Poverty mapping case studies (doi:10.7910/DVN/DQQIXZ)

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Poverty mapping case studies

doi:10.7910/DVN/DQQIXZ

Harvard Dataverse

2020-08-03

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Hyman, Glenn Graham; Larrea, Carlos; Farrow, Andrew, 2020, "Poverty mapping case studies", https://doi.org/10.7910/DVN/DQQIXZ, Harvard Dataverse, V1

Poverty mapping case studies

doi:10.7910/DVN/DQQIXZ

Hyman, Glenn Graham (International Center for Tropical Agriculture (CIAT))

Larrea, Carlos (Facultad Latinoamericana de Ciencias Sociales (FLACSO) Ecuador)

Farrow, Andrew (GeAgrofía)

Consultative Group on International Agricultural Research

2005

Harvard Dataverse

Bioversity International and the International Center for Tropical Agriculture

Alliance Data Management

Alliance Data Management

2020-07-31

https://doi.org/10.7910/DVN/DQQIXZ

Agricultural Sciences, Earth and Environmental Sciences, Poverty, Food security, GIS, Models, Latin America and the Caribbean, Climate Action

Social conditions

This project developed data, information and knowledge on the spatial distribution of poverty in eight developing countries. The eight case studies included poverty and food security maps, the data sets, preprints of journal articles for a special issue of Food Policy, standardized geospatial metadata and a browse graphic showing key maps. The different case studies use cutting-edge poverty mapping techniques such as small area estimation. The countries included in the project were Bangladesh, Ecuador, Kenya, Malawi, Mexico, Nigeria, Sri Lanka and Vietnam. The data set also includes data for Honduras. The case studies were published here: https://www.sciencedirect.com/journal/food-policy/vol/30/issue/5

Bangladesh, Ecuador, Kenya, Malawi, Mexico, Nigeria, Sri Lanka, Viet Nam, Honduras

Geospatial data

Quantitative data

Interpolated Data

Aggregate data

Models

Socioeconomic data

Geographic data

Environmental data

Climate data

All these materials are available on the original website for the study located at http://gisweb.ciat.cgiar.org/povertymapping/, as of July 29, 2020.

Whilst utmost care has been taken by CIAT and data authors while collecting and compiling the data, the data is however offered "as is" with no express or implied warranty. In no event shall the data authors, CIAT, or relevant funding agencies be liable for any actual, incidental or consequential damages arising from use of the data. <BR/><BR/> By using the CIAT Dataverse, the user expressly acknowledges that the Data may contain some nonconformities, defects, or errors. No warranty is given that the data will meet the user's needs or expectations or that all nonconformities, defects, or errors can or will be corrected. <BR/><BR/> The user should always verify actual data; therefore the user bears all responsibility in determining whether the data is fit for the user’s intended use. The user of the data should use the related publications as a baseline for their analysis whenever possible. Doing so will be an added safeguard against misinterpretation of the data. Related publications are listed in the metadata section of the Dataverse study.

<P><a rel="license" href="http://creativecommons.org/licenses/by/4.0/" target="_blank"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br /> These data and documents are licensed under a <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank"> Creative Commons Attribution 4.0 International license.</a> You may copy, distribute and transmit the data as long as you acknowledge the source through proper <a href="http://best-practices.dataverse.org/data-citation/" target="_blank">data citation</a>.</P> <Strong>Disclaimer</Strong> <P> Whilst utmost care has been taken by CIAT and data authors while collecting and compiling the data, the data is however offered "as is" with no express or implied warranty. In no event shall the data authors, CIAT, or relevant funding agencies be liable for any actual, incidental or consequential damages arising from use of the data. <BR/><BR/> By using the CIAT Dataverse, the user expressly acknowledges that the Data may contain some nonconformities, defects, or errors. No warranty is given that the data will meet the user's needs or expectations or that all nonconformities, defects, or errors can or will be corrected. <BR/><BR/> The user should always verify actual data; therefore the user bears all responsibility in determining whether the data is fit for the user’s intended use. The user of the data should use the related publications as a baseline for their analysis whenever possible. Doing so will be an added safeguard against misinterpretation of the data. Related publications are listed in the metadata section of the Dataverse study. </P>

<a href=https://gisweb.ciat.cgiar.org/povertymapping/>https://gisweb.ciat.cgiar.org/povertymapping/</a>

Glenn Hyman, Carlos Larrea, Andrew Farrow, Methods, results and policy implications of poverty and food security mapping assessments, Food Policy, Volume 30, Issues 5–6, 2005, Pages 453-460, ISSN 0306-9192, https://doi.org/10.1016/j.foodpol.2005.10.003.

