- if a country has three or more poverty estimates in ten years, the country is categorized as “satisfactory”.

Based on this classification using the latest data (2002-11), we find that 57 of 155 countries face data deprivation, and only 62 countries have satisfactory frequency of poverty data. Furthermore, there are 20 countries that are vulnerable to becoming data deprived.

Based on projections using the past data, this paper proposes the following three targets:

- Target 1: _All countries will have two or more poverty data points in the last ten years by 2030._

- Target 2: _86 countries will have three or more poverty data points in ten years by 2030._

- Target 3: _All new poverty estimates are of good quality and thus can be included in the WDI._

With the World Bank Group’s recently proposed twin goals, acceptance of target 1 would imply that the world would mobilize efforts to end extreme poverty by 2030 and to end data deprivation by 2030 as well. While SDG indicators are not yet finalized, in the publicly available draft documents, the target of ending extreme poverty features prominently as well. This dual goal of ending extreme poverty and ending data deprivation is critical to ensure that the declaration of “ending extreme poverty” can actually happen. The analysis based on projections suggests that the targets are ambitious but feasible. The proposed targets also rather fittingly align with the call of the United Nations for a ‘data revolution’ – by exploiting advances in knowledge and technology, utilizing resources for capacity development, and improving coordination of efforts among key actors – to mobilize sustainable development (IEAG 2014).<sup>19</sup> Finally, this paper discusses some practical considerations in achieving these targets by carefully looking into countries that face data deprivation or are vulnerable to facing data deprivation. Also, a comparison between the IHSN and WDI databases indicates that a potentially key problem is a lack of coordination between household surveys rather than lack of surveys. The role of NSDS and other coordination mechanisms will be key to improving data availability in a cost-effective manner.

The scope of the present paper has several limitations. The paper does not examine the question of data access. This is a complicated issue as there are several notions of access, which are often difficult to neatly classify. For example, some countries may provide full public access to their microdata, while others may choose to make publicly available a subset of variables (e.g., it may exclude location variables) or a subsample of the survey. Other countries may provide ‘negotiated’ access to their surveys on the basis of a clear understanding of what the data will be used for and some countries may provide no access to their data at all. While lack of data access can hamper poverty monitoring efforts in the same way as lack of data due to consumption surveys not being conducted, solving it would require a different approach and should be examined in greater detail.

The present paper does not delve into granular issues of implementation either. For example, a crucial practical consideration is to cost an initiative to end poverty data deprivation. While this paper does not attempt that, future work ought to carry out a careful analysis of costs based on different plausible scenarios. The database underlying this paper is well suited to that exercise as it pinpoints country-specific poverty gaps. The costs of surveys vary across countries, as do the funding sources (e.g., governments themselves,

> 19 For more information see http://www.undatarevolution.org.

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