Esther Duflo (economics, MIT) just gave a talk here at the School of Social Work, on “political reservations” for women and minorities–that is, electoral rules that set aside certain political offices for women and ethnic minorities. Different countries have different laws along these lines, for example reserving some percentage of members of a legislature for women.

An almost-randomized experiment in India

Duflo talked about a particular plan in India which reserved to women, on a rotating basis, one-third of Village Council head positions. Each election (elections are held every five years), a different one-third of the villages must elect women leaders. (There was also some reservations for ethnic minorities but she did not go into detail on that in her talk.)

Duflo’s findings

Duflo and her colleagues took advantage of the fact that this system is a “natural experiment,” with an essentially random 1/3 of the villages being selected for the treatment each year. They compared the “treated” and “control” villages using data from a national survey to assess the quality and perceptions about public services in the villages. The survey also included objective measures of the quality and quantity of the services (water, education, transportation, fair price shops, and public health facilities). These objective measures were crucial because they allowed the researchers to distinguish between perceptions and reality.

They found that, on average, the quantity and quality of the services were higher in the villages whose leaders were restricted to be women. There’s a lot of variation among villages, and as a result the average differences are not large compared to the standard errors
(the avg difference in quantity of services is 1.9 se’s away from 0, and the avg difference in quality of services is 1.5 se’s away from 0). So they’d be characterized as “suggestive” rather than “statistically significant,” I’d say. Nonetheless, it’s interesting to see this improvement in performance. Because the treatment was essentially randomized (every third village on a list was selected), it would seem reasonable to attribute these changes to the treatment and not to unmeasured observational factors.

OK, so far so good. But here’s something else: they also compared the satisfaction of survey respondents in the villages. On average, people in the villages that were restricted to be headed by women were less satisfied about the public services. This also was barely “statistically significant” (people were, on average, 2% less satisfied, with a standard error of 1%) but interesting. Duflo cited a bunch of papers on biased judgment which suggest that people may very well judge women to be poor leaders, even if they outperform men in comparable positions.

Thus, it seems quite plausible from the data that reserving leadership positions for women could be beneficial–even if the people receiving these benefits don’t realize it!

Some statistical comments

As Duflo emphasized in her talk, the #1 reason they could do a study here was that the “treatment” of reserving political spaces for women was essentially randomly assigned across villages. Random assignment is good, also assigning across villages is good because it gives a high N (over 900).

There are a couple ways in which I think the analysis could be improved. First, I’d like to control for pre-treatment measurements at the village level. Various village-level information is available from the 1991 Indian Census, including for example some measures of water quality. I suspect that controlling for this information would reduce the standard errors of regression coefficients (which is an issue given that most of the estimates are less than 2 standard errors away from 0). Second, I’d consider a multilevel analysis to make use of information available at the village, GP, and state levels. Duflo et al. corrected the standard errors for clustering but I’d hope that a full multilevel analysis could make use of more information and thus, again, reduce uncertatinties in the regression coefficients.

References

Duflo’s papers on this are here and (with Petia Topalova) here and (with Raghabendra Chattopadhyay) here.