Table 2: Aggregate Impact for All Sectors, After Three [Five] Months

||**Uganda**<br>**(UGA)**|**Ethiopia**<br>**(ETH)**|**Rwanda**<br>**(RWA)**|**Senegal**<br>**(SEN)**|**Eswatini**<br>**(ESW)**|**Guatemala**<br>**(GTM)**|**Albania**<br>**(ALB)**|**Ecuador**<br>**(ECU)**|**Montenegro**<br>**(MNE)**|**Costa Rica**<br>**(CRI)**|**Average**|
|---|---|---|---|---|---|---|---|---|---|---|---|
||||**Panel A**|**: As Percen**|**tage of Bas**|**eline, Afte**|**r a Three[**|**Five]-Mon**|**th Lockdow**|**n**||
|**CIT Revenue Loss**|22.2|29.4|24.7|37.4|15.8|51.2|34.4|35.1|38.4|60.2|34.9|
||[35.0]|[44.1]|[35.8]|[51.8]|[24.6]|[65.8]|[48.5]|[49.7]|[54.7]|[71.0]|[48.1]|
|**Payroll Tax Revenue Loss**|3.2|4.9|5.2|6.3|NA|8.9|3.9|5.4|7.4|11.1|5.8|
||[6.9]|[10.5]|[9.6]|[12.0]|NA|[18.1]|[8.5]|[11.3]|[14.8]|[20.6]|[11.7]|
|**VAT Revenue Loss**|11.0|12.0|11.9|10.2|10.3|13.6|9.0|11.2|12.5|13.6|11.5|
||[18.4]|[20.0]|[19.8]|[17.1]|[17.2]|[22.6]|[15.1]|[18.7]|[20.8]|[22.6]|[19.2]|
|**Increase in Firms’ Losses**|77.4|1.3|21.3|8966.5|48.3|117.8|100.8|172.0|86.1|1629.0|1122.0|
||[1642]|[27]|[389]|[164443]|[1120]|[2515]|[2418]|[3560]|[1765]|[31274]|[20915]|
||.|.|.<br>**Panel**|.<br>**B: As Perce**|.<br>**ntage of G**|.<br>**DP, After a**|.<br>**Three[Fi**|.<br>**ve]-Mont**|.<br>**h Lockdown**|.<br>|.|
|**CIT Revenue Loss**|0.9|0.4|0.1|0.7|0.5|0.8|0.6|0.8|0.5|1.0|0.6|
||[1.5]|[0.6]|[0.1]|[1.0]|[0.8]|[1.0]|[0.8]|[1.1]|[0.8]|[1.2]|[0.9]|
|**Payroll Tax Revenue Loss**|0.0|0.0|0.0|0.1|NA*|0.3|0.2|0.1|0.4|0.6|0.2|
||[0.1]|[0.1]|[0.0]|[0.2]|[NA]|[0.6]|[0.5]|[0.2]|[0.9]|[1.2]|[0.4]|
|**VAT Revenue Loss**|0.4|0.6|0.4|0.5|0.4|0.6|0.7|0.7|1.5|0.6|0.7|
||[0.7]|[1.0]|[0.7]|[0.9]|[0.7]|[1.1]|[1.2]|[1.2]|[2.4]|[1.0]|[1.1]|
|**Increase in Firms’ Losses**|0.8|0.8|0.7|3.9|0.4|5.3|1.6|2.1|3.8|9.4|2.9|
||[1.7]|[1.7]|[1.3]|[7.2]|[1.0]|[11.3]|[3.8]|[4.4]|[7.9]|[18.1]|[5.8]|
|**Total Tax Loss =**|1.3|1.0|0.5|1.3|0.9|1.7|1.5|1.6|2.4|2.2|1.5|
|**CIT+Payroll+VAT**|[2.3]|[1.7]|[0.8]|[2.1]|[1.5]|[2.7]|[2.5]|[2.4]|[4.2]|[3.4]|[2.5]|
|**Tax Losses + Firms’ Losses**|2.2|1.8|1.2|5.2|1.3|7.0|3.1|3.7|6.2|11.7|4.4|
||[3.9]|[3.4]|[2.1]|[9.1]|[2.5]|[13.9]|[6.3]|[6.9]|[12.0]|[21.5]|[8.2]|

Note: This table displays predicted tax revenue losses and the increase in firms’ losses, as a percentage deviation from the baseline (last year available in the micro data) in Panel A, and as a percentage change of GDP in the baseline year in Panel B. *Eswatini does not levy payroll taxes.

The third row provides an estimate of lost revenue from the VAT. While we do not work with VAT data directly, we simulate taxable value-added as sales minus material inputs.<sup>12</sup> Since firms adjust their material costs proportionally to the shock, our estimated drop in value-added is exactly proportional to the size and duration of the revenue shock. Annual VAT revenue drops on average by 12% (19%) of its baseline value. This leads to a 0.7% (1.1%) drop in tax revenue as a percentage of GDP on average across countries.<sup>13</sup> The fourth row of table 2 shows the increase in losses accumulated by firms over the year. The absolute

> 12In some countries, a share of the fixed costs—for example machinery—can be deducted from the VAT. Therefore our simulated value added might be too large. To account for this, we obtain the effective VAT rate as the tax rate which, when multiplied by our simulated value-added, equals the official VAT collection at baseline. The average effective VAT rate in our sample is 19%.

> 13The VAT loss calculation assumes that, when sales minus materials costs _<_ 0 in a particular month, the firm pays no VAT that month, but does not “carry forward” the difference between sales and material costs in month _t_ as a deduction in month _t_ + 1. As firms are normally allowed to carry forward negative value-added for some time, this is a simplification which may lead us to under-estimate the true VAT loss.

14