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Issues Related To Household Expenditures And Consumption Economics Essay


With economic and social progression of the nation the minimal basket of basic human needs which a society would expect for its citizen may be expected to keep expanding. These changes in the basic needs of the society may be affordable by the level of income. The level of income of the households ensures the minimum standard of living in the society.

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Household income and consumption expenditure are two direct monetary measures used in assessing the economic well-being of a population. However, consumption expenditure is pre­ferred to income as it reflects long-term economic status of the household, particularly in low income countries (Friedman 1957). It is important to note however that expenditures are not similar with income, which may even be a better indicator of well-being, for various reasons. Among them is the possibility of consumption without expenditures at least within the same period. According to Atkinson, (1998), “Expenditures are thus supposed to better reflect “long-term” or “permanent” income and are from this point of view considered to be a better measure of economic well-being and respective inequalities”.

Besides, in developing countries, income estimates are under-reported, drawn from multiple sources and vary across seasons. Though the consumption expenditure data are collected in many developing countries including India, the process is time-consuming, expensive and needs adjustment for household size, composition and for price level. Owing to these difficulties, the economic proxies (consumer durables, housing quality and household amenities) are collected to measure the economic sta­tus of the households in both small-and large-scale population-based surveys.

In the context of the growth performance during these two decades, economists and policymakers have become interested in the trends in regional inequality during this period. Rising regional inequality can create economic, social and political problems for any country. For the Indian economy, it has serious ramification for the continuation of the reform process. Hence, it is of utmost importance to understand the regional disparity in terms of consumption expenditure on consumer durables, housing quality and household amenities of the economy.

Household expenditures as they result from budget limitations at the one hand and choices based on needs, demand, preferences etc. on the other may be regarded as manifestations of economic and social inequalities as well as cultural differences and social distinctions. Studying the patterns, disparities and determinants of household expenditures and their changes across time by making use of large scale population surveys thus seem to be promising in various respects. At a most general level it may provide insights into general consumption behaviour as a major source of human well-being and respective choices and restrictions.

Investigating household expenditures and consumption patterns is considered to be key for the monitoring and explanation of inequalities and changes in material living standards and general welfare. Studying expenditures and consumption behaviour of households also seems to be an important and promising strategy to extend and supplement mainstream approaches of studying inequality as a key topic of sociological and economic research.

As one would expect, research on household expenditures and consumption is much more common and popular among economists and looks back to a long tradition in economics (Stigler, 1954). This issue was also addressed by Houthakker (1957) as early as in the 1950s.

The issues related to household expenditures and consumption have been disregarded in sociology and particularly empirical sociological research to a large degree, although family and household budget data frequently used for empirical study in the early days. Some observers and commentators of developments in sociological research thus conclude that consumption has been strongly neglected in sociological research (Rosenkranz and Schneider, 2000). Thus it is an area which needs greater attention to be paid.

Although there is a long history of research on patterns of household expenditures and their changes across time, which goes back to the 19th century and the famous work by Ernst Engel and others, these questions have attracted surprisingly little attention in recent years.

Blacklow and Ray, (2000) in their paper compare, using Australian unit record data, income and expenditure inequalities over the period 1975-76 to 1993-94. The study finds inconsistencies between the two inequality movements over much of this period. They, also, observe differences in the nature of income and consumption disparities.

Bögenhold and Fachinger, (2000) used repeated cross sectional data (RCS) in their empirical analysis which is based on the West German Income and Expenditure Survey (IES) in 1973, 1978, 1983, 1988 and 1993. The results revealed that the relationship between income and expenditure is given but it is weak. All in all, the social organisation of consumption is a research object in itself to obtain information about the living standard of individuals and households.

Zaidi and Klass (2001) in their study on poverty and inequality in developed countries focus on income. This paper presents trends in consumption-based poverty and inequality in nine member countries of the European Union. During the 1980s, both poverty and inequality increased in Italy, France, the United Kingdom, Germany and Belgium, while decreases in both poverty and inequality are observed for Spain and Portugal. In Greece only inequality increased.

