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PHDR: Geographic Diversity of Poverty Professor Amani, ESRF
Poverty and Human Development Report
Geographic Diversity of Poverty
Summary of regional performance by single (PRSP) indicators
Frequency ranking among best/worst 5
Region Best Worst BalanceKilimanjaro 22 2 20DSM 15 4 11Tabora 14 6 8Mbeya 10 3 7Ruvuma 10 5 5Iringa 12 9 3Arusha 6 4 2Tanga 7 5 2Morogoro 6 5 1Mtwara 4 5 -1Singida 7 8 -1Kigoma 5 6 -1Mwanza 6 8 -2Mara 7 10 -3Dodoma 2 5 -3Shinyanga 6 9 -3Kagera 5 10 -5Lindi 5 12 -7Rukwa 3 10 -7Pwani 1 9 -8Source: PHDR, Repoa 2002
Note: This map is generated with the Tanzania Socio-economic Database (TSED), National Bureau of Statistics, 2002
Note : The boundaries and the names shown and the designations used on these maps do not imply official endorsement or acceptance by the United Nations.
Dodoma
Arusha Kilimanjaro
Tanga
Morogoro
PwaniDar Es Salaam
Lindi
MtwaraRuvuma
IringaMbeya
Singida
Tabora
Rukwa
Kigoma
Shinyanga
Kagera
Mwanza
Mara
Best performing regions
Missing Data
Poor performing regionsModerately performing regions
Human Development Index by Region
HDI Rank Region HDI value1 Dar-es- 0.7342 Kilimanjaro 0.6033 Mbeya 0.5404 Arusha 0.5395 Iringa 0.5146 Ruvuma 0.5027 Mtwara 0.4888 Tabora 0.4869 Singida 0.468
10 Morogoro 0.46311 Pwani 0.44912 Tanga 0.44713 Mara 0.44714 Dodoma 0.42515 Kigoma 0.42016 Kagera 0.41617 Mwanza 0.41418 Lindi 0.40719 Shinyanga 0.39420 Rukwa 0.390
Source: PHDR, Repoa 2002
Dodoma
Arusha Kilimanjaro
Tanga
Morogoro
PwaniDar Es Salaam
Lindi
MtwaraRuvuma
IringaMbeya
Singida
Tabora
Rukwa
Kigoma
Shinyanga
Kagera
Mwanza
Mara
High HDI Medium HDILow HDI
Missing Data
Mainland HDI 0.482
Human Poverty Index by Region
HPI Rank Region HPI value1 DSM 21.42 Kilimanjaro 22.63 Mbeya 28.74 Arusha 29.75 Singida 30.36 Ruvuma 30.47 Morogoro 34.28 Kigoma 36.69 Mtwara 36.8
10 Iringa 37.411 Tabora 37.612 Dodoma 38.113 Rukwa 39.314 Mwanza 39.315 Mara 40.416 Tanga 40.717 Shinyanga 42.318 Pwani 44.919 Lindi 47.220 Kagera 50.9
Source: PHDR, Repoa 2002
Dodoma
Arusha Kilimanjaro
Tanga
Morogoro
PwaniDar Es Salaam
Lindi
MtwaraRuvuma
IringaMbeya
Singida
Tabora
Rukwa
Kigoma
Shinyanga
Kagera
Mwanza
Mara
High HPI Medium HPILow HPI
Missing Data
Mainland HPI 36.3
This presentation
Introduction Methodologies
Single indicator approach Human Development Index
(HDI) Human Poverty Index (HPI)
Concluding remarks
General Findings
IntroductionWhy analysis of poverty status at sub-national level?
Increased awareness among stakeholders on sub-national differences
Contribution to better focused more effective policies and strategies
Guidance to resource allocation of resources to local authorities, contributing to improved planning at that level
MethodologyChoice of methodology to
assess regional differences in status of poverty depends on purpose of the assessment
To inform planning, policy or strategy development within a sector
To raise awareness and advocate on the overall regional status of human development in a country
Single Indicator Approach
Composite Index Approach
Methodology
Single Indicator Approach
Based on PRSP indicators Total of 28 indicators
from 4 clusters:
Performance by region and ranking included
• Income poverty• Human
capabilities• Survival• Nutrition
Methodology
Human Development Index (HDI)
• Summary measure of human development
• It measures average (regional) achievements in three basic dimensions of human development• A long and healthy
life (life expectancy at birth)
• Knowledge (adult literacy rate, gross enrolment rate)
• A decent standard of living (GDP per capita PPP)
Methodology
Human Development Index (HDI)
PHDR: consumption expenditure (CE)per capita used in stead of GDP per
capita PPP.
