REVIEW OF LITERATURE

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1 CHAPTER 2 REVIEW OF LITERATURE Review of literature helps the researcher not only in understanding the issues involved but also in planning and execution of the experiences of others. Further, the knowledge of possible gap of empirical research provides cue to plug those gaps to the extent possible which in turn helps in making empirical research socially more meaningful. The present chapter reviews the empirical findings of some of the studies related to poverty, its problems and prospectus. Major issues that emerge from empirical studies on poverty concern defining and measuring poverty, extent of shift and factors affecting it, its spatial distribution, inconsistency between official poverty estimates and other estimates, and finally an evaluation of the performance of poverty alleviation programmes. However, it is of course, not possible to refer and comment in detail on all the studies conducted but a brief review of the selected studies is given below. 2.1 Defining and Measuring Poverty Various studies have been conducted in India on the basis of consumption expenditure definition of poverty given by Expert Group of Planning Commission (1962), calorie criteria recommended by Task Force (1977) and state specific poverty line proposed by Expert Group of Planning Commission (1993). Studies reviewed below concentrate on defining and estimating poverty (a brief of these studies is presented in Table 2.1). Minhas (1970) estimated poverty during to on the basis of the definition given by the Expert Group of Planning Commission (1962). Dandekar and Rath (1971), Bardhan (1973), Rudra (1974) and Ahluwalia (1978) defined poverty on the basis of calorie criteria. Ravallion and Datt (1996) used three poverty measures: Headcount Ratio, Poverty Gap Index and Squared Poverty Gap Index to estimate poverty during Mehta and Venktaraman (2000) found that the people on Official Poverty Line had means sufficient to acquire only 1968 calories per capita per day in the rural areas and 1800 per capita per day in urban areas which is quite less than required i.e calories per capita per day in rural and 2100 calories per capita per day in urban areas. In India, this is due Review of Literature 18

2 to changing food preferences. Many of the poverty indices used so far have been criticised on the ground that they do not take into consideration non- income variables, which are essential for preparing poverty index. They opined that much of the problem on measurement of poverty has been on poverty measures. Further, most commonly used poverty measures are Headcount Ratio, Poverty Gap Index, Sen Index, Foster-Greer-Thorbecke Index, Human Poverty Index, and Capability Poverty Index. Normally poverty in India is measured by Headcount Ratio. The incidence of poverty has been estimated by the Planning Commission in India at the state level using Headcount Ratio as a measure of poverty. Sundaram and Tendulkar (2003) used Headcount Ratio, Poverty Gap Index and Squared Poverty Gap to measure change in poverty ratio during Gaur (2005) using deprivation indices for three parameters, i.e. per capita state domestic product, per capita expenditure on medical and public health, per capita expenditure on education, prepared inter-state human poverty indices for 20 major states. He applied methodology of deprivation index as developed by Anand and Sen (1994). Gupta (2005) found that income and consumption measures failed to confine significant aspects of deprivation experienced by the poor. He applied Human Poverty Index and Capability Poverty Index to estimate poverty for different states. He estimated that human poverty ranged between 23 per cent in Kerala to 54 per cent in Bihar during Ray and Lancaster (2005) estimated poverty under alternative definitions of poverty line i.e. nutrient based poverty estimates. The authors used P 1, P 2, P 3, and P 4 Headcount ratios for alternative poverty lines: PL 1 -Official Poverty Line (calculated using consumer expenditure data of NSSO); PL 2 -Calorie Norm Poverty Line ( based on age and gender specific calorie requirement); PL 3 Nutrient Price Based Food Expenditure Poverty Line (calculated as per the recommendation of Indian Council for Medical Research);and PL 4 - Nutrient Price Based Total Expenditure Norm Poverty Line ( obtained by adding an allowance for non-food expenditure to PL 3 ). They calculated Headcount ratios for female headed households and SC households separately. Headcount ratios (P 1 to P 4 ) are 20.5, 47.5, 48.1, 36.6 respectively for female headed households and 33.8, 64.4, 59.6, 44.7 respectively for SC households in rural areas. It is 19.7, 34.3, 30.6, 15.7 for female headed households and Review of Literature 19

