One of the most storied topics in agricultural economics, dating back to Chayanov’s work on Russian peasants published nearly a century ago, is the inverse relationship between scale (in terms of farm or plot size) and (land) productivity - commonly known as the IR.
Message from Gero Carletto (Manager, LSMS)
It has been a busy few months for the LSMS team! Together with several Italian and African institutions, we recently launched the Partnership for Capacity Development in Household Surveys for Welfare Analysis. The initiative cements a long-term collaboration to train trainers from regional training institutions in Sub-Saharan Africa to harmonize survey data and promote the adoption of best practices in household surveys across the region (see below for more details). In addition, we have contributed to several international conferences and meetings, such as the Annual Bank Conference on Africa (featured below), where we witnessed the creative use of the data we helped collect and disseminate. Finally, LSMS was part of a documentary on the Public Broadcasting Service (PBS) called The Crowd & The Cloud. The fourth episode featured our very own Talip Kilic and the Uganda Bureau of Statistics, working hand in hand to produce household and farm-level panel data, which have been game changers in informing government policymaking and investment decisions, as well as in advancing the methodological frontier. We look forward to many more exciting quarters as we continue to work with our partners to improve the household survey landscape!
According to the latest estimates, 33.5% of people in Ethiopia live under $1.90 a day. But how do we know that? Where do this number come from?
Well, it comes from household surveys! To learn more about what it takes to collect these data, we talk to Diane Steele, who’s the Household Survey Coordinator of the Living Standards Measurement Study (LSMS) program here at the World Bank. The LSMS program works with countries to help them collect high-quality household survey data, and also to improve the methods used to collect it.
In this episode, Diane tells us about what it takes to put together a household survey. Among other things, you’ve got to design a questionnaire - but how do you make sure that you’re asking the right questions? And you need to design a sample - but how do you know how large of a sample you need in order for the survey to be nationally representative? And you need to train your interviewers properly - but how do you know that they’ve understood the process clearly?
In a world where 77 countries still don’t have the data that they need to measure and track poverty, it’s all the more important to keep improving the way that we collect surveys, so that we’re confident that we’re getting good data that countries can use to create better policies for their citizens. That’s why the World Bank committed to work with the world’s poorest countries to ensure that they collect household surveys every 3 years, so that we’re all better equipped with the information we need to fight poverty and improve people’s lives.
Aside from all that, you can also tune in to hear me ask Tariq about whether he's the head of his household, how many hours he worked last week, and whether or not he's living under an asbestos roof.
This episode of Between 2 Geeks is hosted by Tariq Khokhar & Raka Banerjee, and produced by Richard Miron. You can chat with us on twitter with the hashtag #Between2Geeks, listen to new episodes on the World Bank Soundcloud Channel and subscribe to “World Bank’s Podcasts” in your podcast app or on iTunes.
But where does data come from? And what’s really going on behind the scenes to arrive at these all-important numbers? A new PBS documentary called The Crowd and the Cloud brings data to life by showing us the real lives behind the data points and the hard work that it takes to turn a human story into a statistic.
Hosted by former NASA Chief Scientist Waleed Abdalati and written and produced by Geoff Haines-Stiles (Senior Producer of COSMOS with Carl Sagan), The Crowd and the Cloud is a four-part documentary that examines the rapidly growing field of citizen data science, showing how regular citizens are increasingly able to gather and share valuable data on the environment, public health, climate change, and economic development.
Episode 4: Citizens4Earth follows Talip Kilic from the World Bank’s Living Standards Measurement Study program as he travels to far-flung rural communities in central and southwestern Uganda, along with the survey teams for the Uganda National Panel Survey (UNPS). In the episode, James Muwonge (Director of Socioeconomic Surveys at the Uganda Bureau of Statistics) explains why household surveys like the UNPS are so important for investment decisions and policy-making, particularly in developing countries like Uganda.
