Community Development and Human Capital
Good afternoon. It is an honor to be the closing speaker at this year’s Policy Summit. For almost 15 years, the Policy Summit has provided an important forum for collaboration between researchers and community development practitioners. Although researchers and practitioners bring different perspectives, they share a common goal: to strengthen communities by improving the opportunities for all people to productively engage in our economy. Research informed by the people who are actually on the ground, working in communities and running the programs, can help identify which strategies, programs, and policies are likely to be most effective. I hope that over the past two days, you’ve had the opportunity to meet someone who has brought a different perspective to the table, whether you are an economist, a nonprofit leader, a policymaker, or someone who puts policy into practice. I know I have and I thank you all for being here and for the effort and dedication to the important work you do.
I also want to thank Paul Kaboth, Theresa Singleton, and Sandy Tormoen, the Community Development officers at, respectively, the Federal Reserve Banks of Cleveland, Philadelphia, and Richmond, as well as their staffs, for putting together such an interesting program. This Policy Summit is just one of the important ways in which the Federal Reserve Banks work together on behalf of the public. The 12 Reserve Banks are part of the Federal Reserve System, which was established by Congress more than 100 years ago. We like to say that the Federal Reserve is a decentralized central bank, which is independent within the government but not independent from the government. The structure is one of balance. Congress designed the Federal Reserve System to alleviate concerns that the central bank would become dominated by financial interests in New York or political interests in Washington. The Fed’s decentralized structure helps ensure that policy decisions take into account a diversity of information and views, reflecting our roots on Main Streets and communities across the country.
As the closing speaker, perhaps my greatest responsibility is to keep my remarks relatively short. Unfortunately, I am not going to meet that goal today because I want to take the opportunity to discuss the important role human capital plays in driving the economic outcomes of individuals and communities. As always, the views I’ll present are my own and not necessarily those of the Federal Reserve System or my colleagues on the Federal Open Market Committee.
Community Development Work at the Fed
The Federal Reserve has had an interest in community development issues for a long time. In 1977, Congress passed the Community Reinvestment Act (CRA) to help address concerns about the deterioration in low- and moderate-income neighborhoods throughout the U.S. Many people blamed urban decline on limited credit availability and illegal practices such as redlining.
The CRA reaffirmed that insured depository institutions must serve the communities in which they are chartered to do business, helping to ensure equitable access to credit for all individuals and neighborhoods.1 The Federal Reserve and other federal financial supervisory agencies were charged with implementing the act. In 1981, the Fed created its Community Affairs function to provide technical training and support to depository institutions to help bolster compliance with the CRA.
From this targeted beginning, the Federal Reserve’s work in the area of community development has evolved and expanded, much as the nature of community development in general has changed over time. As people in this room know, access to credit is but one factor – albeit an important one – in determining the economic vitality of households and neighborhoods. A glance at the agenda for this Policy Summit conveys the wide range of interconnected issues that community development now encompasses, from health and transportation policy, to housing and education policy, to workforce development. While the focus may have changed over time, one thing that hasn’t changed is the Federal Reserve’s commitment to helping to identify effective policies and best practices for promoting economic progress in low- and moderate-income neighborhoods. In addition to its research, the Fed plays an important role as a “convener.” Bringing together people to share their different perspectives and experiences can ultimately lead to more effective economic policies. I have spoken elsewhere about how the diversity of views expressed around the FOMC table helps the Fed make better monetary policy. I believe the same is true for public policies aimed at addressing the challenges faced in community development.
We can all be pleased that the economy has greatly improved since the depths of the Great Recession. Employment is up and unemployment rates are down. But not all households or communities have experienced the same amount of improvement; some of the challenges are long-standing ones that the recent recession and slow recovery exacerbated. According to a 2014 Federal Reserve survey of economic well-being, 65 percent of respondents reported that their families are either “doing okay” or “living comfortably” financially. Yet economic challenges persist for sizable parts of the population.2 Forty-seven percent of respondents said they could not cover a $400 emergency expense using cash or its functional equivalent or would have to sell something or borrow to cover it. Just under a quarter of respondents said they or a household family member had experienced some type of financial hardship in the previous year. And, not surprisingly, feelings about economic well-being vary with household income. For lower-income households, those making less than $40,000 per year and who make up about one-third of the respondents, more than half reported they are finding it difficult to get by or are just getting by financially.
