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Malawi’s Fourth Integrated Household Survey 2016-2017 & Integrated Household Panel Survey 2016: Data and documentation now available

Heather Moylan's picture
Malawi IHS4 Enumerator administering household questionnaire
using World Bank Survey Solutions
Photo credit: Heather Moylan, World Bank

The Malawi National Statistical Office (NSO), in collaboration with the World Bank’s Living Standards Measurement Study (LSMS), disseminated the findings from the Fourth Integrated Household Survey 2016/17 (IHS4), and the Integrated Household Panel Survey 2016 (IHPS), on November 22, 2017 in Lilongwe, Malawi. Both surveys were implemented under the World Bank Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA) initiative, with funding from the United States Agency for International Development (USAID).

The IHS4 is the fourth cross-sectional survey in the IHS series, and was fielded from April 2016 to April 2017. The IHS4 2016/17 collected information from a sample of 12,447 households, representative at the national-, urban/rural-, regional- and district-levels.

In parallel, the third (2016) round of the Integrated Household Panel Survey (IHPS) ran concurrently with the IHS4 fieldwork. The IHPS 2016 targeted a national sample of 1,989 households that were interviewed as part of the IHPS 2013, and that could be traced back to half of the 204 panel enumeration areas that were originally sampled as part of the Third Integrated Household Survey (IHS3) 2010/11.

The panel sample expanded each wave through the tracking of split-off individuals and the new households that they formed. The IHPS 2016 maintained a 4 percent household-level attrition rate (the same as 2013), while the sample expanded to 2,508 households. The low attrition rate was not a trivial accomplishment given only 54 percent of the IHPS 2016 households were within one kilometer of their 2010 location.

Latest from the LSMS: New data from Malawi, measuring soil health & food consumption and expenditure in household surveys

Vini Vaid's picture

 

Message from Gero Carletto (Manager, LSMS)

A few weeks ago, I attended a meeting of the Committee for the Coordination of Statistical Activities (CCSA) in Muscat, Oman, where I joined a panel discussion on how global survey initiatives like the LSMS or Multiple Indicators Cluster Survey (MICS) can help us measure and monitor many of the SDG indicators. We also discussed how global initiatives like the UN Statistical Commission’s Inter-Secretariat Working Group on Household Surveys (ISWGHS) can help coordinate these efforts and position the household survey agenda within the global data landscape. Everyone seems to agree that monitoring more than 70 SDG indicators will require high-quality, more frequent, and internationally comparable household surveys. Yet, the narrative on household surveys continues to be lopsided. In my view, this is partly because strengthening traditional data sources like surveys and censuses is seen as outmoded and ineffective when compared with the more glittering promises offered by alternative data sources like Big Data.

At the risk of sounding like a luddite, I believe that it’s important for countries and donors alike to continue investing in household surveys to both validate and add value to new types of data. In many of the countries we work in, leapfrogging to the digital revolution without having gone through an analog evolution may be an ephemeral proposition. This in no way means that we should continue doing things the same way: during the past decade, household surveys have evolved dramatically, increasingly relying on technological innovation and new methods to make survey data cheaper, more accurate, and more policy relevant. Methodological and technological innovation remains at the core of the LSMS’s raison d’être and, together with our partners, we will continue pushing the frontier. Until more robust and fully validated alternatives materialize, household survey critics may want to recall the old saying, “Can’t live with ‘em, can’t live without ‘em!”

Latest from the LSMS: New data from Tanzania and Nigeria, dynamics of wellbeing in Ethiopia & using non-standard units in data collection

Vini Vaid's picture

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!

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.

Latest from the LSMS: The Crowd & The Cloud, debunking myths about African Agriculture & costing household surveys

Vini Vaid's picture

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.

Special Issue of Food Policy Debunks Myths about African Agriculture

Vini Vaid's picture

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.

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.

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

Raka Banerjee's picture


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 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.

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.