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Sampling Nomads: A New Technique for Remote, Hard-to-Reach, and Mobile Populations
Published in Journal of Official StatisticsSpecial issue on Hard to Reach Populations
Co-Authors:Kristen Himelein, World BankSiobhan Murray , World Bank
Stephanie Eckman
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Background
Livestock play integral role in livelihoods of vulnerable populations‐ Main source of food and transportation‐ Store of wealth‐ Coping mechanism in response to shocks
Under pressure from development & climate change
HH based samples may not be sufficient to capture Pastoralists‐ Coverage error‐ Measurement error
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Our Approach
We propose an alternative sampling approach to reach Pastoralists
Random Geographic Cluster Sampling (RGCS) ‐ 1st stage: select random points‐ 2nd stage: survey all eligible respondents within given radius
Similar designs used:‐ Agricultural statistics agencies (ex: USDA)
‐ Livestock studies in developing world‐ Surveys of forests
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Location: Afar, Ethiopia
More than 40 percent of population owns 10 or more cattle‐ 2009 Agricultural Sample Survey‐ Camels, goats
Bounded by ‐ National borders north & east‐ Mountains to the west‐ Ethnic differences
Stratification
Definition Likelihood Radius1 Towns High 0.1 km2 Settled agricultural areas,
commercial farmsLow 0.5 km
3 Within 2 km of major river or swamps
High 1 km
4 Within 10 km of major river or swamps
Medium 2 km
5 Remainder Low 5 km
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Stratum 3 (High Likelihood)
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Stratum 5 (Low Likelihood)
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Field Work
Selected points pre-loaded on GPS‐ Alarm indicated when interviewer inside radius
Interview all eligible respondents within radius‐ Only HHs with livestock eligible‐ Questions about ownership, vaccination, theft, death, etc
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Weights
Inverse of probability of selection
But what is probability of selection of Household i?
i
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All points that lead to interviewer finding Household i
If any of these points selected, i selected
Base Weights
i
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Base Weights
Probability of selection is:
1 – Pr(none of these points selected)
c is number of points selected
Weight Adjustment
Teams did not always visit entire circle
GPS recorded path as they worked
Most relevant is what they could see from their path
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Source: ASTER GDEM v2 (30 m)
Weight Adjustment
Viewshed analysis tells us how much of circle interviewers could see
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Implementation Challenges
Field workers unaccustomed to technique
Unexpected challenges‐ Early start to rainy season‐ Ethnic conflict / kidnapping‐ Volcanoes‐ River crossings, trouble with vehicles
Interviewers and supervisors cited flooding, difficult terrain, weather as reasons they could not complete work
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Results of Data Collection
102 circles canvassed‐ From 125 selected‐ 59% contained at least 1 HH with livestock
784 households with livestock interviewed ‐ 9 excluded for being outside radius‐ 3,698 individuals
3.4% of persons reported having no permanent dwelling
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Livestock Estimates: Means
RGCS (unadj weights) RGCS (adj weights) ERSS
Cattle 10.4 10.8 15.3Camels 8.1 7.7 6.2Goats 20.2 19.7 20.7
Mean number owned (conditional on ownership)
ERSS: Ethiopian Rural Socioeconomic Survey
Adjusted weights: include adjustment for % of circle observed
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Livestock Estimates: Totals
RGCS (unadj) RGCS (adj) ERSS
Cattle 153,505 186,164 1,092,752Camels 92,009 139,608 237,568Goats 566,139 815,310 2,095,876
Total number owned (conditional on ownership)
ERSS: Ethiopian Rural Socioeconomic Survey
Adjusted weights: include adjustment for % of circle observed
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What Explains Discrepancies in Totals?
Interviewer Effort hypothesis‐ Why were some circles not visited?‐ Far from roads
‐ Why were some circles not entirely observed?‐ Larger circles
‐ Seem unrelated to flooding‐ Strong supervisor effects
ERSS Quality hypothesis‐ Suggestions of problems with weights and missing data imputation
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Conclusions
RGCS can be implemented in a low capacity environment with inexpensive hardware – though not without some difficulties‐ Does capture nomadic populations
RGCS likely under-estimated the total livestock population‐ May be more accurate than census-frame ERSS survey‐ 3rd comparison (in paper) suggests RGCS closer to truth
More on incentivizing interviewers to elicit a high effort response ‐ In published paper
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Papers in Progress
Himelein, Eckman & Murray “Second Stage Sampling for Conflict Areas: Methods and Implications”
Eckman, Himelein & Dever “New Ideas in Sampling for Surveys in the Developing World”
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Resulting Stratification
Description Points%
Visited HHs% Without Livestock
1 Towns 10 100% 69 40%
2Settled agri. areas, commercial farms 15 93% 113 53%
3Within 2 km of major river 60 82% 229 40%
4Within 10 km of major river 30 73% 182 20%
5 Remainder 10 70% 191 10%Total 125 82% 784 34%
Results
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Stratification Complicates Base Weights
Stratum 1 Stratum 2
X
r2
r1
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Stratification Complicates Base Weights
Stratum 1
X
Stratum 2
