Supplementary material from "Mapping poverty using mobile phone and satellite data"
Posted on 2017-01-11 - 09:58
Poverty is one of the most important determinants of adverse health outcomes globally, a major cause of societal instability and one of the largest causes of lost human potential. Traditional approaches to measuring and targeting poverty rely heavily on census data, which in most low- and middle-income countries (LMICs) are unavailable or out-of-date. Alternate measures are needed to compliment and update estimates between censuses. This study demonstrates how public and private data sources that are commonly available for LMICs can be used to provide novel insight into the spatial distribution of poverty. We evaluate the relative value of modelling three traditional poverty measures using aggregate data from mobile operators and widely available geospatial data. Taken together, models combining these data sources provide the best predictive power (highest r2 = 0.78) and lowest error, but generally models employing mobile data only yield comparable results, offering the potential to measure poverty more frequently and at finer granularity. Stratifying models into urban and rural areas highlights the advantage of using mobile data in urban areas and different data in different contexts. The findings indicate the possibility to estimate and continually monitor poverty rates at high spatial resolution in countries with limited capacity to support traditional methods of data collection.
CITE THIS COLLECTION
DataCite
3 Biotech
3D Printing in Medicine
3D Research
3D-Printed Materials and Systems
4OR
AAPG Bulletin
AAPS Open
AAPS PharmSciTech
Abhandlungen aus dem Mathematischen Seminar der Universität Hamburg
ABI Technik (German)
Academic Medicine
Academic Pediatrics
Academic Psychiatry
Academic Questions
Academy of Management Discoveries
Academy of Management Journal
Academy of Management Learning and Education
Academy of Management Perspectives
Academy of Management Proceedings
Academy of Management Review
Steele, Jessica; Sundsøy, Pål Roe; Pezzulo, Carla; A. Alegana, Victor; Bird, Tomas J.; Blumenstock, Joshua; et al. (2017). Supplementary material from "Mapping poverty using mobile phone and satellite data". The Royal Society. Collection. https://doi.org/10.6084/m9.figshare.c.3662800.v1
or
Select your citation style and then place your mouse over the citation text to select it.
SHARE
Usage metrics
Read the peer-reviewed publication
AUTHORS (15)
JS
Jessica Steele
PS
Pål Roe Sundsøy
CP
Carla Pezzulo
VA
Victor A. Alegana
TB
Tomas J. Bird
JB
Joshua Blumenstock
JB
Johannes Bjelland
KE
Kenth Engø-Monsen
Yd
Yves-Alexandre de Montjoye
AI
Asif M. Iqbal
KH
Khandakar N. Hadiuzzaman
XL
Xin Lu
EW
Erik Wetter
AJ
Andrew J. Tatem
LB
Linus Bengtsson