3 32.6, 46.1, 47.4, 27.5 for SC households, respectively in urban areas. Their results show higher headcount ratios (P 1 -P 4 ) among SC households than among female headed households. Further P 2 based on Calorie Norm Poverty (PL 2 ) is observed maximum for all studies in rural as well as in urban areas. Their study also underlines the importance of the public distribution system. The significance of this study lies in considering non-food expenditure along with food expenditure for constructing poverty line. Further, their projected poverty line includes disparity in food preferences due to regional, class, caste and other non-demographical factors that official poverty line did not consider. Sen and Chakarborty (2005) computed human poverty and capability poverty index for and Their study indicate that rank co-efficient of correlation between income poverty and capability poverty is very high (0.68 and 0.59 for and , respectively). Himanshu (2010) first explained the methodology of expert group approach and then suggested a new poverty line for India. The Planning Commission s estimates of poverty are based on food expenditure plus implicit allowance for non-food expenditure. For food expenditure, it relies on Recommended Dietary Allowances (RDA) i.e calories per capita per day for rural areas and 2100 calories per capita per day in urban areas. While calculating implicit allowance for non-food expenditure, it is assumed that health and education are to be provided by the state. After that, state-wise poverty line is calculated from all India poverty line by applying Fisher s indices. Then state-wise poverty line is updated by using Consumer Price Index for Agriculture Labour (CPI-AL) for rural areas and Consumer Price Index for Industrial Workers (CPI-IW) for urban areas. Official poverty estimates for are 28.3 per cent in rural and 25.7 per cent in urban areas. But NSS estimates are 79.8 per cent for rural areas and 63.9 per cent for urban areas. Looking at this discrepancy, the paper proposes a new set of poverty line using consumption expenditure survey of For constructing new poverty line, the author used NSS data for food, fuel, clothing, footwear which account for 75.8 per cent of consumption of poor; and for education expenditure, employment unemployment survey (EUS) of NSS 61 st round has been used. For health expenditure, the author has used 60 th round survey of NSSO. All this cover 90 per cent of consumption basket of the poor. It was assumed that the actual food expenditure of poor is Review of Literature 20

4 sufficient to afford nutritionally balanced diet as suggested by the National Institution of Nutrition (NIN). Also, he suggests that the new poverty line should be based on Mixed Reference Period consumption. Thus, the theoretical literature on defining and measuring poverty includes various studies by several economists like Minhas (1970), Ojha, Dandekar and Rath (1971), Bardhan (1973), Rudra (1974), Ahluwalia (1978), Ravallion and Datt (1996), Malik (2000), Sundaram (2001), Rajan (2002), Mishra and Rao (2003), Sundaram and Tendulkar (2003), Sundaram and Tendulkar (2004), Gaur (2005), Gupta (2005), and Himanshu (2010). They computed the proportion of people below poverty line by headcount ratio. Further, various studies have been conducted which stressed the need to develop poverty index based on income and nonincome variables. Economists like Meenakshi and Ray (2002), Meenakshi and Vishawanathan (2003), Radhakrishna (2004) and Ray and Lancaster (2005) define poverty on the basis of nutrition criterion. 2.2 Extent of Shift and Factors Affecting Poverty Various studies have concentrated on the shift in the percentage of Indian population below poverty line. These studies have shown that poverty declined during 1990s. However, there is disagreement regarding the extent of decline in poverty (a brief of the study has been presented in Table 2.2). The difference in the extent of poverty decline is ascribed to various reasons like difference in methodologies, measures and samples etc. Ravallion and Datt (1996) using time series of consistent consumption for 40 years ( ) and on the basis of poverty measures made an attempt to assess the extent to which India s poor shared the country s economic growth. Three poverty measures used by the authors for this study are: the headcount index; the poverty gap index; and the squared poverty gap index. The results of the study broadly indicate that rural growth reduced poverty; urban growth benefitted only urban poor; and growth in the primary and tertiary sectors reduced poverty both in rural and urban areas; and finally it is concluded that secondary sector growth did not reduce poverty in either of the rural or urban areas. Review of Literature 21

5 Table 2.1: Defining and Measuring Poverty Author/ Minhas (1970) Year Ravallion and Dutt (1996) Mehta and Venktaraman (2000) Sundaram and Tendulkar (2003) Gaur (2005) Gupta (2005) Ray and Lancaster (2005) Sen and Chakarborty (2005) Himanshu (2010) Study Period to Study Level Methodology National He estimated poverty on the basis of definition given by Expert Group Planning Commission, National They used three poverty measures: - Headcount Ratio, Poverty Gap Index and Squared Poverty Gap Index to estimate poverty during National He found that Official Poverty Line was adequate to purchase only 1968 calories in rural areas and 1800 calories per capita per day in urban areas National They used Headcount Ratio, Poverty Gap Index and Squared Poverty Gap to measure poverty ratio National He prepared Deprivation Index to depict inter-state human poverty index for twenty major states State He applied human poverty index and capability poverty index to estimate poverty. He found that in different states poverty ranged from 23 per cent to 54 per cent to to National National They considered non-food expenditure also for constructing poverty line. Their projected poverty line incorporated disparity in food preferences due to regional, class, caste and other non-demographical factors. Their study specifies that income poverty and capability poverty has very high rank coefficient of correlation National His paper proposes a new set of poverty line using consumption expenditure survey of Review of Literature 22

