Effects of Changes in Household Size, Consumer Taste & Preferences on Demand Pattern in India
No 72, Working papers from Centre for Development Economics, Delhi School of Economics
Current research in applied demand analysis has been addressing the twin issues of degree of non-linearity or curvature of the Engel curves and the ability to capture price effects appropriately by the demand system. Further, in addition to income and prices, the role of demographic variables like household size, composition and dynamic aspects like consumer taste & preferences are also emphasized in recent literature. Continuous efforts are being made to modify the existing models and propose new ones to incorporate the above developments. The purpose of this study is to re-examine the usefulness of the popular linear expenditure system vis-à-vis two other flexible models viz. Nasse expenditure system, a generalization of the linear expenditure system itself, and the almost ideal demand system in the above context for India. We extend the above three models by incorporating dummy variables representing three income groups, rural-urban sectors and their interactions; one demographic variable namely household size and time trend variable representing consumer taste & preferences into the appropriate demand model parameters. National Sample Survey data on consumer expenditure for five quinquennial rounds viz. 27 (1972-73), 32 (1977-78), 38 (1983), 43 (1987-88) and 50 (1993-94) at the all India level; and comparable retail price series from Jain and Minhas (1991) and Tendulkar and Jain (1993) are used for estimating the above models. Seven broad commodity groups viz. (i) cereals & substitutes, (ii) pulses, (iii) milk & products, (iv) edible oil & fats, (v) meat, eggs and fish, (vi) other food and (vii) total nonfood are used in this analysis. The empirical results show wide variation in marginal budget shares and demand elasticities across income groups, rural-urban sectors and alternative models. The household size and consumer taste & preferences are found to be statistically significant. The results have confirmed the earlier findings that there are significant changes in consumer tastes away from cereals and pulses in favor of other food and nonfood commodities. It is found that the linear expenditure system, despite its limitations of linearity and additivity, could provide a good description of consumption patterns in India, i.e. able to capture curvature in Engel curves, provided adequate care is taken to distinguish a few meaningful income categories and rural-urban sectors. The demand parameters have also exhibited some well-known patterns. The results show further that flexible models, which are theoretically superior, gave unacceptable positive price responses for some commodities and violated second order conditions of utility maximization. It is found that some ad-hoc separability restrictions are needed, thereby limiting the flexibility of the model, to get negative own-price responses in these models. But, second order conditions are still violated. The tests of nested hypotheses also confirm the need for inclusion of household size, consumer taste, income group and rural-urban dummies along with their interaction variables in the demand system.
Keywords: Engel Curve; Household Size; Demography; Separability (search for similar items in EconPapers)
JEL-codes: D1 O12 (search for similar items in EconPapers)
References: Add references at CitEc
Citations Track citations by RSS feed
Downloads: (external link)
Our link check indicates that this URL is bad, the error code is: 403 Forbidden
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: http://EconPapers.repec.org/RePEc:cde:cdewps:72
Ordering information: This working paper can be ordered from
The price is free.
Access Statistics for this paper
More papers in Working papers from Centre for Development Economics, Delhi School of Economics Delhi 110 007. Contact information at EDIRC.
Series data maintained by Sanjeev Sharma ().