Asha Kapur Mehta


Published on

Day 1

Asha Kapur Mehta, Professor of Economics, Indian Institute of Public Administration
Poverty and Chronic Poverty in India

  • Be the first to comment

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Asha Kapur Mehta

  1. 1. Poverty and Chronic Poverty: An Overview Aasha Kapur Mehta Professor of Economics IIPA, New Delhi and CPRC
  2. 2. <ul><li>Chronic Poverty in India </li></ul><ul><li>  Over the last five decades, systematic efforts </li></ul><ul><li>have been made to alleviate poverty through </li></ul><ul><li>increasing economic growth, </li></ul><ul><li>direct attacks on poverty using targeted programmes, </li></ul><ul><li>land and tenancy reforms, </li></ul><ul><li>participatory and empowerment based approaches and </li></ul><ul><li>provision of basic minimum services. </li></ul>
  3. 3. <ul><li>As a result of these efforts, the incidence of poverty has declined from </li></ul><ul><li>54.9 per cent in 1973-74 to </li></ul><ul><li>26 to 30 per cent in 1999-2000. </li></ul>
  4. 4. Despite plans and poverty alleviation strategies we have: <ul><li>      260 to 300 million people in poverty </li></ul><ul><li>    many of whom don’t get two square meals a day </li></ul><ul><li>    these are unacceptably high levels </li></ul>
  5. 5. Incidence of Poverty in India – % of Population and No of People Below the Poverty Line 1973-74 to 1999-2000   260.2 ?? 26.1 ?? 1999-2000 320.3 36 1993-94 307.1 38.9 1987-88 322.9 44.5 1983 328.9 51.3 1977-78 321.3 54.9 1973-74 Number of poor (millions) % population below the poverty line Year
  6. 6. Spatial concentration of poverty <ul><li>7 states of India or 10 out of 28 new states account for 75% of those in poverty. </li></ul><ul><li>These 7 states have had a very high proportion of their population in poverty over decades (over 35 percent till 1993-94). </li></ul>
  7. 7. Incidence and Concentration of Income Poverty in Selected States of India * including the newly formed states
  8. 8. <ul><li>71.65% of India’s poor and more than half of India’s population are located in the following states. </li></ul><ul><li>Uttar Pradesh (including Uttaranchal), </li></ul><ul><li>Bihar (including Jharkhand) and </li></ul><ul><li>Madhya Pradesh (including Chhatisgarh) </li></ul><ul><li>Maharashtra </li></ul><ul><li>West Bengal </li></ul><ul><li>Orissa </li></ul><ul><li>Assam </li></ul><ul><li>Source: Mehta and Shah CPRC-IIPA working paper 2 </li></ul>
  9. 9. <ul><li>These 7 states had </li></ul><ul><li>50% to 66% of their population below the poverty line in 1973-74. </li></ul><ul><li>35% to 55% of their population still in poverty in 1993-94. </li></ul><ul><li>47% of Orissa’s population was in poverty in 1999-2000. </li></ul>
  10. 10. 5 of these states (Bihar, Orissa, Madhya Pradesh, Assam and Uttar Pradesh) have had more than 30% of their people in poverty over several decades.  So high poverty incidence has existed in these states over a long duration.
  11. 11. <ul><li>It is important to recognise that: </li></ul><ul><li>the poor are a heterogeneous group </li></ul><ul><li>use of the term “the poor” actually refers to “different sociological realities”. </li></ul><ul><li>there is entry and exit or “mobility” for some people into and out of poverty </li></ul>
  12. 12. <ul><li>However there is a hard core that remains poor over time and extended duration poverty refers to this group. </li></ul><ul><li>Extended duration poverty will be the focus of our attention in our primary research as will the question do those in extended duration poverty also suffer severe poverty and multidimensional deprivation. </li></ul>
  13. 13. We view chronic poverty in terms of          long duration        severity and        multidimensional deprivation.