Dhawan-Biswal, (2002) measure inequality in Canada with a comprehensive look at inequality trends in Atlantic Canada during the period 1969 to 19966. They use consumption expenditure as a measure of family well being and compare it with the income based measure of well being. Overall consumption inequality has continuously been lower in Atlantic Canada in comparison to the rest of Canada.

Meyer and Sullivan, (2003) found in their study that it is fairly compelling that most households can more easily report income. They suggested that use consumption to supplement income in analyses of poverty whenever possible.

Kalwij and Salverda, (2004) examine in detail the changes in household expenditures patterns, and in particular services related expenditures, in the Netherlands over the years 1979, 1989 and 1998. Using Engel curve estimations, these changes are related to changes in household demographics, employment, the budget and relative prices. They find that the dominating changes in demand are decreasing shares of expenditures on food and clothing and an increasing share of expenditures on housing. Decrease in food expenditures is for a large part explained by changes in household characteristics and the budget and about a third is a price effect. The increase in housing expenditures share is predominantly a price effect.

Blow, Leicester and Oldfield (2004) examined “how and why has the way in which the average British family spends its money changed over the past 25 years” by using data from the UK FES between 1975 and 1999. It looks not only at broad changes in total spending, but also at how the division of expenditure between basics and non-basics and between durable goods, non-durable goods and services has altered over time.

Johnson, Smeeding and Torrey (2005) used the period 1981 and 2001, to measure economic inequality among groups in the general population in the United States. Two measures of income and consumption are used to gauge relative well-being. Households with children are at a disadvantage, relative to the general population through both prisms. And households with children are the only group whose distribution of consumption was relatively more unequal than their distribution of disposable income throughout the 1981-2001 period studied. Comparison with the general population is a zero-sum game where households with children are relatively less well off, regardless of whether disposable income or consumption is used as the resource measure.

Brewer, Goodman, and Leicester, (2006) in their study on “Household spending in Britain” by using 30 years of data from household surveys conclude that “although there has been much recent emphasis on the advantages of measures of household expenditures in assessing household welfare in more academic circles, this has yet to work its way into the mainstream poverty measurement debate”. This study shows the trends in poverty in Britain since the 1970s when household expenditure is used as a measure of financial well-being, rather than household income and investigates how using spending, rather than income, as a measure of well-being alters our view of who is poor. It examines the spending levels of the lowest-income households and analyses whether low-income pensioners’ spending on basic and non-basic items increased as a result of the large increases in entitlements to means-tested benefits since 1999.

Zhang, Xie and Zhou, (2009) studied the disparity of consumption expenditure among rural areas in China by principle and method of cluster analysis. Results showed that income and consumption expenditure of 31 districts, cities and provinces could be divided into 5 classes of income and consumption. Shanghai City was the only city rated as the first-class areas with highest income and consumption.

Bhattacharya and Mahalanobis (1967) had decomposed the Gini-coefficient and the standard deviation of logarithms for the year 1957-58 based on the household consumer expenditure survey data of India and found that one-quarter of the total inequality was being explained by between-state inequality and the remaining three-quarters was explained by the within-state inequality.

Paul, (1988) studied the importance of household composition in the analysis of inequality measurement based on the National Sample Survey data (25th round). The results for rural Punjab reveal that the ranking of households by per equivalent adult consumption expenditure (PEAE) differs significantly from the ranking by per capita consumption expenditure (PCE). Many households classified as poor according to the criterion of PCE are not so classified by the criterion of PEAE. The exercise also reveals that the distribution of HCE, if not adjusted for household size and composition effects, gives biased measures of the extent of true inequality.

Jain and Tendulkar (1989) in their paper deduces the analytical conditions for the movements in the same or in the opposite direction of the real and the nominal relative disparity in cereal consumption consequent upon the differential movements in the prices of cereals faced by the bottom and the top fractile groups of the population. These conditions are used for interpreting the movements in the real and the nominal relative disparity with reference to the Indian rural population over the period from 1953 to 1978.

