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ID:
115241
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| Publication |
2012.
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| Summary/Abstract |
In this paper, we present highly disaggregated estimates of expenditure-based poverty in Fiji using data from the 2007 national census and 2008-2009 Household Income and Expenditure Survey. Predicted poverty is estimated at provincial and tikina levels. Poverty in Fiji is marked by considerable spatial heterogeneity that cannot be gauged by the division level household survey estimates revealing pockets of poverty even within relatively well-off regions. Predicted poverty is highest in Cakaudrove province in Northern Division. Most strikingly, we find that 50% of all the poor in Fiji are concentrated in just 6 out of 85 tikinas, namely Suva, Labasa, Ba, Naitasiri, Vuda and Nadi. This finding has important implications for efficiency of targeted poverty alleviation programmes. We also focus on squatter settlements for which poverty headcount estimates using the Household Income and Expenditure Survey are not feasible. We find these settlements have rates of poverty headcount ratio that range from 38-55% depending on the Division the squatter settlement is located in; this range is significantly higher compared with the average urban poverty estimated at 26% and raises important social policy issues for addressing urban poverty.
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| 2 |
ID:
168698
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| Summary/Abstract |
This paper attempted to calculate a composite index that would represent the magnitude of incidence and intensity of multidimensional household energy poverty (MEPI) in the Philippines using seven indicators of energy deprivation to analyse 17 regions and 81 provinces. Generally, the MEPI scores of regions from 2011 to 2016 revealed that the proportion of the multidimensional energy poor across all regions improved. Moreover, the study systematically put together a composite index that aims to capture the multidimensional aspects of household energy poverty. It consciously avoided a uni-dimensional stance in measuring energy poverty. Among the seven indicators, access to communication and education related appliances consistently had the highest incidence of deprivation among households across all regions at 90.4 percent. Conversely, a Filipino household is identified as multidimensional energy poor if it is deprived in at least the equivalent of 50 percent of the weighted seven indicators to be considered multidimensional poor. On the average, households in the Philippines are experiencing lower moderate energy poverty. Among the regions, Luzon (except MIMAROPA and Bicol) experienced low energy poverty levels. The energy-poorest regions are ARMM and Region IX (Zamboanga Peninsula). The statistical result suggests the association of MEPI and income poverty incidence points out a high correlation. In conclusion, an increase in poverty incidence would lead to a more multidimensionally deprived household. The correlation outcome validates that a significant relationship exists between MEPI and income poverty.
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