with it, conditional on other observed characteristics. Both these factors suggest that the omission of controls may have biased demand upwards in arm C, although the point estimates remain very close.

The coefficient estimates for the controls in column 2 cannot be interpreted causally, but it can be noted that beliefs about the safety status of the well strongly predict demand: well owners thinking that their well is safe had little to gain from buying a test, and indeed they were 12 percentage points less likely to purchase the test (p-value _<_ 0 _._ 01). The belief that the water was _unsafe_ also decreased the probability of purchase, although by less than half as much ( _β_<sup>ˆ</sup> = _−_ 0 _._ 049, p-value _<_ 0 _._ 01). This is overall consistent with the conceptual framework, where it was highlighted that a key factor for willingness to pay for the test is that its result will provide new information.

# **5.2 Test Results**

Although the purchase rate was low, the intervention generated a large increase in the number of tested wells in Sonargaon. Before looking at the responses to the information made available by the tests, it is useful to first describe such information. The test results are summarized in Table 3, which also includes the detailed figures on switching behavior that will be described later, and so the statistics are calculated for the 10,412 households (91.3% of the total) that could be tracked in the endline survey. Of these, 2,417 purchased tests during the intervention.

Overall, 19% (455/2417) of the tested wells which had been used for cooking and drinking at baseline had unsafe arsenic levels relative to the national standard of 50 ppb.<sup>16</sup> Recall that these results are _conditional on demand_ so that the randomization across treatments does not guarantee similar distributions across arms, even in large samples. However, the distribution of arsenic was overall similar between arms A and B, the two largest arms. Arm C had more unsafe wells (27%, versus 19 and 16% in arms A and B, respectively), although the null of equality among these three arms cannot be rejected at standard levels (p-value= 0 _._ 32). Consistent with the existence of a degree of awareness about arsenic risk, at baseline group C was by far the one with the smallest fraction of respondents thinking that their well was safe, although the fraction believing that the well was unsafe was fairly similar between groups, see Table 1. The larger share of unsafe wells in arm C may thus have been the result of lack of balance at baseline arising by chance, possibly due to the small number of clusters (15) in this treatment arm.

Overall, at the time of the endline survey, of all the wells found to be unsafe, 30% had at least one well identified as safe within 25 m after the testing, 57% had at least one within 50 m, and 78% had at least one within 100 m. This confirms that, in principle, switching to a nearby safe well was a feasible

> 16The prevalence of unsafe wells was much lower than the 40-90% observed at the time of the BAMWSP testing campaign, about 10 years earlier. This is consistent with a degree of learning over time about local arsenic risk and how to avoid it, in particular by digging deeper wells, more expensive but perhaps made more affordable by economic development. Indeed, the data indicate that a majority of wells were of recent construction and were deeper than the older ones. The data also show that the beliefs about the safety of their well water among the minority of respondents who reported to know it were strongly correlated with actual test results. Detailed results for these findings are available upon request from the authors.

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