patterns, here we only consider the mobile direct deposit treatment versus the control.<sup>48</sup> Across most outcomes, we find no detectable heterogeneity in the treatment effects. This suggests that treatment gains, where we find them, tend to be spread evenly across the population. However, we do detect heterogeneity in two important dimensions: consumption as well as our key learning outcomes. Recall that a decrease in consumption is indicative of new savings, rather than a reallocation across formal and informal accounts. Total transactions indicate the level of worker engagement with their accounts, and direct transactions indicate efficient usage of the mobile technology, avoiding illicit fees, an outcome of direct relevance for consumer protection.

Finally, in Table 8, we present a CLAN analysis to better understand which individual traits are associated with the largest impacts on new savings and learning. The first column pertains to the heterogeneity with respect to the effects on total consumption, while columns (2) to (4) pertain to the learning impacts – total transactions, outside transactions, and direct transactions.<sup>49</sup> Interestingly, we find that the results split our sample into “savers” and “learners” – the traits that are correlated with a large, negative consumption response are often the same traits that predict a smaller learning response and vice versa. Females, and workers with low baseline control over expenditures, low levels of savings, and low levels of prior financial experience are more likely to be classified in the group which has the largest decline in consumption. This implies that the treatment enables new savings out of consumption for those individuals who were previously most severely excluded from the formal financial system either through gender norms, spousal sharing restrictions, basic access, or knowledge. In contrast, men, non-parents, workers with more education, and workers with higher levels of savings, or baseline financial inclusion are more likely to be classified into the group with the largest “learning-by-doing” treatment responses. This suggests that learning-by-doing is most effective for those who have some prior exposure to financial products and higher ex ante levels of financial control and literacy.

Taken together, the results suggests that the treatments have two different sets of impacts on the “savers” and “learners.” For those with previously low levels of financial inclusion, the treatments give households access to a safe, convenient, and individually-controlled place to save, which leads treated workers to decrease consumption in order to fund savings. However, learning by doing may not be enough for these individuals to solve important consumer protection problems on their own. More far-reaching interventions may be needed.

In contrast, for those with higher baseline rates of financial inclusion, the treatment does not change the extensive margin of consumption versus savings, but does encourage workers to engage more deeply with the new technology. For these workers, engagement with the account has large impacts on avoiding illicit transaction fees, indicating substantial consumer protection gains from learning through active use of accounts.

> 48Appendix Table D.15 presents the CATE analysis for the same set of outcomes.

> 49Note that the most affected group is the one with the largest absolute treatment effect. In the case of consumption, the least affected group is that with the most negative consumption response.

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