6 Malik (2000) using data based on NSSO from 1952 onwards showed that there was no long-term trend in poverty reduction from But, thereafter up to , a sharp decline in poverty has been observed. The decline however at a lower rate has been reported to continue till The study also showed that there took place a sharp increase in poverty in 1992 which declined after Trends in rural poverty have been found to observe a close proximity with trends in agricultural wages. The author pointed out the fact that the period of decline in poverty is one when rural poverty declines faster than urban poverty. He found that the initial impact of economic reforms undertaken by the government in 1990s was adverse. But subsequently a reversal of adverse trend has been observed. Sundaram (2001) examined the incidence of poverty on the basis of the monthly per capita consumption expenditure. The author developed empirical relationship between employment and poverty in 1990s. He compared data for with that of He computed the proportion of population below poverty line by gender, age and rural/ urban location. The study estimated 7.5 per cent decline in incidence of poverty among agricultural labour households, 6 per cent fall among other labour households, and 2.3 per cent fall among self-employees. Overall, the study emphasized that the results based on NSSO data 55 th round confirmed the direction of change i.e. decline in poverty over 1990s. The same conclusion was found valid for major states. The study found that, rural poverty and urban poverty declined in eight out of the fifteen major states. Rajan (2002) studied the impact of international trade on 100 developed and developing countries during The author provided the empirical evidence that the countries that managed to reduce poverty were those that have adopted trade liberalization policies. Trade leads to rapid growth and it reduces poverty at the same time. But only growth cannot be taken as a sufficient condition for poverty reduction, so the author further suggested the need of social safety nets to protect the poor from the bad impacts of liberalization. He emphasized that trade liberalization should be backed by sound macro policies, strong institutions and good investment environment. Mishra and Rao (2003) made an attempt to show that trade liberalization accelerates growth and thereby reduces poverty. The study, is based on cross- country regression Review of Literature 23

7 analysis from to period. They discussed macro-economic policies such as growth performance, investment, agricultural export, and recent policy developments in their paper. The authors on the basis of their study prepared analytical framework and model estimation. They examined relationship through auto regressive integrated moving average method (ARIMA), in which the dependent variables are explained by their own past i.e. lagged trends. The study shows that the lower tariff during the process of economic reforms in 1991 reduced the relative prices of manufacturing. It influenced the terms of trade in favour of agriculture and lifted private investment in agriculture. These have facilitated in increasing the aggregate crop output over the period. The increase in agricultural output has reduced rural poverty. Sundaram and Tendulkar (2003) found that poverty declined during They examined rural and urban poverty separately for 15 states. For comparison they resolved the problem of comparability of monthly per capita expenditure in 50 th ( ) round based on URP (uniform reference period) and 55 th ( ) round based on MRP (mixed reference period) by re-computing the data of 50 th round on the basis of MRP (mixed reference period). While measuring changes in poverty over 1990s at the state-level, the authors calculated the headcount ratio (HCR), i.e. size of the poor population; the poverty gap index (PGI) i.e. the depth of poverty; and squared poverty gap (FGT) i.e. the severity of poverty. The study found that poverty increased over the six years from to in Assam, Madhya Pradesh and Orissa. Assam recorded rise in poverty in terms of HCR, PGI and FGT. Madhya Pradesh showed a rise in HCR, and a decline in PGI and FGT. Orissa registered a decline in HCR, and rise in PGI and FGT. In the remaining 12 states, a decline in poverty ratio has been observed. The weighted average of PGI on MRP (mixed reference period) of 15 states declined from to and FGT declined from to The crux is that despite diversity across the states, poverty declined in 1990s. Sundaram and Tendulakar (2004) examined the change in magnitude of poor in Indian labour force between and The authors estimated size of poor in labour force in four segments: rural males, rural females, urban males and urban females. They presented the gender, activity status, and rural urban composition of these groups based on employment and unemployment for the 50 th and 55 th rounds of NSS. The study found that Review of Literature 24

8 poverty prevalence is more among rural and urban women workers than those for men. The aggregate magnitude of working poor was estimated to be 93.9 million in rural India and 20.9 million in urban India in Total number of working poor was million, which was 30 per cent of the working force. As per the estimates, from a level of 115 million, the number of working poor declined by a little over 12 million, almost entirely in rural area. The overall picture that emerged from the study is that there is a correlation between reduction in poverty and education. Education endowment increases the productivity of workforce and reduces poverty. Thus, the overall picture presented is that poverty declined in 1990s. Mehta and Bhandari (2005) explored trends in poverty in Asian developing countries. The paper examined trends in poverty in Asian countries using international poverty line at less than $1 and $1.08 per day (a standardized global poverty line at 1993 purchasing power parity) and using national poverty line. The whole frame work shows that poverty incidence has remained same between 1987 and After 1993, incidence of poverty appears to have declined rapidly again (World Bank, 1997). The authors pointed out that there are two causes of the low rate of poverty reduction in South Asia: first, low economic growth in the poorest countries; and secondly, persistent inequalities (in income and non-income dimensions) that prevented the participation of poor in growth. They concluded that pro-poor, sustainable economic growth, social development, good governance and micro finance can reduce poverty. Micro finance provides financial services to low income clients, like landless marginal farmers or poor urban dwellers etc. Micro financing has potential to increase the physical capital of poor and it builds human and social capital. Himanshu (2007) found that poverty did decline during , but the annual rate of reduction during this period had been lower than that of in 1970s and 1980s. The author confirms the earlier findings that the 1990s has indeed been the lost decade for poverty reduction. In this study, a little reduction in poverty has been observed in ; the bulk of decline having occurred in Poverty declined faster during but the annual rate of decline was lower than that of in the previous decade of The picture emerging from the poverty reduction during shows that poverty reduction at national level was due to poverty reduction in the states with above national average poverty till Further, his research paper shows evidence of improvements in non-income indicators during Review of Literature 25

