# **1. Introduction**

Since the 1960s, international institutions active in the field of development and most OECD countries have invested considerable resources in data capacity building in developing countries. For example, just between 2006 and 2015, the total amount spent by the World Bank Group in data capacity building was US$919.4 million, of which 45 percent went to Sub-Saharan Africa (World Bank 2017). This number provided by the World Bank’s independent evaluation group might be on the low side, as it excludes support that may go through development policy financing which does not allow for earmarking.

While it is fair to acknowledge recent progress in household survey data collection in Africa, it is also clear that this massive financial effort has not yielded the expected fruits. To date, there are still very few African countries that can claim to have high-quality data produced regularly and made available to the public in a timely manner. Indeed, Jerven (2013) argues that the world bank GDP data for African economies tends to be underestimated due to outdated data, obsolete methods, lack of data availability and uneven use of methodologies in those countries. Even when data are collected, some countries do choose to keep them confidential.<sup>1</sup> The question is what explains these poor outcomes?

Our conjecture is that the development community has failed in data collection or capacity building for data collection in African countries because this has essentially been a donor-led and supply driven effort. There has been little attention paid to the demand side. In other words, we need to focus more attention on the benefits for countries of producing and sharing data. This could lead to countries’ investing more of their own resources in them, a condition for sustained success. This paper contributes to the literature on the demand side interventions by uncovering the returns from investing in statistical transparency for countries. We focus on economic transparency defined as availability and access of economic information and statistical data (Geraats 2002b).

We explore the relationship between statistical data transparency and sovereign bond spreads while controlling for domestic and external macro-financial variables (classified as pull and push factors). The choice of sovereign bond spreads as the variable of focus is pertinent because of the substantial change in the composition of Sub-Saharan African external debt between 2007 and 2018 (see Figure 1). The share of sovereign bonds and non-Paris Club debt in total outstanding public external debt increased by 18 percentage points and 8 percentage points, respectively. Almost half of the public external debt outstanding and disbursed in 2018 for Sub-Saharan Africa is composed of international bonds and non-Paris Club lending (i.e. 30 percent for bonds and 21 percent for non-Paris club).

This paper improves on the existing literature in three different ways. First, we estimate the impact of public data transparency along with the level of institutional quality and public and external debt. Although greater data transparency alone reduces the external borrowing costs of a country, greater data transparency lowers the external borrowing costs even further when combined with

> 1 Data transparency is not only an issue for low-income countries. It is also problematic in some higher-income countries as well, especially those that do not belong to the Paris Club and therefore are not subject to the standard disclosure requirements, see Horn, Reinhart and Trebesch (2019).

2