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Living Standards Measurement Study

Ethiopia Socioeconomic Survey 2015-2016: Data and documentation now available

Vini Vaid's picture
© Alemayehu A. Ambel / World Bank

The Central Statistical Agency (CSA) in collaboration with the World Bank’s Living Standards Measurement Study (LSMS) team launched the third wave (2015–16) of the Ethiopia Socioeconomic Survey (ESS) panel data, on February 22, 2017.  
 
The ESS is a nationally representative survey administered every 2 years that covers a range of topics including demography, education, health, savings, labor, welfare, and agriculture, food security and shocks. The data is collected in two visits: post-planting and post-harvest seasons. The survey follows the same households over time and collects a rich set of information, to allow for comprehensive panel data analyses that can help shape policies for a wide array of development sectors.
 
Here are some interesting findings from the ESS 2015–16 survey:      

Tanzania Conference on LSMS Data

Gwendolyn Stansbury's picture

Data producers and users from Sub-Saharan Africa meet at the First International Conference on the Use of Tanzania National Panel Survey and LSMS Data for Research, Policy, and Development

Earlier this month, researchers, policymakers, and development practitioners gathered in Dar es Salaam to attend the first of a series of conferences to discuss the use of household panel data produced with support from the Living Standards Measurement Study–Integrated Surveys on Agriculture (LSMS-ISA) program.  
 
The event—co-sponsored by the Tanzania National Bureau of Statistics (NBS) and LSMS of the World Bank’s Development Data Group—brought together more than 100 people, with a large representation of researchers from Sub-Saharan Africa.

The opening session featured the Hon. Dr. Philip Mpango (Minister for Finance and Planning, United Republic of Tanzania), Dr. Albina Chuwa (Director General, Tanzania National Bureau of Statistics), Mr. Roeland Van De Geer (European Union Ambassador to the United Republic of Tanzania and the East African Community), Ms. Bella Bird (Country Director Tanzania, World Bank),  Ms. Mayasa Mwinyi (Government Statistician, Office of the Chief Government Statistician–Zanzibar), and Dr. Gero Carletto (Manager, LSMS program, World Bank)—as well as a keynote speech by Dr. Blandina Kilama (Senior Researcher, Policy Research for Development–REPOA).

Nigeria General Household Survey 2015-2016: Data and documentation now available

Vini Vaid's picture
© Curt Carnemark / World Bank

The National Bureau of Statistics (NBS) in collaboration with the World Bank’s Living Standards Measurement Study (LSMS) team launched the third wave (2015–16) of the Nigeria General Household Survey (GHS)-Panel in Abuja, on December 13, 2016.  
 
The GHS-Panel survey is a nationally representative survey administered every 2–3 years, that covers a range of topics including demography, education, welfare, agriculture, health and food security. The data is collected in two visits: post-planting and post-harvest seasons. The survey follows the same households over time and collects a rich set of information, to allow for comprehensive time-series analyses that can help shape policies for a wide array of development sectors. Here are some interesting findings from the 2015–16 survey:

Why are women farmers in Sub-Saharan Africa less productive?

Kevin McGee's picture
Researchers have documented a wide array of gender disparities in sub-Saharan Africa that have important implications for individual and household well-being. Perhaps one of the most significant disparities is in agricultural production, the primary economic activity for the majority of the population in sub-Saharan Africa. Closing this gender gap in agricultural productivity would not only improve the welfare of female farmers but could also have larger benefits for other members of the household, especially children.

​Good food and good economics both start with quality ingredients

Alberto Zezza's picture
Do economists and policy analysts pay enough attention to the quality of the data they work with? The focus in these professions seems to be much more on using and developing sophisticated econometric and statistical models, or pretty data visualization software, than on assessing the quality of the data that are fed into those models and tools (let alone working to improve the quality of the data).
 

Whose anecdote will it be this time?

Gero Carletto's picture

Within the Living Standards Measurement Study (LSMS) team, the anecdote  goes that in the late 1970s World Bank President Robert McNamara, while reading through the first World Development Report, was stunned to discover that only a handful of countries were collecting any data for the reporting of poverty figures.  He found this situation unacceptable and initiated an effort that among other things resulted in the creati

Welfare, Assets, Data Availability and the Living Standards Measurement Study

Kinnon Scott's picture

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.