The Geography and Lives of the Poor: Evidence from Punjab Ali Cheema Lyyla Khalid Manasa Patnam...

The Geography and Lives of the Poor: Evidence from

PunjabAli CheemaLyyla Khalid

Manasa PatnamLahore University of Management

Sciences 2008

What is to follow

• Identifying endemic poverty regions

• Changing regional socio-economic paths

• Poverty impact of different paths

• HH strategies and payoffs in different regions

• Where do regional differences come from

Motivation• Lack of evidence on district-wise variation in

poverty [World Bank 2002; Anwar, Qureshi and Ali 2004; Qureshi and Arif 2001)

• Some Exceptions [Jamal PDR 2005; Malik 2005 and Gazdar 1999]

• Putting poverty incidence in context of socio-economic change

• Reveal patterns not causality

Constructing the Consumption Aggregate

Dataset: Punjab MICS (2003-04) representative at district level

Money-metric measure

The Aggregate Consumption Function (ACF) is constructed as follows:

a. Aggregate the various sub-componentsb. Adjust for cost of living differences: Deflating Total Household

Expenditure by Paasche’s Index to capture cost of livingc. Adjust for household composition

The Sub-components of ACF can be classified into four categories:i. Food itemsii. Non-food itemsiii. Consumer durables

Use Poverty line for 2000-02 defined by Planning Commission (Economic Survey 2006-07) and adjust it using CPI

Equivalence Factors for age/sex-specific official poverty lines

Age Bracket Energy Per Person Daily Requirement

Children

<1 1010 0.4298

1-4 1304 0.5549

5-9 1768 0.7523

Males

10-14 2,816 1.1983

15-19 3,087 1.3136

20-39 2,760 1.1745

40-49 2,640 1.1234

50-59 2,640 1.0468

60 or more 2,146 0.913

Females

10-14 2464 1.0485

15-19 2332 0.9881

20-39 2080 0.8851

40-49 1976 0.8409

50-59 1872 0.7966

60 or more 1632 0.6945

Source: Poverty Reduction Strategy Paper, 2003

The Geography of Poverty

• High poverty clustered in the South and West regions

• Constitute crescent of endemic poverty

Poor Non Poor

North 21.31 78.69

Centre 28.76 71.24

South 50.79 49.21

West 52.1 47.9Source: MICS (2003-04)

North: Pindi, Chakwal, Jhelum And AttockSouth: R.Y.Khan, Bahawalpur, Bahawalnagar,

Multan, Lodhran, Khanewal And VehariWest : Mianwali, Khushab, Bhakkar, Lyyah,

Muzzafargarh, DG Khan And Rajanpur

Centre : All Others

The Geography of PovertyHead Count Overall Head Count Rural

The Geography of PovertyPoverty Gap Overall Poverty Gap Rural

The Geography of Poverty

• High poverty clustered in the South and South West districts

• Severity of poverty highest in these districts

• Deprivation index correlated with district poverty

Measuring DeprivationDeprivation Indices:

Index 1 Education

Illiteracy Rate (10 years and above)- femaleIlliteracy Rate (10 years and above)- maleProportion out of school Children – femaleProportion out of school Children – male

Housing Quality

Proportion of Non-Pacca housesPersons per roomPercentage of housing Units with one roomPercentage Non-owner householdsHouseholds with no latrine facility

Housing ServicesPercentage of Unelectrified householdsPercentage of households without gasPercentage of households with no inside piped water connectionHouseholds with no telephone connection

EmploymentUnemployment rate [15 - 65 years]

Combining the indicators– Equal weights to different components of the index– Weights assigned by using principle component analysis (PCA)

Choice of Method and Sensitivity of Rankings

Index1 Rank (Average) District

Index1 Rank (PCA)

32 Rahim Yar Khan 34

31 Lodhran 33

34 Muzaffargarh 32

33 Rajanpur 31

28 D.G.Khan 30

26 Bahawalpur 29

27 Okara 28

29 Bhakkar 27

21 Vehari 26

23 Bahawalnagar 25

24 Pakpattan 24

22 Khanewal 23

25 Jhang 22

30 Layyah 21

20 Kasur 20

16 Sheikhupura 19

19 Sahiwal 18

Index1 Rank (Average)

District Index1 Rank (PCA)

14 Multan 17

13 Narowal 16

12 Hafizabad 15

11 T.T.Singh 14

18 Khushab 13

17 Mianwali 12

15 Mandi bahauddin 11

9 Sargodha 10

5 Faisalabad 9

8 Gujrat 8

7 Jhelum 7

10 Attock 6

4 Gujranwala 5

3 Sialkot 4

2 Lahore 3

6 Chakwal 2

1 Rawalpindi 1

Index 2 Includes Social Indicators: Under 5 Mortality Rates and Ante Natal care by skilled health

workers

Index2 (PCA) District Index2(Average)

34 Lodhran 29

33Rahim yar

Khan 28

32 Rajanpur 33

31 Muzaffargarh 34

30 Bhakkar 31

29 Bahawalpur 27

28 Okara 26

27 Bahawalnagar 23

26 Pakpattan 25

25 D.G.Khan 32

24 Vehari 24

23 Khanewal 21

22 Jhang 22

21 Layyah 30

20 Kasur 20

19 Sheikhupura 16

18 Sahiwal 17

Index2 (PCA)

District Index2 (Average)