Data more reliable and more recent
CE direct measure of standard of living and reflects the situation at household level better than GDP
Methodology
Human Poverty Index (HPI)
Summary measure of deprivation in three basic dimensions of human development
• Lack of a long and healthy life. Vulnerability to death at early age (probability of not surviving beyond 40 yrs)
• Lack of knowledge. Exclusion from learning(adult illiteracy )
• Lack of a decent standard of living (population not using safe water, percentage of children <5 who are underweight)
General Findings
Single Indicator Approach
Analysis
• Interregional disparities
• Performance of a region on a range of indicators
• Identification of trends and patterns
Aru
sh
a
DS
M
Do
do
ma
Irin
ga
Kag
era
Kig
om
a
Basic needs poverty headcount ratio (%)
39 18 34 29 29 388 20 12 17 16 10
Rural Basic needs poverty headcount ratio (%)
43 n.a. 36 30 19 438 n.a. 12 17 19 7
Food poverty headcount (%)
25 7 13 10 18 217 20 13 17 10 9
Rural food poverty headcount (%)
28 n.a. 14 11 5 255 n.a. 13 16 19 7
TABLE 2: Income poverty indicators
General Findings
Analysis Interregi
onal disparities
Performance of a region on a range of indicators
Identification of trends and patterns
Single Indicator Approach
• PNER Tanzania 57%
• Kilimanjaro 80.5%
• Lindi 43%Iringa
• Among best 5 on 12 indicators
• Among worst 5 on 9 indicators
• Dar es Salaam and Kilimanjaro region consistently among best 5 for PRSP indicators
• Pwani, Lindi, Rukwa consistently among worst 5 for PRSP indicators
General Findings
Single Indicator ApproachSummary of regional performance by single (PRSP) indicators
Frequency ranking among best/worst 5
Region Best Worst BalanceKilimanjaro 22 2 20DSM 15 4 11Tabora 14 6 8Mbeya 10 3 7Ruvuma 10 5 5Iringa 12 9 3Arusha 6 4 2Tanga 7 5 2Morogoro 6 5 1Mtwara 4 5 -1Singida 7 8 -1Kigoma 5 6 -1Mwanza 6 8 -2Mara 7 10 -3Dodoma 2 5 -3Shinyanga 6 9 -3Kagera 5 10 -5Lindi 5 12 -7Rukwa 3 10 -7Pwani 1 9 -8Source: PHDR, Repoa 2002
Note: This map is generated with the Tanzania Socio-economic Database (TSED), National Bureau of Statistics, 2002
Note : The boundaries and the names shown and the designations used on these maps do not imply official endorsement or acceptance by the United Nations.
Dodoma
Arusha Kilimanjaro
Tanga
Morogoro
PwaniDar Es Salaam
Lindi
MtwaraRuvuma
IringaMbeya
Singida
Tabora
Rukwa
Kigoma
Shinyanga
Kagera
Mwanza
Mara
Best performing regions
Missing Data
Poor performing regionsModerately performing regions
General Findings
HDI rank
Life expectancy
at birth (years) 1988
Adult literacy
rate (% age15
and above) 2000
Combined primary,
secondary and
tertiary gross
enrolment ratio (%)
2000
Mean monthly consumption expenditure per capita (000 Tsh)
2000
Life expectancy
indexEducation
indexExpenditure
index
Human development index (HDI)
value1 Dar-es-Salaam 50 91 98.7 21.9 0.417 0.935 0.849 0.7342 Kilimanjaro 59 85 104.4 11.2 0.567 0.914 0.327 0.6033 Mbeya 47 79 99.7 12.6 0.367 0.858 0.395 0.5404 Arusha 57 78 84.1 10.3 0.533 0.800 0.283 0.5395 Iringa 45 81 102.5 11.2 0.333 0.881 0.327 0.5146 Ruvuma 49 84 89.4 9.6 0.400 0.857 0.249 0.5027 Mtwara 46 68 83.3 12.4 0.350 0.730 0.385 0.4888 Tabora 53 65 81.3 10.4 0.467 0.704 0.288 0.4869 Singida 55 71 94.5 6.9 0.500 0.788 0.117 0.46810 Morogoro 46 72 87.2 10.0 0.350 0.770 0.268 0.46311 Pwani 48 61 79.7 10.5 0.383 0.672 0.293 0.44912 Tanga 49 67 78.4 9.3 0.400 0.707 0.234 0.44713 Mara 47 76 88.7 8.0 0.367 0.802 0.171 0.44714 Dodoma 46 66 86.9 8.5 0.350 0.729 0.195 0.42515 Kigoma 48 71 80.1 7.3 0.383 0.740 0.137 0.42016 Kagera 45 64 80.5 9.0 0.333 0.694 0.220 0.41617 Mwanza 48 65 75.1 8.1 0.383 0.683 0.176 0.41418 Lindi 47 58 67.6 9.5 0.367 0.611 0.244 0.40719 Shinyanga 50 55 68.0 8.0 0.417 0.593 0.171 0.39420 Rukwa 45 68 83.2 6.7 0.333 0.730 0.107 0.390
