The term ‘rural poverty’ is the opposite of the term ‘rural development’. It implies the lack of development, or underdevelopment, and therefore, the knowledge of its measures also is as important for a student of rural development as that of measures of rural development. In this section, we present some commonly used measures of rural poverty.
Rural poverty is a worldwide problem; it exists in both developing and developed countries of the world. Over one billion people in the world are estimated to be living in poverty. The incidence of poverty is highly uneven among the regions of the world, among countries within those regions, and among localities within those countries.
Nearly half of the world’s poor live in South Asia, a region that accounts for roughly 30 per cent of the world’s population. Alleviation of poverty has been an important objective of development policies and programmes all over the world, including India.
Connotations and Defi nitions of Poverty
There is no universally acceptable defi nition of poverty, although there are several connotations and defi nitions in vogue. Poverty implies a con dition of life characterised by deprivation of some sort or the other, and perceived as undesirable by the person(s) concerned or others. It is a multidimensional concept and phenomenon. Generally, there is a con sensus among scholars about poverty being conceived and defi ned as absolute or relative. Absolute poverty implies a person’s lack of access to objectively determined reasonably adequate quantities of goods and services to satisfy his material and non- material basic needs. Relative poverty, on the other hand, means that a person’s access to the basic needs of life is relatively lower, as compared to some reference group of people. Between two households or two persons, one may be considered as poor, while the other in comparison may not be so, even though both may be in a position to fulfi ll their basic material needs.
Criteria for Measuring Poverty
Measurement of poverty is beset with numerous conceptual, method ological and em- pirical problems. Conceptually, it is diffi cult to defi ne poverty in operational terms that are universally acceptable. Method ologically, there is no consensus among scholars about the best indicator or measure of poverty, and empirically, given the choice of a particular measure of poverty, it is very diffi cult to collect reliable data necessary for computing the value of the indicator/measure chosen. These problems notwithstanding, policy makers, planners and scholars have attempted to measure poverty, and have used poverty measures to monitor changes in the level/incidence of poverty and for other purposes.
The magnitude of poverty at any given point in time depends on the criteria or norms used to defi ne poverty and determine the poverty line. There are two criteria or norms usually employed to defi ne the poverty line:
1. The norm based on the concept of a nutritionally adequate diet.
2. The norm based on the concept of a minimum level of living.
A number of research scholars have attempted to estimate the cost of providing a nutritionally adequate diet. For example, Dandekar and Rath (1971: 8–9), on the basis of an average calorie intake of 2,250 per capita per day, estimated the poverty line to correspond to a consumer expenditure of Rs 15 per capita per month for rural households, and Rs 22.50 for urban households at 1960–61 prices.
As far as the second norm based on the concept of a minimum level of living is con- cerned, a distinguished Working Group2 constituted by the Planning Commission, Govern ment of India, in July 1962, deliberated on the question of what should be regarded as the nationally desirable minimum level of consumer expendi ture. The study group recommended that a per capita monthly consumer expenditure at 1960–61 prices of Rs 20 for rural areas and Rs 25 for urban areas should be deemed the national minimum.
This does not include expenditure on health and education, which are expected to be provided by the state; the ‘minimum’ for the urban areas assumed an element of subsidy in urban housing.
A ‘Task Force on Projection of Minimum Needs and Effective Consumption Demand’
constituted by the Planning Commission in 1979 defi ned the poverty line as that per capita expenditure level at which the average per capita per day calorie intake was 2,400 kcal for rural population and 2,100 kcal for urban population. The recommended poverty line was Rs 49.09 per capita per month for rural population and Rs 56.64 per capita per month for urban population at 1973–74 prices. The Task Force also recommended an adjustment in the consumption expenditure levels estimated by the NSSO by raising it by a ‘factor’ to make it consistent with the total level of private consumption expend- iture reported in the National Accounts Statistics (NAS), which was higher. This ‘factor’
was small in the beginning but grew larger and larger over the years.