I am sure it is not news to you, community development professionals, that problems linger and effective solutions remain elusive. However, one thing is clear: human capital – education and skills that make people more productive and able to contribute to the economy – is one of the fundamental factors that determine economic outcomes of communities and individuals.
The Value of Human Capital
Many studies have documented the importance to economic well-being of investments in human capital. For example, Cleveland Fed researchers found that over a 75-year-period, education levels were consistently one of the most reliable indicators for each state’s per capita income growth3 and that counties with higher levels of high school graduates tend to have lower poverty rates and higher levels of labor force participation.4 A study by a Philadelphia Fed researcher found that resilient regions, that is, regions that have been able to avoid persistent declines in population over the long run, tend to have a more educated population and a more diverse industry mix.5
The benefits of investing in human capital are also evident at the individual level. Better education is correlated with higher wages and lower levels of unemployment. For example, the current unemployment rate for those with a college degree is 2.6 percent, compared to 5.4 percent for those with a high school diploma, and 8.0 percent for those who didn’t graduate from high school. The difference in wages between those with a college degree and those without, the so-called skill premium, has widened substantially over time, more than doubling since the 1970s. Median hourly wages for those with a bachelor’s degree are now about 80 percent higher than for high school graduates.6 And over a lifetime, in present value terms, a college graduate can expect to earn nearly twice as much as a high school graduate.7 Other research shows that the skill premium has grown even more for those with a post-graduate degree, even controlling for changing demographics. Those with a graduate degree now earn about 30 percent more than those with a four-year college degree.8
The rising skill premium since the 1970s reflects the fact that over much of the period, real wages (that is, wages adjusted for inflation) rose for skilled workers while they fell for unskilled workers. Several factors could have led to the rising trend in the skill premium. Globalization, which has led to increased trade between the U.S. and countries with lower-skill, lower-wage workers, is one possible explanation. Demand from the U.S. for the products produced by lower-wage workers abroad would put downward pressure on the wages of lower-skill workers producing similar goods in the U.S. And demand from abroad for goods produced by high-skill workers in the U.S. would put upward pressure on their wages. While this is an interesting theory, there is not much empirical support for trade being a major driver of the skill premium.9
Instead, there appears to be considerably more evidence that technological change has increased the demand for skilled workers relative to unskilled workers. This is consistent with the fact that even industries often viewed as less skill-intensive have increased their demand for skilled labor. The manufacturing plant of the 1970s has transformed itself into a high-tech operation, requiring workers who can operate computerized machinery and even robots.
The idea that the rising skill premium is driven by technological change also seems consistent with research showing that mathematical achievement is a fairly good predictor of future earnings.10 As discussed in a recent Cleveland Fed Economic Commentary, even among high school dropouts, those who completed geometry or algebra II earn about $1.50 more per hour in the workforce than those who completed fewer math courses. Math attainment in high school also helps predict admission to and success in college. Some Cleveland Fed economists help run a Math Corps program at Cleveland State University. This program for middle and high school students aims to build confidence and mastery in young people’s mathematical abilities. It appears to be working, as Math Corps students are more likely to score higher on standardized tests and more likely to graduate from high school than their peers.11
A refinement of the idea that technological change has driven the widening skill premium is the polarization hypothesis.12 Data suggest that since 2000, jobs have become “polarized,” meaning that while high-skill and low-skill occupations have seen job growth, medium-skill occupations have experienced job losses. Some jobs involve work that is very routinized, work that involves repeated actions and set rules. Other jobs involve work that is less routine, requiring flexibility. Another dimension along which jobs vary is the extent to which they require cognitive skills versus physical skills. Computers can handle tasks usually found in routinized cognitive jobs, e.g., bookkeeping and other clerical tasks. Computers are less suited to replace workers in occupations that require abstract thinking, high levels of cognition, and higher levels of education. But they are also less able to take on non-routine manual work. Academic and Federal Reserve labor-market researchers have found that since 2000, there has been a decline in employment in the routine cognitive and routine manual job categories – jobs that are considered medium-skill jobs – compared to job gains in non-routine cognitive and non-routine manual occupations – high-skill and low-skill jobs, respectively.13 This shift in the distribution of jobs helps to explain the wider gap in wages for highly skilled vs. lower skilled workers, and the increasing return to gaining the education required to obtain those skills.
