**<u>Table 4.2: Share of oil in exports and revenues, selected countries, 2010-13</u>**

|Country<sup>*/</sup>|Share of oil exports in total|Share of oil revenues in total|
|---|---|---|
|Cameroon|0.53|0.25|
|Chad|0.86|0.66|
|Congo, Rep. of|0.73|0.75|
|Nigeria|0.82|0.68|

*/ We do not consider other SSA oil-exporting countries, such as Gabon or Angola, because they are upper middle income and no DSA has been recently produced.

Source: World Integrated Trade Solution (WITS) and country DSAs.

Overall, as expected, the results show a protracted deterioration in all debt burden indicators vis-à-vis the original baseline in both scenarios, with Cameroon being the country showing the smallest differences with the baseline and Nigeria the largest (see Annex Tables 4A and 4B). Also as expected, among the solvency indicators the PV of debt-to-exports and the PV of debt-to-revenues ratios show the largest differences with the baseline. However, the liquidity indicators – debt service to revenue and to exports ratios – show large differences with the baseline only in the case of Nigeria. The PV of debt-to-GDP ratio also shows a large difference vis-à-vis the baseline in the case of Republic of Congo.

Deterioration in the risk of debt distress classification could be warranted in the case of Nigeria, a low risk of debt distress country according to the latest DSA, where the new scenarios lead to several large breaches of the thresholds – albeit not always protracted. Although the same happens with Chad, a downgrade could not be possible as the country – according to the latest DSA – is already classified as high risk of debt distress. In the case of Republic of Congo a downgrade is possible but would require a deeper analysis, while Cameroon should remain as low risk.

In summary, with the exception of Cameroon which has the lowest shares of oil in total exports and revenues, SSA oil exporters are significantly affected by the drop in oil prices as their debt burden indicators deteriorate significantly.

# **4.4 A sluggish recovery in Europe and lower growth in China**

Similar to the results above, in this subsection we present the results of a simulation exercise that models the effects on SSA exports of the slowdown in China’s growth and the sluggish recovery in Europe. For this purpose we first measure each country’s share of exports to China, Europe and the SSA region.<sup>15</sup> Taking a minimum cut-off of 15 percent, we divide the SSA countries into three groups according to which market receives the largest share of their exports (if none of the three markets reach the minimum of 15 percent, the country is excluded from the exercise). The classification, shown in Annex Table 5, leads to a sub-sample of 24 countries among our 33 DSA sample. The main export market is the Euro Zone, the SSA region and China for half, one-third and one-sixth of the sub-sample, respectively.

The shock consists of applying a lower growth rate on exports destined to the main export market starting in 2015. The new growth rates are 1.01 percent for exports to the Euro Zone, 6.5 percent for exports to China and 1.11 percent for exports to the SSA region. These rates were chosen to reflect the lowest growth of imports observed in Europe and China in the post-crisis years, while for SSA it is the average of the same rates weighted by the share of exports from SSA to Europe and China (0.193 and 0.141, respectively). The exercise then assumes that the increasing external financing gap in the current account is covered from

> 15 Using IMF and WDI data we calculate the average share over 2005-2013, although periods may differ among countries if country data is not available in all years.

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