Multidimensional Human Poverty - New Approaches in Poverty Measurement

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Information about Multidimensional Human Poverty - New Approaches in Poverty Measurement
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Published on February 24, 2014

Author: undpeuropeandcis



Multidimensional Human Poverty “New Approaches in Poverty Measurement”, Ankara University, Ankara, Turkey, 20 February 2014 Mihail Peleah Human Development Officer, UNDP BRC

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Going beyond monetary poverty: where? • Multidimensional wellbeing Alkire-Foster Method • Connecting data Secondary Sources Contextualization • Qualitative and Quantitative data nexus ‘Micronarratives’ Global MPI National MPIs Social Exclusion Index


Poverty in one dimension • Selection of welfare function • Obtaining welfare function distribution • Selecting poverty line • Calculating poverty headcount (H) X% – plus poverty gap (FGT1), poverty intensity (FGT2) – plus sensitivity analysis Y% Y$ X$

Multidimensional poverty

Multidimensional poverty Headcount H Average Deprivation among Poor A MPI = H x A

Multidimensional poverty: setting up • • • • Unit of analysis: individual? household? Select dimensions Select indicators for dimensions Double poverty line method: first, deprivation in each indicator; second, number of simultaneous deprivations for poverty status – ‘Deprivation line’ in each dimension – ‘Poverty line’ for multidimensional poverty • Weighting – Within dimension – Between dimensions

OPHI: Missing Dimensions • Employment – both formal and informal employment, with particular emphasis on quality of employment • Empowerment or Agency – the ability to advance goals one values or has reason to value • Physical safety – Security from violence to property and person, as well as perceived violence • The ability to go about without shame – emphasize importance of dignity, respect and freedom from humilation • Meaning and value – emphasize meaning, satisfaction and their determinants

MPI: Data Source • Data hungry—all variables for one household / person • Existing Survey(s) – Global MPI: Demographic and Health Surveys, Multiple Indicator Cluster Surveys, World Health Surveys and National Surveys. • New Survey – Regional Social Exclusion Index: 6 countries • Combination – Moldova HBS: Core Questionnaire plus Additional Module – Ukraine HBS: Additional Modules, once in 1-2 years • Matching data

Multidimensional poverty: counting • H – poverty headcount – Sensitive to frequencies – Not sensitive to breadth • A – average share of deprivations – Sensitive to breadth • M0=H•A – multidimensional poverty index – Sensitive to frequencies – Sensitive to breadth

Multiple deprivation • Unidimensional – Variable – income 100 • Multidimensional – Variables – income, employment, access to water, … 100 y y 125 – Poverty line z 190 –  Deprivation vector –  Gap vector – Headcount ratio – how many are “poor” – Gap – how far from poverty line 8 250 40 9 36 24 125 500 16 500 250 38 12 – Poverty lines – first cutoffs z 190 35 12 –  Deprivation matrix –  Gap matrix – Second cut off k • • • Deprived in one dimension Deprived in all dimensions Deprived in more than k dimensions – H – headcount rate – A – average breath of deprivation – M0 – adjusted headcount rate


Dimensions and Indicators of MPI

MPI Poor and Income Poor OPHI, Multidimensional Poverty Index 2013

Changes in MPI: Incidence and Intensity OPHI, Multidimensional Poverty Index 2013

Turkey MPI: Deprivation in each Indicator OPHI, Turkey Country Briefing, 2013

Turkey MPI: Urban – Rural disparities OPHI, Turkey Country Briefing, 2013

MPI in Turkey Regions

Inequalities matter

Inequality of Opportunities matters most E. Molina et al. Outcomes, Opportunity and Development , WPS 6735


Why this index? • Objective and multidimensional measure of social exclusion • Measures status of exclusion or non-exclusion, rather than ‘perceptions’ or ‘risks’ • Applicable for Europe and Central Asia region • Useful for policymaking

Social Exclusion Chain Individual characteristics interact with Drivers of social exclusion Structures and institutions; values and behavior patterns; policies Drivers are external factors, influenced by legacies, that either speed up or slow down the process of individual vulnerabilities turning into social exclusion (social exclusion risk factors), like poor education, disability, minority status in context of Specific local conditions Predominant industry, single or multiple employment opportunities, local infrastructures, history of violent conflict or environmental disaster …and result in Social exclusion status of the individual in three dimensions— exclusion from economic life, social services, and civic and social participation

Construction of index • Based on Alkire-Foster (2009) • Exclusion is overlapping deprivations • 3 areas of exclusion, 24 indicators, 8 per area –Economic exclusion –Exclusion from social services –Exclusion from civic and political participation • Threshold is 9 out of 24 possible deprivations, but other possible thresholds tested

Profiles of exclusion

Different combinations of individual risks, drivers and local context produce different levels of social exclusion If you are young person, with low education, living in village, with single company—you face high risk of exclusion …and secondary education doesn’t help much in these conditions… + …while vibrant business environment makes a lot of difference + …economic centers offer more opportunities (even with low education) + + + + …and much more if you are educated Source: RHDR ―Beyond Transition: Toward Inclusive Societies‖, 2011

Secondary Source Contextualization Administrative datasets Survey Statistical databases

Local economy matters

Serbia: Social Exclusion and Health

Serbia: Social Exclusion and Education

Serbia: Social Exclusion and Employment


Why the ‘micronarratives’? • QxQ—combine the best from Qualitative and Quantitative research • Zoom in and Zoom out—see the pattern and investigate a case study • Suitable for all stage of policy process: – – – – Understanding Planning Implementation Monitoring and Evaluation • Could be a tool of empowerment and trust building

How it works? Vestibulum nec libero at libero condimentum condimentum ut at neque. Past Maecenas pellentesque porttitor lacus, eget venenatis ipsum eleifend sit amet. Present People tell stories about the topic and tag them against some questions Future When we get more and more stories patterns start emerge • easy to catch by human eye, hard to compute • less sensitive to number of stories, more sensitive to topic Patterns and stories help identify issues, solutions and actions and create feedback loops, involving people in solutions and monitoring

Where we implement it? • • • • Montenegro — Environmentally protected areas Montenegro — Civil service and civilians Serbia — Roma people Belarus, Russia, Ukraine — Chernobyl-affected areas • Belarus — people with disabilities • Georgia, Kyrgyzstan — youth perception of development • UNDP — internal business processes

Cooperation Competition Thanks to Borko Vulikic for this case Corruption

Jeeps and Sheeps • Cluster of stories re: – – – – Communities Revenues Source of incomes Limitations of income or business activities • Dig into the stories – – – – Jeep tours were organized to protected areas …but they raise dust clouds …which spoil milk, the raw material for cheese …cheese is major local commodity and source of incomes • Solution – Move jeep trail 500 m from village Thanks to Borko Vulikic for this case

Questions for discussion • Do Turkey need national MPI? • What are relevant dimensions and indicators? • What could be a data source for index?

Mihail Peleah Human Development Programme and Research Officer UNDP Bratislava Regional Center

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