  14. 14. Panel Data Analysis <ul><li>Panel Data Analysis (for over 3000 rural households) </li></ul><ul><li>  </li></ul><ul><li>shows that there is both </li></ul><ul><li>substantial persistence </li></ul><ul><li>and substantial mobility into and out of poverty </li></ul><ul><li>   </li></ul><ul><li>-  47% of the poor were chronically poor as per the NCAER national rural panel for the late 1960s. </li></ul><ul><li>-  52% of the poor were chronically poor based on the NCAER 1970 and 1981 national rural panel. </li></ul>
  15. 15. <ul><li>NCAER Panel Data for 3139 households from 260 villages of India shows that: </li></ul><ul><li>   More than half (52.61%) of the households remained in poverty </li></ul><ul><li>   47.39% of poor households escaped from poverty. </li></ul><ul><li>   25.74% of non poor households entered </li></ul><ul><li>poverty. </li></ul><ul><li>  “ therefore the persistently poor are by no means a small subset of the poor.” </li></ul><ul><li>Source: Bhide and Mehta CPRC-IIPA working papers 6 and 15 </li></ul>Chronic Poverty, Exit and Entry: 1970-71 and 1981-82
  16. 16. Chronic Poor, Transient Poor and Non Poor
  17. 17. Incidence of Poverty in Panel
  18. 18. <ul><li>A recent wave of the NCAER Rural Panel Data Set (1981-1998) confirms: </li></ul><ul><li>substantial persistence and </li></ul><ul><li>substantial mobility </li></ul><ul><li>into and out of poverty </li></ul><ul><li>Between 1981-98, of those who were poor in rural areas, 38.6% of the households remained in poverty or were chronically poor. </li></ul><ul><li>Source: Bhide and Mehta CPRC-IIPA working paper 28 ) </li></ul>
  19. 19.   , Important determinants of poverty are: Caste, Tribe and Household Demographic Composition The probability of being chronically poor is greater for:            Casual Agricultural Labour            Landless households            Illiterate households            Larger households with more children Source: Bhide and Mehta CPRC-IIPA working papers 6 and 15
  20. 20. Factors that drive escape from poverty are <ul><li>increased income earning opportunities – </li></ul><ul><li>proximity to urban areas, </li></ul><ul><li>improved infrastructure </li></ul><ul><li>initial literacy status of the household head </li></ul><ul><li>ownership of or access to income from physical assets –cropland, livestock, house </li></ul><ul><li>Source: Bhide and Mehta CPRC-IIPA working papers 6 and 15 </li></ul>
  21. 21. Perceived reasons for decline into poverty <ul><li>Shocks such as </li></ul><ul><li>crop failure </li></ul><ul><li>high health care costs </li></ul><ul><li>adverse market conditions </li></ul><ul><li>loss of assets </li></ul><ul><li>high interest from private money lenders </li></ul><ul><li>social expenses on deaths and marriages. </li></ul><ul><li>Entry into poverty can be prevented by policies that reduce health care related shocks or costs and high interest debt. </li></ul><ul><li>Source: Anirudh Krishna JHD 2004; Bhide and Mehta JHD 2004 </li></ul>
  22. 22. Who are the chronically poor <ul><li>Casual agricultural labourers were the largest group </li></ul><ul><li>Most chronically poor </li></ul><ul><li>were landless or near- landless </li></ul><ul><li>had higher dependency burden and illiteracy. </li></ul><ul><li>depended on wages. </li></ul><ul><li>Therefore the chronically poor are critically dependent on changes in wages. </li></ul><ul><li>M any of those in Chronic long duration poverty tend to be stuck in a low wage-high drudgery-tough job groove with little opportunity for escape. </li></ul>
  23. 23. Low wages and drudgery maintain casual agricultural labourers in chronic poverty <ul><li>Ratnapandi is a labourer who climbs date palm trees every day to tap them for juice. (Sainath 1996) </li></ul><ul><li>      He works 16 hours a day </li></ul><ul><li>      climbs date palm trees he does not own, </li></ul><ul><li>      risks his neck, </li></ul><ul><li>      shins up using his hands and legs and </li></ul><ul><li>      earns as little as Rs.5 a day. </li></ul><ul><li>These are </li></ul><ul><li>the toughest jobs </li></ul><ul><li>with the lowest pay and </li></ul><ul><li>the maximum danger </li></ul>
  24. 25. Multidimensional deprivation <ul><li>Several states with high incidence of income poverty also have poor multidimensional indicators. </li></ul>