9 Thakur (2010) examined the impact of growth on poverty and income distribution. He found that, at all India level, headcount ratio was per cent in and declined to 39 per cent in Inverse relation between growth and poverty has been observed in this study. Quoting the IGIDR (Indira Gandhi Institute of Development and Research) estimates, the author noticed that the Gini co-efficient was per cent in rural areas in During , it increased to per cent in rural areas. Thus, with development, magnitude of inequality has widened during post reform period, as per the study of the IGIDR, the World Bank (1955), the Planning Commission (1977) and the Tendulkar estimates. Some empirical studies in India like Ravallion and Datt (1996), Malik (2000), Sundaram (2001), Rajan (2002), Mishra and Rao (2003), Sundaram and Tendulkar (2003), Himanshu (2007), Mehta Rekha and Santosh Bhandari (2005) and Thakur (2010) have observed reduction in poverty during the post reform period. Poverty reduction is observed to be associated with economic growth. However, rate of reduction and factors affecting poverty differ from study to study. 2.3 District Level Studies A number of efforts have been made by researchers to investigate poverty at district level (see Table 2.3 for a brief summary). Mukherjee (2002) made an attempt to examine hunger at micro level. Using secondary data with Participatory Learning and Action (PLA) techniques, he carried micro study in 8 villages in various states. He found that while on the one hand we have the highest production of food, and on the other, we have largest number of people going to bed hungry. It is a harsher reality that the average Indian is hungry because they don t have food to get required nutrition. Even for 30 per cent of the poorest people, their food intake provides them with only about 1600 calories. Kozel and Parker (2003) reviewed the nature and evolution of poverty in Uttar Pradesh (UP). The authors used data collected by NSS, 55th round, administrative records, participatory studies and consultations. Along with the UP state sample of NSS, 55 th round data on a set of monitoring indicators was collected by the Government of Uttar Pradesh. For the same households, a special poverty module (Schedule 99) was prepared. The new module included information on many indicators, e.g. access to education, health services, infrastructure (water, sanitation), and use of specific anti-poverty programme. The authors found that poverty in UP is related to material deprivation, deprivation of human resources, Review of Literature 26

10 Table 2.2: Empirical Studies at a Glance: Extent of Shift and Factors Affecting Poverty Author/ Year Ravallion and Datt (1996) Malik (2000) Sundaram (2001) Rajan (2002) Mishra and Rao (2003) Sundram and Tendulkar (2003) Sundram and Tendulkar (2004) Mehta and Bhandari (2005) Himanshu (2007) Thakur (2010) Study Data Study Level Period Source Conclusion National Secondary Rural growth reduced overall poverty. Urban growth reduced only urban poverty National Secondary The decline in poverty during NSSO the study period was due to data decline in rural poverty faster National Secondary data based on NSSO 55 th round National Secondary NSSO data National Secondary NSSO data than urban poverty. Rural poverty and urban poverty declined in the eight of the fifteen major states. Trade liberalization policies reduce poverty. The increase in private investment in agriculture has contributed to reduction in rural poverty State Level Secondary Despite increase in poverty in a few states, overall poverty declined in 1990s National Secondary 50 th and 55 th round of NSSO data 1987 onwards There is a correlation between reduction in poverty and education. International Secondary After 1993 incidence of poverty declined rapidly in Asian developing countries. Low economic growth and persistent inequalities were the two causes of the low rate of poverty reduction in poorest countries of South Asia. National Secondary Rate of poverty reduction was lower in in comparison to 1970s and 1980s. National Secondary At all India level, headcount ratio was per cent in and it declined to 39 per cent in Review of Literature 27