Datt and Ravallion, (1990) argued that the costs and the benefits of regional policies will tend to be borne widely within regions. Some benefits are likely to leak to the nonpoor in recipient regions, and some costs to the poor in donor regions. The paper suggests that the quantitative potential for alleviating national poverty through purely regional redistributive policies is small. Even assuming no political problems, the maximum impact on poverty is nomore than could be achieved simply by giving everyone a uniform (untargeted) windfall gain equal to about 1.5 percent of India’s mean consumption. And other considerations – including increased migration to areas of higher benefits – make it unlikely that the maximum impact will be attained in practice. Greater alleviation of poverty requires supplementary interventions that reach the poor within regions, by reducing the costs borne by the poor in donor regions and enhancing benefits to the poor in recipient regions.

Mishra and Parikh (1992) in their paper measured household consumer expenditure inequalities in India by regions (states) and sectors (urban-rural) for the years 1977-78 and 1983 based on the National Sample Survey data. The results consistently indicate that the inequality within states contributes much more towards national inequality and within-sector inequality explains a large part of state level inequality. The inequality at state levels has shown a decline from 1977-78 to 1983 due to a better monsoon season in 1983, and anti-poverty programmes.

Dubey and Gangopadhyay (1998) in their analytical report mention intra-state disparities by using NSSO consumption income data set. There are several states in India where the incidence of poverty across regions within a state is very high. They reported for seven regions of Madhya Pradesh, poverty incidence varied from one of the lowest in the country in the western region to one of the highest in the eastern region.

Deaton and Dreze (2002) in their paper presents a new set of integrated poverty and inequality estimates for India and Indian states for 1987-88, 1993-94 and 1999-2000. The poverty estimates are broadly consistent with independent evidence on per capita expenditure, state domestic product and real agricultural wages. They show that poverty decline in the 1990s proceeded more or less in line with earlier trends. Regional disparities increased in the 1990s, with the southern and western regions doing much better than the northern and eastern regions. Economic inequality also increased within states, especially within urban areas, and between urban and rural areas. They also examine other development indicators, relating for instance to health and education. Most indicators have continued to improve in the nineties, but social progress has followed very diverse patterns, ranging from accelerated progress in some fields to slow down and even regression in others.

Gaiha, Thapa, Imai and Kulkarni (2007) in their analysis of the 61st round of the NSS for 2004-05 confirms higher incidence and intensity of poverty among the STs and SCs, relative to non-ST/SC (Others). A decomposition of poverty gap suggests that a large part of the gap between the ST and Others is due to differences in returns or structural differences while among the SCs it is due largely to differences in characteristics or endowments. Whether these structural differences are a reflection of ‘current’ discrimination is far from self-evident, given the important role of personal identity in determining performance. The policy design therefore cannot be limited to enhancing the endowments of the STs, SCs and other disadvantaged groups.

Dubey (2009) examine the interstate disparity in five states in India i.e. Gujarat, Haryana, Kerala, Orissa and Punjab by using NSSO data of 50th round and 61st round. He used three indicators, consumption, inequality and incidence of poverty. Highest level of disparity emerged in Punjab followed by Gujarat and Kerala. Haryana has least disparities only marginally lower than that in Orissa.

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Singh (2010), in her study examined and analysed the disparities in level of living as measured by monthly per capita consumption expenditure across different income groups in various states in India based on 61st round survey of NSSO. Various measures like gini coefficient and rank for the states in rural and urban areas has been calculated. Disparities in MPCE across income groups are observed in Punjab.

Srivastava and Mohanty (2010) in their study used data from the World Health Survey, India, 2003, covering a nationally representative sample of 10,750 households and 9,994 adults, examines the extent of agreement of monthly per capita consumption expenditure and economic proxies (combined with the wealth index) with the differentials in health estimates.

Cain, Rana, Rhoda and Tandon, (2010) utilise household-level consumption expenditure data to examine the evolution of inequality during 1983-2004 in India. Various measures of inequality show that inequality levels were relatively stable during 1983-93, but increased during 1993-2004. The increases in inequality have not precluded reductions in poverty, however. They are also more of an urban phenomenon and can be accounted for by increases in returns to education in the urban sector to a considerable extent, especially among households that rely on income from education-intensive services and/or education-intensive occupations.

