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Beyond MDG Dashboards: Consideration of Joint Distribution in Measuring Poverty Evidence and Measures of Progress in International Development RSS 2013 International Conference, Newcastle UK Suman Seth September 5, 2013. Outline.

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slide1

Beyond MDG Dashboards: Consideration of Joint Distribution in Measuring Poverty

Evidence and Measures of Progress in International Development

RSS 2013 International Conference, Newcastle UK

Suman Seth

September 5, 2013

outline
Outline
  • Why is there a need to consider joint distribution and a multidimensional framework for measuring poverty
  • The Multidimensional Poverty Index: A Proposal
    • Methodology
    • Illustrations
  • MPI 2.0 and the post 2015 discussion
slide3

Why New Emphasis on Poverty Measurement?

  • What we have: Technical
    • Increasing data
    • Improving methodologies
  • What we need: Policy
    • Make growth to be inclusive through active policies
    • Go beyond income poverty (it is important but insufficient)
    • Go beyond dazzlingly complex dashboards of indicators
    • Understanding the joint distribution across deprivations
  • Path ahead: Ethical and Political
    • Political critique of current metrics; exploration
    • Measures in 2010 HDR sparked interest and debate
    • Post-2015 requires re-thinking Data and Measures
eradicating income poverty is not sufficient global monitoring report progress status 2013
Eradicating Income Poverty is not Sufficient (Global Monitoring Report Progress Status, 2013)

Reduction in income poverty does not reduce other MDG

deprivations automatically. Source: World Bank Data

mdg dashboards fail to reflect joint distribution of deprivations
MDG Dashboards Fail to Reflect Joint Distribution of Deprivations

An example with four persons (deprived=1, non-deprived=0)

Case 1

Case 2

In both cases, 25% deprived in each MDG indicator

BUT, in Case 2, one person is severely deprived

motivation for a multidimensional approach
Motivation for a Multidimensional Approach
  • “MDGs did not focus enough on reaching the very poorest” - High-Level Panel on the Post-2015 Development Agenda (2013)
    • Should be able to distinguish poorest from the less poor. How?
    • Deprived in many dimensions simultaneously?
  • “Acceleration in one goal often speeds up progress in others; to meet MDGs strategically we need to see them together” - What Will It Take to Achieve the Millennium Development Goals? (2010)
    • Emphasis on joint distribution and synergies
  • “While assessing quality-of-life requires a plurality of indicators, there are strong demands to develop a single summary measure” - StiglitzSenFitoussi Commission Report (2009)
    • One summary index is more powerful in drawing policy attention
slide8

Value-added of a Multidimensional Approach

  • What can a meaningful multidimensional measure do?
    • Provide an overview of multiple indicators at-a-glance
    • Show progress quickly and directly (Monitoring/Evaluation)
    • Inform planning and policy design
    • Target poor people and communities
    • Reflect people’s own understandings(Flexible)
    • High Resolution
    • – zoom in for details by regions, groups, or dimensions
alkire foster methodology
Alkire Foster Methodology
  • Select dimensions, indicators and weights (Flexible)
  • Set deprivation cutoffs for each indicator (Flexible)
  • Apply to indicators for each person from same survey
  • Set a poverty cutoff to identify who is poor (Flexible)
  • Calculate Adjusted Headcount Ratio (M0) – for ordinal data (such as MDG indicators),

– Reflects incidence, intensity

Sabina Alkire and James Foster, J. of Public Economics 2011

multidimensional poverty index mpi
Multidimensional Poverty Index (MPI)

An adaptation of Alkire and Foster (2011) which can deal with the binary or categorical data and was introduced by Alkire and Santos (2010) and UNDP (2010)

A person is identified as poor using a counting approach in two steps

1) A person is identified as deprived or not in each dimension using a set of deprivation cutoff

2) Based on the deprivation profile, a person is identified as poor or not

Terms: deprived and poor are not synonymous

how is mpi computed
How is MPI Computed?

The MPI uses the Adjusted Headcount Ratio:

H: The percent of people identified as poor, it shows the incidence of multidimensional poverty

A: The average proportion of deprivations people suffer at the same time; it shows the intensity of people’s poverty

Alkire, Roche, Santos, and Seth (2013)

.