The increase in the return to education over the past 35 years has spurred more people to get their degrees – for example, the percent of the U.S. labor force that is college-educated has more than doubled since the 1970s. But because demand for these higher-skill workers continues to grow, the skill premium has continued to rise even as the supply of skilled workers has risen.14
While much of the research has focused on college vs. high school, this partly reflects the availability of data. Some of the skills required to meet the demand of jobs in today’s economy can be acquired in settings other than four-year colleges. Also note that some of the cognitive skills needed are not necessarily acquired by studying only math and science. The critical thinking and judgment acquired by studying the social sciences and humanities is very valuable in the modern workplace. And, of course, not every high school graduate earns less than the average college graduate – wages vary quite a bit within an educational level. Indeed, recent research by Cleveland Fed staff shows that across 100 metro areas in the nation, the top 30 percent of earners aged 18-35 without a college degree earned more than a quarter of the workers in this age group who have a bachelor’s degree.15
Still, the earnings prospects of less-educated workers seem to depend on subsequent training and also on location. The locational aspect is being investigated in forthcoming research led by the Philadelphia Fed in collaboration with the Cleveland and Atlanta Feds. Other researchers have provided evidence that less-educated workers benefit in the form of higher wages from working in areas populated with more-educated workers. Such knowledge spillovers mean that the return to communities from education can be higher than the return any one person gains by becoming more educated.16 Evidence of human capital spillovers is also provided by another study that finds that cities with more highly educated populations experience lower unemployment rates, higher productivity growth, and higher growth in entrepreneurship than what would have been predicted by considering only individuals’ educational levels.17 Thus, education appears to be a valuable investment not only for the individual but also for the communities in which people live.
It is important to note that the statistics I’ve quoted on the skill premium and the social return to education are based on people who actually obtain their degrees. While enrollments in college are near historic highs, non-completion rates are also quite high. According to data from the National Center for Education Statistics, only about 55 percent of students who start college earn bachelor’s degrees within five years.18
Several factors are likely at play. First, some people aren’t prepared for college when they enter. Research is increasingly pointing to the fact that the foundation has to be laid very early in life – at the pre-school level. When children fall behind early on, it is often difficult to catch up.19 Research is also shedding light on which type of early childhood education programs work and the ways in which they can affect economic outcomes later in life. One study found that a main way in which the influential Perry Preschool Program, which predates Head Start, affected longer-run outcomes was by affecting the social skills of the participants, e.g., lowering aggressive and anti-social behaviors.20 Home environment also matters. Research by a Cleveland Fed economist shows that home environment, as measured by the number of books at home, has a significant impact on achievement in elementary school.21
A second factor affecting college enrollment and completion rates is that college has become increasingly expensive over time. The average cost of tuition and fees at four-year institutions is now over $14,000 a year, and has more than doubled since 2000.22 Subsidies for higher education fell during the Great Recession, shifting costs to students. According to data compiled by the New York Fed, more people are borrowing to go to school: The share of 25 year olds with student debt rose from 27 percent in 2004 to about 45 percent in 2013. And the average debt per borrower has increased from about $15,000 in 2004 to $27,000 in 2014.23 Some students do not have the financial wherewithal to start or to complete their degrees. According to the Fed survey of economic well-being that I mentioned earlier, of those respondents who didn’t attend or complete college, 30 percent reported that they didn’t attend college because it was too expensive, while 24 percent of those who started college said they didn’t complete their degree for this reason. In some cases, family obligations take precedence over education. Forty-three percent of women and 32 percent of men said they didn’t finish because of family obligations. This gender gap was even larger among younger respondents.24
A third factor affecting enrollment and completion rates is that some people may have a personal preference to enter the workforce after high school rather than to go to college. But that choice might really reflect a person’s view that he or she is unprepared to succeed in college or that the return to a college education does not justify the tuition expense or the burden of student loan debt. In other words, while, on average, the return to investing in education is positive, for some individuals it is not, especially if they have to take on high levels of debt. Research by the Richmond Fed, which models college choice, illustrates that uncertainty about whether you’ll complete college or whether you’ll get a good-paying job after graduating will offset some of the positive effects of a rising skill premium on your decision to enroll in college. The effect of uncertainty is larger for lower-income people who need to borrow to go to college, since they’ll need to earn more post-college to make the investment pay off.25
This work, as well as the other research on educational attainment, suggests to me that college enrollments and completion rates could be increased by programs that help prepare students to enter college and programs that help ensure that financial support is available to students who have the desire and qualifications to earn a college degree. Student loan programs should encourage students to choose colleges or other types of educational programs that maximize the return on the student’s investment in human capital.
