Bayesian Estimation of a Censored Linear Almost Ideal Demand System: Food Demand in Pakistan: American Journal of Agricultural Economics

P. Kasteridis, S. T. Yen, C. Fang

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Pages (from-to)1374-1390
Number of pages17
JournalAmerican Journal of Agricultural Economics
Volume93
Issue number5
Publication statusPublished - Oct 2011

Keywords

  • censoring demand elasticities gibbs sampling laids mcmc pakistan c11 c34 d12 non-negativity constraints binding nonnegativity constraints equation models coherency regression

Cite this