The Expert Group (EG) constituted by the Planning Commission in 1989 recommended the continuation of the Task Force poverty line (Rs 49.09 for rural areas and Rs 56.64 for urban areas at 1973–74 prices) as the level separating the poor from the non-poor. The EG recommended specially constructed state-wise indices for updating the poverty line for price changes. It also recommended the abandoning of the adjustment of NSSO-based consumption expenditure with NAS consumption expenditure, since the reasons for the differences were diverse and the NSSO survey obtained direct information on consumption and, hence, was more reliable. Following the EG recommendation, the poverty series were revised by the Planning Commission from 1973–74 onwards. Since then the offi cial poverty estimates are based on the methodology recommended by the EG. The methodology suggested by the EG is summarised as follows (Radhakrishna and Ray 2005).
The poverty lines are anchored to a fi xed commodity basket corresponding to the Task Force recommended poverty line (Rs 49.09 per person per month at 1973–74 prices for rural areas and Rs 56.64 for urban areas, as specifi ed in the previous paragraph). The rural commodity basket suggested by the EG contained 2,400 kcal per capita per day in rural areas and the urban food basket had 2,100 kcal per capita per day in 1973–74.
The use of calorie norm was taken as an approximation to what may be considered as an acceptable ‘minimum needs’. The consumption basket is common to all states. In order to take care of the changing tastes and preferences, the EG recommended that the consumption basket be revised once in fi ve years. This was to take care of ‘minimum needs’
as derived from the chosen nutrition attributes as revealed by the behaviour patterns of consumers.
The consumption basket thus identifi ed separately for rural and urban areas is evaluated at state specifi c prices to arrive at state specifi c poverty lines in the base year, 1973–74. The state-wise poverty lines computed for the base year 1973–74 are adjusted for prices for the subsequent years. For any year, poverty levels are estimated for each state using the state level consumer expenditure distribution. Aggregating the state-wise poverty ratios, the all-India poverty ratio is estimated. Given the all-India poverty ratio, poverty line is estimated using the consumer expenditure distribution for that year. The state specifi c poverty lines for the year 2004–05 are presented in Table 3.7.
We now briefl y present some commonly used measures/indicators of poverty.
Some Common Measures and Indicators of Poverty
Though Head Count (HC) is the most popularly used measure, three other measures, that is, Poverty Gap (PG), Squared Poverty Gap (SPG) and Sens’s Index are also important for their properties. The fi rst three measures belong to a class of additive measures.
There are good surveys on the measurement of poverty (Atkinson 1987; Foster 1984).
We briefl y mention the main issues having a bearing on policy analysis. Let y denote per capita consumer expenditure and z denote the poverty line. Let f(y) be the density function and f(y) be the cumulative distribution function (CDF). A function f(y, z), non- increasing in y and non-decreasing in z, is a measure of poverty. A desirable property for the function is homogeneity. In other words, the measure is scale neutral. Various ways of aggregating the p(y, z)’s have been proposed in the literature. However, additive measures satisfy sub-group consistency, which means that when poverty increases in any sub-group of the population (say agricultural labourers) without a decrease elsewhere, the aggregate poverty should also increase.
A sub-group inconsistent measure may mislead policy analysis, as the measure may not show decline in national poverty even when it declined in a particular area. The class of additive poverty measures is given by:
P (z) = ∫p (y, z) f (y) dy (3.1)
The limits of integration are 0 and q. All the three measures of poverty, that is, HC, PG and SPG are derived by taking (1 – y/z)α for p (y, z) and giving 0,1 and 2 to α:
P (z) = ∫(1 – y/z)α f (y) dy (3.2) The limits of integration are 0 and q.
