MULTI-DIMENSIONAL POVERTY (MPI) METHODS APPLIED TO THE SAINT LUCIA LABOUR FORCE SURVEY SOME IDEAS FOR THE DEVELOPMENT OF AN OECS MULTI-DIMENSIONAL POVERTY.

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Presentation transcript:

MULTI-DIMENSIONAL POVERTY (MPI) METHODS APPLIED TO THE SAINT LUCIA LABOUR FORCE SURVEY SOME IDEAS FOR THE DEVELOPMENT OF AN OECS MULTI-DIMENSIONAL POVERTY INDEX BASED ON AVAILABLE DATA SOURCES BY EDWIN ST CATHERINE DIRECTOR OF STATISTICS, SAINT LUCIA

ST LUCIA LABOUR FORCE SURVEY (LFS) METADATA Country Year2013 Dataset SourceSaint Lucia Labour Force Survey (LFS) Population Sample8,865 Persons 3,235 Households To Guide and Evaluate Poverty Reduction Interventions

LFS DIMENSIONS & INDICATORS DimensionIndicatorDeprivation Cut-offs Weight EducationEducational Attainment Level (Alt: Years of Schooling) Persons in Households with All Persons at Primary School Level or Below who are 15 Years and over 1/8 LabourHousehold Employment Rate* No Employed as a Percent of Total Number of Persons in Household (less than 1 out of every 5 adults in household employed) 1/8 Household with Any Person 15 – 29 Unemployed Persons Living in Households with an unemployed youth age /8 Child WelfareChildren Living in Over- Crowded Housing (Child Mortality) Person’s Under 15 years living in household with 3 or more persons per bedroom 1/8 Living Standards Asset OwnershipOwnership of less than Four Assets1/8 ConnectivityNo Access to the Internet1/8 Type of HousingPersons Living in Plywood Housing1/8 IncomePersons living below 50% of Mean household income 1/8 1/4 1/2

SAINT LUCIA LFS 2013 INDICATORS HEADCOUNT AND MISSING VALUES DimensionIndicator Raw Headcount Censored* Headcount % Missing Values EducationPerson in HH with only Primary 22.5%14.8% - LabourHousehold Employment Rate* 22.4%20.8% - Household with Any Person 15 – 29 Unemployed 22.5%14.9% - Child WelfareChildren Living in Over- Crowded Housing 17.6%11.2% - Living Standards Asset Ownership 8.2%6.4% - Connectivity to Internet 59.7%32.2% - Type of Housing 16.0%12.1% - Income 30.6%25.9% -

Poverty Cut-off (k) Headcount Ratio (H) Intensity of Deprivation (A) Adjusted Headcount Ratio (M 0 ) 20% 57%40% % 35%49% % 21%57% % 8%67% % 3%88% % 0%100%0 ST LUCIA: ANNUAL LFS 2013 MULTI-DIMENSIONAL POVERTY INDEX RESULTS

H = 35% - THIS MEANS THAT 35% OF THE POPULATION IS POOR (DEPRIVED IN 30% OR MORE DIMENSIONS/INDICATORS), A LIMIT CASE WOULD BE MAXIMUM POVERTY HEADCOUNT IF PERSONS WERE CONSIDERED POOR IF POOR IN ONE OR MORE DIMENSIONS….) A = 49% - ON AVERAGE THE POOR (THOSE DEPRIVED IN 30% OR MORE DIMENSIONS) ARE DEPRIVED IN APPROXIMATELY 49% OF THE INDICATORS. M0 = THE POOR IN THIS SOCIETY EXPERIENCE 17.3% OF THE TOTAL POSSIBLE DEPRIVATIONS THE SOCIETY COULD EXPERIENCE.

LFS HEADCOUNT RATIO UNDER DIFFERENT CUT-OFFS Poverty Cut-off Headcount Ratio Person is poor if they experience deprivations in at least 3 of 10 indicators

ADJUSTED HEADCOUNT RATIO UNDER DIFFERENT CUT-OFFS Poverty Cut-off Adjusted Headcount Ratio

ADJUSTED HEADCOUNT RATIO UNDER DIFFERENT CUT-OFFS BY DISTRICT

RAW HEADCOUNT RATIOS BY URBAN/RURAL

CENSORED HEADCOUNT: PERSONS POOR AND DEPRIVED IN SPECIFIC INDICATORS

OUR MPI SHOULD BE LIKE A HIGH POWERED LENS You can zoom in to see more

REGIONAL EXAMPLES OF MPI THE MULTIDIMENSIONAL POVERTY MEASUREMENT DEVELOPED BY CONEVAL (MEXICO) IS A BI-DIMENSIONAL MEASURE. THE MODEL’S CONCEPTUAL FRAMEWORK IS THE HUMAN RIGHTS APPROACH AND THE DIMENSIONS INCLUDED IN THE MODEL ARE GUIDED BY THE SOCIAL DEVELOPMENT LAW (2004). COLUMBIA HAS ITS OWN VERSION OF THE MPI

INSTITUTIONAL PROCESSES TO ENSURE DATA IS COLLECTED TO DELIVER DEVELOPMENT PARTNERS ( CDB, UN AGENCIES, OECS SEC., ETC.) HAVE AGREED TO SUPPORT THE DEVELOPMENT OF AN HARMONIZED MULTIDIMENSIONAL POVERTY MEASUREMENT (MPM) FOR THE SUB-REGION AS A WAY OF REGULATING THE COLLECTION, ANALYSIS AND DISCUSSION OF CORE SOCIAL. THE MPM WILL INCLUDE THE DEVELOPMENT OF A SUB-REGIONAL MULTIDIMENSIONAL POVERTY INDEX USING: A REVISED LFS AND A REVISED COUNTRY POVERTY ASSESSMENT (CPA) THE DEPRIVATION IN KEY AREAS SUCH AS I) HOUSING, II) EMPLOYMENT, III) SAFE DRINKING WATER, IV) INFORMATION, V) FOOD AND INCOME VI) EDUCATION VII) HEALTH BY GENDER, AGE, GEOGRAPHIC LOCATION, TO SUPPORT THE FORMULATION OF NEW POLICIES AND PROGRAMS THAT CAN ADDRESS AND EFFECTIVELY TARGET DISADVANTAGED GROUPS IN SOCIETY.

CONCLUSIONS Political and policy framework for the indicators and dimensions to be included in the MPI OECS Authority CDB Board Ministerial Meeting on MPI – identify an MPI Champion Minister Questions to Supplement the LFS to make it a more robust tool for constructing an MPI Pool at least one year of this data to report on an annual basis Align the eventual indicators chosen to a philosophical framework, example Human Rights or Post 2015 Sustainable Development Indicators

THANK YOU