open, such a program would impose no net present fiscal cost.<sup>18</sup> This number considers only the government’s revenue and therefore ignores any savings to the government on healthcare, as well as the large economic benefits to workers of the wages that they do not pay in taxes, and all non-economic benefits of better health. Of course, this result does not, itself, provide any advice to the Indian government about _how_ to reduce open defecation; nor would there be any effect on wages of spending government revenue on an unsuccessful sanitation program. However, our results indicate that public investments to change sanitation behavior and – reduce open defecation as well as investments in other mechanisms of reducing infant – mortality could improve well-being at a low net present cost to the government.

# **A Testing for Selective Migration**

One possible factor that could be responsible for our findings is selective migration. It would require a fairly complicated migration pattern: it would have to be the case that higher-skill individuals among the younger cohorts net migrate selectively into districts where the disease environment improved the most, or out of districts where the disease environment did not improve. Therefore, wages among young workers in improved districts would be higher not because of any causal effects of the improved disease environment but rather because they are naturally more skilled workers.<sup>19</sup> Fortunately, the IHDS includes data on migration, so we can test this hypothesis. The data report whether a particular individual moved since their birth, though we cannot see where they migrated from, so we are likely to overstate migration as many moves would be within the same district. We run the regressions of wages on IMR and sanitation only for stayers, by omitting all individuals who report ever having moved. The results are presented in Table 7, and the coefficients are nearly unchanged. Therefore, selective migration does not appear to be responsible for our results.

We can further test to see if there is any evidence for selective migration at all. We divide the sample into two halves, with all districts above the median improvement in IMR in our sample period in one half (“improved districts”) and all districts below the median in the other (“nonimproved districts”), and calculate total migrants in each half by age, smoothed over age using a local average. Then we examine the share of overall migrants going to improved districts by age. If selective migration was occurring, we might expect that a greater share of migrants would be found in improved districts among the younger cohorts, but in Figure 6 we see that, if anything, the opposite has actually occurred, with a general tendency towards a smaller fraction of migration to improved districts among younger workers.

Next, we also divide our population into two halves: we regress wages on year-of-birth and district fixed effects, and place all individuals with above-median residuals in one half and those below the median in the other, as a proxy for high- and low-skill groups. We then ask: has there

> 18Indeed, the government would make money if a successful program were less expensive than this!

> 19Alternatively, and more likely since the districts with the biggest improvements in IMR and sanitation tended to be districts with worse disease environments and lower wages both before and after our sample period, we would have a problem if older high-skill workers net migrated to districts that did not see significant improvements in disease environment.

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