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Latest from the LSMS: DNA fingerprinting, population mapping, energy access, and surveying forests and livestock

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The LSMS team continues to support the World Bank's pledge to collaborate with the 78 poorest countries to collect high-quality national household survey data every three years, to better inform investments and policies to eradicate extreme poverty and boost shared prosperity. A big part of this effort involves improving data collection methods in key areas. Toward that end, under the aegis of the World Bank’s Household Survey Working Group, we have developed a methodological research plan that focuses on welfare, gender, agriculture, and data processing/dissemination. Work is underway, and LSMS is collaborating with UNESCO, ILO, FAO, and other international organizations to establish standards and validate methods for data collection. As part of this effort, at a recent expert consultation at our Center for Development Data in Rome (hosted with FAO), representatives from development agencies and national statistical offices agreed on draft guidelines for collecting data on food consumption. Currently, there are no internationally agreed-upon standards for household consumption and expenditure surveys, so bringing this agenda forward can greatly improve the quality and comparability of global poverty, food security, and nutrition data.

New Data from Niger and Uganda!

Image Niger: The data from wave 2 of the Niger Enquête Nationale sur les Conditions de Vie des Ménages et l'Agriculture (ECVMA 2014) are now available. This panel dataset follows from the 2011 survey; 3,614 of the original 3,859 households were re-interviewed. The ECVMA is implemented in collaboration with the Niger Institut National de la Statistique (INS).

Uganda: The Uganda National Panel Survey (UNPS) 2013/14 data are also available.  This round follows from the 2005/06, 2009/10, 2010/11, and 2011/12 rounds and includes 3,119 households. The UNPS is implemented in collaboration with the Uganda Bureau of Statistics.

DNA Fingerprinting, Drones and Remote Sensing in Ethiopia

CGIAR-Standing Panel on Impact Assessment (SPIA) implemented two data experiments in collaboration with LSMS, the World Bank, and the Ethiopian Central Statistical Agency. One experiment examined data accuracy on measuring improved sweet potato varietal adoption. It compared three household-based methods against DNA fingerprinting benchmark. These included: (i) farmer elicitation, (ii) farmer elicitation using visual-aid, and (iii) enumerator elicitation using visual-aid. Visual-aid protocols were better than farmer elicitation, but still far below the benchmark estimates. Another experiment focused on crop residue coverage measurement. It compared four survey-based (interviewee and enumerator estimations as well as use of visual-aid protocol) and two aerial (drones' images and remote sensing) methods against a line-transect benchmark. The results ranked measurement options for survey practitioners and researchers in conservation agriculture.

LSMS Partners with Facebook on Population Mapping

ImageLSMS is collaborating with the Facebook Connectivity Lab and the Center for International Earth Science Information Network (CIESIN) on the validation of Facebook’s unprecedentedly high-resolution population maps, which are being generated as part of the initiative that aims to bring the internet to the globally unconnected. Facebook's initial release includes maps for Ghana, Haiti, Malawi, South Africa, and Sri Lanka, which provide data on the distribution of human populations at 30-meter spatial resolution. As part of the collaboration, LSMS is comparing the high-resolution population projections against ‘ground truth’ census and household survey data in selected countries. Read more about the initial results from the validation work program based on the Malawi Third Integrated Household Survey (IHS3) data.

Forests and Livestock: Two Additions to the LSMS Guidebook Series

Two new volumes published in partnership with FAO add to the growing list of LSMS Guidebooks. Forests and livestock contribute in multiple ways to reducing food insecurity, supporting sustainable livelihoods, and alleviating poverty, but their contribution is often not adequately acknowledged by survey data because of weaknesses in survey design. These Guidebooks aim to help practitioners address those weaknesses. Read more and download the Guidebook on National Socioeconomic Surveys in Forestry here and the Guidebook on Measuring Livestock in the Household Economy here. The Guidebooks present module templates for effectively including forests and livestock in multi-topic household surveys. They are practical tools for survey practitioners to collect data on the role of forests and livestock in the household economy and their contribution to livelihoods.

Energy Access: How Much and How Often?

One of the United Nations Sustainable Development Goals (SDGs) is to ensure access to affordable, reliable, sustainable, and modern energy for all. LSMS is supporting the World Bank/Energy Sector Management Assistance Program (ESMAP) in their efforts to gather data on energy under the Sustainable Energy for All (SE4All) initiative's Global Tracking Framework (GTF). The GTF recommends gathering data regularly to monitor progress in energy access measured in terms of a multi-tier framework (MTF). The LSMS team has worked closely with the ESMAP team to develop an Energy Module that can be incorporated into household surveys and is also working toward (i) promoting the integration of the Energy Module in LSMS-type surveys; (ii) facilitating the implementation of and providing technical support for full-scale energy surveys in selected countries; (iii) and leading the design and implementation of methodological experiments to improve the measurement of the MTF. More information can be found here.

New Data for the Bio-Economy

ImageThis fall, the LSMS team participated in the 5th Conference of African Association of Agricultural Economists (AAAE) in Addis Ababa and the 7th International Conference on Agricultural Statistics (ICAS) in Rome. The AAAE conference attracted a global audience, with high participation from African economists. Many presentations at the conference cited LSMS data. Producers, suppliers, and users of agricultural data and statistics attended the ICAS conference, which responded to the changing needs and opportunities for agricultural statistics and brought together research and best practices in in the field.     


Not Your Average Job: Measuring Farm Labor in Tanzania

Vellore Arthi, Kathleen Beegle, Joachim De Weerdt, and Amparo Palacios-López examine how the legnth of the recall period impacts the accuracy of household farm labor estimates obtained by surveys. Using insights from cognitive and social psychology, they investigate the sources of recall bias, and find that where working patterns are irregular, current survey strategies impose cognitive burdens that lead to dramatic overestimations of season-level working hours. For more, read: Not Your Average Job: Measuring Farm Labor in Tanzania.    


Raka Banerjee

Project Coordinator, Development Data Group, World Bank

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