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Category: Impact Evaluation

A Nifty Fix for When Your Treatment Variable Is Measured with Error (Technical)

One of the advantages of having really smart colleagues — the kind who exhibit genuine intellectual curiosity, and who are truly interested in doing things well — is that you get to learn a lot from them.

I was recently having a conversation with my colleague and next-door office neighbor Joe Ritter in which we were discussing the possibility that the (binary) treatment variable in a paper I am working on might suffer from some misclassification. That is, my variable D = 1 if an individual has received the treatment and D = 0 otherwise, but it is possible that some people for whom D = 1 actually report D = 0, and that some people for whom D = 0 actually report D = 1.

When the possibility that my treatment variable might suffer from misclassification (or measurement error) arose, Joe recalled that he’d read a paper by Christopher R. Bollinger about this a while back. A few hours later, he sent me an email to which he’d attached the paper. Here is the abstract:

The Miracle of Microfinance?

This paper reports on the first randomized evaluation of the impact of introducing the standard microcredit group-based lending product in a new market. In 2005, half of 104 slums in Hyderabad, India were randomly selected for opening of a branch of a particular microfinance institution (Spandana) while the remainder were not, although other MFIs were free to enter those slums. Fifteen to 18 months after Spandana began lending in treated areas, households were 8.8 percentage points more likely to have a microcredit loan. They were no more likely to start any new business, although they were more likely to start several at once, and they invested more in their existing businesses. There was no effect on average monthly expenditure per capita. Expenditure on durable goods increased in treated areas, while expenditures on “temptation goods” declined. Three to four years after the initial expansion (after many of the control slums had started getting credit from Spandana and other MFIs), the probability of borrowing from an MFI in treatment and comparison slums was the same, but on average households in treatment slums had been borrowing for longer and in larger amounts. Consumption was still no different in treatment areas, and the average business was still no more profitable, although we find an increase in profits at the top end. We found no changes in any of the development outcomes that are often believed to be affected by microfinance, including health, education, and women’s empowerment. The results of this study are largely consistent with those of four other evaluations of similar programs in different contexts.

A new working paper (older, ungated copy here) by Duflo et al. The emphasis is mine.

This is consistent with another careful study (link opens a .pdf file) by Crépon et al. of the impact of microfinance in Morocco, where there authors also find that microfinance has no discernible impact on the usual development indicators (i.e., consumption, health, education, etc.)

To be sure, microfinance does appear to have some impacts, as the abstract above indicates — just not the miraculous impacts that are often touted by microfinance advocates.

Managing Basis Risk with Multiscale Index Insurance

That’s the title of my article with Ghada Elabed, Michael Carter, and Catherine Guirkinger, which was just published online in Agricultural Economics. Here is the abstract:

Agricultural index insurance indemnifies a farmer against losses based on an index that is correlated with, but not identical to, her or his individual outcomes. In practice, the level of correlation may be modest, exposing insured farmers to residual, basis risk. In this article, we study the impact of basis risk on the demand for index insurance under risk and compound risk aversion. We simulate the impact of basis risk on the demand for index insurance by Malian cotton farmers using data from field experiments that reveal the distributions of risk and compound risk aversion. The analysis shows that compound risk aversion depresses demand for a conventional index insurance contract some 13 percentage points below what would be predicted based on risk aversion alone. We then analyze an innovative multiscale index insurance contract that reduces basis risk relative to conventional, single-scale index insurance contract. Simulations indicate that demand for this multiscale contract would be some 40% higher than the demand for an equivalently priced conventional contract in the population of Malian cotton farmers. Finally, we report and discuss the actual uptake of a multiscale contract introduced in Mali.

The article discusses the index insurance contract my coauthors and I have developed for and sold to cotton producer cooperatives in southern Mali. The rest of this post is more technical, as it goes into the details of the two contributions I’ve highlighted above.