Significance of the study

The National Human Development Report 2001 for India (2002) reveals vast differences in human development and poverty between the States of India in 1981. The report notes that “At the state level, there are wide disparities in the level of human development.” (NHDR 2002, page 4). The report also notes that disparities amongst the States with respect to human poverty are quite striking. Socio-economic disparities across the regions and intra-regional disparities among different segments of the society have been the major plank for adopting planning process in India since independence.

Even after its impressive performance in the field of science, technology and agriculture during the last three or four decades, a vast majority of Indians are facing the problems of poverty. They are denied even the basic needs of human life like food, safe drinking water, shelter, health, education etc., and are forced to live in a degraded social and physical environment. According to the 61st NSS, the proportion of persons living below poverty line was estimated at 27.5%3 (i.e., more than 315 million people). But, about one third of the population lives under the poverty line of $1 a day, and out of them three in four poor people live in rural areas. Thus, poverty in India is most widespread in the rural areas.

Despite a vast range of poverty eradication programmes and several measures adopted in this regard, even after more than 60 years of Independence the situation is still very critical. In recent years, some significant changes have occurred in the poverty alleviation strategy. The Government of India has launched various programmes, such as NAREGA, MNAREGA, Integrated Rural Development Programme (IRDP), Training of Rural Youth for Self Employment (TRYSEM), Development of Women and Children in Rural Area (DWCRA), Wage Employment Programme, National Rural Employment Programme, Jawahar Rozgar Yojana, etc., for the alleviation of poverty. Further, these programmes are now the responsibility of the local bodies (Panchayati Raj institutions) that are expected to improve their performance. But despite all the rigorous efforts, the desired results could not be achieved and considerable level of regional disparities remained in the society. The Structure Adjustment Programme of economic reforms since 1991 with stabilisation and deregulation policies as their central pieces seems to have further widened the regional disparities. Sen 2002 rightly observed that, “the real concern of the so called anti-globalization protesters is surely not globalization per se, for these protests are amongst the most seem to stem in large part from the continuing deprivations and rising disparities in level of livings that they see in current period of globalization. Liberalisation had resulted in the rich becoming richer and the poor, poorer. No State actually got poorer in terms of falling per capita income but the interstate inequality certainly increased [1] . The seriousness of the emerging acute regional imbalances has not yet received the public attention it deserves.

On the basis of above it can be understood that no significant study has been found in the area of disparity in household consumption expenditure for the period 2005-06, 2006-07 and 2007-08 by using NSSO unit level data in India. The NSSO has been collecting data on consumption expenditure on a regular basis for over four decades. Along with other infor­mation, it collects detailed information on food and non-food items in a reference period. While majority of the studies happen to be at macro level, this study is a more specific analysis in micro frame by using unit level data household survey conducted by NSSO in India. It is able to lay stress on certain vital issues that needed a more serious discussion. To large extent, the study can be regarded as pioneering one.

Objective of the study:

The major objectives of the study are as follows:

To know the expenditure structures and consumption patterns

To know the level of disparity in household consumer expenditure in Indian society.

To know the level of disparity in household consumer expenditure in various regions (states) and sectors (urban-rural) in the society.

To know the difference in levels and patterns of household consumer expenditure and across socio-economic groups i.e. caste, religion and family structure in the society.

To know the difference in levels and patterns of food and non-food expenditure of across socio-economic groups i.e. caste, religion and family structure in the society.



Collecting consumption expenditure data is not new in India. The National Sample Survey Organisation (NSSO) conducted an all-India survey of households on participation and expenditure in education, employment, unemployment, migration and consumer expenditure on a regular basis for over four decades. Surveys on consumer expenditure are being conducted quinquennially on a large sample of households from the 27th round (October 1972 – September 1973) of NSS onwards. Additionally, the NSSO has conducted annual consumer expenditure surveys using a smaller sample of households from 1986-87 to 2007-08. In the present study data will be utilised from the three rounds of NSSO consumer expenditure survey i.e. 62, 63 and 64 round collected in the year 2005-06, 2006-07 and 2007-08 respectively .These three consumer expenditure surveys belongs to annual series.

