The Way to Help the Poor by Dean Karlan

You can't make money without money. That was the exciting and intuitively obvious idea behind microloans, which took off in the 1990s as a way of helping poor people out of poverty. Banks wouldn't give them traditional loans, but small amounts would carry less risk and allow entrepreneurs to jump-start small businesses. Economist Muhammad Yunus and Bangladesh's Grameen Bank figured out how to scale this innovation and won the 2006 Nobel Peace Prize for their work.

The trouble is that although microloans do have some benefits, recent evidence suggests that on average they increase neither income nor household and food expenditures—key indicators of financial well-being.

That a program could be celebrated for more than 20 years and lavished with money and still fail to help people out of poverty underscores the paucity of evidence in antipoverty programs. Individual Americans, for instance, spend $335 billion a year on charity, yet most people give on impulse or a friend's recommendation—not because they have evidence that their giving will do any good. Philanthropies also often give money to projects without really knowing if they are successful.

Fortunately, we are living in the age of big data: decisions that used to be made on instinct can now be based on solid evidence. In recent years social scientists have begun to marshal the tools of big data to ask the hard questions about what works and what doesn't. The goal is to turn philanthropy into a science, where money gets directed to programs for which there is strong evidence of their effectiveness.