Establishing a Practical, Return-on-Investment Framework for Education and Skills Development to Expand Economic Opportunity

This working paper is a collaborative project co-authored by Dan Lips, Senior Fellow at FREOPP, Matthew Barry, Partner at Learn Capital, and Arushi Mathavan, Analyst at Learn Capital.

The United States spends $1.6 trillion annually on K-12 and postsecondary education, or seven percent of the nation’s gross domestic product. Average per-pupil spending in elementary and secondary schools was $15,600 in 2022, indicating that the average American student will have roughly $200,000 spent on her education through high school.

Federal expenditures on K-12 education have reduced resource inequality in elementary and secondary schools. On average, the United States spends more on higher poverty school districts than lower poverty school districts. During the 2019-20 school year, high-poverty districts and middle-high-poverty districts spent $13,400 and $14,600 per pupil, compared to $13,300 and $11,912 spent by low- and middle-low poverty school districts.

Yet academic achievement gaps persist in American education. For decades, children from lower-income households have typically performed worse than their peers on long-term measures of academic achievement. As Eric Hanushek and Paul Peterson wrote in 2019, “the opportunity gap—that is, the relationship between socioeconomic status and achievement—has not grown over the past 50 years. But neither has it closed. Instead, the gap between the haves and have-nots has persisted.” During the COVID-19 pandemic, widespread public school disruptions set American students back and widened achievement disparities. 

The American education sector also faces significant fiscal challenges. The federal government’s deficit spending is projected to total $22 trillion over the next ten years. In 2024, the federal government will pay nearly $900 billion in interest for the national debt, or more than the national defense budget, and net interest payments are set to rise to $1.7 trillion in 2034. These numbers are unsustainable. As a result, states and school districts cannot expect significant funding increases or emergency funds for K-12 education moving forward. 

Around the world, providing access to universal basic education and improving opportunities for human capital development must be addressed to reduce global poverty. A report sponsored by the World Bank, the United Nations, and other international organizations found that “nearly 6 out of every 10 ten-year-olds in low- and middle-income countries [were] suffering from learning poverty—meaning they were unable to read and understand a simple story.” Notably, these data pre-dated the COVID-19 pandemic, which caused widespread schooling disruptions and imposed learning losses on countless children across the globe. Economists have found a potential remedy for these losses: research from sub-Saharan Africa suggests that increasing human capital through additional years of schooling yields a high return-on-investment (ROI).

Reducing inequality, expanding education opportunities, and promoting human capital development in the United States and around the world will require new approaches from the public and private sectors. Establishing an ROI framework for analyzing and estimating education interventions has the potential to increase the efficiency of investment and improve education outcomes. 

This report reviews the academic literature on human capital development and the relationship between education outcomes and lifetime earnings. It highlights recent data analysis on differences between the returns-on-investment for for-profit education ventures. This study was conducted in partnership between FREOPP, the University of Texas at Austin Salem Center for Public Policy, and Learn Capital. The analysis establishes a Learning Impact Index (LII) to measure social and economic value created across ventures by comparing (1) enhanced lifetime earnings and (2) estimated cost savings that ventures drive. This collaborative project shows how academic researchers—in partnership with educational institutions, service providers, and other stakeholders—can develop frameworks for estimating the ROI for education to guide and inform future investments. For the public sector, such a framework could prioritize resources and access to education services that yield longer-term benefits for students. For the private sector, an ROI framework could improve and increase resources for ventures and services that provide a higher ROI and social benefit.

The report presents the following recommendations: 

1. The academic research community can further develop and apply return-on-investment frameworks to analyze available data to provide estimates of the value of specific education interventions.
2. Congress and the Department of Education should engage leading institutions—such as the Institute of Education Sciences and the National Academies of Sciences, Engineering, and Mathematics—to develop a credible return-on-investment framework or frameworks that can evaluate education interventions and investments.
3.  Congress and the Department of Education should develop a framework for evaluating the return-on-investment of specific federally funded education interventions. This framework could focus and prioritize government grants and other expenditures on education services that provide high ROI. 
4. The private sector—including venture capital and the philanthropic communities—should incorporate education ROI estimates into their investment evaluations.