The Head Count (HC) Index
This measure is widely used now-a-days. It is simply the proportion of population whose consumption (y) is less than the poverty line (z). This is simply the value of P(z) when α = 0 in equation (3.2). The measure is easy to understand and communicate, but it has two serious drawbacks which affect policy analysis. First, it violates monotone axiom of welfare, which states that an improvement in the income of some people, given the incomes of others, should reduce poverty. The HC ratio is not sensitive to changes in income as long as these changes do not move a person from one side of poverty line
Table 3.7 State Specifi c Poverty Lines in India in 2004–05
(Rs per capita per month)
S.No. State/UTs Rural Urban
1. Andhra Pradesh 292.95 542.89
2. Assam 387.64 378.84
3. Bihar 354.36 435.00
4. Chhattisgarh 322.41 560.00
5. Delhi 410.38 612.91
6. Goa 362.25 665.90
7. Gujarat 353.9 541.16
8. Haryana 414.76 504.49
9. Himachal Pradesh 394.28 504.49
10. Jammu & Kashmir 391.26 553.77
11. Jharkhand 366.56 451.24
12. Karnataka 324.17 599.66
13. Kerala 430.12 559.39
14. Madhya Pradesh 327.78 570.15
15 . Maharashtra 362.25 665.90
16. Orissa 325.79 528.49
17. Punjab 410.38 466.16
18. Rajasthan 374.57 559.63
19. Tamil Nadu 351.86 547.42
20. Uttar Pradesh 365.84 483.26
21. Uttarakhand 478.02 637.67
22. West Bengal 382.82 449.32
23. Dadra & N. Haveli 362.25 665.90
All-India* 356.30 538.60
Source: Anonymous (2007: 44).
Note: *The poverty line (implicit) at the all-India level is worked out from the expenditure class-wise distribution of persons (based on Uniform Recall Period [URP] consumption, that is, consumption data collected from 30-day recall period for all items and the poverty ratio at all -India level. The poverty ratio at all- India level is obtained as the weighted average of the state-wise poverty ratios.
to the other. The measure also violates the transfer axiom of welfare, which states that transfers from a richer to a poorer person should reduce poverty. This violation has a serious implication that a given improvement of incomes through policy interventions will have high impact if those who are close to the poverty line are selected.
The Poverty Gap (PG) Index
This is obtained by setting α = 1 in equation (3.2). It measures the depth of poverty as it depends on the distances from the poverty line as well as the number of the poor. The widely used income gap ratio is I = 1 – μP/z = PG/H, where, μP is the mean value of y for the poor. It measures average proportionate shortfall below the poverty line. This is a deceptive measure because if a poor person with a standard of living above μP escapes poverty, the income gap ratio will rise, though no one is worse off and one of the poor is, in fact, better off. Therefore, PG is a better measure than the income gap ratio. While it satisfi es the monotone axiom, it is insensitive to transfers from a better off poor to another poor person, as the gap remains the same as long as both remain poor. While it gives depth of poverty, it does not indicate the severity of poverty, as it uses no weight for the gap from the poverty line.
The Squared Poverty Gap (SPG) Index
This measure, proposed by Foster et al. (1984), indicates the severity of poverty and it is obtained by taking α = 2. This is a strictly convex function, a desirable property of a welfare function.
Sen’s Index
Sen (1976) proposed an index of poverty that combines the number of poor, the depth of poverty and the distribution of the poor within the group. The formula is given by:
Ps = 2/(q + 1) n Σ (1 – yi/z) (q + i + 1) (3.3) where q is the number of poor and q + i + 1 is the weight accorded to the ith poor person from the poverty line. The formula can be expressed in terms of the average of the HC (P0) and PG (P1) measures weighted by the Gini coeffi cient of inequality among the poor (Gp).
Ps = P0Gp + P1 (1 – GP) (3.4)
Some estimates of HC index of poverty are presented in Chapter 10, Section 10.2 of this book.
The Housing Index
Gibbons (1997) proposed this index as a cost effective measure/tool for identifying the poor. He asserts that this index has been found to be valid and useful in a number of countries, such as China, Vietnam, the Philippines, Indonesia, India and Bangladesh, and that the index can help identify about 80 per cent of the poor very quickly; it takes about fi ve minutes for an experienced fi eld assistant to use the index properly.
The Housing Index has three components, namely, (a) the size of the house; (b) the physical condition of the house, as refl ected in the mate rials used in its construction; and (c) the type of materials used for making the roof of the house. All the three dimensions of the index can be looked at and assessed through going up and down the lanes/streets in a village. One does not have to conduct any interviews using questionnaires or schedules.