17 Multan 15

16 Hafizabad 12

15 Narowal 13

14 Khushab 19

13 T.T.Singh 10

12 Mianwali 18

11 sargodha 9

10Mandi

Bahauddin 14

9 Faisalabad 6

8 Attock 11

7 Gujrat 5

6 Jhelum 8

5 Gujranwala 4

4 Sialkot 3

3 Chakwal 7

2 Lahore 1

1 Rawalpindi 2

Ranking of Most Deprived DistrictsIndex 1 & 2 combined with HCRs

Index 11 Index 22 MICS

2003-04

SPDC

2007

1 Rajanpur Rajanpur Rajanpur Lodhran

2 RYKhan RYKhan D.GKhan MGarh

3 MGarh Lodhran Bhakhar Rajanpur

4 Lodhran MGarh MGarh Layyah

5 D.GKhan Bhlpur Bhlpur D.GKhan

6 Bhlpur D.GKhan Lodhran Pkpattan

7 Okara Bhlnagar Pkpattan RYKhan

8 Bhlnagar Okara Bhlnagar Bhlpur

9 Pkpattan Pkpattan RYKhan Vehari

10 Layyah Bhakhar Kasur Jhang

Divergent Socio-Economic Paths

• Access to land deteriorating sharply for landless

• Similar trend across all regions

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

1980 2000 1980 2000

Sharecropped Leased

(% F

arm

Are

a)

North

Centre

West

South

Divergent Socio-Economic Paths

• Mitigated by diversification out of agriculture in North and Centre

• Continued agrarian dependence in the South and West

Occupational Structure

0

10

20

30

40

50

60

North Centre South West

% Working Age Pop in Agri

% Adults Non-Agri/Non-Labour

Source: Population Census (1997) and MICS (2003-04)

The Poverty Impact

• Diversification out of agriculture negative correlate of poverty

• Limited possibilities in the South and West exacerbating problem

Source: MICS (2003-04)

The Poverty Impact

• Deteriorating access to land worsening matters


The Poverty Impact

• Incidence of poverty much higher – Labour dependent

HHs– Long-term

unemployed

• Effect more pronounced in South and West


Using dependents!

• Proportion of dependents much higher in South and West


Dependency ratio

0

5

10

15

20

25

30

35

40


% D

epen

dent

s

Dependency ratio (%)

The Poverty Impact

• Related vulnerabilities in the South and West


Vulnerabilites

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1


% H

Hs w

ith W

orki

ng D

epen

dent

s (O

ld a

nd th

e Ve

ry Y

oung

)

Non-Poor

Poor

HH Coping Strategies

• Intra HH occupational diversification

• Similar trend across all regions


Does it pay?

• Not at the same rate across all four regions!

• Much flatter effect in the South and West


Creating Remittances

• Stark regional differences


Remittances

0

5

10

15

20

25


Prop HH reporting remittance

Remittance % total income

The Remittance Effect

• Strong negative correlate of poverty


Migration and Remittances

• No of migrants per HH explains a large part of variation in remittances

• However, presence of endogeneity

Prop. Remittance Income

Coeff. T-Stat

hh size -0.004 -11.8

District Dummies Yes

R-Squared 0.0851

N 29258


Prop. Remittance Income

Coeff. T-Stat

hh size -0.029 -15.06

No. Migrants .0693 108.21

District Dummies Yes

R-Squared 0.21

N 29258

Migration and Remittances

• Use mean rainfall as IV for number of migrants

– Controlling for HH size West and South more migrants per HH

– But proportion of remittance income much less in South and West

• Indicates migrants from North entering a different segment of labour market

Source: MICS (2003-04), Punjab Economic Report (2004-05)

No. Migrants (First Stage)

Coeff. T-Stat

hh size -.00001 -0.00

Rainfall 0.0006 11.46

North -0.09 0.04

South 0.114 4.27

West 0.102 3.91

R-Squared 0.0673

N 29258

Prop. Remittance Income (Second Stage)

Coeff. T-Stat

hh size -0.004 -13.44

No. Migrants 0.101 10.01

North 0.067 15.66

South -0.015 -5.87

West -0.008 -2.88

R-Squared 0.3

N 29258

Missing Investments

• In part the answer lies in missing investments

Educational Attainment (Boys)

0

5

10

15

20

25

30

35

40

45

50

Never enrolled inschool

Completed primary Completedsecondary

Completed Matric

% o

f 1

5-1

7 Y

ea

r o

lds

North

Centre

South

West


Educational Attainment (Girls)

0

5

10

15

20

25

30

35

40

45

50

Never enrolled inschool

Completed primary Completedsecondary

Completed Matric

% 1

5-1

7 Y

ea

r o

lds

North

Centre

South

West

Where do the differences come

from?

• History

• An earlier migration

• A large part still unexplained!

Source: MICS (2003-04), Punjab Economic Report (2004-05)

Poor

Coeff. T-Stat

North 0.059856 1.04

South 0.023486 1.28

West 0.026934 1.52

percentage displaced 0.049831 2.25

Canal -0.13063 -9.5

Military -0.00566 -8.8

Rainfall -3.5E-05 -1.27

wheat_area -0.00117 -7.76

rice_area 0.000372 5.42

cotton_area 0.000504 4.45

tot_area_sown 9.91E-05 1.79

tot_irrig 0.000235 3.21

no_factories<100 -0.00021 -15.05

no_factories>100 0.000318 3.18

R-Squared 0.08

N 29258

Determinants

• Much of the variation within district

• Started exploring tip of the iceberg

Poor Coeff. T-Stat

Regional 1 -0.074 -8.11Regional 2 0.22 30.08Regional 3 0.2333 28.5

R-Squared 0.0568 N 29258

Poor Coeff. T-Stat

Regional 1 0.015 0.74Regional 2 0.2043 11.15Regional 3 0.128 6District Dummies Yes

R-Squared 0.101 N 29258

The Geography and Lives of the Poor: Evidence from Punjab Ali Cheema Lyyla Khalid Manasa Patnam...

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