Background on academic research on education outcomes and earnings

A central question in education economics concerns the relationship between human capital development and economic outcomes. During the later half of the 20th century, economists and academics developed theories and quantified the relationships between educational attainment or achievement with economic outputs including earnings. Nobel laureate Gary Becker identified the relationship between formal education and earnings in 1964. Ten years later, professor Jacob Mincer published a seminal analysis that established a model for identifying the relationship between school outcomes and individual earnings, based on educational attainment or years of schooling as the measure of human capital development. This ongoing education and economic research provides valuable evidence for the relationships between education attainment, achievement, and long-term economic outcomes. 

Years of Schooling and Earnings: In 2018, the World Bank Group published a meta-analysis of global literature by George Psacharopoulos and Harry Antony Patrinos. Using a database of 1,120 estimates in 139 countries, the authors found that “the private average global rate of return to one extra year of schooling is about nine percent a year and very stable over decades.” The authors explained that scholars have used two primary methodologies for estimating ROI: the Mincerian earnings function and the full-discounting methods. The authors also found that “[p]rivate returns to schooling are higher in low-income countries by about one percentage point relative to high-income countries” and, that “private returns to female education exceed that of males by about two percentage points.” Finally, the authors note that “social returns to schooling remain high, above 10 percent at the secondary and higher education levels.” 

Achievement and Earnings: Education economists have expanded this literature in important ways, including identifying which inputs of education affect economic outcomes. In addition, economists have quantified the relationship between educational achievement, such as test scores, rather than simply focusing on attainment or years of schooling. In 2010, Professor Eric A. Hanushek explained: 

“Three parallel U.S. studies provide very consistent estimates of the impact of test performance on earnings for young workers (Mulligan (1999); Murnane, Willett, Duhaldeborde, and Tyler (2000); Lazear (2003)). These studies employ different nationally representative data sets that follow students after they leave school and enter the labor force. When scores are standardized, they suggest that one standard deviation increase in mathematics performance at the end of high school translates into 10-15 percent higher annual earnings.”

A 2010 NBER paper National Bureau of Economic Research found: 

“…a standard deviation improvement in a birth cohort’s 8th grade math achievement was associated with an eight percent rise in income, as well as improved educational attainment and declines in teen motherhood, incarceration and arrest rates.” 

Raj Chetty and his co-authors have conducted groundbreaking analysis showing similar relationships, including identifying the value of high-quality teaching. For example, in 2014, Chetty, John N. Friedman, and Jonah E. Rockoff found that a one standard deviation increase in math or English test scores resulted in a 12 percent increase in earnings after controlling for several factors, including students, teacher, and prior year test scores.

Learning Losses and Projected Lifetime Earnings: In recent years, economists and researchers have focused on the relationships between learning losses and lifetime earnings and other outcomes, particularly following prolonged school closures and remote learning during the pandemic. For example, researchers estimated that recent declines on National Assessment of Educational Progress (NAEP) following the pandemic “would represent a 1.6 percent decline in present value of lifetime earnings for the average K-12 student (or $19,400), totaling $900 billion for the 48 million students enrolled in public schools during the 2020-21 school year.”

New estimates of the return-on-investment of postsecondary education

In 2013, President Obama announced the creation of a U.S. Department of Education College Scorecard (Scorecard) to provide transparent information about education outcomes. The data published in the Scorecard—including costs, outcomes, postgraduate earnings, and employment—provide valuable information about return-on-investment.

Since 2021, Preston Cooper, a former senior fellow with the Foundation for Research on Equal Opportunity, has published an index showing the lifetime ROI by college and includes 50,000 degrees, based on data from the Scorecard, the National Center for Education Statistics, and the Census Bureau. Cooper published an explanation of his assumptions here. Cooper’s key findings include: 

For students who graduate on time, the median bachelor’s degree has a net ROI of $306,000. But some degrees are worth millions of dollars, while others have no net financial value at all. After accounting for the risk of dropping out, ROI for the median bachelor’s degree drops to $129,000. Over a quarter of programs have negative ROI. Four in five engineering programs have ROI above $500,000, but the same is true for just one percent of psychology programs.

Importantly, Cooper’s analysis provides insight into the role of higher education in promoting social mobility, highlighting the institutions and degrees that provide a high return-on-investment for lower-income students.

Estimating the Return on Investment of Specific For-Profit Education Services

Learn Capital (Learn), the University of Texas Austin Salem Center for Public Policy (UT), and the Foundation for Research on Equal Opportunity (FREOPP) have partnered to explore how specific learning outcomes reported by for-profit ventures could be analyzed to develop a social ROI estimate, including lifetime earnings. This section of the paper presents an analysis developed by Learn Capital to estimate the return on investment for specific for-profit education services as a means to assess the social impact of venture investments.