According to Gibbons, the material of the roof is a simple but powerful indicator of poverty in most countries of Asia. The poor in those countries live in houses having thatched roofs or roofs made out of woven bamboo or twigs, or plastic sheets that have holes, with the roofs leaking and creating health problems. Nobody wants to live in such houses unless one has to. So the people living in such houses are really very poor. If we combine this with the small size of the houses and the very simple building materials, such as mud, jute sticks, and such other things, then we are very close to identifying most of the very poor. Gibbons admits two limitations of this index. First, some poor people live in bigger and better houses because they inherited those houses, but now they no longer have any income. Second, in many countries (including India), the gov- ernment provides reasonably good houses to the poor free of cost. So, in those areas, this index cannot identify the poor. To overcome these and other similar limitations, there is an appeal procedure. The poor people living in good houses could appeal to the fi eld assistant and convince him/her that they are not rich. A senior offi cer could later interview such people and take a fi nal decision in the matter. In such cases, use of the Participatory Rural Appraisal (PRA) method of wealth ranking has been found to be useful. In the PRA method, all the villagers are brought together to fi nd out who are the very poor, poor, not so poor and not poor at all. The two methods, Housing Index and PRA, were found to be com parable in terms of cost effectiveness and the time taken. They could both be used by governmental and non-governmental organisations (NGOs) engaged in rural development, for identifying the poor for targeting their projects. The Housing Index has a serious limitation in the sense that it cannot be used for making international and even intra-national comparisons, when the type of houses varies widely from country to country, or from state to state within the country. But the primary purpose of this index is to identify the poor in a particular area, for giving some benefi ts or services to them. For this purpose, the index seems alright. Another limitation is that there is no way to combine the three components into a single index. Hence, the name Housing Index is misleading.
The Human Poverty Index (HPI)
The Human Development Report 1997 (UNDP 1997) presents an HPI and ranks 78 poor countries using it. The report asserts that poverty is multidimensional, and poverty measures based on the income criterion do not capture deprivation of many kinds.
The HPI is based on the following three different types of deprivation (UNDP 1997:
17–23):
1. Survival deprivation, as measured by the percentage of people (in a given country) not expected to survive to age 40 years (P1).
2. Deprivation in education and knowledge, as measured by the adult literacy rate (P2).
3. Deprivation in economic provisioning (P3), which is computed as the mean of three variables: population without access to safe water (P31), population without access to health services (P32), and underweight children under the age of fi ve years (P33)—all three expressed in percentages.
The HPI is then obtained as the cube root of the average of the cubes of the three components of deprivation. This is a ‘power mean’ of order three. The power mean of order one is the simple mean, the average of the values.
Out of the 78 developing countries, Trinidad and Tobago had the lowest HPI at 4.1, and Niger had the highest at 66.0. India’s HPI was 36.7 and its rank was 47.
The report says that the HPI can be used in at least three ways: as a tool of advocacy;
as a planning tool for identifying areas of concentrated poverty within a country; and as a research tool. For example, the HPI can help summarise the extent of poverty along several dimensions, the distance to go and the progress made.
This index has some drawbacks and, therefore, is not yet acceptable to scholars and policy makers (Krishnaji 1997: 2202–05). The HPI does not include certain critical dimensions of human poverty, such as low incomes, lack of political freedom, inability to participate in decision-making, lack of personal security and threats to sustainability and inter-generational equity. In addition, the quality and reliability of data used for computing the HPI are also questionable in many cases.
MAIN POINTS
1. Measurement of the level and pace of rural development is useful for a number of purposes, such as the determination of the extent of economic and social well- being of the rural people, serving as a benchmark for future planning, facilitating the monitoring, evaluation and control of ongoing programmes, and spatial and temporal comparisons of development.
2. To be meaningful, measures of rural development must be consistent with the objectives of rural development. A measure should provide, at the minimum, an indication of such commonly accepted objectives of development as per capita availability of life sustaining goods or per capita income in rural areas as well as some idea of the distribution of income, assets and other means of socio-economic welfare.
3. There is no universally acceptable measure of rural development that captures its multi-faceted nature. The choice of measure depends upon the purpose of measure- ment and the availability of requisite data/information. Commonly used measures