Synthesis and Way Forward

Routinizing Leadership: Creating a Market for Outcomes

By Ian Galloway

By the late 1980s, acid rain had become a global scourge. Man-made emissions of sulfur dioxide and nitrogen oxides, byproducts of burning fuel for electricity generation and other industrial uses, were alarmingly high. Congress responded by passing the Clean Air Act, a multi-pronged policy to address pollution, which included a cap-and-trade program specifically targeting acid rain. This novel program incentivized power companies to find creative solutions to lower their own emissions, leading to a 76 percent reduction since 1990.1 “The brilliance of the scheme,” according to The New York Times columnist Joe Nocera, was “that while [cap-and-trade] set emissions targets, it did not tell power companies how to meet those targets, allowing them a great deal of flexibility.”2 That flexibility led to industry-wide innovation and, ultimately, a solution at scale: near-elimination of acid rain in the United States.

In the mid-1990s, getting to space meant booking a seat on the NASA shuttle. Sensing an opportunity, Peter Diamandis traveled to Missouri in honor of Orteig-Prize-winner Charles Lindbergh’s Spirit of St. Louis solo transcontinental flight from New York to Paris and proposed something bold: a $10 million prize for the first company to send three people 100 kilometers above the Earth twice in two weeks (and bring them back alive).3 Eight years later, the Ansari XPRIZE was claimed by SpaceShipOne, a spaceplane designed by aerospace engineer Burt Rutan and financed by Microsoft co-founder Paul Allen (see Bravo/Frangione/Wander in this volume). This was, by all accounts, an enormous scientific breakthrough in a relatively short period of time. But the Ansari XPRIZE paid dividends beyond SpaceShipOne. While competing to win the $10 million prize, 26 companies from around the world spent a combined $100 million developing new space technology. That collective investment now forms the foundation of today’s $2 billion private space industry.4

At the turn of the century, pneumococcal infections were killing half a million children annually worldwide.5 There was no viable market for vaccine development to prevent these infections, which primarily afflicted children in developing countries. At the same time, in 2000, the Global Alliance for Vaccines and Immunization (GAVI) was formed by the Bill & Melinda Gates Foundation in partnership with the United States, United Kingdom, Norway, and several other large donors to bring expensive vaccines to impoverished countries. However, this wasn’t enough to get pharmaceutical companies to create new vaccines specifically for use in the developing world, given the limited market potential for low-cost treatments. So GAVI took a different tack, making an advance market commitment to buy, at a pre-specified cost, a certain volume of vaccine doses should a company choose to produce one (see Levine). This $1.5 billion commitment led directly to the creation of a new vaccine, which now protects children from pneumococcal infections in 54 countries around the world.

These examples showcase inspired leadership: Congress aggressively tackling acid rain; Diamandis launching a modern-day space race; GAVI saving millions of lives. But what makes their leadership notable is actually what they didn’t do. Congress didn’t reflexively mothball power plants. Diamandis didn’t hire engineers to build him a spaceship. GAVI didn’t directly fund vaccine research and development. They knew that their challenges were too hard to solve alone and that the solutions they needed were largely unknown. They understood that trying to “pick winners” from among any number of proposals at hand would likely fail. So they created an incentive to unleash creativity, a reward for outside-the-box thinking. And they insisted on results.


Some 400,000 mission-driven nonprofits provide critical services to people in crisis every year in the United States.6 Serving these communities effectively — e.g., the homeless, mentally ill, abused, and neglected — is incredibly hard and a clear moral imperative. Yet, even as we routinely talk about exceptional social programs that work (and we published a book predicated on that idea),7 there are very few genuinely “evidence-based” programs from which funders can choose.8 “In many areas of public policy, we simply don’t know much about what works, for whom, and under what circumstances,” according to Erica Brown, Josh McGee, and Kathy Stack.9 Many programs, while promising, are ultimately unproven. In other words, they can be risky bets.

This risk matters. Funders, both government and philanthropic, don’t want to invest in programs that don’t work. But their ability to assess the likelihood that a program will succeed is limited. Social challenges are dynamic: Something that once worked, in a different place, with a different set of people, may not work again. Programs are dynamic, too: Fidelity to the model isn’t just a matter of following a recipe; the people following the recipe matter, too. Put the two together and it’s easy to see that any social program, however well-studied or replicated, entails taking a risk.