As background, Learn is a venture capital fund that invests in rapidly scaling tech-enabled education companies that empower individuals with the capacity, knowledge, and tools to thrive. Learn’s focus areas include innovations in K-12 education, higher education, and lifelong learning. Learnhas invested over $1.3 billion across more than 200 portfolio companies that cumulatively reach one billion learners across the globe. Like many venture capital firms, Learn has strived to measure impact alongside financial returns to evaluate the scale of their societal impact. While their original strategy was rooted in measuring access and quality of educational interventions, their comparison methodology limited cross-company and cross-fund comparability, as these metrics largely represented highly individualized outcomes. 

Learn is piloting a new impact methodology, the Learning Impact Index, to systematically and equitably measure the socio-economic value of its investments for individuals and systems. The LII aims to provide directional assessments of company impact relative to size and user base to indicate how effectively they are delivering on their intended mission. Naturally, these data will help evaluate future investments and grant opportunities. The LII takes a wide array of company-provided inputs and employs four approaches in calculating the dollar value of the socioeconomic impact driven. The company-provided inputs are subject to screening and verification, as well as weighting based on data rigor, as well as depth and quality of impact.

There are inherent limitations of this analysis due to several factors. First, the learning outcomes are, in most cases, self-reported data produced by the ventures rather than independently verified outcomes. Second, the analysis is based on differing degrees of evidence, which is weighted in the attribution factor scoring but still largely limits accuracy. Third, ventures change their products and services over time, which poses a challenge to estimating potential returns-on-investment into the future. 

The LII was designed in conjunction with policy experts from UT and FREOPP that advised the methodology and broader insights.

The Learning Impact Index

The Learning Impact Index is a systematized metric that enables consistent tracking and capturing of the social and economic value created by for-profit educational companies. This metric looks at lifetime earnings enhancement,efficiency, and cost savings driven by ventures and provides directional guidance on the relative impact across companies.

Objective and Intended Use Case

The primary purpose of the LII is for investors to gain a directional understanding of the impact driven by companies in a way that can be standardized for cross-portfolio comparison. The LII is not intended to represent actual impact values with 100 percent certainty, as investing bodies rarely have enough granular data and user tracking for that. But using basic inputs—such as users, learning impacts, and retention and engagement data—investors can utilize the LII to ascertain impact values.

The early pilot results demonstrate value not just for Learn to measure portfolio-wide impact, but also for investors and ventures to assess their estimated impact promoting human capital development. Investors benefit from the LII as a portfolio aggregate measure that helps investors evaluate the collective impact of the entire portfolio, capturing the broad value created across ventures. More broadly, Learn’s long-term goal is for investing bodies across impact fields to utilize the LII as a metric across companies and portfolios, promoting greater transparency and accountability in impact measurement and reporting over time.

Ventures can also benefit from and use the LII as a starting point and incentive for high-quality impact tracking. As K-12 funding and COVID relief funds run out, the demand and pressure for solutions to differentiate themselves with strong evidence will be stronger than ever. There is a clear opportunity for education technology companies to use the LII or similar measures of return-on-investment or projected long-term human capital development to establish evidence-backed credibility for outcomes-based purchasers, communicate impact and value to end users, and establish a positive feedback loop for delivering the intended mission that drives long-term accountability and impact.

The Learning Impact Index includes two different models, which are based on mathematical formulas based on assumptions discussed below. The first model projects lifetime earnings enhancements. The second model estimates efficiency and cost-savings.

Lifetime Earnings Enhancements: The Lifetime Earnings Enhancement model refers to the increase in an individual’s earning potential over their working life as a result of improved education, skills, and career opportunities. This model also emphasizes the foundational role of youth education in shaping the future earning potential of individuals. This dimension recognizes that investment in the education and development of younger learners significantly influences their career trajectory and earning capacity in the long term. This impact is measured through both direct and indirect means:

• Direct Impact on Lifetime Earnings Enhancement: Companies providing tangible increases in earning potential through direct intervention in education or career advancement

• Indirect Advancement of Lifetime Earnings: Companies contributing to enhanced earning potential by fostering formative educational outcomes with a depth of engagement. This goes beyond the foundational role of youth education and entails an evidence-based approach to demonstrating how these outcomes serve as leading indicators of lifetime increased earnings.