People who prefer not to attend college will also have to build their human capital to be productive members of the modern workforce. Apprenticeships, certificate programs, and on-the-job training can all potentially play an important role. The U.S. spends a significant amount of money on education. In 2011, total spending on public primary and secondary education was over $600 billion, more than $12,000 per public-school student.26 That same year, private industry spent more than $156 billion on employee learning and development programs.27 But at a time when funding is scarce and the needs are plentiful, rigorous evaluation of the effectiveness of educational and training programs is needed, and there is an active research agenda in this area. I’d like to conclude my remarks with a few examples of such efforts.
Some Examples of Program Evaluation Efforts
It is impossible to evaluate the effectiveness of a program without the data to do it. In Maryland, the Jacob France Institute at the University of Baltimore keeps a repository of wage and labor market data to track program participants over several years and to coordinate with on-the-ground agencies in designing longer-run programs.28 Similar centers around the country are collecting information as part of new federal workforce investment rules. Data collection and program evaluation are important aspects of the U.S. Department of Education’s Promise Neighborhoods program, which aims to improve the educational outcomes of children in distressed neighborhoods by improving the neighborhoods themselves.
In addition to data collection efforts, there is ongoing work to identify the most effective programs for hard-to-employ individuals. A Cleveland-based organization, Towards Employment, is leading NEO WorkAdvance, a collaborative effort of more than 13 Northeast Ohio workforce and economic development organizations that are partnering with employers to identify hiring and training needs in manufacturing and health care, two industries significant in the Northeast Ohio region.29 The program is designed to rigorously evaluate what helps unemployed and low-wage working adults succeed in the workplace in general and, in particular, in these two sectors.
Other work is also underway to evaluate job training programs focused on particular industrial sectors. One Cincinnati agency, Partners for a Competitive Workforce, is a leader in tracking its results and sharing information with researchers.30 Research could help identify whether certain sectors, like health care or high-tech manufacturing where qualified workers are in short supply, are more amenable to these kinds of programs or whether such programs can be replicated across multiple industries. Such knowledge could help inform policies that provide incentives to industry to develop meaningful training programs for both new and continuing employees.
As I mentioned earlier, some of the early childhood education research suggests that the future success of disadvantaged individuals can be improved by strengthening their social skills. Studies are underway to examine the role of characteristics like persistence and other personality traits as they relate to labor market outcomes,31 and the Commonwealth of Kentucky is using the ACT WorkKeys test, which attempts to measure these “soft skills,” as part of its evaluation metrics for qualifying certain communities as having the infrastructure and workforce sought by employers. By their very nature, soft skills are difficult to measure, but furthering our understanding of the extent to which these types of skills improve future success and the ways in which they might be taught may help people successfully enter and remain in the workforce.
These are but a few examples of agencies undertaking initiatives to critically evaluate educational and workforce development programs. Improving our knowledge about which programs are effective and what makes them so will help ensure that we design the best programs to help the most people and that our investment in these programs is money well spent. This Policy Summit and other similar conferences have an important role to play by bringing together the program designers, community development practitioners, and researchers who will lead the way in developing effective methods to raise the human capital levels in our nation. I encourage you all to keep working toward this very important goal.
