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An attempt has been made in this study to examine the consumption demand behavior in rural Bangladesh across different dynamic groups such as non-poor,descending non-poor,ascending poor and chronically poor.We have selected some factors,which are responsible for consumption expenditure.An extended version of Almost Ideal Demand system or AIDS model has been applied for estimating the demand pattern of the dynamic groups.To observe the impact of per capita monthly expenditure on the budget share the AIDS model has been extended by incorporating various household characteristics such as…mehr

Produktbeschreibung
An attempt has been made in this study to examine the consumption demand behavior in rural Bangladesh across different dynamic groups such as non-poor,descending non-poor,ascending poor and chronically poor.We have selected some factors,which are responsible for consumption expenditure.An extended version of Almost Ideal Demand system or AIDS model has been applied for estimating the demand pattern of the dynamic groups.To observe the impact of per capita monthly expenditure on the budget share the AIDS model has been extended by incorporating various household characteristics such as household size,dependency ratio,sex ratio,total year of schooling,age,sex and occupation of household head.The study based on Household budget data(2009)in selected rural areas of Bangladesh for 1212 households.From our findings we have found serious discrimination in the consumption pattern across the dynamic groups. Chronically poor household is found to be more vulnerable position in in rural society. We have also found the relation between the per capita income and the assets of rural people by creating an asset index using Factor Analysis.
Autorenporträt
Jannatul Adnin is currently working as an Associate Research Analyst at Kaz Software Limited (www.kaz.com.bd). She has obtained her B.S. (Hons) and M.S. Degree in Applied Statistics from University of Dhaka. Her main research interests are econometrics, generalized linear modeling, multivariate analysis and statistical computing.