analysing relationships among socio- economic, environmental, governance, and water supply and...
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Analysing relationships among socio- economic, environmental, governance, and water supply and sanitation variables in developing countries Summary Sept 2009-2010
Celine DONDEYNAZSupervisors: Prof Chen, Dr C Carmona-Moreno, Dr X Zhang
Background
GOAL 7 : Environmental sustainability Target 3Halve, by 2015, the proportion of the population without sustainable access to safe drinking water and basic sanitation
Indicators on Water Supply and Sanitation (WSS)-Proportion of the population having access to improved water source -Proportion of the population having access to improved sanitation
United Nations Millennium Goals for Development
International initiative to reduce poverty by 2015
To reach this objective intermediate goals were established
http://www.un.org/millenniumgoals/
Pit latrine in Lalibela , Ethiopia, C.Dondeynaz
Subject and questions
The efficiency of the WSS management in a specific developing country = a combination of a wide range of variables¹= > a complex and a cross cutting issue
OBJECTIVE :Better understand the keys elements involved in an improved WSS management.
Main QUESTIONS1. Are the different variables and data coherent enough to establish spatial-temporal behaviors?
2. Can be established measurable protocols and can behavior patterns be extrapolated in time and at other spatial scales?
3. Can data and patterns be integrated into a tool for better understanding these mechanisms ?
¹ Integrated water resources management Principles laid down at the International Conference on Water and the Environment held in Dublin in January 1992
DATA COLLECTION
Scope of the data collection International data providers : UNEP – FAO – JRC – WB … Scale : National country level over the world Time series : consistency issue requires a strict
examination of data coherence and methodologies. 2004 year of reference
Variables selection criteria Relevance : potential role regarding water supply and
sanitation Data availability : enough observations Reliability : produced by trustfully providers and
described132 indicators examined shortlist of 53 indicators
Logical framework of dataEnvironmental Cluster
• Water resources availability
(Water poverty index, Water stress, water bodies ...)
• Land cover indicators (dryland coverage, forest cover..)
Human pressure Cluster
• Activities pressure ( water demand, irrigation level, industrial pollution, production indexes..)
• Demographic pressure ( growth, repartition Urban-rural
Accessibility to WSS Cluster
• Population access to Sanitation
• Population access to Water Supply
Country Well being Cluster
• Health indicators (water-born disease, mortality, life expectancy..)
• Poverty indicators ( HDI, National poverty index, education level...)
•Education indicators
Official Development aid flow : global and WSS ODA
Governance cluster
Stability and level of violence, government effectiveness, rule of law, regulatory quality , control of corruption
Missing data treatment
Objective : Qualitative approach –> find order of range rather than
exact valueMethods
0.0 0.2 0.4 0.6 0.8 1.0 1.2
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Observed and Imputed values of NBI
NBI -- Percent Missing: 0.16
Re
lativ
e D
en
sity
2. Expectation – Maximization algorithm combined with bootstraps (EMB)1
1.Manual Hot deck imputation for series having few missing data
¹Amelia II software is provided by Honaker James, King Gary, Blackwell Matthew, http://gking.harvard.edu/amelia/
Verification of dataset coherence
Initial verification process 1. Variable normalization
2. Principal Component Analysis (PCA) performance to see correlations
3. Linear regression to find out key elements explaining the WSS level paying attention to coherence
Step 1. Checking the Normal Distribution of the variables
• Standard normalization not possible on the worldwide dataset because of too diverse behaviour among countries
• So Restriction on African data to smaller dataset as a preliminary phase
Test phase on AfricaStep 2 : Checking Variable Relationships
Coherence (PCA Analysis)
Agri.Area.
WaterBodies
Particip to IEAg
WGI.RofL
WGI.RQ
NBI
WGI.W.A.2004
RatioGirls.to.boys
GI Afr
WGI.GE
PovertyRates
Malaria.2004
CPI.
Official.Dev.Aid
Environmental.gov
ODA.WSS.TOT
WGI.PS.AV.2004
X.DryLands
Femal.economic.activity
DAM.Capacity.Pond.Surf
WaterUseInt.Agri
TOT..AIWS.