11 social contacts, voice and power. Poverty data for UP reveals considerable regional differences, and shows that levels of poverty increases from west to east. The authors concluded that programme and policies designed to redress poverty must be aware of its various dimensions. Murgai and Suryanarayan (2003) pooled central and state samples for Karnataka from the NSSO 55 th round to examine regional variations in poverty. Using official poverty line, the authors estimated district-wise headcount ratios and poverty gap. The broad picture that emerged from poverty estimates is that urban poverty in Karnataka is the same as at the all India level, but it is higher than its rural poverty. The study also found concentration of poor in northern districts and significant variation in poverty levels within divisions. Krishna et al. (2004) selected 36 villages from three districts of Andhra Pradesh. Almost all the selected villages had majority of SC, ST and OBC groups. Their study reveals that 65.5 per cent of households in these villages were poor 25 years back and 63.5 per cent are poor today; the net change is negligible. It is merely 1.9 percentage points. Further, 14.1 per cent of all households were found to have escaped poverty. At the same time, 12.2 per cent of households were found to have simultaneously fallen into the trap of poverty over 25 years. The extent of poverty varied considerably from village to village. Percentage of households in poverty decreased in 22 out of 36 villages, but it increased in the remaining 14 villages. A combination of factors i.e. ill health, health related expenses, social and customary expenses, high-interest rate on private debt, large size of family, laziness and drunkenness etc. were major causes of poverty. Jobs in private and government sectors, irrigation, government assistance and new agricultural technologies helped in escaping poverty. The authors suggested one set of policies to promote households to escape from poverty, another and different set of policies to prevent descent into poverty. The author suggested both sets of policies simultaneously to deal separately with these two trends. Kohli (2005) conducted a study for whole of the state of Rajasthan as well as for its different regions during and For the analysis of poverty, the state was divided into four regions. The author computed region-wise different measures of poverty i.e. HCR, PGI and FGT. The study found that rural poverty declined in all the regions. Highest poverty was observed in southern Rajasthan. Regional variations increased during this period. Rate of decline in urban poverty was less than rural poverty. Urban poverty increased in the east and the south-east of Rajasthan. Increase in urban poverty was due to migration of rural poor to urban areas. A social poverty index was constructed by the author. Positive rank correlation co-efficient was found between economic poverty and social poverty. The author Review of Literature 28

12 concluded that if economic poverty is to be removed, policies should be made to reduce social poverty. Further, growth does not trickle down to the poor, so development decisions should be taken at micro level. Sailbala (2005) made an attempt to study the pattern of poverty in rural Orissa and role of education in reducing poverty. Using the secondary data for the year , she calculated percentage of families below poverty line by social groups, by income categories and by occupation status. The study reveals that incidence of poverty was high among the lower income categories, scheduled tribes and marginal farmers. It also found a strong inverse relationship between education and poverty. The study suggested that the government should educate people to promote their participation in poverty eradication programme. Sidhu et al. (2005) made an empirical analysis of economic conditions of agricultural labour in rural Punjab. On the basis of value of crop productivity, they divided districts of Punjab in three regions, and selected one district from each region. They surveyed 150 agricultural labour households from three districts namely Fatehgarh Sahib, Bathinda and Ferozepur. They calculated levels and patterns of income, distribution of income, levels and pattern of consumption, distribution of consumption and incidence of poverty. Their focus was on determinants of poverty. Their study estimated that 41 per cent of agricultural labour was below poverty line. Their average propensity to consume was 1.07, which is greater than one, implying that there is agricultural deficit. About 84 per cent of the households were found under debt and it is to be noted that 85 per cent of their debt was from non-institutional sources. Also, per cent of debt was used for non-productive purposes. The study recommended that income level of poor people can be increased by increasing wage rate and creating opportunities of labour employment. Further, top priority should be given to development of non-farm sector. They suggested that mass campaign should be launched against intoxicants and conservative social values. A thorough analysis of empirical literature on district level studies on poverty reveals that there is variation in poverty level. Further, some of the district level studies endeavored to examine extent of poverty by income group, social group and occupation categories. Other studies examined the factors affecting poverty at district level. However, a few studies concentrated on construction of composite poverty index. Under the thrust of poverty reduction, most of the district level studies suggested that poverty decisions should be taken at micro level and maximum participation of the poor should be ensured. Review of Literature 29

13 Table 2.3 : Empirical Studies at a Glance: State and District Level Studies Author / Year Study Period Study Level Data Source Conclusion Mukherjee (2002) Haryana, U.P., West Bengal Primary data of 8 villages 30 per cent of people took only about 600 calories. Despite surplus food production, a large number of people go to the bed hungry. Kozel and Parker (2003) Study of Uttar Pradesh Secondary 55 th round of NSSO Data, CSO Data By land 33.2 per cent, by education 31.1 per cent and by occupation 32.4 per cent people live below poverty line. In UP poverty was not only due to material deprivation but also due to poor human resource, inadequate social contacts. Murgai and Suryanarayan (2003) State Level Secondary 50 th round of NSSO Data 16.8 per cent rural people and 22.6 per cent urban population is BPL. The urban poverty in Karnataka was at par with India, but it was higher than rural poverty level. Krishna et al. (2004) 2000 and 25 years ago (1975) District Level (Andhra Pradesh) Primary Data of 36 Villages of 3 districts of Andhra Pradesh were surveyed. In Andhra Pradesh about 65.5 per cent were poor in 1975 and it reduced to 63.5 per cent in The reasons for falling in to poverty and escaping poverty are different, so one set of policies is required to enable households to escape from poverty and another to prevent households from falling into poverty. Review of Literature 30

14 Author / Year Study Period Study Level Data Source Conclusion Kohli (2005) State Level (Rajasthan) Secondary NSSO rounds Sarvekshana, Economic Survey In , per cent, and, in , per cent people were poor in Rajasthan. To remove economic poverty, focus should be on policies to remove social poverty. Sailbala (2005) District Level Rural Orissa Secondary Data Incidence of poverty was high among lower income categories, scheduled tribes and marginal farmers per cent rural were poor. A strong inverse relationship between education and poverty is observed. Government should educate people for their participation in poverty alleviation programmes. Sidhu et al Rural Punjab Primary data of 160 households from 8 villages trough the personal interviews. They recommended that income level of poor people (41 per cent of agricultural labour) can be increased by increasing wage rate and employment level. Review of Literature 31

