Xavier Mancero Statistics Division, ECLAC Seminar on poverty measurement Geneva, 5-6 May 2015.

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Presentation transcript:

Xavier Mancero Statistics Division, ECLAC Seminar on poverty measurement Geneva, 5-6 May 2015

Background Income provides an incomplete assessment of living standards. Possible bias characterizing poverty Income poverty measure does not account for the impact of public policies in various areas of welfare Multidimensional poverty is increasingly being monitored at the country level (Mexico, Colombia, Chile). Social Panorama of Latin America 2014 presented a multidimensional poverty index, that: Builds upon “Unmet Basic Needs” method Includes deprivations in terms of employment, social protection and schooling gap, thus widening the set of dimensions commonly used; Integrates monetary and non-monetary dimensions, so as to minimize errors of inclusion and exclusion in identifying the poor; Includes new deprivation cut-offs that better reflect the current regional reality

Regional multidimensional poverty index DimensionType of deprivationW DwellingInadequate housing materials Overcrowding Insecure housing tenure 22,2% Basic servicesLack of access to improved water source Lack of improved sanitation Source of energy 22,2% EducationNon-attendance Schooling gap Low attainment 22,2% Living standard Insufficient income Lack of durable goods 22,2% Employment and social protection Unemployment Lack of social protection 11,1%

Regional multidimensional poverty index Weights Equal weights (7.4%), excluding social security (3.7%) and income (14.8%). Deprivation of social protection  less associated with the traditional concept of poverty. Income  income is itself a synthetic indicator of welfare. Multidimensional threshold k = 25%. Poor = deprivation in a complete dimension plus an indicator from other dimension; or deprivation in income and at least two additional deprivations. No person who is deprived in only one dimension is identified as multidimensionally poor.

DEPRIVATION INDICATORSW DWELLING22,2% Housing materialsHouseholds with dirt floor or precarious roof or wall materials (waste, cardboard, tin, cane, palm, straw, other materials). 7,4% CrowdingThree or more people per room7,4% Insecure housing tenureHouseholds: (i) living as squatters; or (ii) living in ceded or borrowed housing.7,4% BASIC SERVICES22,2% Water source-Main network off the premises (only in urban areas) -Unprotected wells or lacking a motor pump -Mobile sources (village tank, tank cart, tanker truck, etc.) - Bottled water - River, stream, rainwater, other 7,4% Sanitation-Waste not connected to a sewer system or septic tank (urban areas) -Shared toilet -No sanitation -Waste going untreated to ground surface, river or sea. 7,4% EnergyHouseholds without electricity or using firewood, coal or waste for cooking.7,4% EDUCATION22,2% Non-attendanceHousehold has at least one child of school age (6 to 17 years old) who does not attend school. 7,4% Education lagHousehold has at least one child or adolescent aged 6 to 17 who is more than two years behind schooling grade for age. 7,4% Non-attainmentHousehold has nobody aged 20 or above with a minimum level of schooling. - Persons aged 20 to 59: have not completed lower secondary education. - Persons aged 60 and above: have not completed primary education. 7,4%

DEPRIVATION INDICATORSW LIVING STANDARD22,2% Insufficient resourcesHouseholds with insufficient per capita income to meet food and non-food needs. 14,8% Lack of durable goodsHouseholds that have none of the following goods: (i) vehicle; (ii) refrigerator; (iii) washing machine. 7,4% EMPLOYMENT AND SOCIAL PROTECTION11,1% UnemploymentHousehold has at least one person aged 15 to 65 in one of the following situations: - Unemployed - Employed without pay - Discouraged worker 7,4% Social protectionHousehold has at least one person in one of the following situations: - Without some sort of contributory health insurance - Not affiliated to a contributory social security system - No income from pensions or retirement 3,7%

Source: ECLAC (2014), Social Panorama of Latin America 2014

Contribution of each dimension to overall poverty, around 2012 Source: Santos et al (2014), “A Multidimensional Poverty Index for Latin America”

es robustness Source: Santos et al (2014), “A Multidimensional Poverty Index for Latin America” Estimates for Different k Values

Otro grafico Source: Santos et al (2014), “A Multidimensional Poverty Index for Latin America”

Exclusion discrepancy and multidimensional poverty rate Source: Santos et al (2014), “A Multidimensional Poverty Index for Latin America” “ Exclusion discrepancy”: percentage of total population that is multidimensionally poor but not income poor

Some results Deprivations suffered by the poor vary from country to country in respect of intensity and the forms they take. Income insufficiency is important, but it is not the only hardship that the poor suffer. Income deprivation has the highest contribution, and it is higher in countries with low poverty rates. Contribution of precarious housing, lack of energy and of durable goods is higher in high-poverty countries. Multidimensional poverty yields similar headcount ratios to income poverty in most countries, but both methods do not necessarily identify the same population as poor. Poverty reduction requires coordinated policies across multiple sectors.

Multidimensional poverty and data Adopting a multidimensional index provides useful information for analysis of living conditions and to guide policy. Current information is insufficient and lacks comparability. Education: Indicators of access but not quality or competency in adults. Housing: variables and categories not clearly linked to deprivations. Health: not measured in most regular surveys of the region. Current context (SDGs and data revolution) offers an opportunity to improve household surveys. Moving towards the harmonization of certain basic dimensions. More comprehensive (within the constraints of sample size and representativeness). Taking advantage of existing survey programs, in the context of stronger and better coordinated National Statistical Systems