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Submitted by Gero Carletto on
It is refreshing to read such an enthusiastic support for more data generation, which remains indeed deficient in several regards. Over the past three decades, in the Living Standards Measurement Study (1), we have made it our mission to work towards the improvement of the quality and policy relevance of household survey data, the backbone of much of the poverty and policy analysis work at the Bank. And we have done so by providing countries with much needed technical assistance and, on the research side, by working on improving methods in data collection. The situation in terms of data availability has improved considerably; however, the glass is probably still three quarters empty! Particularly in Sub-Saharan Africa, enormous gaps remain both in terms of data availability and quality. As already mention in a recent blog post (2), while 43 out of 49 Sub-Saharan African countries have now conducted at least one household survey, for half of those the latest survey was carried out more than six years ago. And even when multiple data points exist for a country, issues of comparability hamper their use to monitor progress over time. I could not agree more that the Bank should make it a central part of its public goods agenda and probably few would object to that. The real question is how to best move the agenda forward. The solution is making countries full partners, with clearly defined responsibilities for supporting such endeavors both technically and financially. At the country level, this means having individual Ministries of Finance fully invested in this global endeavor. At the Global level, as you also point out, it means having institutions like the Bank putting “their money where their mouth is” and investing more human and technical resources in data generation and use. Several development partners have been instrumental in maintaining the momentum but it is time for others to “step up to the plate” and push the data agenda in a coordinated fashion. Nice to feel the breeze of change, but it must keep blowing with substance and resources if we really want to see enduring improvements in data. (1) and (2)

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