All the same, substantial data gaps persist. During the ten year period between 2002 and 2011, among the 155 countries<sup>3</sup> for which the World Bank monitors poverty data using the WDI database, 29 countries do not have any poverty data point and 28 countries have only one poverty data point.<sup>4</sup> Thus, in over a third of the world’s developing or middle income countries there is essentially no meaningful way of monitoring poverty or shared prosperity for that specific period. Moreover, among countries that have poverty estimates for two years over the ten year period, often large time gaps exist. Of 35 such countries, 20 have two poverty estimates with a larger than five year interval, which resulted in poverty monitoring efforts being dated. Therefore, a total of 77 countries – about half of the 155 countries – faced challenges in producing timely or any poverty estimates during the 2002-11 period. If one considers intervals shorter than 5 years, the picture becomes worse.

The analysis in this note is conducted using a World Bank database of poverty monitoring data for 155 countries and territories. By examining the availability of data across countries over the last two decades, the note identifies improvements that have taken place over time and provides a richer understanding of the current state of data deprivation, which hinders effective poverty monitoring. This discussion can then be used as a benchmark to set targets for addressing poverty data deprivation in the medium and long term.

While this note focuses on ‘poverty’ data, it should be noted outright that surveys collecting consumption data collect information on many human development and social indicators, and addressing poverty data deprivation can go a long way – if not all the way – in addressing data deprivation regarding many other indicators as well. Thus the usefulness of consumption surveys goes far beyond that of poverty monitoring. By gathering a host of statistics on individual and household attributes, as well as on locational attributes, such surveys are the pivotal source of data for governments and policy makers in understanding linkages between poverty and other socioeconomic outcomes and policy. At the same time as informing key priorities of governments, such as the design of social programs and the impacts of policy interventions or shocks, such data also provide vital input to constructing national accounts and the CPI (consumer price index).

Alongside household consumption survey data, complementary data are also needed for tracking poverty (Jolliffe _et al_ 2014). For example, if population census data are unavailable, outdated or unreliable, it is problematic to make inferences about a country’s population from a sample-based household survey. Cross-country comparisons place additional data demands. Cost of living adjustments are necessary to count the poor across countries using a common currency and a global poverty line. At present, this comes from data on purchasing power parity (PPP) collected by the International Comparison Program (ICP) every few years. Moreover, to compare poverty across countries in any given year, inflation data and real GDP growth data (or private/household consumption data) would be needed to account for changes in prices and in real economic activity between the survey year and the reference year.

However, in reality, the main bottleneck for poverty data is lack of household surveys. Usually if household survey data are available, the aforementioned complementary data are available. Therefore, it is safe to say lack of poverty data can be attributed to lack of household survey data.

> 3 When using the term countries, we refer to countries and territories.

> 4 A poverty data point consists of a poverty estimate in a certain year at either the international poverty line of $1.25 a day or the national poverty line compiled from household consumption survey data.

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