Efficiency and Cost Savings: The Efficiency and Cost Savings model encompasses optimized resource utilization and reduced financial barriers to meaningful education that unlocks upward mobility outcomes. These savings play a significant role in societal impact by optimizing the utilization of resources and accelerating desired outcomes. Efficiency and Cost Savings focus on optimizing resource utilization and reducing financial barriers to human capital development, thereby making education and training more accessible and effective. This framework for estimating ROI assumes that not all interventions improve learning outcomes directly but can still be crucial by providing a more efficient path to existing outcomes. This model involves projecting two levels of impact:

• Individual savings: How the company’s services make learning and career development more time or cost-efficient for individuals.
• Systems savings: Impact on system-wide optimization, which includes reducing costs and improving the efficiency of education and human capital development on a broader scale.

Definitions and Methodology: An explanation of the process of calculating the Learning Impact Index

Figure 1: Overview of 4 LII sub-methodologies

Figure 1 provides further detail on the definition, focus area, metrics, and evidence required to calculate the LII via one of the four sub-methodologies.  

The LII takes these metrics, which are often company-provided access and quality metrics, and translates them into estimated lifetime earnings gains or overall cost and efficiency savings to measure social mobility. These Estimated Lifetime Earnings and Cost Efficiency Savings models are weighed against an Outcomes/Efficiency Attribution Score and scaled for relative company magnitude. Figure 2 below provides an overview of how the Lifetime Earnings and Cost Efficiency Savings models require estimated earnings/savings, an Outcomes/Efficiency Attribution Score, and Magnitude to calculate the LII in sum. 

Figure 2: LII calculation methodology overview

The Outcomes/Efficiency Attribution Score is a model variable that accounts for the confidence level of the impact assumptions based on the information available to measure and estimate. This score is calculated based on key factors related to the directness, depth, and evidence of impact. For example, in some cases, a company’s evidence will include a randomized control trial or quasi-experimental study, which in academic analysis are considered best research methods to assess impact. The attribution also considers the intensity of the intervention (including how much time a student or learner spends using the service), the company sector based on the time that the intervention occurs in a learner’s life, and a “perceived quality score.” 

Magnitude of impact is a model variable that projects the growth of a company’s impact over a set amount of years and across a scaled estimate of current and future users in this time period. These growth rates are largely based on the company growth projections weighed against perceived quality score. In other words, the model projects how many people may use a product or service, based in part on a company’s growth projections, to estimate the scale of the impact over a period of time. Figure 3 below details the variables affecting the Efficiency/Outcomes Attribution Factor and Magnitude calculations.

Figure 3: Variables accounted for by Efficiency/Outcomes Attribution Factor and Magnitude assumptions

At a high level, the first step of calculating the LII is using company-provided data to estimate Lifetime Earnings Enhancement or Cost/Efficiency Savings model using the following classification process presented in the Figure 4 flow chart. For example, this involves determining whether it is appropriate to measure a venture’s Lifetime Earning Enhancement impact or Efficiency and Cost Savings impact based on the type of service or intervention provided. As the flow chart shows, each calculation involves determining the appropriate way to measure impact based on the venture’s service, whether the impact is direct or indirect (or whether the cost saving attribute to a person or system). Further, the analysis involves answering questions about the data available to measure impact, the academic literature that can support long-term outcome estimates, and so on.

Figure 4: LII calculation steps

Indirect Lifetime Earnings Enhancement calculations are the most challenging to initially ascertain. They require leveraging high-quality evidence bases to find correlations between leading indicators and lifetime earnings. For example, a company focused on early childhood literacy could leverage the studies finding ties between 3rd grade reading scores and lifetime earnings potential. 

Once this step is complete, the Outcomes/Efficiency Attribution Score (40-80 percent range) is calculated using an index weighing the factors mentioned above  (impact evidence, intensity, etc.). For lifetime earnings enhancements, the total dollar amount is scaled to account for user growth and duration of impact, with 40 years being the average earnings increase horizon. For Cost and Efficiency Savings, dollar savings are calculated per annum and efficiency savings are computed as ratios. 

Assumptions

The LII’s key assumption is that lifetime earnings advancements and efficiency and cost savings are the primary ways to measure socio-economic value created. In doing so, this approach neglects other primary measures of societal impact, such as increased mental well-being, access to career-advancing networks, and lifetime mental and personal satisfaction that enables individuals to reach self-actualized goals.

The LII also assumes that company-reported data on impact—such as learning gains or income improvements—are empirically sound and ethically reported.

Pilot Case Studies:

Note: In the interest of company privacy, the following four examples are hypotheticals based on real companies but leveraging “dummy” company-provided data.

