that increasing both technical and financial support from international development agencies will be necessary to aid survey implementation.

Despite the high financial burden (in per capita terms), we would like to argue that it is vital for all countries – regardless of their size and impact on global poverty rates – to maintain regular monitoring systems of poverty and shared prosperity. Many of the small island states face frequent weather shocks, which are likely to be magnified by climate change, and these countries are also vulnerable to global economic shocks.

Several countries with no poverty data availability, such as Algeria, do in fact carry out household consumption surveys and maintain poverty estimates. However, they do not share data and estimates with the World Bank. For those countries, creating closer relationships and collaboration with the National Statistical Offices (NSO) would be essential.

For the 28 countries with a moderate data deprivation in monitoring poverty<sup>16</sup> , it is vital to benefit from the countries’ already existing capacity and structures (of conducting household consumption surveys) by providing additional technical and financial support. Most countries in this group are low income countries in Sub-Saharan Africa where the technical capacities of NSOs tend to be low and domestic funds for household surveys are limited. It would therefore be essential to build statistical capacity through a longer term collaboration of NSOs and the World Bank.

Reducing vulnerability to data deprivation requires that household consumption surveys are carried out not only frequently but also regularly with the same intervals (of five years). Supporting countries in this effort is demanding as countries with irregular poverty estimates are often countries with low statistical capacity or countries that are affected by external shocks (e.g., conflict) that prevent them from regular data collection.

Lastly, it is instructive to discuss the timeframe of achieving the targets. Poverty data is available with a lag due to the long data processing time: collecting, cleaning, and preparing data for analysis tends to be a prolonged process, at times, spanning multiple years from the start of fieldwork to the time when the data are ready for analysis.<sup>17</sup> For this reason this paper, written toward the end of 2014, uses the period 20022011 as the reference period for setting targets for 2030. If the same trend persists, the reference period to judge whether or not the targets have been met in 2030 would be 2017-2026 (and so the projections in figure 4 use this as the end period). This suggests a 12 year window to achieve the targets of ending data deprivation, a rather tight operational period. It would be expected that due to the technological progress being made, timeliness of poverty data can be improved and an active effort should be directed to this end. If data eventually become timelier it would add some extra time to the operating period for the targets. However, as matters stand at present, the timeframe to achieve the targets is quite small.

> 16 These countries are: Zimbabwe; Seychelles; Yemen, Rep.; Timor-Leste; Tanzania; Swaziland; Sudan; South Sudan; Solomon Islands; São Tomé and Principe; Papua New Guinea; Morocco; Mauritius; Maldives; Liberia; Lebanon; Kenya; Iraq; Iran, Islamic Rep.; Ghana; Gabon; Equatorial Guinea; Djibouti; Congo, Dem. Rep.; Comoros; Cameroon; Burundi; and Angola.

> 17 For example, of the 61 data points in 2011 (Figure 1), only one data point became available in 2011, 15 in 2012, 21 in 2013, and 24 in 2014. It took three years for all of the data points in 2011 to be finalized and available in the WDI.

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