  25. 27. Deprivation at the District Level: Identifying the 50 most deprived districts in India <ul><li>Multidimensional indicators were estimated for 379 districts in 15 large states of India based on data for the early 1990s. </li></ul><ul><li>Choice of Variables was based on: </li></ul><ul><ul><li>reflection of long duration deprivation to the extent possible </li></ul></ul><ul><ul><li>Data availability at the district level. </li></ul></ul><ul><ul><li>Source: CPRC-IIPA Working Paper 9 </li></ul></ul>
  26. 28. For example, persistent spatial variations in the infant mortality rate could reflect persistent deprivation to the means of accessing good health <ul><ul><li>due to inability to get medical care </li></ul></ul><ul><ul><li>due to lack of income or </li></ul></ul><ul><ul><li>lack of available health care facilities in the vicinity or </li></ul></ul><ul><ul><li>poor quality of drinking water resulting in water borne diseases that cause mortality </li></ul></ul><ul><ul><li>or lack of roads and public transport that enable quick transportation to hospitals in case of emergency or </li></ul></ul><ul><ul><li>all of the above. </li></ul></ul>
  27. 29. Similarly, illiteracy could be considered to be a persistent denial of access to information, knowledge and voice. <ul><li>Low levels of agricultural productivity may reflect poor resource base, </li></ul><ul><li>low yields due to lack of access to irrigation and other inputs, </li></ul><ul><li>poor quality of soil resulting from erosion or </li></ul><ul><li>lack of access to resources for investment because of lack of collateral or </li></ul><ul><li>adverse climatic or market conditions. </li></ul>
  28. 30. <ul><li>Poor quality of infrastructure reflects persistent denial of opportunities for income generation and growth. </li></ul><ul><li>We use various combinations of multidimensional indicators that could reflect persistent deprivation, such as illiteracy, infant mortality, low levels of agricultural productivity and poor infrastructure </li></ul>
  29. 31. Three groups of indices are computed. <ul><li>1) An average of three indicators representing education, health and income, with equal weights of one third each assigned to each. These are: </li></ul><ul><li>a.   An average of female literacy and percent population in the age group 11-13 years attending school </li></ul><ul><li>b.   Infant mortality rate </li></ul><ul><li>c.   Agricultural productivity </li></ul>
  30. 32. <ul><li>An average of four indicators representing education, health, income and development of infrastructure with equal weights of one fourth each assigned to each. These are: </li></ul><ul><li>a.   An average of female literacy and percent population in the age group 11-13 years attending school </li></ul><ul><li>b.  Infant mortality rate </li></ul><ul><li>c.   Agricultural productivity </li></ul><ul><li>d. Infrastructure development </li></ul>
  31. 33. <ul><li>3) An average of four indicators representing education, health, income and development of infrastructure with equal weights of one fourth each assigned to each. These are: </li></ul><ul><li>An average of literacy and percent population in the age group 11-13 years attending school </li></ul><ul><li>Infant mortality rate </li></ul><ul><li>Agricultural productivity </li></ul><ul><li>Infrastructure development </li></ul>
  32. 34. <ul><li>Each of these sets of three indices are computed on the basis of three different methods with a view to determining robustness of the results. The three methods are: </li></ul><ul><li>1) the method used by the UNDP with the minimum-maximum range given below: </li></ul><ul><li>a. For literacy, female literacy and percent population in the age group 11-13 years attending school – 0 to 100 in each case </li></ul><ul><li>b. Infant mortality rate - 0 to 200 </li></ul><ul><li>c. Agricultural productivity – 0 to 30 </li></ul><ul><li>d. Infrastructure development – 0 to 500 </li></ul>
  33. 35. <ul><li>2) calculating an Adjusted value of each index so that the values obtained are not sensitive to changes in the ranks with changes in the minimum – maximum limits used. The method for calculating the AHDI is given in a footnote in working paper 9. The minimum-maximum used is the same as in the UNDP method in (1) above. </li></ul><ul><li>3) calculating an Adjusted value of each index so that the values obtained are not sensitive to changes in the ranks with changes in the minimum – maximum limits used. The minimum-maximum used are the actual minimum and maximum for each of the variables. </li></ul>