GrowthUrban
School EnrolmentHealth.expenditurel
Tot.Irrigation
GrowthRural
TOT.AIS.2004
ESI.
Literacyrate.youth
PRECIPIT
water_.hous_connect.
HDI.2005
HPI.1.
FertilRates
LifeExpectBirth
Tot.WITH.
%diarrhea in urban slums
WaterPoverty.
Mortal_u5
BOD.emissions
GDP.PPP.
WITH.IndTIWRR.WITH.Dom.
AgriProdIndex.
Children with diarrhea
UrbanPop
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1
F1
F2
Group 1 Group 2
Group 4
Group 3
Figure 1: the first two PCA factors of variables, (accumulated variability equal to 43,02%)Figure 1: the first two PCA factors of variables, (accumulated variability equal to 43,02%)
Adjusted R2 = 50.386-> Coherence of the relationships observed with expectations :
On F1 axis group 1-2 representing the society development – poverty
On F2 group 3-4 represents the balance between water demand and resources
Coherency of the dataset on Africa
For water supply coverage53% variability explained
For water supply coverage70% variability explained
Test phase on AfricaStep 3 : Getting first key variables (Linear Regression)
Source Value SE Pr > |t| Lower bound (95%)
Upper bound (95%)
Mortal_u5.2005 -0.584 0.130 < 0.0001 -0.847 -0.320UrbanPop.pop_2005 0.176 0.100 0.086 -0.026 0.379
WGI.PS.AV.2004 -0.226 0.115 0.056 -0.459 0.006
WGI.GE2004 -0.357 0.182 0.057 -0.726 0.012GrowthUrbanPop_2000.
20050.184 0.096 0.064 -0.011 0.378
RatioGirls.to.boys.98.01 0.115 0.129 0.380 -0.147 0.376Tot.Irrigation....Agr_are
a.20030.137 0.094 0.154 -0.054 0.328
CPI.2004 0.343 0.189 0.078 -0.040 0.725PovertyRates.1987.2006
.0.244 0.102 0.021 0.038 0.451
%diarrhea in urban slums
-0.224 0.124 0.078 -0.475 0.026
Environmental.gov 0.388 0.110 0.001 0.165 0.611Gross.enrolement -0.276 0.149 0.073 -0.578 0.027
Health.expenditure 0.239 0.155 0.132 -0.075 0.552
Source
Value SE Pr > |t| Lower bound (95%)
Upper bound (95%)
FertilRates2000.2005 -0.206 0.246 0.408 -0.702 0.291
Mortal_u5.2005 0.221 0.213 0.305 -0.208 0.651
UrbanPop.pop_2005 0.365 0.127 0.006 0.108 0.622
WGI.PS.AV.2004 -0.396 0.171 0.026 -0.741 -0.050
WGI.RofL.2004 0.640 0.291 0.033 0.053 1.227
RatioGirls.to.boys.98.01 0.245 0.124 0.055 -0.005 0.496
Tot.Irrigation2003 0.133 0.123 0.285 -0.115 0.381
CPI.2004 -0.346 0.216 0.118 -0.783 0.091
BOD.emission 98 0.131 0.123 0.293 -0.117 0.379
Environmental.gov 0.234 0.129 0.078 -0.027 0.495
Key elements 1. Mortality of children under 52. The environmental management capacity but non only3. Living conditions4. The urbanisation process
Key elements1.The governance aspects (general +environmental)2. The urbanisation process3.The irrigation capacity and BOD as expressing
technical progress level.4. An unexpected point is the education of girl at primary
level.
Next activities and planning
Confirm and expand analyses on Africa1. Complementary analyses
2. Find complementary variables to increase the level of variability explained (sanitation)
3.Paper Submission for publication
4. Regroup variables to end up with few key indicators explaining the WSS level
5. Analyze different country behaviors to build country profiles
Octobre 10
Decembre 10
May 2011
Publication 2009-2010
• Article on dataset building, data collection, imputation and verification of coherence
almost ready ( Conference 2011)
• Article on preliminary results on AfricaTo be submitted in December 2010
• JRC Report to be published by mid-October
Conclusion
Thanks you for attention Questions ?
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