Predictably, in light of this risk, nonprofit reporting and program monitoring requirements have gotten more onerous (see Gustafsson-Wright). Funders want to know that their investments are performing as promised. But that isn’t enough to guarantee results, so they also tend to fund programs at their base cost.10 This may be rational (if you don’t know if something’s going to work, invest sparingly), but it’s pernicious in practice. The consequences are familiar and widespread: administrative functions are underfunded and undervalued; innovation is discouraged because it threatens lean program budgets; and nonprofits are frequently treated like commodities, competing primarily on price, not performance. Paying nonprofits on a cost-of-service basis, and not a value-creation basis, makes it very difficult for them to build organizational capacity.11 As Kelly Fitzsimmons observed, “Foundations were reluctant to pay for evidence building. However, when…asked for program funding, they demanded evidence of impact — evidence that we couldn’t build without the funding they were hesitant to provide.” This reluctance to fund organizational capacity leads to an endless cycle of resource scarcity which, tragically, is reinforced by the continuing lack of capacity needed to prove program effectiveness, which would otherwise limit funder risk and break the cycle of scarcity.


The way out of this performance-risk trap is for funders to stop gambling on individual programs and take an adaptive, program-agnostic approach that mirrors the breakthrough examples at the start of this essay. There’s actually precedent for this in the social sector: the Low Income Housing Tax Credit (LIHTC). LIHTC is the primary subsidy source for multifamily affordable-housing construction and rehabilitation (see Ludwig). To date, the LIHTC program has produced over three million affordable housing units nationwide (see Erickson), while leaving nearly all the risky design, construction, and financing details up to the project developer.

LIHTC works like a tax coupon that raises money for affordable housing. State housing finance agencies award the credits to housing developers, who sell them to investors with tax liability — usually through a syndicator — and then use the proceeds to lower the overall project cost. This, in turn, allows developers to take out a smaller mortgage to cover the remainder of their expenses. A more manageable mortgage allows them to charge lower rents, effectively transferring the project subsidy to the individual tenants living in the building. As long as rents stay low, the investors who bought the credits get to keep them. However, if rents go up beyond a certain threshold, the IRS recaptures the credits, and the investors lose their money.

Critics of LIHTC’s complexity call for the government to simply award subsidies directly to affordable housing developers, cutting out the syndicators, investors, reporting requirements, and consultants. But there’s a good reason for the complexity: It buys the government a performance guarantee. If an affordable housing project can’t maintain affordable rents for a minimum of 15 years, the government gets its money back. This performance guarantee — effectively an adaptive, program-agnostic feature — is widely considered to be an improvement over the largely maligned top-down, federally funded public housing projects of the past.12

The LIHTC program recognizes that affordable housing needs will be different in different places. In some cases, affordable housing should be blended with market-rate housing to create mixed-income communities; in others, it should be anchored by a health clinic or grocery store. One community may need senior housing; another, housing for foster care families. Low-income renters have different needs and preferences. It’s difficult for the federal government alone to properly assess these and craft an affordable housing solution to meet them. Instead, LIHTC allows the government to buy what it really wants — housing affordability — and leaves the community customization to the housing developer.

Much like the federal government’s role in LIHTC projects, the prototypes highlighted in this book suggest a new role for nonprofit funders. Instead of investing in programs, funders would purchase outcomes and leave the program specifics to the provider. Funders could buy these outcomes any number of ways — through a rate card, an advance market commitment, a loan modification covenant, an impact insurance policy, a Pay for Success contract, or even a prize — but they wouldn’t need to become program experts to do so. By shifting out of their traditional investor role, which depends on correctly identifying winners, funders would be funding what works, at the price they agreed to, without taking any risk. This is how an adaptive, program-agnostic social sector could function. Getting there successfully, though, will depend on whether we can define and deliver outcomes that matter.


In an adaptable, program-agnostic world, the party paying for the outcome generally decides “what matters” based on its own set of preferences. A hospital system, for example, may care deeply about reducing health disparities in its local community (see Norris/McLean) or fear a financial penalty from its state health authority for failing to deliver on a particular health measure (see Long). In either case, the hospital would be the party deciding the outcome it would be willing to pay for.