Data Analysis:

In the present study the disparity in terms of consumer expenditure will be measured in the above mentioned three rounds of survey. Data provided by NSSO is in text document. For the analysis of these unit level data we will use statistical software (STATA). Disparity in terms of MPCE will be calculated for the state wise, region wise, caste, religion and family structure. Different statistical methods (like; descriptive statistics, range, standard deviation, coefficient of variation, Gini coefficient Lorenz curve, Theil’s index, etc.) will be utilised for measuring inequality and disparity. Graphical presentation of the results will be used for the easy understanding of the data.

There are the criteria (Mean Independence, Population size independence, Symmetry, Pigou Dalton Transfer sensitivity [2] , Decomposability, Statistical Testability) that make a good measure of income inequality. Among the most widely used are the Theil indexes and the mean log deviation measure. Both belong to the family of generalized entropy. The formula is given by

Where is the mean income per person (or expenditure per capita).The value of the measures vary between zero and infinity, with zero representing an equal distribution and higher values representing higher levels of inequality. The parameter in the GE class represents the weight given to distances between incomes at different parts of the income distribution, and can take any real value. For lower value of GE is more sensitive to changes in the lower tail of the distribution and for higher values GE is more sensitive to changes the affect the upper tail. The most common values of used are 0, 1, and 2. GE(1) is Theil’s T index and GE(0) is Theil’s L (sometimes refered to as the mean log deviation measures) are given by:

Atkinson has proposed another class of inequality measures that are used from time to time. This class also has a weighting parameter É› (which measures aversion to inequality). The Atkinson inequality measures defined as

Decomposition of Income Inequality

The issue of relating subgroup inequality levels to overall inequality has been discussed in the number of recent studies (Cowell 1980, Cowell and Kuga 1981, Bourguignon, 1979, Shorrocks 1980 and 1984, Shorrocks and Mukherjee, 1982, Das and Parikh 1982, Mishra and Parikh 1992).

If the total inequality can be expressed as a function of sub-group inequality values, when the sub-groups are mutually exclusive and exhaustive, then a variety of ways is found to decompose the total inequality. The particular method of decomposition depends on the nature of the inequality index and the way in which it is decomposed since the decomposability of the indices differ from measure to measure.

The most attractive type of decomposability has been additive decomposability. An index is additively decomposable if it can be neatly expressed as the sum of a “between-group” term and a “within-group” term. Conceptually, the between-group component can be defined as the value of the inequality index when all the within-group inequalities are assumed to be non-existent by a hypothetical assignment of the group average income to each member of the same group.

The common inequality indicators mentioned above can be used to assess the major contributors to inequality, by different subgroups of the population and by region. For example, average income may vary from region to region, and this alone implies some inequality “between groups.” Moreover, incomes vary inside each region, adding a “within-group” component to total inequality. For policy purposes, it is useful to be able to decompose these sources of inequality: if most inequality is due to disparities across regions, for instance, then the focus of policy may need to be on regional economic development, with special attention to helping the poorer regions.

More generally, household income is determined by household and personal characteristics, such as education, gender, and occupation, as well as geographic factors including urban and regional location. Some overall inequality is due to differences in such characteristics-this is the “between-group” component-and some occurs because there is inequality within each group, for instance, among people with a given level of education or in a given occupation. The generalized entropy (GE) class of indicators, including the Theil indexes, can be decomposed across these partitions in an additive way, but the Gini index cannot.

To decompose Theil’s T index (that is, GE(1)), let Y be the total income of all N individuals in the sample, and be mean income. Likewise, Yj is the total income of a subgroup (for example, the urban population) with Nj members, and is the mean income of this subgroup. Using T to represent GE(1),

Where is the value of GE(1) for subgroup j. Equation separate the inequality measure in to two components the first of which represents within group inequality while the second term measures the between-group inequality.

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