15 2.4 Identification of the Poor Identification of poor households is very important for result oriented implementation of government poverty alleviation programme. But official calorie based definition of poverty excludes many poor from below poverty line. There are various scholars who have suggested broader criterion, for identification of poor. A few studies conducted for identification of poor have been mentioned below (see Table 2.4 for a brief summary of this section). Rao (1998) is of the view that poverty is a multi-faceted phenomenon; and identification of poor on the basis of income may not be acceptable. There is need to replace the conventional norm with multiple indicators. He has quoted the survey conducted in Senapannallur, a backward village in Trichy district of Tamil Nadu state, during The sample of 300 households was classified on the basis of income earned of Rs.700 per annum into poor and non-poor. At this income level, almost 75 per cent of households were found below poverty line. A list of 56 indicators of poverty, based on the perceptions of the poor was prepared. A three stage process was pursued on the basis of these 56 indicators of poverty. For each indicator, mean and standard deviation were calculated separately for poor and non-poor. After calculating T-test for difference of mean or proportions selected indicators were retained on which poor differ from non-poor. These indicators were further analysed. Some indicators were dropped on the basis of correlation analysis. With the help of discriminant function technique, the indicators with low discriminating power were deleted and indicators with higher discriminating power were selected. In this way eight indicators were selected in all. But the set of selected variables used were not sufficient to replace income criterion. He emphasized the fact that there was need of inclusion of few more indicators for comprehensive analysis. Rudra et al. (1998) emphasized that the effective implementation of individual beneficiary oriented programme of the government depends on identification of poor households; otherwise non-poor households get the support under poverty alleviation programme by hiding their income. The authors suggest a much broader criterion for identification of the poor, which is different from official working group criterion. They pointed out that on the basis of schedule on Fulfillment of Basic Needs consisting 17 items related to basic needs of food, clothing, bedding, shelter, health care etc. poor household can be judged by median and quartiles of deprivation score. Review of Literature 32

16 Slanthi (1998) highlighted drawbacks in existing criteria of identification of poor. A few of the drawbacks pointed out are: i) The calorie norm is calculated on least cost diet; ii) The qualitative dimension is completely ignored; iii) Inter-regional, intra-regional, interpersonal and intra-household variations in calorie intake are ignored; iv) Ignoring two important needs, i.e. health and education, and v) Poverty is analysed in absolute terms, not in relative terms. He suggested that there is need of alternative criteria for identification of the poor. Guruswamy and Abraham (2006) established that Planning Commission has been defining poverty on the basis of a nutritional norm of 2400 and 2100 calories respectively in rural and urban India. They argued that poverty line that takes into account only food consumption and ignores other basic needs of non-food requirements is in fact a Starvation Line. They stressed that the new poverty line should include proper nutrition, drinking water availability, shelter, hygiene, clothing and education. According to them, the present poverty line has three major problems viz: poor class does not even meet the calorie norm; only calories standard is not enough; no norm is specified for non-food basic needs. So, there is a need to redefine poverty in India. It should include the cost of nutrition, healthcare, clothing, etc. In addition to this, there are some needs that cannot be quantified in money terms such as access to water, education, sanitation etc. To take decision on the basis of only food in-take is aiming too low. By including minimum cost for nutrition, health, clothing, energy and miscellaneous (Rs.573, Rs.30, Rs.17, Rs.55, and Rs.164, respectively) the poverty line calculated is approximately Rs. 840 per capita per month. On the basis of above calculated poverty line of Rs. 840 per month, a household of five people should earn Rs per month or Rs.50, 000 per year and should have access to pucca house with the facilities of electricity and toilet connected to a sewage system. Children of the household should have access to education and they should have access to water within 1 to 15 meters of the dwelling unit. They defined a person as poor if MPCE is less than Rs. 840 or does not have access to basic amenities. At this expenditure level, 84.6 per cent of rural, 42.4 per cent of urban and 68.8 per cent of India s population is below poverty line. Their calculated poverty ratio is over two-and-a- half times of official poverty ratio. Majumder and Basu (2006) concentrated on four states of India, i.e. Andhra Pradesh, Kerala, Punjab and West Bengal. They used NSSO 50 th round ( ) data for Review of Literature 33

