1. Microcredit Impact: One way to judge the impact of microcredit is randomizing access. Another way is to see what happens when microcredit is suddenly taken away. There are two new papers that use the latter approach based on the sharp reduction in lending that ensued from the Andhra Pradesh crisis in 2010 (has it really been that long ago?) by Emily Breza and Cynthia Kinnan, and Banerjee, Breza, Duflo and Kinnan. BK find decreases in wages, wage earnings and consumption concentrated among poorer borrowers when microcredit goes away. BBDK find sharp heterogeneity in effects on "gung-ho" entrepreneurs and "reluctant" entrepreneurs of access to and then loss of access to microcredit. Of course, that leaves the question of the underlying differences between gung-ho entrepreneurs and reluctant entrepreneurs. Could it be aspirations? You should ask Stefan Dercon or Bruce Wydick about that.
2. Income Volatility: This week, the Aspen Institute launched the website for the Emerging Prosperity Impact Collaborative, an ongoing effort to draw attention to emerging economic issues that affect household financial security in the United States. The first year is focused on income volatility, inspired in part by the US Financial Diaries. EPIC has an overview paper, some cool data viz, and videos (some better, some worse) of researchers and practitioners discussing income volatility and its effects.
3. On-Demand Debt Traps?: Income and expense volatility create challenges of illiquidity. An obvious approach to that problem is more frequent access to pay (though it has some concerning behavioral drawbacks). Uber is trying that. But more frequent access to pay may not provide the lump sums necessary--short-term credit is another approach. Now Uber is trying that too. But the terms and conditions, and the people the credit is being offered to, seem pretty likely to pull in the naive and trap them in debt. While there is good reason to be skeptical of Uber's approach to finance, it has been rightly praised for fighting racial discrimination by both drivers and customers. AirBnB not so much--it's being sued for not taking action even when racial discrimination is obvious.
4. Suckers Games: Speaking of behavioral drawbacks, a key behavioral insight is limited attention. That's led to lots of experimental interventions in two orthogonal directions: using defaults so that people don't have to pay attention, and attempts to get people to pay attention to the "right" things at the "right" time. This past weekend I was at IPA's researcher gathering on Advancing Financial Inclusion, where new papers on work with digital finance, attention and defaults in Afghanistan, India, the Philippines and the UK strengthened my priors: trying to capture attention is a sucker's game. (yes, that's a lot of papers, but they are good papers and you should at least read the abstracts).
5. Microfinance Investment: While we in the research world tend to obsess over measures of microfinance impact, the "real world" chugs on. In recent weeks, two Indian MFIs have had successful IPOs, Ujjivan and Equitas, both attracting substantially more investor interest than they could accommodate (it really has been that long since the AP crisis). Meanwhile, Daniel Rozas looks at the inexorable growth of microfinance in Cambodia which increasingly looks like the next overheated market. I'm getting conflicting signals--I hear about a dramatic decrease in investors' interest in microfinance but I'm also seeing evidence of continued flows. What are you hearing or seeing?
Bonus Updates:
Our Algorithmic Overlords: (Are you noticing a theme?) Zeynep Tufecki writes in the NYTimes about the "real" bias in Facebook's algorithms, while Mullainathan et. al. find that using machine learning can improve hiring decisions for police and teachers.
A new approach to measuring financial inclusion via BBVA Research
