ESTIMATION OF URBAN-RURAL EXPENDITURE AND SIZE ELASTICITIES OF FOOD ITEMS IN PAKISTAN: EVIDENCE FROM PSLM DATA
Journal: Academic Research International (Vol.3, No. 2)Publication Date: 2012-09-15
Authors : Shireen Safdar Nisar Ahmad Falak Sher;
Page : 474-481
Keywords : Urban-Rural; Households; Income Groups; PSLM Data; Income Elasticities and Size Elasticities.;
Abstract
This study aims at the determination of the household consumption pattern of food items among different income groups in urban and rural of Pakistan and estimation of food expenditure and household size elasticities. The study evaluates the household food demand patters for various income groups in urban and rural area of Pakistan. Pakistan Social and Living Standard Measurement Survey (PSLM) 2007-08 data collected by Federal Bureau of Statistics (FBS), Government of Pakistan, Islamabad are used for the analysis purpose. Engel (Expenditure) elasticities are a powerful research tool in the analysis of household analysis. If expenditure on a certain item is proportional to income or total expenditure then the income elasticity of demand, better known as Engel elasticity is unity. The food expenditures are the sum of expenditures by each household on the following commodity groups: cereals, pulses, fruits, vegetables, dairy products, chicken, meat, fish, condiments, sugar, edible oils, drinks and miscellaneous food products. The household size and income elasticities are estimated to explain the food consumption trends in Pakistan. The results of the study indicate that all the income and household size elasticities are positive and significant at one percent level of significance. Results of the study indicate that the urban food consumption is higher in the upper income group (IG) while households belonging to other classes of rural area are more food responsive. Urban households depict higher size elasticities in overall, lower IG, lowermiddle IG and middle IG whereas households belonging to upper-middle IG and upper IG of rural area are also more food responsive.
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