Before discussing impacts on other primary outcomes, it is useful to consider the size of these effects on total consumption, which are substantially smaller than the transfers received by beneficiary households. The treatment group, at a mean size of six at baseline, should be receiving around TRY720 per month, which is almost exactly what they report receiving on average during the past month at the 12-month follow-up.<sup>27</sup> However, the difference in the shares of the treatment and control groups reporting being ESSN beneficiaries is down to 44% by this time, meaning that the difference in transfer income between the two groups should be approximately TRY320 (720 x 0.44 = 317). Furthermore, the transfers may be crowding out earnings from working, making the net income gain even smaller in the treatment group. We do not have data on income from work for the first two follow-ups, but an additional question on total household income from working during the past month was asked at the 18-month follow-up. Reported household earnings were TRY118 higher in the control group (TRY1,280 vs. TRY1,161; p-value<0.01). Assuming this difference to be approximately the same at the 12-month follow-up leaves a net expected income gain of approximately TRY200 for the treatment group, compared with our point estimate of TRY100 for the value of treatment.

Hence, one year after baseline and the start of ESSN, we are unable to account for approximately TRY100 of the expected net income gain in the treatment group, which is less than 15% of the average transfer size to a beneficiary household.<sup>28</sup> This is based on the point estimate; confidence intervals imply that the unaccounted amount is between TRY50 and TRY150, while upper bound estimates of impact leave no unaccounted transfer income (Table 6, Columns 5-7). Reported savings are rare in this population and not differential across groups, therefore unlikely to account for the gap between our impact estimate and the expected gain in net income. One explanation, especially early on, is the possibility that treatment households purchased durable assets with the transfers – such as refrigerators, TVs, air conditioners, smartphones, and the like – which are not captured by our surveys.<sup>29</sup> Another possibility is that the aggregate expenditure categories in the phone survey (such as food, rent, utilities, and so on) did not fully capture the extent of the impacts on household expenditures. Specifically, total food expenditures can be substantially lower when households are asked to report them in collapsed categories rather than each food item separately. Furthermore, this underreporting can be differential

> 27 ESSN operations have been found to be carried out with relatively high implementation fidelity. Program records show that more than 99.5% of cash transfers to eligible beneficiaries were redeemed (World Food Program 2020). In addition, an external assessment of the program found that ESSN adequately disseminated information about the program and conducted efficient distribution of ATM cards and timely delivery of cash transfers (Oxford Policy Management 2018).

> 28 The unaccounted amount is approximately the same at the 18-month follow-up, but substantially higher at the 6-month follow-up, primarily because the eligibility gap between the two groups was larger early on.

> 29 One question was asked to households, to better understand access to communications and social media, on ownership of smartphones. Over the course of the 18-month study, the treatment group was 3.2 percentage points more likely (83.8% vs. 87%; p=value<0.01) to own a smartphone. Similar modest gains in asset ownership over a number of household durables could plausibly add up to explain a substantial part of the unaccounted transfer income. However, without data on these expenditures, this claim remains speculative. The study team added questions on asset ownership to the 24-month follow-up phone survey, which was interrupted by the pandemic and is not used in this paper.

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