Multidimensional Poverty

Index − Pakistan

Dr. M. Aman UllahChief Economist

Planning & Development DepartmentGovernment of the Punjab

Formerly: Planning Commission, Government of Pakistan October 10, 2017

Why a multidimensional approach to measuring poverty?

• Poverty is a complex and multifaceted phenomenon. Aunidimensional measure based on income alone cannotcapture the true extent and depth of poverty.

• While official monetary measures reflect deprivation inincome/consumption only – MPI reflects deprivation in otherdimensions such as education, health and living standards.Hence MPI complements monetary measures of poverty.

• Pakistan’s official poverty measure estimates 29.5% ofpopulation to be living below the poverty line of PKR3,030.32 per adult per month.

Construction of a National MPI

A thorough process of Provincial and Regional consultations with Government officialsincluding Planning & Development Departments & Bureau of Statistics, and CSOsincluding academia and NGOs was undertaken to finalize the indicators.

Consultation in Sindh (Karachi)

(29th Oct 2014)

Consultation in Punjab (Lahore)

(30th Oct 2014)

Consultation in Khyber Pakhtunkhwa (Peshawar)

(20th Nov 2014)

Consultation in Balochistan(Quetta)

(30th Dec 2014)

Consultation in Azad Jammu & Kashmir (Muzaffarabad)

(19th Feb 2015)

MPD&R and UNDP organized 10 day

training course on Multi-

dimensional Poverty Index (MPI)

from 7 - 18 April 2014. The training

was delivered by the OPHI

Background

• The first ever national report on multidimensional poverty in Pakistan waslaunched on Monday, 20thJune 2016.

• The process began in April 2014 when an agreement was signed betweenthe Ministry of Planning, Development & Reform, OPHI and UNDP

• Pakistan's MPI builds upon the global MPI, retaining the same three coredimensions: education, health and living standards.

• The choice of indicators, however, reflects the country's particular contextand political priorities, as well as the data available in the PSLM surveys.

• In total, 15 indicators are used in this national index, of which 7 indicatorsare the same as those used in the global MPI.

What does Pakistan’s MPI include?

Education

Health

Standard of Living

Data Source: PSLM Survey – 2004/05, 2006/07, 2008/09, 2010/11, 2012/13 and 2014/15

National Multidimensional Poverty Headcount

55.2%52.5%

49.3%

44.7%

40.8%38.8%

70.3% 69.5%

65.2%

60.2%

56.0%54.6%

24.0%

19.4%17.3%

12.7%10.1% 9.4%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

2004/05 2006/07 2008/09 2010/11 2012/13 2014/15

Multidimensional Poverty Headcount

National - overall Rural Urban

Current Statistics

• National: 38.8%

• Rural: 54.6%

• Urban: 9.4%

Provincial Poverty Headcount

31.4%

43.1%

49.2%

71.2%

43.2%

24.9%

73.7%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

Punjab Sindh KP Balochistan GB AJK FATA

Headcount

Provincial Poverty Headcount

49.7%46.4%

43.2%38.1%

34.7% 31.4%

57.3%53.7%

51.2%

48.0%44.6% 43.1%

65.8% 66.1%

60.5%

55.0%

49.1% 49.2%

83.4%79.8% 78.9%

75.9%71.9% 71.2%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

2004/05 2006/07 2008/09 2010/11 2012/13 2014/15

Provincial Headcount (2004/05 - 2014/15)

Punjab Sindh KP Balochistan -36.9

-24.7 -25.3

-14.6

-40.0

-35.0

-30.0

-25.0

-20.0

-15.0

-10.0

-5.0

0.0

Punjab Sindh KP Balochistan

Provincial Decrease in Headcount (%)

Composition of National MPI

Percentage Contribution of each indicator to MPI

Use of MPI for resource allocation

The statistics show that more resources should be allocated to the education sector in

Muzaffargarh.

Creating incentives for families to send their children to school and focusing on both

demand and supply factors of educational sector

can reduce the number of households deprived in indicators of ‘years of schooling’,

‘child school attendance’ and ‘educational quality’.

It will reduce the MP headcount for the district of Muzaffargarh

Benefits of MPI for Policy Makers

• Helps to identify where poor people live (district) and how theyare poor (sectors)?

• Learning from the experiences of the districts that reducedpoverty the most

• As a tool for effective resource allocation

• Can be used as a criteria for resource allocation in National andProvincial Finance Commission Awards

• Effectiveness of poverty reduction programmes can be gaugedby changes in MPI

Way Forward

• Regular publishing of MPI report with updated data

• Launch of provincial MPI reports

• An online dashboard for MPI

• Promoting the use of MPI for resource allocation - NFCand PFC

• Capacity building of national and provincial institutes forcomputing MPI