includes a low-to-high
wage ratio defined as the ratio of wages in the highest quintile of earners to those in the lowest
quintile. This provides an indication of how effectively the market spreads wealth, and
subsequently the population’s ability to participate in market activities.
3. Poverty Rate and Change (2000-2009)
Analyzing and understanding changes in the level and geographic distribution of poverty helps
illuminate failures to ensure that regional human capital is fully developed and utilized. Highly
concentrated poverty creates issues across a number of different areas, but it poses a particular
threat to individual access to opportunity. If the new economy being planned for your region is
to include everyone, then poverty rates must be given serious consideration.
4. Gini Index and Percent Difference from US Average
Wealth inequality is similar to wage inequality in that it influences access to opportunity and
prosperity across the population. People living in highly unequal regions may be less able to
invest in important human capital inputs like education and healthcare. Such regions may also
suffer from a narrower consumer base and experience less sustainable growth over time.

Job Structure
5. Percent Middle-Wage Jobs
The availability of middle-wage jobs provides the foundation for the development of a strong
middle class. Since middle class prosperity is a major contributor to economic growth, this is an
important area of focus for any metro team. Definitions of this and the next indicator vary, but
as a starting-point, it might be useful to define middle-wage jobs as those comprising the middle
third by average wages paid. Occupations that fall into this category could be identified using
MSA-level BLS occupation estimates (which include wage data) available online.
6. Percent Middle-Skill Jobs
Middle-Skill jobs provide individuals with fewer years of formal education with the opportunity
to work and advance in certain careers. Middle-skill jobs may be defined as all clerical, sales,
construction, installation/repair, production, and transportation/material moving jobs. Put
differently, middle-skill occupations are those not in the professional/technical, managerial,
service, and agricultural categories.15 Data on the number of middle-skill jobs in your region
could be produced using the same MSA-level BLS occupation estimates mentioned above.
7. Upward Mobility
The definition included here is based on that used in: Holzer, Harry, and Robert Lerman, “The Future of MiddleSkill Jobs,” Center on Children and Families Brief #4 (2009).
15
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Many factors affecting upward mobility, including education quality, access to middleskill/middle-wage jobs, and wealth inequality are already listed above as potential indicators16.
While these give some indication of the potential for upward mobility, it would also be helpful to
examine the specific institutions and pathways in place in your region. This might mean looking
at before- and after-school programs, costs of community college and university attendance
(including the availability of scholarships), and the presence and quality of career ladders within
local businesses.
16
Recent research suggests that contrary to popular perception, the United States exhibits less intergenerational
income mobility than other OECD countries such as Denmark, Norway, Finland, Canada, Sweden, and Germany, to
name a few, as measured by how predictive a parents’ income levels are of their child’s income levels. See Isabel
Sawhil and John E. Morton, “Economic Mobility: Is the American Dream Alive and Well?” Report from the
Economic Mobility Project of the Brookings Institution, 2008; and Julia Isaacs, Isabel Sawhill and Ron Haskins,
“Getting Ahead or Losing Ground: Economic Mobility in America,” report for the Economic Mobility Project of the
Brookings Institution, 2007.
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Appendix: Table of Suggested Indicators and Sources
Category
A. Local Human
Capital
B. Alignment of
Supply and
Demand
Indicator
1. Working Age Population
and Change (2000-2009)
Suggested Source(s)
Brookings Strategic Overview
Metrics (ACS 1-year Estimates,
2009)
2. Educational Attainment
Brookings Strategic Overview
Metrics (ACS 1-year Estimates,
2009)
3. Percent of Population with Brookings Strategic Overview
Bachelor’s Degree or
Metrics (ACS 1-year Estimates,
Higher by Age Cohort
2009)
4. Technical and Trade
Local Community Colleges,
Certifications awarded
Technical Schools, and
Workforce Training Providers
5. Soft Skills and Experience BLS; O*NET; Interviews with
Local Employers and Workers
6. New Graduates with STEM NSF (WebCASPAR)
Degrees
7. Workforce Development
Local Community Colleges,
and Continued Education
Technical Schools, Education
Agencies, and HR Directors
8. K-12 School Quality: Math NCES; Local Education
and Verbal Scores for 4th,
Agencies and School Districts
8th, and 12th Grades
9. High School Graduation
Local Education Agencies and
Rate
School Districts
10. Immigration and Immigrant Brookings Strategic Overview
Skills
Metrics (“The Geography of
Immigrant Skills,” 2010)
11. Change in Percent of
ACS 1-year Estimates, Multiple
Population with a
Years
Bachelor’s Degree or
Higher
12. In- and Out-flows of
ACS 1-year Estimates, Multiple
Recent Graduates
Years
13. ‘Livability’ Measures
Metro Team Discretion
1. Skill Gap Index
2. Demand Measures
3. Unemployment Rate
Brookings Strategic Overview
Metrics (Brookings Analysis of
BLS data)
Industry and Occupational
Clusters Market Lever Analysis
BLS Local Area Unemployment
Statistics
13
Category
Indicator
4. Unemployment Rate by
Industry
5. Average Time Spend on
Job Search
6. Jobs Being Left Unfilled
C. Job Structure and
Opportunity
Richness
7. Ratio of Job Openings to
Unemployed Individuals
1. Median Household Income
2. Low-to-High Wage Ratio
3. Poverty Rate and Change
(2000-2009)
4. Gini Index and Percent
Difference from US
Average
5. Percent Middle-Wage Jobs
6. Percent Middle-Skill Jobs
7. Upward Mobility
Suggested Source(s)
BLS Unemployment Rates for
Nonagricultural Workers (Table
31), 2010
CPS; Interviews With Local
Unemployed Workers
Interviews with Local Businesses
Multiple; Metro Team Discretion
Brookings Strategic Overview
Metrics (ACS 1-year Estimates,
2009)
Brookings Strategic Overview
Metrics (ACS/State of
Metropolitan America)
Brookings Strategic Overview
Metrics (ACS/State of
Metropolitan America)
Brookings Strategic Overview
Metrics (ACS/State of
Metropolitan America)
BLS Occupational Employment
and Wage Estimates, 2010
BLS Occupational Employment
and Wage Estimates, 2010
Local Education Agencies and
School Districts; Community
Colleges and Universities;
Interviews with Local Businesses
14