17 rural and urban sector separately. They pointed out that most of the studies on poverty are based on the assumption that there is equal distribution of funds among all the members of the households. But in reality women don t receive appropriate share. So, women living in non-poor households may actually be poor. In this way, there is under estimation of female poverty and over estimation of male poverty. When the unequal sharing aspect is taken into account the results are quite different. Dreze and Khera (2010) made an attempt to explore simple method of identification of BPL households on the basis of exclusion and inclusion criteria. The BPL census conducted in 2002 based on a "Scoring method" to identify BPL households has had serious conceptual defects. Their study shows that hardly half of all household in the poorest monthly per capita consumption expenditure quintile have had a BPL card, while 18 per cent of households in the richest quintile had this. Even the wealth index found high rate of exclusion from BPL list among the underprivileged social groups. They criticised scoring method because it lacks transparency as well as verifications. The study suggests exclusion and inclusion criteria for identification of Social Assistance Base. Person possessing simple list of durable assets: car, refrigerator, landline telephone, scooters and coloured television and amenities like electricity, tap water and flush toilet and multi-storied pucca house is also considered as base line exclusion criteria. They formulated four sets of exclusion criteria. They suggested inclusion criteria as a complement to exclusion criteria.the priority groups suggested for inclusion criteria are: SCs/STs households, landless households, households with no adult member educated beyond class 5, single women households and agriculture labour households. They further suggested different ways of merging exclusion and inclusion criteria for identification of Social Assistance Base (SAB). From the above literature on identification of poor, it is clear that poverty is not only material deprivation but also deprivation of social contacts and power. So, its various dimensions must be considered for identification of poor. 2.5 Inconsistency between Official Poverty Estimates and Other Estimates In this section an effort has been made to explore the gaps of various poverty estimates. (a brief of the studies is presented in Table 2.5). Review of Literature 34

18 Datt, et al. (2003) states that following 30/30/365 days recall estimates, the NSS 55 th round shows reduction in poverty. The Planning Commission s (2001) estimate also indicates that national poverty rate fell by about 10 per cent, from 36 per cent in 1993 to 26 per cent in The rural poverty rate is also estimated to have fallen from 37 per cent to 27 per cent. If the 7/30/365 day estimates from the 55 th round are compared with the past 7/30/365 day estimates rounds (51 st to 54 th ) an increase in poverty by 2 percentage points in the rural and by 5 percentage points in urban area between 1994 and 1999 is observed. Table 2.4 : Empirical Studies at a Glance: Identification of the Poor Rao Author / Year (1998) Rudra et al. (1998) Slanthi (1998) Guruswamy and Abraham (2006) Majumder and Basu (2006) Dreze and Khera (2010) Study Period Study Level Conclusion 1985 District Poverty being a complex phenomenon, there is need to replace conventional indicators with a set of correlated indicators Five Districts of West Bengal to Suggested comprehensive criterion for the identification of poor. Poor household can be judged on the basis of schedule on Fulfillment of Basic Needs covering 17 items. National Identifying the drawbacks in existing criterion for the identification of poor, he suggested an alternative criterion for the identification of poor National There is need to redefine poverty line on the basis of basic needs such as nutrition, drinking water availability, shelter, hygiene, clothing and education State Female poverty is underestimated and male poverty is over estimated as women do not get their fair share of household resources. This feature of unequal sharing affects the rank of the state National They suggested exclusion and inclusion criterion for identification of poor. Review of Literature 35

19 Gupta (2003) found that the expert committee method of poverty estimation excluded many poor from below poverty line. He is of the view that the poverty line both in rural and urban areas was estimated by updating the nominal value of the poverty line expenditures of through appropriate price deflators. The index used by committee for updating poverty line was based on Laspeyre s formula. This resulted in an underestimation of poverty. Rath (2003) stated that poverty line by Dandekar and Rath (1971) was calculated on the basis of household consumer expenditure survey of by NSSO. But from 1972 onwards, though NSSO carried out a large sample consumer expenditure survey but the tabulated calorie data was not published. Rather, in poverty determination, focus has shifted from calorie based approach to income based approach. He examined a method of estimating poverty on the basis of price indices. His study based on the NSSO data has created a detailed price index structure for each state of India. It used maximum individual commodities and subsequently he found deep disconnection between income poverty and food consumption. Complexity of monetary poverty and nutritional status has been observed. Increasing income and declining calories intake among poor in many states has shown declining poverty incidence of monetary poverty. The results of the studies based on price indices and those of the expert group are noticeably different. Ravallion, et al. (2003) found that there are discrepancies between National Accounts Statistics (NAS) and National Sample Survey (NSS) estimates of poverty. Final consumption expenditure of NAS is based on commodity flow approach whereas NSS collects data from the household survey. The poverty estimates based on consumption measured through NSS are, therefore, higher than that of obtained from NAS. There are also conceptual differences between the two measures. National Accounts Statistics (NAS) includes expenditure of NGOs and religious institutions in compiling national accounts. So, their estimates show lower poverty ratios as compared to National Sample Survey (NSS) estimates. Besides this the difference in method and coverage, the extent of difference also matters. NSS underestimates consumption level and ignore consumption growth. Thus it is underestimating the rate of poverty reduction also. There is inconsistency between NSS and NAS as regards poverty estimates and poverty reduction. An alternative source of household survey data for Review of Literature 36