Projected cost savings can also drive outcomes-based funding projects. A program that promises to reduce unnecessary incarceration, for example, may be selected over a program that increases child literacy on purely a cost-savings basis. This is a controversial aspect of outcomes-based funding, and the moral, ethical, and political implications of prioritizing cost savings are discussed at length in this volume (see Golden/Kohli/Mignotte and Halpern/Jutte). But the fact remains: The virtuous cycle of prevention leading to less treatment is financially compelling. This may prove short-sighted, however, in cases where the cost of producing a particularly valuable social outcome (ending homelessness, for example) exceeds the current cost of treating it or in cases where a successful outcome leads to greater use of a different, more expensive, service. Cost savings, while instructive, shouldn’t be the sole basis on which outcomes are decided.

Outcomes-based funding tools also require a high degree of nonprofit capacity. An outcomes rate card may be an efficient way to deliver social programs at scale (see Metcalf/Levette), but its success will depend on whether nonprofits are prepared to use it. Capacity is a significant predictor of what types of projects receive outcomes-based funding. Nancy Andrews argues in her chapter that we need an onramp (what she calls “Equity with a Twist”) to outcomes-based funding that allows nonprofits to build capacity around measurement and program administration. Kerry Sullivan argues for the same. Without sufficient capacity-building, the field will be limited by the relatively small universe of evidence-based providers that can take advantage of these tools. “If we truly desire a systemic shift, we need to invest in organizations’ ability to make the initial transition, and to continue to measure their outcomes on an ongoing basis,” note Kristin Giantris and Jessica LaBarbera. Another reason to invest in capacity building: Existing high-capacity providers may influence how the outcomes-based funding field evolves to their advantage, potentially freezing out peer organizations that could one day participate.

The maxim “you get what you measure” applies doubly here. Getting the measurement piece right is critical to defining outcomes. “Reliance on the wrong measures, lack of data on key measures, or poor-quality data can lead to faulty conclusions,” warns Gordon Berlin. If we’re serious about funding outcomes, we need absolute confidence that we’re measuring them correctly. This means being scientific about enrollment processes, intervention tracking metrics, and “compared to what?” counterfactuals. Good information technology solutions (see Whistler/Gee) will be crucial.

Data availability plays an important role as well. At root, outcomes-based funding models depend on data to prove that an outcome has been achieved (or not). Acquiring useful data is critical to the success of any outcomes-based funding project. But in some cases, what we track may be less a function of what matters and more a function of what data we can collect. This is immensely limiting and risks moving the field toward outcomes that happen to be easy to track and away from outcomes that may be more valuable but aren’t currently measured. “We cannot allow [information] availability bias to determine how we understand organizations,” according to Jacob Harold. This caution should also extend to outcomes. If we allow existing data to define what’s valuable, simply because we can measure it, we may end up celebrating statistically significant outcomes but not meaningful ones.


An adaptable, program-agnostic approach is not a good fit for every social challenge, nor is it a good fit for every nonprofit. Right-sizing the intervention to the outcome is crucial. A preschool provider shouldn’t be held accountable for high-school graduation rates. Likewise, a job training provider shouldn’t be held accountable for reducing homelessness, even if a job is a critical factor in housing stability. Outcomes-based funding is better used in cases where there is a clear and direct relationship between a given program intervention and the desired outcome: For example, reducing foster-care placements by addressing family substance abuse (see Merriman) or increasing post-release employment for former prisoners with in-prison computer coding classes (see Beck/Schwab/Pinedo). Holding nonprofits accountable for outcomes outside of their direct purview is unfair to them and unlikely to succeed.

Moreover, meaningful social change can take a long time. We know that high-quality early childhood education increases the chances of graduating from high school and leads to higher rates of adult employment, lower rates of criminal behavior, and greater family stability.13 But these outcomes don’t appear for years — and, in some cases, decades — after early childhood. This makes structuring outcomes-based contracts for interventions like early childhood education more difficult. Someday, it may be possible to link outcomes-based funding projects, with each delivering a component piece of the outcome “value chain.” For instance, there are certain intermediate markers throughout childhood — healthy birth, third-grade reading scores, pro-social behavior development, high-school graduation, etc. — that could be standalone links in that chain but, put together, lead to a longer-term “stretch goal,”14 such as avoiding teenage pregnancy or graduating from college. Each successful link would trigger an outcomes payment, which could be valued based on its relative importance in the chain.

