The Geography and Lives of the Poor: Evidence from Punjab

1. The Geography and Lives of the Poor: Evidence from Punjab Ali Cheema Lyyla Khalid Manasa Patnam Lahore University of Management Sciences 2008

2. 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

3. 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

4. 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-components b. Adjust for cost of living differences: Deflating Total Household Expenditure by Paasche’s Index to capture cost of living c. Adjust for household composition The Sub-components of ACF can be classified into four categories: i. Food items ii. Non-food items iii. Consumer durables Use Poverty line for 2000-02 defined by Planning Commission (Economic Survey 2006-07) and adjust it using CPI

5. Equivalence Factors for age/sex-specific official poverty lines Source: Poverty Reduction Strategy Paper, 2003

6. The Geography of Poverty • High poverty clustered in the South and West regions • Constitute crescent of endemic poverty

7. The Geography of Poverty Head Count Overall Head Count Rural

8. The Geography of Poverty Poverty Gap Overall Poverty Gap Rural

9. 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

10. Measuring Deprivation Deprivation Indices: Index 1 • Education Illiteracy Rate (10 years and above)- female Illiteracy Rate (10 years and above)- male Proportion out of school Children – female Proportion out of school Children – male • Housing Quality Proportion of Non-Pacca houses Persons per room Percentage of housing Units with one room Percentage Non-owner households Households with no latrine facility • Housing Services Percentage of Unelectrified households Percentage of households without gas Percentage of households with no inside piped water connection Households with no telephone connection • Employment Unemployment rate [15 - 65 years] Combining the indicators • Equal weights to different components of the index • Weights assigned by using principle component analysis (PCA)

11. Choice of Method and Sensitivity of Rankings

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

13. Ranking of Most Deprived DistrictsIndex 1 & 2 combined with HCRs

14. 35.00 30.00 25.00 20.00 (% Farm Area) North Centre West South 15.00 10.00 5.00 0.00 1980 2000 1980 2000 Sharecropped Leased Divergent Socio-Economic Paths • Access to land deteriorating sharply for landless • Similar trend across all regions

15. Divergent Socio-Economic Paths • Mitigated by diversification out of agriculture in North and Centre • Continued agrarian dependence in the South and West Source: Population Census (1997) and MICS (2003-04)

16. The Poverty Impact • Diversification out of agriculture negative correlate of poverty • Limited possibilities in the South and West exacerbating problem Source: MICS (2003-04)

17. The Poverty Impact • Deteriorating access to land worsening matters Source: MICS (2003-04)

18. The Poverty Impact • Incidence of poverty much higher • Labour dependent HHs • Long-term unemployed • Effect more pronounced in South and West Source: MICS (2003-04)

19. Using dependents! Proportion of dependents much higher in South and West Source: MICS (2003-04)

20. The Poverty Impact • Related vulnerabilities in the South and West Source: MICS (2003-04)

21. HH Coping Strategies • Intra HH occupational diversification • Similar trend across all regions Source: MICS (2003-04)

22. Does it pay? • Not at the same rate across all four regions! • Much flatter effect in the South and West Source: MICS (2003-04)

23. Creating Remittances • Stark regional differences Source: MICS (2003-04)

24. The Remittance Effect • Strong negative correlate of poverty Source: MICS (2003-04)

25. Migration and Remittances No of migrants per HH explains a large part of variation in remittances However, presence of endogeneity Source: MICS (2003-04)

26. 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)

27. Missing Investments • In part the answer lies in missing investments Source: MICS (2003-04)

28. Where do the differences come from? History An earlier migration A large part still unexplained! Source: MICS (2003-04), Punjab Economic Report (2004-05)

29. Determinants • Much of the variation within district • Started exploring tip of the iceberg