A pilot of OPHIs Internationally Comparable Indicators on Missing Dimensions of Poverty in urban, ru

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A pilot of OPHIs Internationally Comparable
Indicators on Missing Dimensions of Poverty in
urban, rural and estate communities in Sri Lanka

• PEP training on Survey Design
• OPHI University of Oxford
• 04th 25th March 2009

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Outline of the presentation

• Part 1 Introduction to CEPA and its work
• Poverty Assessment at CEPA
• Relevance of study for CEPA
• Part 2 Conceptual framework Research
  objectives/Questions
• Part 3 Methodology and analysis
• Policy relevance and dissemination of findings
• Part 4 Issues to be consider

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1. Introduction to CEPA and its work

• Independent, non-profit Sri Lankan organization
  providing services on poverty related issues
  (2001)
• Programmatic focus
• Poverty Impact Monitoring (PIM)
• Poverty and Conflict (PAC)
• Poverty Assessment Knowledge Management (PAM)
• Service provision
• Applied Research (APR)
• Advisory Services (ADV)
• Training (TRG)
• Dialogue and Exchange (DAE)
• Quantitative and qualitative applied research for
  informed decision making

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1. Introduction to CEPA and its work (contd.)

• Poverty Assessment at CEPA
• Designated programme at CEPA
• Multidimensional approach reviewing
  measurement methodologies, disaggregated
  analysis
• Generating and disseminating data Poverty
  Database, qualitative indicators, exploring
  alternative dimensions using CEPAs research
• Understanding of practitioners Samurdhi,
  SLIDA, SLPI, training module on understanding
  poverty
• Relevance of the study for CEPA
• Moves forward in understanding poverty in Sri
  Lanka
• Help to understand poverty pockets
• Helps develop policies that can address
  different dimensions of poverty
• Dynamics of poverty

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2. Conceptual framework Research
objectives/Questions

• Development as capability expansion
• The objective of human development is to expand
  the freedoms that people value and have reason to
  value, enabling people to live more fulfilled
  lives and to flourish.
• (Sen,1989)
• Capability approach, sees human life as a set of
  functions. But to asses these functions there is
  a need of multidimensional data.
• (Sen,1989..)
• The reality of poverty in Sri Lanka
• Limited research/discussion on multiple
  dimensions
• HDI MDG indicators misses out on access and
  quality
• Scope to look at other indicators of human
  wellbeing national and local levels

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2. Conceptual framework Research
objectives/Questions (contd.)
Contribution to the global debate on Poverty

• Consensus that poverty is multidimensional but
  less on what this means and how can it be
  measured/verified
• Sri Lanka a good case
• Opportunity for Sri Lanka to be part of the
  debate
• Methodological advancement - Using Q-squared
  approaches
• Opportunity to consolidate all this learning and
  expand on the pilot
• OPHI/CEPA

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2. Conceptual framework Research
objectives/Questions (contd.)

• Research objectives

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2. Conceptual framework Research
objectives/Questions (contd.)

• Research questions
• Validating research questions
• How valid/relevant are the indicators/tools?
• How can the indicators be refined?
• Learning research questions
• What aspects of poverty are captured?
• What makes people poor in the present what
  could make people poor in the future?
• How does vulnerability affect the poor and
  influence the dimensions? How do they cope?
• Feed into poverty reduction policy/practice?

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3. Methodology
External validity testing (qualitative methods)
Internal validity testing (household survey)
using quanti and quali methods

• Objectives
• To test applicability of the To test the
  predesigned
• questions tools
• To prepare tools for Operationalize learning
• quantitative component component
• Sampling
• Method
• Purposive selection of Stratified systematic
• respondents random sample
• Tools
• KPIs HH questionnaire
• FGD 10 of qualitative in depth study

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3. Methodology (contd.)

• External validity testing (qualitative methods)
• Key person interviews (Approximately 12)
• Data producers (quanti/quali) and
• Department of Census and Statistics, SPARC
  (Social Policy Analysis and Research Centre),
  and university departments. Etc .
•  
• Data users
• Samurdhi Authority (the governments cash
  transfer programme), Department of
  NationalPlanning,NGOs such as CARE and Oxfam,
  research organizations, academics and donors
  (World Bank and Etc).

