2002
DOI: 10.1086/345454
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The Robustness of Poverty Profiles Reconsidered

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Cited by 69 publications
(39 citation statements)
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“…It is not uncommon for poverty analyses based on the FEI method, where separate poverty lines are calculated, to indicate higher poverty rates in urban than in rural areas. At a given level of income, urban households tend to consume fewer, but more expensive, calories (Tarp et al 2002). Therefore, higher calorie consumption in rural areas is not an uncommon result, and has been found in other similar empirical studies (Hoddinott and Yohannes 2002;Skoufias 2001).…”
Section: Caloric Availabilitysupporting
confidence: 59%
“…It is not uncommon for poverty analyses based on the FEI method, where separate poverty lines are calculated, to indicate higher poverty rates in urban than in rural areas. At a given level of income, urban households tend to consume fewer, but more expensive, calories (Tarp et al 2002). Therefore, higher calorie consumption in rural areas is not an uncommon result, and has been found in other similar empirical studies (Hoddinott and Yohannes 2002;Skoufias 2001).…”
Section: Caloric Availabilitysupporting
confidence: 59%
“…Because consumption baskets used to measure absolute poverty in developing countries ideally reflect consumption patterns of the poor (Deaton 1998;Ravallion and Bidani 1994), steps are increasingly taken to account for these variations (Arndt and Simler 2010). Indeed, under the costs of basic needs approach, failure to account for the specific consumption patterns of the poor can lead to erroneous conclusions about poverty levels and trends (Tarp et al 2002;Günther and Grimm 2007).…”
Section: Motivationmentioning
confidence: 99%
“…Although official poverty estimates have always been reported at a regional level in Malawi, region-specific poverty lines were last constructed using the first IHS1 of 1997/98 (NSO 2010b; also see Mukherjee and Benson 2003). Taking account of 13 regional and temporal differences in prices and preferences, as we do in this study, is likely to alter estimated poverty lines significantly (Tarp et al 2002). Source: Generated by IFPRI GIS analysts using data from Global Administrative Areas (2012).…”
Section: Regions Preferences and Utility Consistencymentioning
confidence: 99%