- For more on the historical context of the CRA, see Sandra F. Braunstein, “The Community Reinvestment Act,” testimony before the Committee on Financial Services, U.S. House of Representatives, February 13, 2008. Return
- Board of Governors of the Federal Reserve System, “Report on the Economic Well-Being of U.S. Households in 2014,” May 2015. Return
- “Altered States: A Perspective on 75 Years of State Income Growth,” Federal Reserve Bank of Cleveland 2005 Annual Report. Return
- Mark Schweitzer and Peter Rupert, “Understanding the Persistence of Poverty,” Federal Reserve Bank of Cleveland 2006 Annual Report. Return
- Jeffrey Lin, “Regional Resilience,” Federal Reserve Bank of Philadelphia Working Paper No. 13-1, December 17, 2012. Return
- Jonathan James, “The College Wage Premium,” Federal Reserve Bank of Cleveland Economic Commentary, August 2012. Return
- Kartik Athreya and Janice Eberly, “The College Premium, College Noncompletion, and Human Capital Investment,” Federal Reserve Bank of Richmond Working Paper 13-02R, February 2015. Return
- Rob Valletta, “Higher Education, Wages, and Polarization,” Federal Reserve Bank of San Francisco Economic Letter, 2015-02, January 12, 2015. Return
- See Keith Sill, “Widening the Wage Gap: The Skill Premium and Technology,” Federal Reserve Bank of Philadelphia, Business Review, Fourth Quarter 2002, pp. 25-32, and Aaron Steelman and John A. Weinberg, “What’s Driving Wage Inequality?” Federal Reserve Bank of Richmond Economic Quarterly 91, Summer 2005, pp. 1-17. Return
- Jonathan James, “The Surprising Impact of High School Math on Job Market Outcomes,” Federal Reserve Bank of Cleveland Economic Commentary, November 2013. Return
- Math Corps Return
- See Daron Acemoglu and David Autor, “Skills, Tasks, and Technologies: Implications for Employment and Earnings,” in Handbook of Labor Economics, vol. 4B, Orley Ashenfelter and David Card, eds., Amsterdam: Elsevier-North Holland, 2011, pp. 1043-1171. Valletta (2015) provides an accessible explanation of the polarization hypothesis. Return
- See Valletta (2015) and Jaison R. Abel and Richard Deitz, “Job Polarization and Rising Inequality in the Nation and the New York-Northern New Jersey Region,” Federal Reserve Bank of New York Current Issues in Economics and Finance 18, 2012. Return
- See Sill (2002). Return
- Lisa Nelson and Francisca Richter, “The Prospects of Non-College Bound Workers in the Fourth District,” Federal Reserve Bank of Cleveland A Look Behind the Numbers, February 2014. Return
- Enrico Moretti estimated spillovers from college education by comparing wages for similar individuals who work in cities that differ by the proportion of college graduates in their labor force, being careful to consider unobserved differences in the individuals and the cities. He found that each percentage point increase in the share of college graduates between 1980-1990 was associated with 1.6 percent higher wages of high school graduates and 0.4 percent higher wages of college graduates. See Moretti, “Estimating the Social Return to Higher Education: Evidence from Longitudinal and Repeated Cross-Sectional Data,” Journal of Econometrics 121, 2004, pp. 175-212. Return
- See Edward L. Glaeser, Giacomo A.M. Ponzetto, and Kristina Tobio, “Cities, Skills, and Regional Change,” Regional Studies 48, 2014, pp. 7-43, and the discussion in Lisa Nelson and Francisca Richter, “The Prospects of Non-College Bound Workers in the Fourth District,” Federal Reserve Bank of Cleveland A Look Behind the Numbers, February 2014. Return
- See Digest of Education Statistics, table 302.60 for enrollment rates (http://nces.ed.gov/programs/digest/d13/tables/dt13_302.60.asp) and table 326.10 for completion rates (http://nces.ed.gov/programs/digest/d13/tables/dt13_326.10.asp). Return
- See, for example, James Heckman, Rodrigo Pinto, and Peter Savelyev, “Understanding the Mechanisms Through Which an Influential Early Childhood Program Boosted Adult Outcomes,” American Economic Review 103, 2013, pp. 2052- 2086, and Douglas Almond and Janet Currie, “Human Capital Development Before Age Five,” in Handbook of Labor Economics, vol. 4B, Orley Ashenfelter and David Card, eds., Amsterdam: Elsevier, North-Holland, 2011, pp. 1315–1486. Return
- Heckman, Pinto, and Savelyev (2013). Return
- See Dionissi Aliprantis, “When Should Children Start School?” Journal of Human Capital 8 (Winter 2014), pp. 481-536. Return
- Digest of Education Statistics, table 330.10 for enrollment rates (http://nces.ed.gov/programs/digest/d13/tables/dt13_330.10.asp). Return
- James McAndrews, “Student Debt and Higher Education Financing: A Public Finance Perspective,” remarks at the National Association of College and University Business Officers, New York, NY, February 5, 2015. Return
- See Board of Governors of the Federal Reserve System, May 2015, pp. 34-35. Return
- Athreya and Eberly (2015). Return
- Source: National Center for Education Statistics. Return
- Source: Association for Talent Development 2012 State of the Industry Report. Return
- See the Jacob France Institute. Return
- See Towards Employment. Return
- See Partners for a Competitive Workforce. Return
- Paul Tough discusses some of the research in How Children Succeed: Grit, Curiosity, and the Hidden Power of Character, Houghton Mifflin Harcourt: New York, 2012. Return