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3. Methodology (contd.)

• Community FGDs
• Why?
• To be able to validate with a wider group having
  characteristics of the dimensions
• Capture as many features that affect the
  dimensions
• What types?

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3. Methodology (contd.)

• Community FGDs (contd.)
• Composition of the FGDs ?
• 6-8 participants
• within a randomly select village ?
• maximum variety of communities within the
  sector ?

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3. Methodology (contd.)

• The sample HH survey
• Revised sample
• Number of sampling units has been increased to
  240 with additional 60, to make the margin of
  error to 6.3 instead of additional increase of
  204 to have 5 margin of error.
•  

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3. Methodology (contd.)

• Badulla district in Uva province
• Rationale
• All 3 sectors are present in the district
• Diversity in poverty (17-51 in poverty) at DS
  level
• Relatively less heterogeneity  enables studying
  dimensions using smaller sample

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3. Methodology (contd.)

• Source World Bank and DCS 2005

Poverty map of Sri Lanka
Badulla
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3. Methodology (contd.)

• The sample
• Stratified systematic sampling method
• DS divisions per sector (strata)
• GNs households (random)
• 32 DS clusters in Badulla

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32 DS clusters in Badulla
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3. Methodology (contd.)

• Proportional allocation for each sector within
  Badulla district

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3. Methodology (contd.)

• Sample distribution within the each sector
• 1st stage - DS-Sectoral cluster at random from
  each sector
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• 2nd stage - GN division (2 GN per DS-Sectoral
  cluster in order to Capture variation within
  cluster) at random within each cluster Note GN
  division covering more than one sector will be
  c onsidered for the major share (E.g..
  Rural/Estate)
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• 3rd stage - households (6 households per GN
  division) at random within GN division

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3. Methodology (contd.)

• Sample is purposively allocated for each sector
• 10 of sample for qualitative component
• HH selection with the support of GN , based on
  the population distribution map,
• Respondent selection HHH /Spouse
• if not any other senior hh member who can
  answer the questionnaire

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3. Analysis

• 1. Validating questions within each dimension
• Qualitative data will use to validate the
  developed questions
• Suggestions to improve the quanti questionnaire
• 2. Identifying factor variables within dimensions
• Descriptive analysis
• Correlation analysis/factor analysis
• Cross sectional/sub-group analysis
• 3. Composite measure for each dimension
• Simple average
• Define weights based on prioritisation/ranking
  data KPIs FGDs

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3. Analysis (CONTD.)

• 4. Household and sectoral profiling (to
  set proxy variables of wellbeing)
• To examine other indicators of household
  wellbeing
• 5. GIS mapping with missing dimensions
• Relative differences in regions between the
  dimensions
• Illustrate poverty pockets/regional disparities

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3. Policy relevance of the study

• Data producers helps fill the gap of having
  micro data, building on consumption indicators
• Data users (national)
• Samurdhi refining selection criteria
• Dep. of National Planning moving away from the
  reliance on consumption indicators and encourage
  data collection to reflect reality
• Data users (donors) supporting recommendations
  to prioritize areas for policy focus

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3. Dissemination of findings

• Consultation and dissemination partners state
  and non-state researchers and practitioners
• Material
• User manual that consolidates the experience for
  further training on poverty assessment and
  analysis
• Electronic working paper
• Increasing availability of meta-data and analysis
  on CEPA poverty database
• Engaging in the global debate CEPA capacity
  building on poverty assessment and global debate

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4.Issues to be consider

• Tool development (KPI,FGD,HH )
• - What other dimensions/indicators need to be
  include (ie.access)
• - HYPOTHISIS
• - Structure of the questionnaire
• -Reliability and validity testing
• Sample - Composition of the KPI,FGD
• - Selection criteria for FGD
• Analysis - Assigning weights
• - Robustness with respect to weights
• - Relation between different dimensions and
  different indicators

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Thank you

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Questions comments