Orefice (2019) and are assumed to be constant. For each country, results are aggregated using weighted averages with weights equal to the share of imports of a certain product over total food imports.

# **6. Sensitivity**

In this section, we perform two sensitivity analyses. First, we use a different set of import demand elasticities from Kee and Nicita (2020) to assess the impact of changes in export supply on food prices. Second, we consider different scenarios of the initial shock that Covid-19 and containment policies could have on food export supply. For those scenarios, in turn, we recalculate the impact on world food prices with no trade policy intervention and with uncooperative trade policies.

Estimates of trade elasticities tend to vary across different studies due to different methodological approaches. Hence, as a first sensitivity test, we calculate the impact of the export supply shocks on world food prices with the elasticity estimates from Kee and Nicita (2020) and compare the findings at the aggregate level and at the food category level with the results based on the elasticities from Fontagné et al. (2019). The Kee and Nicita (2020) elasticities are estimated for a group of 40 countries, which makes it less suitable for the purpose of this exercise. But differently from the Fontagné et al. (2019), which are estimated at the product level, the Kee and Nicita (2020) elasticities are estimated at the bilateral-product level.

The results for the baseline scenario in Section 5 are reported in Table 4. Under this different set of elasticities, the impacts of the Covid-19 shock and of escalating export restrictions on food prices are significantly larger compared with the findings in Section 5. In particular, the average effect on food prices of escalating export restrictions is 39.1 percent with the Kee and Nicita (2020) import demand elasticities compared to 12.9 percent based on Fontagné et al. (2019). At the food category level, the results can be quite different. For fresh fruits and vegetables, the finding that escalating restrictions would lead to limited price increases is reversed and the estimated price increase is up to 71.0 percent (as opposed to 4.5 percent with the elasticities from Fontagné et al. (2019)). In addition to the different sample of countries and methodology used in the estimation, this finding is telling of the possible underlying economic mechanism. The Kee and Nicita (2020) elasticities capture that it could be difficult in the short term to substitute away from certain sources of imports when producers are hit by a shock, thus leading to larger price increases. This effect may be larger for certain food products, for instance as they are perishable as in the case of fresh fruits and vegetables.<sup>17</sup>

**Table 4: Price effects of Covid-19 under different trade policy scenarios using different import elasticities (percentage change)**

||**Price effect using product level elasticities from**<br>**fontgane et al (2019)**|**Price effect usi**|**ng product level ela**<br>**and Nicita (2020**|**sticities from Kee**<br>**)**|
|---|---|---|---|---|
||**i. Covid-19 shock**<br>**ii. Export**<br>**restrictions**<br>**iii. Retaliation**|**i. Covid-19**<br>**shock**|**ii. Export**<br>**restrictions**|**iii. Retaliation**|
|Cereals|4.9<br>9.9<br>16.1|12.1|25.9|44.4|
|Dairy and eggs|2.2<br>4.4<br>7.8|2.5|4.8|8.4|

17 This insight is similar to the finding in Kee (2020) that the supply shock in China leads to larger price effects for products that are inputs into global value chains, as they are likely to have less elastic import demands.

15