20 India is the Market Information Survey of Household (MISH) done by NCAER, but this survey does not include food consumption. So, consumption poverty measures are not comparable with NSS. Sundaram and Tendulker (2003) observed National Accounts Statistics (NAS) has wider coverage than and National Sample Survey (NSS) estimates. The estimation procedure of NAS and NSS is quite different. PFCE from NAS is an indirect, residual macro level estimation. Where as HCE drawn from NSS is a directly observed over a period of given time. Further, there are differences in the estimation procedure also. NSS is sensitive to cooperation from respondent households. NAS is required for economic policy formulation. As a result, NAS results are updated periodically. Due to above differences the estimates of consumption are lower in NSS as compared to NAS. Poverty ratios are therefore higher in case of NSS. The estimates of poverty of NSS are considered reliable as it is based on direct observation. Himanshu (2008) observed that the international poverty line of $ 1 per day per person was taken for international comparison programme for the first time in This poverty line was updated at $ 1.08 and $ 1.25 cut off in 2001 and 2005 respectively. The new World Bank estimates put the total number of poor in the world at 1.4 billion (25 per cent of world population) which is 400 million more than previous World Bank estimates of global poverty. The World Bank estimates for poverty in India based on $ 1.25 cut off line in 2005 is 41.6 per cent. Asian Development Bank using $ 1.35 per day per capita cut off estimates poverty in India at 63.9 per cent. The Planning Commission, estimated poverty in India at 27 per cent for It clearly indicates that Indian poverty line underestimates poverty in India. The reports (2005) of the World Bank and the Asian Development Bank estimate that India is a country with largest number of poor in the World. It accounts for 1/3 rd of the total poor in the developing countries of the world. Patnaik (2010) collected data of average monthly per capita expenditure (AMPCE) and average calorie intake by expenditure classes. This data was collected from NSS reports 508 and 513 relating to the 61 st round for the period The study reveals that with mean expenditure level of Rs , average calorie intake of 2100 is possible. In urban Review of Literature 37

21 areas 64.5 per cent population spends less than Rs yet, the official Planning Commission figure of urban poverty is 25.7 per cent. The difference between 64.5 per cent poverty ratio on the basis of nutrition norm and 25.7 per cent official poverty ratio is 38.8 percentage points. It implies that two- fifth of urban poor have been excluded from the set of the officially poor in The author calculated the poverty percentage on nutrition norms and compared it with the official poverty ratio for all 18 states for The results show an alarming scenario that 60 to 80 per cent of urban population in these 18 major states did not have access to 2100 calorie intake. Patnaik analysed that, in Punjab, officially only 7.1 per cent of urban persons were poor at poverty line of Rs , i.e. less than Rs. 16 per day. At this spending level, only 1435 calories could be accessed, i.e. deficit of 665 calories from urban nutrition norm. In order to reach 2100 calories, Rs.1280 MPCE was required. In this way, nearly 68.8 per cent of urban population was below poverty line. The study shows that actual urban poverty ratio is 70 per cent whereas officially it is only 7 per cent. The study further recognized that food grain allocation from central pool to most states is inadequate. The study suggests going reverse to universal distribution system. In short, inconsistency between official poverty estimates and other estimates has been observed by many empirical studies. This has been attributed to differences in coverage, concepts, time period, and estimation procedure. 2.6 Performance of Poverty Alleviation Programmes Poverty is a multi-dimensional problem. War against poverty has, therefore, to be fought in different sectors from several angles. In order to alleviate poverty, different policies and programme are required. Various studies, e.g. Ahluwalia (1978), Shrinivasan (1985), Dev (2000) show that agriculture has direct impact on poverty. Substantial literature is available to examine performance of poverty alleviation programmes. Rangnekar (1958) analyzed that agriculture is basic and vital to Indian economy. Therefore, the first task is to tackle the agricultural problem, to boost agricultural production and to plant some dynamism in rural economy. Review of Literature 38

22 Table 2.5 : Empirical Studies at a Glance: Inconsistency Between Official Poverty Estimates and other Estimates Author/ year Study Period Study Level Conclusion Datt et al. (2003) Gupta (2003) National The NSS 55 th round compared with (51 st to 54 th ), shows 10 per cent reduction in poverty on the basis of uniform recall period (30/30/365) but on the basis of mixed recall period (7/30/365) the poverty decreased by 2 percentage points in rural area and 5 percentage points in urban area during period National The direct method of poverty estimation (Expert Committee Criterion on calories basis) showed lower percentage of population below poverty line. Rath (2003) to State Compared his results with those of Planning Commission and found them to be considerably different. Ravellion (2003) National NAS estimates show significantly lower poverty ratios as compared to NSS estimates. Sundaram and Tendulkar National The estimates of NSS are reliable as these are based on direct observation. (2003) Himanshu (2008) and 2005 National Indian Poverty Line underestimates poverty in comparison to estimates of World Bank and Asian Development Bank. Patnaik (2010) State The urban poverty is 70 per cent whereas the official poverty is only 7 per cent in Punjab. Even the state estimates of BPL population are not correct though they are much higher than the Planning Commission estimates. Review of Literature 39

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