(2018).<sup>16</sup> We assume a factor of informality on goods that incur VAT of 0.5<sup>17</sup> , estimated exogenously to the model.<sup>18</sup>

# 3.4.4. Water Subsidies

Water users are identified as those households in the survey that report using a publicly provided water source – that is, households that receive either piped water into the yard or dwelling or have access to public taps or a public borehole. Water tariffs are not directly subsidized, but the Rural and Urban Water Supply program provides (to the utility operators) a fixed, on-budget sum annually that is meant to cover network maintenance, investment, and upgrading costs. We assume that without this budget support, utility operators would raise prices so that total revenues collected privately covered these costs as well. For these programs, we allocate the total (scaled) expenditure on these programs according to the urban and rural water users’ share of reported urban and rural water consumption, respectively.

# 3.4.5. Agricultural Input Subsidy

The survey does not identify recipients of free agricultural inputs. We turn to Uganda’s National Service Delivery Survey (NSDS) 2015 to generate a propensity score for acquiring subsidized inputs conditional on being a small-scale crop farmer or livestock farmer. We predict that same propensity score within a similar pool of UNHS households and select UNHS households with the highest propensity scores until the proportion of subsidy beneficiaries in the UNHS (out of the pool of small-scale farming households in the UNHS) matches the proportion of subsidy beneficiaries in the NSDS (out of the agricultural-inputpurchasing pool of households in the NSDS). Given the technique we use to allocate agricultural input expenditures, this allocation can be described as the expected allocation of expected benefits available under the inputs program. We then divide the total scaled expenditure on the program by the total number of simulated recipients to get a per-household subsidy.

# 3.4.6. In-kind Subsidies

Uganda’s expenditures on education and health are allocated to those households that report using the public education or public health care service system (respectively). The subsidy amount imputed was obtained by scaling the in-kind spending divided by the total number of UNHS users in order to get a “per student” or “per patient” cost. An individual’s user fee is then subtracted from this average cost amount

> 16 The approach also distinguishes between domestic and imported products, as the price of imported inputs is not affected by unrecoverable _domestic_ input VAT. This method is not directly comparable to the approach used in 2012/13, in the following ways: in 2012/13 indirect effects of VAT were not included in the calculation, VAT on imports was excluded, and it was assumed that 50 percent of domestic VAT comes from households, and the rest from NGOs and exempt producers.

> 17 This is in contrast to the standard Harris et. al (2018) methodology which estimates an endogenous rate of informality.

> 18 We assume this level of informality, as it is consistent with the fact that informality accounts for about one half of the national output (https://www.citiesalliance.org/sites/default/files/PB_Uganda_WEB.pdf) and the proportion of informal firms reaches 45 percent (UBOS 2018).

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