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surveys

Between 2 Geeks: Episode 6 - Collecting data with surveys is easy, right?

Raka Banerjee's picture

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.

Every data point has a human story

Raka Banerjee's picture


Good data leads to good policy, which means better lives for people around the world. 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.

A new commitment to household surveys at the World Bank

Household surveys are crucial for monitoring progress towards the Sustainable Development Goals 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, 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.

SDGs 1 & 2: Meeting the demand for more and better household survey data

Alberto Zezza's picture

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.

Seeing the forests and the trees

Gwendolyn Stansbury's picture

Forests and trees are sources of energy, food, shelter, and medicine—and, as such, contribute in multiple ways to reducing food insecurity, supporting sustainable livelihoods, and alleviating poverty.

But measuring forests’ socioeconomic benefits has been difficult due to methodological limitations and the lack of reliable data. As a consequence, the contribution of forests to sustainable development is not only underestimated, but is in some cases invisible, preventing policy makers from considering forest production and consumption benefits when developing social-welfare policies.

A new multi-partner publication provides a landmark contribution to data collection on the socioeconomic benefits of forests. Countries can use the modules and guidance in the book to help close the information gap on the multiple relationships between household welfare and forests. This, in turn, will help capture the true value of forests and other environmental products in gross domestic product measurements and increase understanding of their roles in livelihoods, ultimately leading to evidence-based policy decisions that ensure appropriate recognition of the socioeconomic benefits of forests in post-2015 development programs.

The publication is the result of collaboration between the Food and Agriculture Organization of the United Nations (FAO), Center for International Forestry Research (CIFOR), International Forestry Resources and Institutions (IFRI) Network, and the World Bank's Living Standards Measurement Study (LSMS) team and Program on Forests (PROFOR).

Link to the webcast publication launch: http://www.fao.org/webcast/home/en/item/4227/icode/

For practical guidance on household survey design, visit the LSMS Guidebooks page: http://go.worldbank.org/0ZOAP159L0 
 

New paper: "Milking the Data"

Tariq Khokhar's picture
Quick: how much milk did you drink last year?
 
If you can answer that accurately, you’re either taking the “quantified self” thing a bit far, or you may have been reading some of our research.
 
A new paper co-authored by our colleges on the Living Standards Measurement Study (LSMS) team compares different methods for estimating how much milk is being taken from livestock for human consumption.
 
Alberto wrote about this research last year and the work has been published in Food Policy under an open access license. I think the findings are super-interesting - the authors are trying to understand how to accurately find out from individuals “how much milk did you collect from your animals this year?”
 
Simply asking that question isn’t likely to get you an accurate answer, but if you had to rely on questions in a survey, which questions would you pick? The study compares the answers provided by different survey “recall methods” in Niger against benchmark data gathered by actually measuring the volume of milk taken (weighing it in a jug... ) one day every 2-weeks over the course of a year.