TANZANIA 50 71 84.9 10.1 0.417 0.756 0.273 0.482
HumanDevelopmentIndex
Marked gap
between 1-2, 2-
rest
General Findings
Human Development IndexHuman Development Index by Region
HDI Rank Region HDI value1 Dar-es- 0.7342 Kilimanjaro 0.6033 Mbeya 0.5404 Arusha 0.5395 Iringa 0.5146 Ruvuma 0.5027 Mtwara 0.4888 Tabora 0.4869 Singida 0.468
10 Morogoro 0.46311 Pwani 0.44912 Tanga 0.44713 Mara 0.44714 Dodoma 0.42515 Kigoma 0.42016 Kagera 0.41617 Mwanza 0.41418 Lindi 0.40719 Shinyanga 0.39420 Rukwa 0.390
Source: PHDR, Repoa 2002
Dodoma
Arusha Kilimanjaro
Tanga
Morogoro
PwaniDar Es Salaam
Lindi
MtwaraRuvuma
IringaMbeya
Singida
Tabora
Rukwa
Kigoma
Shinyanga
Kagera
Mwanza
Mara
High HDI Medium HDILow HDI
Missing Data
Mainland HDI 0.482
General Findings
Human Poverty Index
HPI rank Region
Probability at birth of
not surviving to
age 40 1988
Adult illiteracy rate (% age 15
and above) 2000
Population without
access to safe water
2000
Underweight children
under age 5 (%) 1996 HPI value
1 Dar-es-Salaam 0.41 9.0 6.4 22.2 21.42 Kilimanjaro 0.31 15.0 22.7 21.0 22.63 Mbeya 0.42 21.0 25.1 20.8 28.74 Arusha 0.29 22.0 41.0 35.1 29.75 Singida 0.27 30.0 39.1 28.4 30.36 Ruvuma 0.37 16.0 46.9 29.4 30.47 Morogoro 0.46 29.0 29.6 25.5 34.28 Kigoma 0.47 29.0 24.2 43.1 36.69 Mtwara 0.36 33.0 47.0 35.6 36.8
10 Iringa 0.46 19.0 46.2 48.2 37.411 Tabora 0.33 35.0 75.4 14.2 37.612 Dodoma 0.46 34.0 34.5 34.2 38.113 Rukwa 0.48 32.0 45.5 30.5 39.314 Mwanza 0.46 35.0 46.9 27.0 39.315 Mara 0.58 24.0 59.4 18.9 40.416 Tanga 0.44 33.0 54.0 36.2 40.717 Shinyanga 0.38 45.0 60.1 27.8 42.318 Pwani 0.46 39.0 65.2 34.3 44.919 Lindi 0.39 42.0 80.0 41.4 47.220 Kagera 0.65 36.0 67.2 36.0 50.9
Tanzania Mainland 0.43 29.0 44.3 29.4 36.3
HumanPovertyIndex
Marked gap between
Kilimanjaro and
Mbeya
Regardless of Methodology
Dar es Salaam, Kilimanjaro,
Mbeya and Ruvuma
consistently at top end of
the ranking
Lindi and Shinyanga
consistently at bottom end
of ranking
General Findings
Human Poverty Index by Region
HPI Rank Region HPI value1 DSM 21.42 Kilimanjaro 22.63 Mbeya 28.74 Arusha 29.75 Singida 30.36 Ruvuma 30.47 Morogoro 34.28 Kigoma 36.69 Mtwara 36.8
10 Iringa 37.411 Tabora 37.612 Dodoma 38.113 Rukwa 39.314 Mwanza 39.315 Mara 40.416 Tanga 40.717 Shinyanga 42.318 Pwani 44.919 Lindi 47.220 Kagera 50.9
Source: PHDR, Repoa 2002
Dodoma
Arusha Kilimanjaro
Tanga
Morogoro
PwaniDar Es Salaam
Lindi
MtwaraRuvuma
IringaMbeya
Singida
Tabora
Rukwa
Kigoma
Shinyanga
Kagera
Mwanza
Mara
High HPI Medium HPILow HPI
Missing Data
Mainland HPI 36.3
Human Poverty Index
General Findings
Inconsistencies when comparing HDI and HPI
1
20
10
HDI rank
HPI rank
18
13
Pwani (11)
Rukwa (20)
Caused by different indicators used in HDI and HPI
• Absence of expenditure component in HPI improves Rukwa’s ranking, but has a negative effect on Pwani’s Ranking
• Introducing access to safe water in the equasion for HPI has a negative effect on the ranking of Pwani.
Concluding remarks This analysis provides further
evidence on diversity of poverty in Tanzania
A national perspective alone obscures details important for informed decision making on poverty reduction
The methodologies used reveal both similarities in regional performance as well as differences
No single methodology will provide all answers
More in depth analysis required focusing on WHY some regions perform better than others
Future work may also include sub-regional analysis, using census data and poverty mapping