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To achieve this, MCA analyses a multiway table of all associations amongst pairs of indicators (variables), As out aim is to reduce and not model poverty/deprivation, we opt for descriptive methods of the kind Operatively, MCA performs a simple corrrespondece analaysis on the Burt matrix. The main advantage

Table 2 To achieve this, MCA analyses a multiway table of all associations amongst pairs of indicators (variables), As out aim is to reduce and not model poverty/deprivation, we opt for descriptive methods of the kind Operatively, MCA performs a simple corrrespondece analaysis on the Burt matrix. The main advantage

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Panel A: Sudan Figure 2: Gender Status of the Illiterate Adult Population, by State
Panel A: Sudan Figure 2: Gender Status of the Illiterate Adult Population, by State
Panel B: South Sudan Thus, Khartoum and Upper Nile are the states in Sudan and South Sudan, respectively, with the largest distribution of illiteracy gender gaps across all other states for the two countries shows that most of
Panel B: South Sudan Thus, Khartoum and Upper Nile are the states in Sudan and South Sudan, respectively, with the largest distribution of illiteracy gender gaps across all other states for the two countries shows that most of
Panel B: South Sudan
Panel B: South Sudan
Public and private assets Table 2: Household Expenses by Sub-Category of Consumption The welfare pattern in the distribution of public assets indicates that households in Sudan are better off
Public and private assets Table 2: Household Expenses by Sub-Category of Consumption The welfare pattern in the distribution of public assets indicates that households in Sudan are better off
Panel A: Sudan the four public assets indicators and is the one we use in the next two sections.
Panel A: Sudan the four public assets indicators and is the one we use in the next two sections.
MCA of “Private” Assets As with public assets, we also apply MCA to the indicators of private assets in each country. The results
MCA of “Private” Assets As with public assets, we also apply MCA to the indicators of private assets in each country. The results
Panel A: Sudan
Panel A: Sudan
Panel B: South Sudan Unidimensional Poverty Section 3 described the patterns of welfare status among Sudanese and South Sudanese households. In
Panel B: South Sudan Unidimensional Poverty Section 3 described the patterns of welfare status among Sudanese and South Sudanese households. In
9 Standard errors and confidence intervals of each estimated poverty rate are reported in Appendix A.3, Table A.3.1. 10 Standard errors and confidence intervals of each estimated poverty rate are reported in Appendix A.3, Table A.3.2. By Sudanese states, Khartoum exhibits the lowest poverty incidence in three out of the four dimensions
9 Standard errors and confidence intervals of each estimated poverty rate are reported in Appendix A.3, Table A.3.1. 10 Standard errors and confidence intervals of each estimated poverty rate are reported in Appendix A.3, Table A.3.2. By Sudanese states, Khartoum exhibits the lowest poverty incidence in three out of the four dimensions
In South Sudan, the state profiles of poverty among children clearly point towards two states: Western
In South Sudan, the state profiles of poverty among children clearly point towards two states: Western
Table 8: Unidimensional Poverty Profiles
Table 8: Unidimensional Poverty Profiles
Table 9: Multidimensional Poverty Profiles important regional and sub-population differences in unidimensional and multidimensional poverty in
Table 9: Multidimensional Poverty Profiles important regional and sub-population differences in unidimensional and multidimensional poverty in
Note: The masses and % of inertia of categories across all variables add up to 100%.
Note: The masses and % of inertia of categories across all variables add up to 100%.
Note: The masses and % of inertia of categories across all variables add up to 100%. Appendix A.2 — MCA on Indicators of Private Assets
Note: The masses and % of inertia of categories across all variables add up to 100%. Appendix A.2 — MCA on Indicators of Private Assets
Panel A: Sudan
Panel A: Sudan
Head Count Ratio (“%)
Head Count Ratio (“%)
Note: Standard errors are in italics.
Note: Standard errors are in italics.
Note: Standard errors are in italics. Panel A: Sudan
Note: Standard errors are in italics. Panel A: Sudan
Note: Standard errors are in italics.
Note: Standard errors are in italics.
Note: Standard errors are in italics.
Note: Standard errors are in italics.
Related topics:
Multidimensional PovertyPoverty StudiesSouth SudanMultiple Correspondence AnalysisCounting Approach to poverty measurement
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