1 1 The Multidimensional - PowerPoint Presentation

Slide1

1

1

The Multidimensional

Poverty

Index:

Achievements

,

Conceptual

,

and

Empirical

Issues

Caroline Dotter

Stephan Klasen

Universität Göttingen

Milorad Kovacevic

HDRO

HDRO Workshop

March 4, 2013Slide2

The MPI

Measuring acute multidimensional poverty

;

Based

on dual cut-off approach (1/3);Dimensions: Health (mortality and nutrition), Education (years and enrolement), Standard of living (house, water, sanitation, electricity, cook fuel, assets);MPI = Headcount * Intensity;Data used: DHS, MICS, WHSCalculated for some 110 countries (increasingly available for more than 1 period);

2Slide3

In praise

of an MPI-type Indicator

Direct

multidimensional

complement/competitor to $ a day indicator;Similar breadth and coverageCould possibly calculate and monitor global poverty;Also based on capability approach (as is the HDI);Actionable and policy-relevant at the national (and sub-national level); advantage largely unexploited

by

UNDP;

Consistent with reasonable set of poverty measurement axioms (in contrast to HPI);Based on high quality and comparable data, with potential to measure poverty over time;

3Slide4

Conceptual

IssuesDual cut

-off

navigates

between union and intersection approachBut leads to formal and interpretational problems: deprivations entirely ignored below the cut-off seems problematic;Union approach conceptually to be preferred?Neglect of inequality in the spread of dimensions across

the

population, which is also problematic;Proposal by Rippin: In the poverty identification step, use square of weighted deprivation share as poverety indicator (and

add

those up in aggregation step);Other proposals in the literature;Use of intensity in the MPI: cannot compare with $ a day headcountlittle variation in intensity (heavily driven by second cut-off); use headcount as headline indicator with intensity-inequality sensitive measure as complementary indicator?

4Slide5

Empirical Issues

WHS limiting

and

problematic (and now superfluous?); suggestion to just use MICS and DHS;Standard of living:Unclear interpretation of electricity access (unequal use!), cooking fuel (depends on cooking situation), and sanitation (needs differ across rural/urban, regions);Quite large influence on overall MPI;

3

indicators

would suffice (and capture others as well): floor, assets, and drinking water;Enrolments:One child not enrolled, household deprived;Problem of late enrolments;

Adjust

time

window to allow for late enrolments (e.g. allow for 2 years late enrolment);5Slide6

6Slide7

Empirical Issues

Mortality:Only

consider

recent child deaths (MICS: only consider deaths of women who gave births in last 10 years?);Nutrition:BMI of adults and childhood undernutrition cut-offs not directly comparable;BMI and underweight subject to bias due to nutrition transition;Focus on children beyond

6

months

?Proposal: Just focus on childhood undernutrition and stunting; Education: Cut-off (one person with 5 years enough for non-deprivation) and implies perfect economies of scale (asymmetry

);

Proposal

: deprived if less than 50% of adults have 5 years+7Slide8

Empirical Issues

Asymmetric cut-offs

in

health

, enrolment, nutrition, education:Has systematic influence on impact of household size on MPI;Not clear that asymmetries are justified;Define cut-offs with respect to hh size (e.g. 20% of children are undernourished);Ineligible population:No children (in school-going

age

or with nutritional measurement);Presumed non-deprived in MPI (serious problem and bias!);Makes severe poverty near-impossible for hh without eligible population;A serious problem

of

differential importance across countries;8Slide9

9

All

solutions

problematic:Non-deprivation assumption;Dropping observations;Using other indicator from same dimension;Proposal: Hybrid approach: Use indicator from same dimension if one indicator is missing, and adjust overall MPI cut-off if both

are

missing (can be easily implemented);Advantage: Keeps all observations in, uses information to maximum extent; likely to generate least bias;Disadvantage: Decompositoion no

longer

possible;Slide10

Implementing the

ProposalsA reduced

and

(more robust) MPI?3 standard of living indicators;Nutrition: stunting (>6mts)Mortality: only recent deaths;Enrolment: allow for late enrolment;Cut-offs more uniform (>20% affected in nutrition, enrolment, mortality, <50% with 5 years+ education);Hybrid approach for ineligible population;Implement

approach

using DHS for Armenia, Ethiopia, and India;Changes incidence (mainly due to education cut-off), but also correlates of poverty (e.g. hh size);10Slide11

11Slide12

Conclusion

MPI has been a

good

start to develop internationally comparable multidimensional poverty indicator;But there are open issues and problems, and refinements at conceptual and empirical level warrantedConceptual level: Union approach, incorporating inequality, headcount the headline indicator?Empirical level: Changes

to

indicators, cut-offs, data sets used, and assumptions about ineligible population;Most issues can be readily addressed and are worth addressing.

12Slide13

13

Original (current) MPI

New

proposal

Implications

Headline index

MPI

Headcount of MP

Better comparability with income poverty

Complementary indicators of poverty

Headcount, Intensity

Intensity, Inequality

Intensity of MP; but

Which

approach to i

nequality of deprivation ?

Cut-off approach

Dual

Dual

→ MP

Union

approach

→ Measure of deprivation, inequality in deprivation

Possible differentiation

of deprivation and multidimensional poverty. More analytic power.

Dimension

cut-off

Absolute

Consider ‘relative’ cut-offs

Hard to implement

and also arbitrary?

Dimension weights

Equal

(

1/3)

Equal (1/3)

Within dimension weights

Equal

EqualSlide14

14

Original (current) MPI

New

proposal

Implications

Living

standard

Drinking water, sanitation, electricity,cooking fuel, floor, assetsDrinking water

,

floor,

assets

Reduces the importance of living standard;

Reduces

the headcount

Education

Enrollment

(ages

6-14)

Any school-aged child is not attending school in grades 1 to 8

Shorter the

enrollment window by 2

years (8 to 14); size adjustment (1 in 5)

Reduces the headcount

Years of schooling (age

15

and above)

Years of schooling is a public

good

(

no

one has 5 or more years of primary education)

Some economies of scale but not

full;

Size adjustment (1 in 2 adults)

Increases the headcount

Health

Nutrition

BMI

for adults

Weight-for-age for

children

Exclude

BMI for adults

Height-for-age

for

children

No

health indicator for adults; reduces the headcount

Mortality

Death of children any age, no reference period

Death of children below age 5 in the past 5

years;

Reference

period ?Slide15

15

Original (current) MPI

New

proposal

Implications

No eligible population

Enrollment,

Health

HH is non-deprivedHybrid approach:

Double the weight on adult education

BMI of adults

Lower cut-off: 2/9

Large number of

hh

(20%); me

ssy

calculation

Severe

poverty

Deprived

in more than 1/2 of weighted indicators

At least 50% of eligible

population in HH is deprived i

n enrollment and health; no assets;

Cut-off 1/3

Reduced

headcount