Another promising approach is comprehensive, place-based development that targets an entire neighborhood with services over a sustained period of time. Melody Barnes, former director of the White House Domestic Policy Council, made the observation at a 2010 Federal Reserve conference that low-income people don’t have a housing day, then a transportation day, then a job day, then a fresh food day — every day is an everything day.15 Put another way, interrupting the cycle of intergenerational poverty requires a complex set of effective interventions. Maggie Super Church makes the case in this volume that investment funds can be structured to capture an array of health benefits based on a successful neighborhood investment strategy. Similarly, Kate Howard and Fred Blackwell are piloting an outcomes-oriented collective impact approach to transform four low-opportunity neighborhoods in San Francisco. These examples offer proof of concept that neighborhood-scale, place-based developments, augmented by effective social programming, can deliver meaningful outcomes for whole communities.

Looking ahead, there’s an untapped opportunity to build on these early success stories. Purpose Built Communities (see Naughton) has pioneered a place-based model in Atlanta — now replicated nationwide — that integrates mixed-income housing, a pre-K-through-college education pipeline, and wellness programs ranging from physical fitness, to job training, to financial literacy. Importantly, these supports aren’t offered in isolation; They’re carefully coordinated by a “community quarterback” that senses and responds to changing needs on the ground. In the future, organizations like community quarterbacks could be funded for achieving a set of stretch goals related to health, education, employment, and crime that are achievable only through large-scale neighborhood coordination.

Regardless of the intervention, these projects must deliver on their core promises to be successful. If you commit to getting kids ready for kindergarten, you have to actually prepare them for kindergarten (see Dubno). If you commit to reducing opioid use disorders (see Klem), you’re on the hook to reduce opioid use disorders. In the end, delivering the outcome is what matters most.


When my colleagues and I wrote “Routinizing the Extraordinary” in the first book of this series, most of our focus was on the nonprofits themselves: BakerRipley (formerly Neighborhood Centers Inc.) in Houston; Harlem Children’s Zone in New York City; Purpose Built Communities in Atlanta.16 They were all producing astonishing results in health, education, housing, and employment for their communities. They also tended to be entrepreneurial in nature, fundamentally cross-sectoral, and data-driven, and they deployed a careful blend of human services and place-based interventions.17 We wanted to highlight these examples so they could be replicated in the field.

But replicating transformational community change is hard. Not every nonprofit can become the Harlem Children’s Zone. The better solution, we thought, was to routinize the key elements. Make it easy for anyone, anywhere to do this work. It would also depend on a certain kind of leadership “able to promote a compelling vision of success for an entire community, marshal the necessary resources, and lead people in an integrated way.”18 Routinizing extraordinary results meant routinizing extraordinary nonprofit leadership as well.

A new kind of institution was needed to coordinate community development activity that anyone would deploy, which we termed a community quarterback. The quarterback could take on any number of forms depending on community needs; it would be empowered by real-time data and sophisticated data systems; it would deploy a mix of people- and place-based strategies; and it would be held accountable for results. And, ideally, those results would be carefully tracked and rewarded through an investment tax credit, a social impact bond, or another outcomes-based funding tool.

But in our rush to routinize nonprofit leadership, we failed to account for something else: Just as we can’t “rely on saints”19 to produce outcomes, we can’t rely on saints to pay for them. Ben McAdams and Armond Budish are rare.20 The Bill & Melinda Gates and XPRIZE foundations are rare.21 And as the outcomes-based funding field has matured, this overreliance on extraordinary funder leadership has been laid bare. It’s not enough to deliver better outcomes for Medicaid-eligible patients, or foster children, or the chronically homeless if someone isn’t willing to pay for them. Routinizing nonprofit leadership will fall short if we don’t routinize funder leadership as well.


At the beginning of this book, David Erickson imagines a future market for social outcomes that will “permit problem-solving ideas to come from every direction.” This market would be “inherently anti-monopoly, pro-local, and community-empowering.” It would also be adaptive and program-agnostic, like the three examples highlighted at the outset of this essay. By intentionally not picking winners, Congress, Diamandis, and GAVI were able to achieve their goals without gambling on the wrong solution. Their leadership was the act of handing over program-selection control to a market that selects on their behalf. They understood that markets can be useful tools when you aren’t sure if something is going to work. Framing the solution to poverty in market terms may seem counter-intuitive. After all, the market economy created many of the challenges we’re trying to address in this book. These concerns also extend to “privatizing” the social safety net. “There is no private-sector-based magic that will solve these critical needs,” cautioned Richard McGahey and Mark Willis at the conclusion of their chapter. This common view is rooted in a long history of neighborhood disinvestment and the economic marginalization of low-income communities by the private sector. But it also misses the mark.