  34. 36. <ul><li>The 9 sets of results were then sorted to identify the 52 to 60 most deprived districts out of 379 districts in 15 large states of India. These are: </li></ul><ul><li>1 district in Assam, </li></ul><ul><li>between 5 to 8 districts in Bihar, </li></ul><ul><li>11 to 12 districts in Rajasthan, </li></ul><ul><li>21 to 26 districts in Madhya Pradesh, </li></ul><ul><li>4 districts in Orissa, and </li></ul><ul><li>6 to 10 districts in UP. </li></ul>
  35. 37. <ul><li>What clearly emerges is the constancy of districts regardless of indicators used and method of computation. The same 52 to 60 districts are identified as the most deprived in almost all 9 cases listed below. </li></ul><ul><li>Identification of districts that reflect chronic deprivation in multidimensional parameters is the first step in determining strategies to correct such imbalances. </li></ul>
  36. 41. Chronic Severity poverty is viewed in three ways: <ul><li>those who are chronically or severely below the poverty line or with incomes that are 75% of the poverty line or less; and </li></ul><ul><li>  those suffering hunger or not getting even two square meals a day as an extreme form of deprivation. </li></ul><ul><li>inability to absorb the impact of shocks can also lead to extreme poverty, starvation and suicide. </li></ul><ul><li>  </li></ul>
  37. 42. Severe Poverty <ul><li>134 million people were earning incomes that were less than or equal to three fourths of the poverty line or were chronically below the poverty line in the severity sense based on data for 1993-94. </li></ul><ul><li>Rural poverty was severest or the proportion of those who were very poor was largest in South Western Madhya Pradesh, Southern Uttar Pradesh, Southern Orissa, Inland Central Maharashtra, Southern Bihar, Northern Bihar and Central Uttar Pradesh. </li></ul><ul><li>Urban poverty was specially severe in Inland Central, Eastern and Northern Maharashtra, Southern Uttar Pradesh, Inland Northern Karnataka, South Western and Central Madhya Pradesh and Southern Orissa. </li></ul><ul><li>Source: Datta and Sharma, Planning Commission, 2000 </li></ul>
  38. 43. Regions with very high incidence of very Poor and Poor in Rural Areas : 1993-94 50.02 26.79 Central U.P. 58.68 27.62 Northern Bihar 62.44 31.57 Southern Bihar 50.02 28.91 Inland Central Maharashtra 69.02 34.08 Southern Orissa 66.74 39.7 Southern U.P. 68.2 42.24 South Western M.P. Poor Very Poor State/Regions
  39. 44. Hunger Hunger And Lack Of Availability Of Two Square Meals A Day         Starkest indicator of severe poverty        Within the over 200 million people identified as undernourished in India is a subset that is unable to access even two square meals a day.       Issues of state failure and community failure especially in the context of starvation related deaths.
  40. 45. Shock: Entry into Poverty <ul><li>Severe poverty could result from sudden shocks such as ill health or crop failure. The impact of such shocks can be transient if households </li></ul><ul><li>        could sell assets or </li></ul><ul><li>        borrow or </li></ul><ul><li>   generate income from alternative employment opportunities </li></ul><ul><li>However, if the household has </li></ul><ul><li>        no assets to sell </li></ul><ul><li>        or no access to credit, or </li></ul><ul><li>       is able to borrow at exploitative rates of interest and gets into a debt trap, shocks can have long duration ramifications in terms of pushing households below the poverty line. </li></ul><ul><li>Policy changes such as globalisation can also be sources of shock. </li></ul>
  41. 46. Globalisation: Suicide to escape chronic poverty <ul><li>Konda Kistiah a powerloom weaver of Rajivnagar in Sircilla town, was unable to feed his family, including aged parents and two children. His wife had died of tuberculosis. He was unable to get a job for over three months and the debts were increasing. </li></ul><ul><li>In despair he committed suicide at the young age of 32, due to lack of hope for himself or in the future for his children, </li></ul><ul><li>lack of perceived alternative avenues for employment </li></ul><ul><li>hunger and poverty, </li></ul><ul><li>lack of assets, </li></ul><ul><li>ill health, </li></ul><ul><li>responsibility for elderly and other dependents, </li></ul><ul><li>is repeatedly seen in many reports and needs attention in any discussion of chronic severity poverty. </li></ul>
