Spatial Durbin Model for Poverty Mapping and Analysis
Date
2008Author
Adebanji, A
Achia, T
Ngetich, R
Owino, J
Wangombe, A
Type
ArticleLanguage
enMetadata
Show full item recordAbstract
The use of spatial regression models for describing and explaining spatial data variation in
poverty mapping has become an increasingly important tool. This study considered the
spatial Durbin model (SDM) in identifying possible causes of poverty in Bari region of
Somalia using Somalia settlement census data. Data properties were identified using
exploratory spatial data analysis (ESDA) and the output ESDA provided input into the
spatial Durbin model. Parameter estimation and hypotheses testing and assessment of
goodness of fit were carried out for the specified model. Dissimilarity of neighbouring
settlements in North West Somalia and similarity of neighbouring settlements in North East
and South Central Somalia with respect to the variables of interest were observed using the
Global and Local Moran's I test statistic. The proportion of families who cannot afford two
meals per day was taken as a proxy indicator for poverty level and the implication of the
findings on policy decision making for development planning are discussed.
Citation
Adebanji, A., Achia, T., Ngetich, R., Owino, J., & Wangombe, A. (2008). Spatial Durbin Model for Poverty Mapping and Analysis. Editorial Advisory Board, 5(4), 194.Publisher
University of Nairobi. School of Mathematics