The social safety net was privatized long ago. The 400,000 service nonprofits that currently comprise the social sector are nongovernmental.22 The real issue, I suspect, isn’t the privatization of the sector but more broadly a fear of the “private prison” scenario. Private prisons represent, for many people, the open-and-shut case for why we shouldn’t hand crucial government services over to the private sector. But the comparison fails to account for two significant distinctions: First, the private prison system is largely comprised of profit-driven companies, not mission-driven nonprofits; and second, it probably fingers the wrong culprit. Most private prison operators are paid based on how many beds they fill.23 But what if they were paid for reducing recidivism rates instead? Prison operators may focus more on rehabilitation and skill building. Prisoners may reenter their communities better prepared to succeed, leading to fewer reoffences. Long-term criminal justice outcomes may actually improve. The private sector isn’t inherently better or worse at delivering important services provided we’re mindful of the incentives that drive it.

Another commonly voiced concern about market-based solutions to poverty is the role financial institutions play. Peter Nadosy, the chairman of the Ford Foundation’s investment committee, echoed this recently in The New York Times: “Not to malign Wall Street, but when they smell a profit opportunity, you have to be careful.”24 Nevertheless, financing is often a necessary component of outcomes-based funding. In order to pay staff, run programs, and otherwise “keep the lights on,” nonprofits may have to appeal to a financial institution for up-front working capital. That financing may come from a private philanthropy like Ford, an impact investor, a community development financial institution, or even a bank. While outcomes-based financing is relatively new, it’s a natural extension of 40 years of community development lending and investing, which has produced millions of affordable housing units, in addition to thousands of health clinics, community centers, and schools, all located in historically underinvested neighborhoods.25

Still, for many people, financing social services just feels different from other types of financing. But it’s a distinction without a difference. The mortgage attached to an affordable housing building, for example, is paid back based on how well the housing performs: Unrented apartments, or unexpectedly low rents, and the project won’t generate enough cash flow to repay the loan. Outcomes-based financing, likewise, is repaid based on the nonprofit’s performance: Failure to deliver the specified outcome(s) and the nonprofit won’t be able to pay back its investor. In both cases, the financing is tied to how well the project serves its intended beneficiaries. Whether that’s through a real estate development or a social program should be immaterial.

Despite a veneer of efficiency, there is also a worry that markets can create unnecessary complexity and waste. This seems to be borne out in our early experience with Pay for Success: Projects take a long time, involve many partners, and cost more than a conventional service contract. Tamar Bauer and Roxane White’s observation, “If parenthood is the toughest job you will ever love, then Pay for Success may be the most grueling growth strategy we will someday celebrate,” seems to confirm this worry. But as LIHTC has proven, the complexity can be worth it. A performance-based guarantee allows for maximum provider flexibility and minimal funder risk. It can be a good tradeoff in cases of performance uncertainty. Likewise, the added expense of transaction structuring, evaluation, and cross-sector data management serves a purpose, which is to ensure a higher level of measurement and implementation rigor.

That said, for all the attention successful programs receive in an outcomes-funding context, less is paid to the program “losers” that have innovated and failed. It’s fair to ask: Shouldn’t the net benefit of a successful outcome factor in the cost of all the programs that tried but ultimately didn’t work? Given the potentially net-negative cost of producing a positive outcome, it can be tempting to first test promising programs with grants before going to scale. The flaw with this kind of accounting is that program-related innovations that fail aren’t sunk costs. The $100 million collectively spent competing for the Ansari XPRIZE wasn’t wasted. It became the foundation of a $2 billion private space industry. Contrast that with the substantial time and resources required to respond to grant requests from funders. That energy produces fundraising innovation, not program innovation. And if the grant isn’t secured, the effort that went into the grant application often becomes a sunk cost that doesn’t grow the organization or contribute to the field.

The biggest concern of all, though, is probably trust. Why should we trust a market mechanism to deliver better results than funders who are disciplined, evidence-based, and in tune with the needs of the communities they care about? This is the central question of this book. In my view, we depend too much on the leadership of funders — both government and philanthropic — to direct resources. Nonprofits shouldn’t have to convince funders that their programs are valuable in order to be funded. If the value is self-evident then their funding should be routine. A market for social outcomes — deployed through all the tools highlighted in this book — would be an adaptable, program-agnostic method of distributing resources based on value. But it requires that funders give up control over program selection. If they resist that role, a market for social outcomes will never materialize.

