Catching up with MicroFinance

A while ago (May 28th) we discussed a paper that claimed to be the first randomized study proving microfinance did not seem to work . The conclusion of that was that such studies that the studies could not be definitive. Specifically:

"...more research is needed to determine what about microfinance works (or under what conditions), and when it does not."

This morning I had several follow ups cross my screen (thanks to Ryan Calkins and Twitter) that warrant an update on the May 28th post:

Hammer Blows or Pinpricks? Stories vs. Statistics in Microfinance | David Roodman's Microfinance Open Book Blog: "

"It’s been a tough season for the proposition that “microfinance is a proven and cost-effective tool to help the very poor lift themselves out of poverty and improve the lives of their families.” In May came a randomized trial of microcredit in Hyderabad finding no impacts on poverty 15–18 months out. In June came a paper challenging the leading older-generation studies that seemed to show that microcredit had cut poverty in Bangladesh in the 1990s. Now in July we have another randomized trial, of microcredit in Manila, also finding no impact on bottom-line measures of household welfare.

A couple of people, including Tim Ogden, have raised a good question with me in the last few days: What does this mean for microfinance? Has a myth been debunked? Is the whole movement about to implode in a ball of fire? More precisely, will this research perturb the dominant narrative about microfinance in the public mind, about microenterprise as a reliable ladder out of poverty?"

Roodman had written back in June a piece called "Why I Doubt Most Microfinance Impact Studies" in which rightly criticizes all of the studies on theoretical grounds. He begins by talking about studies about foreign aid helping or not helping and then explains that the same logic can be used on Microfinance studies.

"These studies were not randomized: no government has ever experimentally given lots of aid to some countries while randomly withholding it from others. One major shortcoming in these papers, which I defined in the post on which Asif commented, is data mining. Non-randomized studies are more prone to it. Another is the difficulty of going beyond correlation to prove causation....

All of these concerns apply to the academic studies done over the last two decades of the impacts of microcredit on families and businesses. "

So where does this leave us? Pretty much back where we started. Still waiting for definitive research but cautiously optimistic that by increasing the financing alternatives, the poor are made better off.

BTW I also recommend Oxford's Daniel Clarke comment to the recent Roodman post:



http://blogs.cgdev.org/open_book/2009/07/hammer-blows-or-pinpricks-statistics-vs-stories-in-microfinance.php#comment-219