half lacked sufficient data for measuring poverty between 2002 and 2011. In response, the World Bank has committed itself to reversing this dismal state of affairs: in October 2015, World Bank President Jim Yong Kim announced that the Bank would support the 78 poorest countries in conducting an LSMS-type household survey every 3 years.and the Bank’s twin goals of ending global extreme poverty by 2030 and boosting shared prosperity. However, we still face significant challenges around the world in terms of data availability - among the 155 countries for which the World Bank monitors poverty data,
Message from Gero Carletto (Manager, LSMS)
I would like to take this opportunity to remember Hans Rosling, a friend and supporter of the LSMS. I don’t need to tell you about his contagious enthusiasm for data or his masterful use of visualization tools to communicate statistics. I can’t say I knew Hans that well, but over the years, even if only based on sporadic interactions, I came to appreciate him both as a person and a scientist. I met him for the first time in 2013 and still remember the flabbergasted look on his face when Kathleen Beegle and I told him that the core LSMS team consisted of only four part-time staff. He was astounded to find out that we were so small, yet we looked so big. And, of course, being the visualization maestro that he was, he immediately came up with his own visual representation of the LSMS with a tool he had at his disposal at that moment: his hand!
From that day on, every time we met, he greeted me with his "LSMS hand." To this day, it remains a good, and fun, memory of Hans.
In this era of alternative facts, the use of high-quality data to set the record straight is more important than ever. In Africa, there has been a pressing need to revisit the conventional wisdom on the region’s agriculture. However, relevant data—where available—have long been outdated and inadequate.
With this in mind, the World Bank’s Africa Chief Economist Office and its partners initiated the Agriculture in Africa– Telling Facts from Myths project. It explores the validity of the conventions surrounding Africa’s agriculture and its farmers’ livelihoods that experts and policymakers considered as self-evident truths. The impact of such stylized facts cannot be underestimated. They shape the policy debates and drive research agendas
Now, a Special Issue of Food Policy brings together 12 open-access articles based on the project, drawing mainly on data from the first rounds (2009–2012) of the nationally representative Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA). Four innovative features of the LSMS-ISA data—integration, individualization, ICT use, and intertemporal tracking—allowed for a more refined insight into African agriculture and rural livelihoods.
Household survey data constitute a cornerstone of the statistical toolkit for addressing the data needs for the monitoring of the Sustainable Development Goals (SDGs) on poverty and hunger. A seminar convened today by the FAO and the World Bank, under the aegis of the Inter-Agency and Expert Group on Food Security, Agricultural and Rural Statistics during the 48th Session of the UN Statistical Commission will provide chief statisticians of several low- and middle-income countries an opportunity to discuss a common agenda for fostering the adoption and implementation of a new set of guidelines for the measurement of food consumption data in household surveys.
Food constitutes a key component of a number of fundamental dimensions of well-being: food security, nutrition, health, and poverty. It makes up the largest share of total household expenditure in low-income countries, accounting on average for about 50 percent of the household budget. Low levels of food access contributed to an estimated 800 million individuals who were chronically undernourished in 2014-16.
Proper measurement of food consumption is therefore central to the assessment and monitoring of the well-being of any population, and to several development domains: social, economic, and human. Food consumption data are needed to monitor global and national goals including the SDGs. But the measurement of food consumption data is also crucial for assessing and guiding FAO’s mandate to eradicate hunger, food insecurity, and malnutrition, as well as the World Bank’s twin goals of eliminating extreme poverty and boosting shared prosperity.
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!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 EthiopiaCGIAR-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.
Since its inception, the World Bank’s Open Data initiative has generated considerable excitement and discussion on the possibilities that it holds for democratizing development economics as well as for democratizing the way that development itself is conducted around the world. Robert Zoellick, in a speech given last year at Georgetown University, expounded on the many benefits resulting directly from open data. Offering the example of a health care worker in a village, he spoke of her newfound ability to “see which schools have feeding programs . . . access 20 years of data on infant mortality for her country . . . and mobilize the community to demand better or more targeted health programs.” Beyond this, Zoellick argued that open data means open research, resulting in “more hands and minds to confront theory with evidence on major policy issues.”
The New York Times featured the Bank’s Open Data initiative in an article published earlier this month, in which it referred to the released data as “highly valuable”, saying that “whatever its accuracy or biases, this data essentially defines the economic reality of billions of people and is used in making policies and decisions that have an enormous impact on their lives.” The far-reaching policymaking consequences of the data are undeniable, but the New York Times touches upon a crucial question that has been overshadowed by the current push for transparency: what about quality?