The latest World Bank estimates suggest that the percentage of the developing world’s population living below $1.25 a day declined from 52% in 1981 to 22% in 2008. While this indicates that there is still a long way to go in poverty reduction, the progress is encouraging. Moreover, we now also appear to be in a much better position to make such statements. The numbers above, by my colleagues at the Department Research Group, are based on over 850 household surveys for nearly 130 developing countries, representing 90% of the population of the developing world. By contrast, they used only 22 surveys for 22 countries when the first such estimates were reported in the 1990 World Development Report.
As international migration and migrant remittances have increased in recent years, there is a clear need for improved data on international migration and migrant remittances to understand the effects that various policies can have on migrants and migrant households. In a new paper, we argue that large, multi-purpose data collection efforts present good opportunities to study migration in a cost-effective manner. Many countries now implement nationally representative, multi-topic household surveys à la Living Standards Measurement Study (LSMS) surveys, primarily for the purposes of welfare monitoring and analysis. Although LSMS survey questionnaires are designed to study numerous aspects of household welfare and behavior, collecting detailed migration information has not been a priority for most multi-topic household surveys, resulting in large knowledge gaps on migration. Integrating migration information into these data collection efforts can be an efficient way to collect migration data.
A very good panel discussion this week on Gender Equality Data and Tools at the Bank reminded me of the research we did in transport on household surveys with my friend and a World Bank colleague, Kinnon Scott. In retrospect, this work should be better advertised as it touches upon many of the points that were raised on the importance of gender-relevant data for policy. The three main questions that follow permeate t
One is always grateful to see attention paid to the quality and quantity of household data available to study poverty. It is a subject dear to my heart and to my colleagues in the Living Standards Measurement Study (LSMS ) in the World Bank. In sub-Saharan Africa, as a recent Global Dashboard post titled “What do we really know about poverty and inequality?” by Claire Melamed points out, there is still a dearth of data, even after years of government effort and international support. But there are data -- in some countries lots of data -- so it’s worth highlighting what is there. Today I wanted to add some nuance to the discussion of income and assets raised by Claire and, probably more importantly, steer people to some new data that will, we hope, excite the most blasé of you out there.
We invite you to use open and free access to data collected through the Migration and Remittances Household Surveys conducted for the Africa Migration Project. Please access the household data here. We present the methodological apects and main finidngs of the surveys in our paper, Migration and Remittances Household Surveys: Methodological Issues and New Findings from Sub-Saharan Africa. For information on the report “Leveraging Migration for Africa: Remittances, Skills, and Investments” please visit our website.
As part of the Africa Migration Project, we conducted six Migration and Remittances Household Surveys in Burkina Faso, Kenya, Nigeria, Senegal, South Africa, and Uganda. The surveys used a standardized methodology developed by the Migration and Remittances Unit of the World Bank and were conducted by primarily country-based researchers and institutions during 2009 and 2010.