  42. 47. Health related shocks <ul><li>In the context of health related shocks casual labourers cannot afford to take time off from work in case of ill health. </li></ul><ul><li>The food that they and their families eat, depends on the money earned from working that day. </li></ul><ul><li>  </li></ul><ul><li>  </li></ul>
  43. 48. Rising Morbidity Based on 30 Day Recall NSS 2 Rounds 89 33 F 81 30 M 84 31 P Urban 89 63 F 84 64 M 86 64 P Rural 1995-96 1986-87
  44. 49. Drinking Water, Illness and Poverty <ul><li>Poor Quality Drinking Water exists in both rural and urban areas. Data does not reflect the reality. </li></ul><ul><li>This has serious health related ramifications. </li></ul><ul><li>High incidence of hepatitis. </li></ul><ul><li>Pathogens, excess flouride, arsenic, salinity, iron and chemical pollutants like pesticides and insecticides in water </li></ul><ul><li>The poor cannot afford either the devices or the health related shocks and loss of work days from diseases caused by poor quality of water. </li></ul><ul><li>  </li></ul><ul><li>Source: Mehta and Menon, Alternative Economic Survey, 2000-01 </li></ul>
  45. 50. <ul><li>21% of all communicable diseases (11.5 % per cent of all diseases) are water related. Every year 1.5 million children under 5 years die in India of water related diseases and the country loses 1800 million person hours (over 200 million person days) each year due to water borne diseases. </li></ul><ul><li>Providing safe drinking water for all in real terms is a key policy concern. </li></ul><ul><li>Source: Mehta and Menon, Alternative Economic Survey, 2000-01 </li></ul>
  46. 51. Older Persons <ul><li>71 million persons > 60 and 27.1 m > 70 years old </li></ul><ul><li>58% of older females and 45% males in rural areas and 64% of females and 46% males in urban areas are fully dependent on others. </li></ul><ul><li>58% of older females and 28% of males had no financial assets and 52% of females and 19% of males owned no property. </li></ul><ul><li>63% of males and 58% of females continue to work beyond the age of 60. Even 80 year olds: 22% males and 17% females continue to work ostensibly due to poverty. </li></ul><ul><li>Source: Irudaya Rajan CPRC-IIPA working paper 17 </li></ul>
  47. 52. Urban Slums <ul><li>The urban poor in slums face situations of conflict and contested claims on spaces that provide livelihood earning opportunities and escape from chronic poverty. </li></ul><ul><li>  </li></ul><ul><li>forced relocation to areas that reduce access to livelihood opportunities increases costs. </li></ul><ul><li>fractured claims get reflected in other indicators such as prolonged low incomes, low food intake, and sustained exposure to health risks. </li></ul><ul><li>Source: Benjamin CPRC-IIPA working paper 4 </li></ul>
  48. 53. Remote Rural Areas <ul><li>Livelihoods based on seasonal migration from tribal areas as a coping strategy did not lead to exit from poverty in villages in south western MP. </li></ul><ul><li>  </li></ul><ul><li>Migrants face hostile situations in urban receiving areas access to home-based networks and services are ruptured. </li></ul><ul><li>a very basic level of sustenance is assured </li></ul><ul><li>indebtedness usually remains </li></ul><ul><li>human capabilities hardly change </li></ul><ul><li>in destination areas abuse is common </li></ul><ul><li>rights are not upheld and it is hard to avoid low self esteem. </li></ul><ul><li>Source: Shah and Sah, CPRC-IIPA working paper 5 and JHD 2004 </li></ul>
  49. 54.               A large proportion of the poor in remote areas are both chronically and severely poor and the incidence of this is negatively associated with size of land holding and household population. Remote rural areas are likely to experience chronic poverty on the basis of agro-ecological and socio-economic factors.            Unless efforts are made to develop the deprived areas, out migration from drought prone regions may only shift poverty from rural to urban or from dry land to agro-climatically better endowed regions.
  50. 55. Rural Infrastructure: Key to Anti Chronic Poverty Strategy <ul><li>Superior rural infrastructure accounts for regional differences in poverty among rural casual labourers. </li></ul><ul><li>promotes the shift from low productivity casual labour in agriculture to more productive casual labour in non farm sector </li></ul><ul><li>is the key to higher wages </li></ul><ul><li>Focus on improvement of rural infrastructure in states where poverty ratios are persistently high. </li></ul><ul><li>Source: Sheila Bhalla CPRC-IIPA working paper 14 </li></ul>