10.1016/j.foodpol.2005.10.003

Glenn Hyman, Carlos Larrea, Andrew Farrow, Methods, results and policy implications of poverty and food security mapping assessments, Food Policy, Volume 30, Issues 5–6, 2005, Pages 453-460, ISSN 0306-9192, https://doi.org/10.1016/j.foodpol.2005.10.003.

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01 Bangladesh.pdf

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Preprint of Bangladesh study published in a special issue of the Journal food policy

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02 Bangladesh.zip

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GIS format files with Bangladesh poverty data

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03 Geographical Concentration of Rural Poverty in Bangladesh.html

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Geospatial metadata for Bangladesh poverty map

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04 Ecuador.pdf

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Preprint of Ecuador study published in a special issue of the Journal food policy

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05 Ecuador.zip

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Ecuador GIS format files with poverty and environmental data

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06 drymonths.jpg

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Map of the number of dry months for Ecuador

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07 ecuador_acc.jpg

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Map of time to cities of 50,000 or more in Ecuador

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08 Ecuador_headcount.jpg

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Headcount ratio 1998-2001

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09 Ecuador_PovIntensity1990.jpg

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Poverty intensity in Ecuador, 1990

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10 Ecuador_PovIntensity2001.jpg

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Poverty intensity in Ecuador, 2001

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11 Ecuador_PovCons2001.jpg

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Incidence of poverty consumption, 2001

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12 Accessibility to Local Markets, Ecuador..html

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Geospatial metadata for accessibility model of Ecuador

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13 Ecuador - Poverty 2001.html

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Geospatial metadata of 2001 Ecuador poverty map

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14 Ecuador - Poverty Headcount 1998-2001.html

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Geospatial data of 1998 to 2001 poverty headcount map of Ecuador

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15 Ecuador - Unsatisfied Basic Needs (UBN) 1990.html

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Geospatial data of unsatisfied basic needs map of Ecuador for 1990

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16 Ecuador - Unsatisfied Basic Needs (UBN) 2001.html

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Geospatial data of unsatisfied basic needs map of Ecuador for 2001

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17 Number of Consecutive Dry Months, Ecuador.html

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Geospatial metadata for data and map of the number of consecutive dry months in Ecuador

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18 Honduras.zip

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GIS format files of poverty indicators for Honduras

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19 municipios_pobreza.gif

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Browse graphic of Honduras poverty map

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20 Honduras - Unsatisfied Basic Needs (UBN) 1988, Human Development Index (HDI) and UBN 2001.html

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Geospatial metadata for data set of poverty indicators for Honduras, including human development index and unsatisfied basic needs maps.

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21 Kenya.pdf

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Preprint of Kenya study published in a special issue of the Journal food policy

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22 Kenya.zip

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GIS format files for one district in Kenya with poverty data

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23 kenya_poverty.gif

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Browse graphic of Kenya poverty map

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24 Kenya - Kajiado - Poor People Density.html

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Poverty data set for Kenya’s Kajiado District, showing the density of poor people

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25 Malawi.pdf

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Preprint of Malawi study published in a special issue of the Journal food policy

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26 Malawi.zip

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GIS format files for poverty map of Malawi

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27 malawi_ruralaggreg.gif

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Browse graphic of Malawi poverty map

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28 Malawi - Poverty Headcount.html

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Geospatial metadata for poverty data set of Malawi in Africa

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29 Mexico.pdf

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Preprint of Mexico study published in a special issue of the Journal food policy

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30 Mexico.zip

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GIS format files for food poverty data at municipality level for Mexico

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31 mexico_foodPoverty.gif

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Browse graphic of Mexico poverty map

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32 Mexico - Mexican Municipalities below Food Poverty Line.html

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Geospatial metadata for Mexican data set of municipalities with data on the food poverty line.

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33 Nigeria.pdf

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Preprint of Nigeria study published in a special issue of the Journal food policy

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34 Nigeria.zip

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GIS format files for poverty and nutrition data for Nigeria

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36 Nigeria_poverty.jpg

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Browse graphic of Nigeria poverty map

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37 Income Poverty, Vitamin A and Iodine in Nigeria.html

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Geospatial metadata for data set of poverty and nutrition in Nigeria

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38 SriLanka.pdf

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Preprint of Sri Lanka study published in a special issue of the Journal food policy

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39 SriLanka.zip

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GIS format files for poverty data for Sri Lanka

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40 Sri Lanka - Poverty at District Level.html

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Geospatial metadata of Sri Lanka poverty data set at the district level

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41 Vietnam.pdf

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Preprint of Vietnam study published in a special issue of the Journal food policy

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42 Vietnam.zip

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GIS format files for poverty data for Vietnam

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43 Vietnam - Poverty Distribution.html

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Geospatial metadata of Vietnam poverty data set

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