I. Company A: Direct Lifetime Earnings Enhancement

Company A is a higher education solution that primarily serves global learners from emerging economies. Company A focuses on providing skills-based education and leveraging technology to scale-up degree programs to be accessible for learners across the globe. Company A’s accessible programs enable students from emerging markets to attain degrees that enhance their job marketability, leading to higher starting salaries, better job positions, and accelerated career progression. 

Company A polled their 3,500 graduates and collected data on the students’ base salary earning with and without Company A’s education. Students reported, on average, a 26 percent salary increase during their first year of employment, and a 50 percent increase during their second year. Income gains were then projected at a standard 5 percent annual growth rate across a 40 year horizon for all existing graduates, at a 68 percent attribution factor to Company A’s learning intervention. Gains were estimated at roughly $98 million in additional lifetime earnings across the 3,500 graduates, or roughly $28,000 additional lifetime earnings per individual (discounted at a 5 percent rate).

Figure 5: Company A LII Calculation

II. Company B: Indirect Lifetime Earnings Enhancement

Company B is a K-12 curriculum solution that helps improve early childhood math and reading scores by providing high quality education that is otherwise inaccessible in emerging economies. 

Company B significantly enhances the long-term academic and professional trajectories of its students by providing high-quality early childhood education that sets students up for long-term success, proven by marked improvements in reading and math assessments. Through its evidence-based teaching methodologies, Company B not only elevates immediate learning results, but indirectly boosts future earning potentials, thereby contributing to a cycle of sustained educational success and economic mobility.

Peer-reviewed and independently conducted studies found that Company B’s early childhood interventions added about 1.8 additional years of learning in childhood development gains, as measured by math and reading performance. Income gains for the 1.5 million students Company B serves were projected across a 40 year horizon, applying data on lifetime earnings advancements to the estimated 1.8 years of additional schooling students received. Learn applied an estimate of 9 percent ROI per year of schooling (referenced in 2018 World Bank meta-analysis) and an impact attribution score of 70 percent to arrive at an estimated $9 billion in additional earnings across Company B’s 1.5 million students, or roughly$6,000 per student.

Figure 6: Company B LII Calculation

III. Company C: Individual Cost Savings

Company C is a learning app that helps students with homework. Their services follow a “freemium” model in which users can access some support features for free, and around two million annual users opt for a paid subscription. By providing a low-cost alternative to traditional tutoring and support services, Company C drives individual cost and efficiency savings.

Company C examined pricing differences between their product and competitor tutoring platforms and found that users on average spent $12 on Company C vs $27 on an alternative platform. Thus, the assumed cost savings were $15 per individual and applied across the two million subscribers to estimate $30 million in cost savings. While this figure is largely directional and doesn’t factor in nuances of willingness to pay, it can highlight the cost effectiveness of using Company C.

A case study Company C conducted found that users on average had 35 percent higher knowledge retention than alternative platforms, highlighting the efficiency savings Company C drives. Using the 35 percent higher outcomes, $15 price differential, and a 48 percent efficiency attribution factor, we can measure the efficiency and cost savings ratio to be 1.9x. This datapoint suggests that Company C’s more than two million subscribers receive about 90 percent higher cost efficiency for learning outcomes produced with Company C vs. competitor products.

Figure 7: Company C LII Calculation

IV. Company D: System cost savings 

Company D is a college student platform that improves pathways to employment by providing students with career and financial support needed to complete their education and enter the workforce. Its model is designed to expand access to quality education while addressing the financial barriers that many students face and simultaneously enabling institutions to deploy these funds more effectively​​.

Across more than 1,000 colleges and university programs, Company D has been able to save around $345,000 in system-wide efficiencies per program annually. Company D drives these systemic changes by providing students with the career and financing support that enables them to pay back loans at a lower default rate over time. In total, these system-wide efficiencies drive approximately $345 million in annual cost savings. 

Figure 8: Company D LII Calculation

The value of establishing education return-on-investment frameworks for private ventures

Establishing a credible ROI framework for evaluating private venture education interventions has the potential to yield significant benefits for expanding economic opportunity and improving the economic prospects for Americans, particularly economically disadvantaged students. With guidance from the nation’s leading academics, an ROI framework could analyze education interventions and maximize their value for students and society writ large. 

To be clear, the ROI framework and long-term economic projections should be interpreted with caution. The projected outcomes from this analysis are an attempt to quantify the long-term impact of learning programs to help guide impact investment on learning ventures, which could help inform other investments in or expenditures on learning programs, education providers, and related services. 

