Mission Impossible? : Exploring the Promise of Multiple Imputation for Predicting Missing GPS-Based Land Area Measures in Household Surveys
Research has provided robust evidence for the use of GPS technology to be the scalable gold standard in land area measurement in household surveys. Nonetheless, facing budget constraints, survey agencies often seek to measure with GPS only plots wi...
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| Format: | Working Paper |
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World Bank, Washington, DC
2017
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| Online Access: | http://hdl.handle.net/10986/27641 |
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okr-10986-276412017-12-13T09:00:45Z Mission Impossible? : Exploring the Promise of Multiple Imputation for Predicting Missing GPS-Based Land Area Measures in Household Surveys Kilic, Talip Yacoubou Djima, Ismael Carletto, Calogero LAND USE GLOBAL POSITIONING SYSTEM LAND AREA MEASUREMENT Research has provided robust evidence for the use of GPS technology to be the scalable gold standard in land area measurement in household surveys. Nonetheless, facing budget constraints, survey agencies often seek to measure with GPS only plots within a given radius of dwelling locations. Subsequently, it is common for significant shares of plots not to be measured, and research has highlighted the selection biases resulting from using incomplete data. This study relies on nationally-representative, multi-topic household survey data from Malawi and Ethiopia that exhibit near-negligible missingness in GPS-based plot areas, and validates the accuracy of a multiple imputation model for predicting missing GPS-based plot areas in household surveys. The analysis (i) randomly creates missingness among plots beyond two operationally relevant distance measures from the dwelling locations; (ii) conducts multiple imputation under each distance scenario for each artificially created data set; and (iii) compares the distributions of the imputed plot-level outcomes, namely, area and agricultural productivity, with the known distributions. In Malawi, multiple imputation can produce imputed yields that are statistically undistinguishable from the true distributions with up to 82 percent missingness in plot areas that are further than 1 kilometer from the dwelling location. The comparable figure in Ethiopia is 56 percent. These rates correspond to overall rates of missingness of 23 percent in Malawi and 13 percent in Ethiopia. The study highlights the promise of multiple imputation for reliably predicting missing GPS-based plot areas, and provides recommendations for optimizing fieldwork activities to capture the minimum required data. 2017-07-19T17:04:53Z 2017-07-19T17:04:53Z 2017-07 Working Paper http://hdl.handle.net/10986/27641 English en_US Policy Research Working Paper;No. 8138 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Publications & Research Publications & Research :: Policy Research Working Paper Africa |
| institution |
Open Data Bank |
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Open Knowledge Repository |
| building |
World Bank |
| language |
English English |
| topic |
LAND USE GLOBAL POSITIONING SYSTEM LAND AREA MEASUREMENT |
| spellingShingle |
LAND USE GLOBAL POSITIONING SYSTEM LAND AREA MEASUREMENT Kilic, Talip Yacoubou Djima, Ismael Carletto, Calogero Mission Impossible? : Exploring the Promise of Multiple Imputation for Predicting Missing GPS-Based Land Area Measures in Household Surveys |
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Africa |
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Policy Research Working Paper;No. 8138 |
| description |
Research has provided robust evidence
for the use of GPS technology to be the scalable gold
standard in land area measurement in household surveys.
Nonetheless, facing budget constraints, survey agencies
often seek to measure with GPS only plots within a given
radius of dwelling locations. Subsequently, it is common for
significant shares of plots not to be measured, and research
has highlighted the selection biases resulting from using
incomplete data. This study relies on
nationally-representative, multi-topic household survey data
from Malawi and Ethiopia that exhibit near-negligible
missingness in GPS-based plot areas, and validates the
accuracy of a multiple imputation model for predicting
missing GPS-based plot areas in household surveys. The
analysis (i) randomly creates missingness among plots beyond
two operationally relevant distance measures from the
dwelling locations; (ii) conducts multiple imputation under
each distance scenario for each artificially created data
set; and (iii) compares the distributions of the imputed
plot-level outcomes, namely, area and agricultural
productivity, with the known distributions. In Malawi,
multiple imputation can produce imputed yields that are
statistically undistinguishable from the true distributions
with up to 82 percent missingness in plot areas that are
further than 1 kilometer from the dwelling location. The
comparable figure in Ethiopia is 56 percent. These rates
correspond to overall rates of missingness of 23 percent in
Malawi and 13 percent in Ethiopia. The study highlights the
promise of multiple imputation for reliably predicting
missing GPS-based plot areas, and provides recommendations
for optimizing fieldwork activities to capture the minimum
required data. |
| format |
Working Paper |
| author |
Kilic, Talip Yacoubou Djima, Ismael Carletto, Calogero |
| author_facet |
Kilic, Talip Yacoubou Djima, Ismael Carletto, Calogero |
| author_sort |
Kilic, Talip |
| title |
Mission Impossible? : Exploring the Promise of Multiple Imputation for Predicting Missing GPS-Based Land Area Measures in Household Surveys |
| title_short |
Mission Impossible? : Exploring the Promise of Multiple Imputation for Predicting Missing GPS-Based Land Area Measures in Household Surveys |
| title_full |
Mission Impossible? : Exploring the Promise of Multiple Imputation for Predicting Missing GPS-Based Land Area Measures in Household Surveys |
| title_fullStr |
Mission Impossible? : Exploring the Promise of Multiple Imputation for Predicting Missing GPS-Based Land Area Measures in Household Surveys |
| title_full_unstemmed |
Mission Impossible? : Exploring the Promise of Multiple Imputation for Predicting Missing GPS-Based Land Area Measures in Household Surveys |
| title_sort |
mission impossible? : exploring the promise of multiple imputation for predicting missing gps-based land area measures in household surveys |
| publisher |
World Bank, Washington, DC |
| publishDate |
2017 |
| url |
http://hdl.handle.net/10986/27641 |
| _version_ |
1610830972354297856 |