Formula: MPI = H × A

identify who is poor
Identify Who is Poor

A person is multidimensionally poor if she is deprived in 1/3 of the weighted indicators.

(censor the deprivations of the non-poor)

39%

33.3%

properties useful for policy
Properties Useful for Policy

The MPI

  • Can be broken down into incidence(H)and the intensity(A)
  • Is decomposable across population subgroups
    • Overall poverty is population-share weighted average of subgroup poverty
  • Overall poverty can be broken down by dimensions to understand their contribution
policy relevance incidence vs intensity
Policy Relevance: Incidence vs. Intensity

Country B:

Country A:

Povertyreductionpolicy

(withoutinequaliyfocus)

Policyorientedtothepoorest of thepoor

Country B reduced the intensity of deprivation among the poor more. The final index reflects this.

Source: Roche (2013)

policy relevance incidence vs intensity1
Policy Relevance: Incidence vs. Intensity

Very similar annual reduction in MPI

Alkire and Roche (2013)

india 1999 2006 uneven reduction in mpi across population subgroups
India (1999-2006): Uneven Reduction in MPI across Population Subgroups

Slower progress for Scheduled Tribes (ST) and Muslims

Religion

Caste

Alkire and Seth (2013)

reduction in mpi across indian states
Reduction in MPI across Indian States

Slower reductions in initially poorer states

Stronger reductions in Southern states

We combined Bihar and Jharkhand, Madhya Pradesh and Chhattishgarh, and Uttar Pradesh and Uttarakhand

distribution of intensities among the poor
Distribution of Intensities among the Poor

Madagascar (2009)

MPI = 0.357

H = 67%

Rwanda (2010)

MPI = 0.350

H = 69%

slide25

The MPI 2.0 and the

Post-2015 discussion

slide26

MPI vs. $1.25-a-day

Height of the bar: MPI Headcount Ratio

Height at ‘•’ : $1.25-a-day Headcount Ratio

slide27

Measuring the Post-2015 MDGs

  • What we found from Global MPI
  • $1.25/poverty and MPI do not move together
  • MPI reduction is often faster than $1.25/day poverty
  • Political incentives from MPI are more direct
measuring the post 2015 mdgs
Measuring the Post-2015 MDGs

Create an MPI 2.0 in post 2015 MDGs (Alkire and Sumner 2013)

  • To complement $1.25/day poverty
  • To reflect interconnections between deprivations
  • To track ‘key’ goals using data from same survey
  • To celebrate success

Note: MPI is not a Composite Index like the HDI or the HPI

multidimensional poverty index mpi1
Multidimensional Poverty Index - MPI
  • Shows joint distribution of deprivations (overlaps)
  • Changes over time: informative
    • by region, social group, indicator (inequality)
  • National MPIs: tailored to context, priorities
  • MPI 2.0: comparable across countries
  • National MPI and Global MPI 2.0 can be reported like national income poverty and$1.25/day
  • Data needs: feasible – use 39 of 625 questions in DHS
  • Published: in annual Human Development Report of UNDP
  • Method: Alkire and Foster 2011 J Public Economics Examples: see www.ophi.org.uk
the global multidimensional poverty peer network global mppn

The Global Multidimensional Poverty Peer Network (Global MPPN)

Angola, Bhutan, Brazil, Chile, China, Colombia, ECLAC, Ecuador, El Salvador, Dominican Republic, Germany, India, Iraq, Malaysia, Mexico, Morocco, Mozambique, Nigeria, OECD, the Organization of Caribbean States, OPHI, Peru, Philippines, SADC, and Vietnam

Joined by: President Juan Manuel Santos of Colombia

Nobel Laureate AmartyaSen

Launched: June 6, 2013

the global multidimensional poverty peer network global mppn1
The Global Multidimensional Poverty Peer Network (Global MPPN)
  • On 24 September, 2013: event in the United Nations N Lawn Conf room 7
  • Attendees: Ministers from Philippines, Nigeria, Mexico, Colombia, El Salvador, the Secretary of State of Germany, President of Colombia, Head of DAC at OECD, and others
  • Subject: Speak on an MPI 2.0
    • The Network has decided to advocate a MPI 2.0 as part of the post-2015 process as a measure of income poverty is not enough, and nor is a dashboard.