One way to tell GiveDirectly’s story is thus as a bellwether for evidence-based decision-making. To win over skeptics we invested heavily, as I will describe, in causal evidence. And we benefited from the growth around us of an ecosystem that took that evidence seriously. If even a nutty idea like giving away money for nothing could survive and thrive in this environment, this bodes well for other efforts to elevate evidence over anecdote.

But there is more to it than that. Part of the point was to provoke questions not just about how to spend development dollars, but also about who should spend them. Questions, that is, about the allocation of power and not just its optimal exercise. From this point of view it was not so obvious what role program evaluation should play. If the money really is for nothing—free not just of strings, but of any particular sought-after result—then what exactly should one evaluate?

Experimental research can, in fact, still be useful even in this regard. It can because of a key difference between experiments in the social as opposed to the physical sciences. When Sir Ronald Fisher pioneered experimental methods at the Rothamsted Experimental Station, one of the world’s oldest centers for agricultural research, in order to figure out which fertilizers or seeds worked best, his “subjects” had no ethically significant agency: they were plants. But the subjects in a cash transfer experiment do. When a researcher documents the choices they make, we learn something about their preferences, their priorities, their vision of a good life. These insights have no analogue in a purely technical matter like agriculture productivity. And they have been an essential part of the story.

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The question was whether we needed to produce that evidence ourselves. Governments in South and Central America were already running large conditional cash transfer programs and, in many cases, measuring their effects using randomized controlled trials (RCTs). The results as we read them were broadly “positive” in that recipients spent money on reasonable-seeming things—investment as well as consumption, for instance—and that various indicators of well-being improved. Indeed, this evidence was one of a few things that had convinced us to begin in the first place. Would yet another RCT really be any more convincing?

We ultimately decided to run one as a matter of principle. Any non-governmental organization (NGO) asking for donations ought, we felt, to run an RCT if it could, as a sort of due diligence. Running one would be a statement of intent. It would show that we planned to do things the right way, and not market the idea on the basis of cherry-picked success stories.

It almost didn’t happen, even so. It almost died in—of all places—ethics review: Harvard’s Institutional Review Board worried that giving people money might harm them. This put us in a Catch-22: we had to argue that transfers would not have bad effects in order to justify a study to find out what effects they would have. Eventually, after months of delay, we prevailed.

It was worth the struggle. Transfers turned out to have a variety of positive effects, from reducing malnutrition to stimulating business investment to enabling people to build more durable homes. They did not increase spending on “temptation goods” like alcohol or tobacco. The study documenting these impacts has been influential among economists (cited nearly 1,900 times). And it has been influential for GiveDirectly—helping to earn a series of top charity recommendations from GiveWell, for instance.

So we carried on. At this time, we’ve completed or initiated 24 RCTs. We’ve come to see conducting—and not just citing—experimental research as a core strategy. It differentiated us. And it let us fuse research with direct impact to create an attractive risk-return profile. Worst case, your money substantially improves the lives of some very poor people. Best case, the evidence this yields also changes other people’s minds.

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We’d chosen to focus on making a few big payments for three reasons. One was the descriptive evidence that accumulating lumps of capital is otherwise hard for people near the poverty line. This makes it hard to start a business or make other productive investments, because these often require a large lump-sum purchase. A large transfer also enabled these larger purchases. Another was that they earn higher rates of return on their investments—in small businesses, agricultural inputs, housing, and so on—than we do when we keep the money in a bank or brokerage account. This means that keeping money on our books while we wait to transfer it to them is inefficient. And a third, perhaps reflecting the first two, was that when we asked people what they preferred, they almost all wanted lump sums. Yet for all that, we had never convincingly compared the impacts of the two. When we did, the results surfaced a lot of interesting economics—including the fact that UBI recipients often formed savings clubs to “reverse-engineer” their streams of small payments back into lumpier ones.

In short, setting out to solve what Bush might have called applied problems has often led to more basic scientific insights. As a result GiveDirectly studies have published in many of the top economics journals—including (if the names mean anything to you) the American Economic Review, Econometrica, Review of Economic Studies, and Quarterly Journal of Economics—even though in no case was publication in a top journal the goal.