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Field
Secondary Outcomes (End Points)
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Before
Union Parishad Chairman
-Arsenic understanding (after using the application–before the app is shared will be used for heterogeneity)
-Self-described motivations for final allocation
-Average levels of household wealth, education, and other observable characteristics in the mauzas chosen by the union leader
-Average level of arsenic in the mauzas chosen by the union leader
-Arsenic level of the mauzas in the wells chosen by the union leader
-Average level of population density in the mauzas chosen by the union leader
-Proxies for political gains from, and political pressure for, well allocations
-Choice of the union leader's own mauza
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After
-Arsenic understanding (after using the application; the pre-app measurement in the website arms will be used for heterogeneity)
-Self-described motivations for the final allocation
-Average level of arsenic in the mauzas chosen by the union leader
-Average levels of household wealth, education, and other observable characteristics in the mauzas chosen by the union leader
-Average level of population density in the mauzas chosen by the union leader
-Proxies for political gains from, and political pressure for, well allocations
-(Well-level outcomes) Choice of the union leader's own mauza and the expected arsenic contamination levels of a well in the chosen mauzas
-Transformations of the primary outcome: unnormalized benefit, order-weighted score, and top-choice score
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Field
Secondary Outcomes (Explanation)
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Before
Union leaders’ understanding of local arsenic contamination will be measured by asking engineers to rank three mauzas based on their well-water arsenic contamination levels, and then computing the Kendall’s tau metric using true ranking. The understanding will be measured once for unions that do not receive the website, and twice for union leaders that do receive the website intervention (once before, once after, for the same pool of mauzas).
Self-described motivation for preferred allocation will be collected immediately following the solicitation of preferred allocation, where the leaders will be asked an open-ended question on what motivated their choices.
Average level of arsenic in the mauzas chosen by the union leader is the (potentially population-weighted) average of well-water arsenic contamination in the mauzas selected by the union leader for the DPHE well allocation. The individual well-level arsenic contamination % will be also obtained using the mauza-level arsenic contamination rate.
Average levels of household wealth, education, and other observable characteristics will include (population-weighted) average of (proxies) of household wealth, education, sectoral employment (agricultural/industry/service), religion, and other observable characteristics. The data for this will be obtained from the most recent census of Bangladesh, conducted in 2022 by the Bangladesh Bureau of Statistics (BBS).
Proxies for political gains and political pressure from, political pressure for, well allocations will refer to polling station-level vote margins (in favor of the incumbent BNP (Bangladesh Nationalist Party) and voter turnout in the most recent national election, the first election after the July Student Uprising of 2024. The polling station’s location will be matched with mauzas to obtain mauza-level estimates of vote returns and voter turnout. The polling station-level returns may be difficult to obtain in practice, in which case we will use upazila-level election results as a potential driver of heterogeneous treatment effects.
Choice of the union leader's own mauza is the indicator variable of whether the any of the wells (or individually chosen wells) is placed in the mauza inhabited by the union leader himself. The union leader's residence mauza will be elicited in the survey.
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After
-Arsenic understanding. Union leaders' understanding of local arsenic contamination will be measured by asking them to rank three mauzas from their own union (a preloaded high/middle/low contamination triple) by well-water arsenic contamination, and computing Kendall's tau against the true ranking. The mauza pool is restricted to mauzas tested in the ARRP campaign, so the truth is measured rather than imputed. With three items, tau takes four values (−1, −1/3, 1/3, 1); we therefore also report two coarser binaries: an indicator for the ranking being exactly correct, and an indicator for correctly identifying the most contaminated of the three. Understanding is measured once (after elicitation) for union leaders who do not receive the website, and twice for those who do (once before and once after the website is introduced, on the same triple). The post measurement, which exists in all four arms, is the secondary outcome; the pre measurement, which exists only in the website arms, is used as a heterogeneity dimension rather than as a covariate.
-Self-described motivations. Immediately after the preferred allocation is elicited, union leaders are asked an open-ended question on what considerations entered their choices. Responses are coded into a fixed taxonomy: applicant need, water quality, village-level equity, opinions of elected representatives, opinions of unelected elders, own constituency, and other (additional categories may be added depending on responses). Each category yields an indicator; the water-quality indicator is of primary interest, since it tests whether the treatments change the stated objective and not only the chosen allocation. We report the indicators separately and as a standardized index.
-Average level of arsenic in the chosen mauzas. The (population-weighted) average of well-water arsenic contamination rates across the mauzas selected by the union leader for the DPHE well allocation, using ARRP field-kit readings recalibrated against DPHE laboratory analysis and, for untested mauzas, the random-forest downscaling model. This outcome drops the families-served weighting and within-union normalization of the primary outcome, isolating the contamination margin from the size margin. Individual well-level arsenic contamination will also be obtained from the mauza-level rate.
-Average levels of household wealth, education, and other observable characteristics. Population-weighted averages across the chosen mauzas of proxies for household wealth (e.g., household structure type), educational attainment, sectoral employment (agriculture/industry/services), religious composition, and other observable characteristics, from the 2022 Population and Housing Census of the Bangladesh Bureau of Statistics (BBS). These are the principal evidence on the distributional incidence of the treatments: because arsenic contamination and poverty are not strongly correlated, improved arsenic targeting may redirect wells away from poorer mauzas.
-Average level of population density. Population-weighted mean density of the chosen mauzas from the 2022 BBS census. Read alongside the average-arsenic outcome, this decomposes movement in the primary outcome into a contamination component and a population component.
-Proxies for political gains and political pressure. Polling-station-level vote margins in favor of the incumbent BNP (Bangladesh Nationalist Party) and voter turnout in the most recent national election (the first after the July 2024 student uprising), matched to mauzas via polling-station location and averaged across the four chosen mauzas. This tests whether arsenic-based targeting displaces politically based targeting. If polling-station returns cannot be obtained, we will use upazila-level election results as a driver of heterogeneous treatment effects rather than as an outcome, and will state which is being reported.
-(Well-level outcomes) Choice of the union leader's own mauza and the expected arsenic contamination levels of a well in the chosen mauzas. An indicator for whether any of the four named wells is sited in the mauza in which the union leader resides, elicited pre-treatment in the characteristics battery. We also report the analogous indicator for the union leader's childhood mauza, the count of named wells falling in either, and the indicator restricted to the first-named well. Because the leader's own mauza may itself be high-arsenic, the indicator is additionally reported separately for leaders whose own mauza is above versus below the union median contamination, distinguishing targeting from self-dealing that happens to look like targeting. We will also use the average contamination levels of wells in the chosen mauzas to obtain a well-level estimate of expected arsenic levels for each chosen well.
-Transformations of the primary outcome. (a) Unnormalized benefit: the raw number of arsenic-exposed families reached by the four named wells, in levels and in logs. This is the quantity of interest to a public-health planner and the natural scale for national-level extrapolation; it is not the primary outcome only because its across-union variance is dominated by the choice set. (b) Order-weighted score: the primary score recomputed with the first- through fourth-named wells weighted 4, 3, 2, 1, with the attainable maximum and minimum renormalized using the same weights. Because order is payoff-irrelevant under the lottery device, any treatment effect on this score beyond the effect on the unweighted score is informative about how the leader ranks, not only which set he names. (c) Top-choice score: the normalized score of the first-named well alone, which isolates the single choice least contaminated by list-completion behavior.
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