Eighty authors contributed to this volume, offering a range of perspectives on outcomes-based funding. Through all the diversity of opinion, one thing is clear: The sector’s shift to outcomes is as much a cultural departure as it is a technical one. “A paradigm shift toward results-based funding is a major analytical breakthrough. But its benefits can be realized only if we look at the number of rituals that need to change and make sure we balance strategy with culture in thinking about how to make those changes,” predicts Zia Khan.

The hardest part of this cultural transition will be getting comfortable with a different kind of leadership, both from nonprofits and their funders. In a market that values social outcomes, leadership will be routinized by a set of market conditions that identifies and rewards results. To skeptics, this may seem like letting the fox guard the henhouse. But a market is just a tool, a social compact that steers resources on behalf of society — an invisible hand attached to the body politic, so to speak.26 A market that values social outcomes would be no different, steering resources based on results. Those results may be guided by a market mechanism but what matters will still be up to us.

Thanks to my Federal Reserve colleagues David Erickson and Joselyn Cousins for their assistance with this chapter. The views expressed are my own and may not reflect those of the Federal Reserve Bank of San Francisco or the Federal Reserve System.

1 U.S. Environmental Protection Agency, “National Air Quality: Status and Trends of Key Air Pollutants” (last updated September 15, 2016), available at
2 Joe Nocera, “Obama’s Flexible Fix to Climate Change,” The New York Times (August 4, 2015), available at
3 XPRIZE Foundation, “Mojave Aerospace Ventures Wins the Competition that Started it All,” available at
4 Ibid.
5 Ruth Levine, Michael Kremer, and Alice Albright, “Making Markets for Vaccines: Ideas to Action,” Center for Global Development Advance Market Commitment Working Group (2005).
6 Defined as social safety net nonprofits. Lester M. Salamon, America’s Nonprofit Sector: A Primer, 3rd edition (New York: Foundation Center, 2012).
7 Nancy O. Andrews and David J. Erickson eds., Investing in What Works for America’s Communities (San Francisco: Federal Reserve Bank of San Francisco and Low Income Investment Fund, 2012).
8 Steven Goldberg, “Scale Finance: Industrial Strength Social Impact Bonds for Mainstream Investors,” Federal Reserve Bank of San Francisco (April 2017), available at
9 Uncited quotations in this essay refer to What Matters book chapters.
10 Claire Knowlton, “Why Funding Overhead is Not the Real Issue: The Case to Cover Full Costs,” Nonprofit Quarterly (January 25, 2016), available at
11 Ibid.
12 David Erickson, The Housing Policy Revolution: Networks and Neighborhoods (Washington, DC: Urban Institute Press, 2009), pp. 90–91.
13 James Heckman, “Invest in Early Childhood Development: Reduce Deficits, Strengthen the Economy,” The Heckman Equation (July 2013), available at
14 The term “stretch goal” refers to a difficult-to-achieve outcome, as described in James Radner and Jack Shonkoff’s essay “Mobilizing Science to Reduce Concentrated Poverty,” Investing in What Works (2012), available at
15 Melody Barnes, Remarks at Federal Reserve Healthy Communities Conference (Washington, DC: Federal Reserve Board of Governors, 2010).
16 David Erickson, Ian Galloway, and Naomi Cytron, “Routinizing the Extraordinary,” Investing in What Works (2012), available at
17 Ibid, p. 378.
18 Ibid, p. 382.
19 A reference to Langley Keyes’ book Strategies and Saints: Fighting Drugs in Subsidized Housing, as cited in Erickson, Galloway, and Cytron, “Routinizing the Extraordinary,” Investing in What Works (2012).
20 Ben McAdams, Salt Lake County (see Keele/Peters); Armond Budish, Cuyahoga County (see Merriman). There are other outcomes funders that deserve recognition for their leadership but space precludes naming them here.
21 Bill & Melinda Gates Foundation (see Levine); XPRIZE Foundation (see Bravo, Frangione, and Wander).
22 Salamon, America’s Nonprofit Sector: A Primer (2012).
23 In the Public Interest, “Criminal: How Lockup Quotas and Low-Crime Taxes Guarantee Profits for Private Prison Companies” (September 2013),,-In-the-Public-Interest,-9.13.pdf.
24 James B. Stewart, “Ford Foundation Is an Unlikely Convert to ‘Impact’ Investing,” The New York Times (April 13, 2017), available at
25 Erickson, The Housing Policy Revolution (2009), pp xii-xv.
26 Gary Gutting, “Why Conservatives Should Reread Milton Friedman,” The New York Times (September 26, 2013), available at