hence raise the cost of borrowing. A one-point increase in the World Bank data transparency index conditional on a better ICRG reduces sovereign bond spreads by 0.49 ([5] in Table 7). In the same regression, a one-point increase in the data transparency conditional on greater trade and financial openness reduces borrowing costs by 0.109 and 0.00388, respectively. Consequently, opening-up markets in goods and financial assets brings more benefits in terms of lower borrowing costs as long as the country has a better level of institutional quality. Table 7 also shows robust estimations for the interaction terms between data transparency and public debt in [5] and between data transparency and external debt in [6]. Data transparency, conditional on higher public debt and conditional on higher external debt, is positively corelated with larger bond spreads. This implies that there are increasing marginal costs of borrowing to having higher (public and external) debt.

# **4.3 Calculating Impacts of Data Transparency by Country**

We calculate how much a country could directly benefit from improving data transparency. First, we calculate the impact of data transparency on sovereign bond spreads conditional on the level of external public debt by region and by country. Then we compute how much a country could gain in terms of lower spreads by improving their data transparency to levels determined by a certain benchmark. Finally, we also estimate how much a country could reduce their external debt burden by improving data transparency. We use the IV estimation from Table 5 [1] to calculate those impacts. Figure 5.a shows the impact of data transparency on sovereign bond spreads conditional on the level of external public debt for five different regions such as Africa, emerging Asia, Latin America, emerging Europe and the Middle East. We use the 2018 average bond spreads for each region to calculate the change of spreads in basis points. We take the coefficient of the World Bank data transparency index of 3.112 in Table 5 [1] and the interaction with external debt (while holding constant for the level of institutional quality). Our estimates suggest that if there is, for instance, a 10 percent improvement in data transparency, and we account for the average of external public debt in SSA (average of 22.42 percent of GDP from 2009 to 2018), the sovereign bond spreads in the region could be reduced by 0.7 basis points (see Figure 5.a). This drop in sovereign spreads is slightly larger than that of Latin America and Asia. Figure 5.b shows changes in sovereign spreads across Sub-Saharan African countries. An increase of 10 percent in data transparency leads to the largest declines in sovereign spreads in Nigeria, Zambia and Cameroon whereas the cost of external borrowing increases in Mozambique. This finding implies that countries with lower stock of external debt tend to have largest drop in spreads in the event of improved data transparency. In the case of Mozambique, a high and unsustainable external debt position more than offsets any progress in data transparency.

Figure 6 shows the potential gains from greater data transparency across Sub-Saharan African countries measured in terms of lower external public debt burden expressed in million dollars and as a percentage of GDP. We calculate the gains from improving data transparency to the level of two benchmarks: the top quartile of the middle-income countries and the top quartile of the uppermiddle-income countries. We compute the likely reduction in their amount of external debt using the outstanding Euro bonds (expressed in millions of US dollars and as a percentage of GDP). For example, from Table 8, if Angola improves its level of data transparency to the top quartile of the 13