Nevertheless, the further development, broader uses, and application of such a framework has the potential to dramatically increase the efficiency of the $1.6 trillion education sector in the United States. For example, Cooper’s groundbreaking work estimating the return-on-investment of postsecondary education provides a useful guide for students and parents considering higher education programs. Widespread use of Cooper’s ROI estimates or a similar framework could yield significant efficiency gains across the $700 billion postsecondary education sector. 

For parents and students, such information could inform decisions including choosing learning environments and accessing outside-of-school instruction. In the United States, education savings accounts (ESAs) are revolutionizing the elementary and secondary education systems across the country. ESAs provide parents with greater ability to choose their child’s school or take direct control of a share of public funds through to purchase services and customize their child’s educational experiences. In April 2024, Tyton Partners estimated that 20 percent of American students, or roughly 10 million children, will have access to an ESA program in 2024. One million American students are now participating in private education choice programs. Approximately 22 million children are now eligible for such programs. With expanding options to use public funding to decide how their children learn, parents could use information from an ROI framework to provide their children with schools and learning environments that promise long-term economic benefits. 

The ongoing decentralization in K-12 education and proliferation of parental choice options should also spur the public education sector to increase efficiency and provide high-quality options to maintain and attract student enrollments. Therefore, a credible ROI framework could inform state and local education agencies, and improve public school procurement of education services. 

Internationally, a credible ROI framework for analyzing the impact of learning ventures could promote human flourishing and reduce global poverty by expanding access to quality educational services. The need is particularly acute in developing countries where the potential value of high-quality education and increasing human capital development has the greatest potential to promote economic growth.

Recommendations academia, government, and impact investors 

Recommendations for academia 

1. The academic research community has an opportunity to further develop and apply return-on-investment frameworks to analyze public and private sector data to provide estimates of the value of specific education interventions. The academic literature on education outcomes and earnings provides a foundation for additional research. Economists and education scholars should build upon the existing evidence by conducting additional analyses to inform the development of ROI frameworks for specific education interventions. 

Recommendations for federal policymakers 

2. Congress and the Department of Education should engage leading institutions—such as the Institute of Education Sciences and the National Academies of Sciences, Engineering, and Mathematics—to develop a credible return-on-investment framework or frameworks that can be used to evaluate education interventions and public and private sector investments. The federal government has provided valuable leadership by identifying important policy questions. For example, in the 1990s, Congress directed the formation of a national reading panel to review available research to identify best practices to improve student literacy. A similar federal initiative to support the development of return-on-investment frameworks for the education sector could inform public and private sector activities to improve education options and outcomes. Importantly, the development of a ROI framework could complement the federal Institute of Education Sciences’s recent announcement signaling interest in embracing a “living evidence” model for federal education research and development, which would involve a “dynamic progress of evidence synthesis” and the use of “evidence hubs” to identify and close gaps in R&D literature.

3. Congress and the Department of Education should develop a framework for evaluating the return-on-investment of specific federally funded education interventions. This framework could be used to focus and prioritize government grants and other expenditures on education services that provide a higher ROI. Federal policymakers should apply ROI frameworks to identify how current and future public expenditures affect long-term education and economic outcomes for beneficiaries. For example, the Department of Education’s Institute of Education Sciences describes examples of expenditures on research-based education technology programs that have yielded improvements in student outcomes in its annual budget submission to Congress. Applying an ROI framework to education R&D expenditures would be an initial way to begin analyzing federal education investments to identify and prioritize funding for effective interventions.

Recommendations for impact investors 

4. The private sector, including venture capital and the philanthropic community, should incorporate education return-on-investment estimates in evaluating investment opportunities and measuring their societal impact. In recent years, the private sector has increasingly sought to apply ethical frameworks for guiding investment and business activity. Given the longstanding bipartisan support for promoting equal opportunity in education, analyzing the ROI of education initiatives to improve economic opportunities for all Americans, particularly disadvantaged children. 

Conclusion

Improving education outcomes and expanding social mobility in the 21st century will require the public and private sector to increase the efficiency of the time and resources that are invested on K-12 and postsecondary education, including private ventures and learning programs. Building upon the foundation of academic literature showing the relationship between education outcomes and economic opportunities, the development of new return-on-investment frameworks to guide public and private sector investment in education has the potential to expand and promote economic opportunity for students across the world.