Premium
Bayesian Estimation of a Censored Linear Almost Ideal Demand System: Food Demand in Pakistan
Author(s) -
Kasteridis Panagiotis,
Yen Steven T.,
Fang Cheng
Publication year - 2011
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.1093/ajae/aar059
Subject(s) - almost ideal demand system , markov chain monte carlo , economics , econometrics , estimation , bayesian probability , sample (material) , markov chain , bayes estimator , agricultural economics , statistics , demand management , mathematics , macroeconomics , chemistry , chromatography , management
A censored linear almost ideal demand system for food is estimated with a Bayesian Markov chain Monte Carlo procedure, using a sample of urban households from Pakistan. All own‐price elasticities but one are found to be negative, and all total food expenditure elasticities are found to be positive, with a high posterior probability. There is a mix of gross complements and substitutes among the food products, while net substitution is the predominant pattern. Household characteristics play a role in food expenditures, and regional differences exist. These demand elasticities can inform policy deliberations by the national government and international organizations.