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Revista Colombiana de Estadística

Print version ISSN 0120-1751

Abstract

RAMIREZ, ANDRÉS. A Multi-Stage Almost Ideal Demand System: The Case of Beef Demand in Colombia. Rev.Colomb.Estad. [online]. 2013, vol.36, n.1, pp.23-42. ISSN 0120-1751.

The main objective in this paper is to obtain reliable long-term and short-term elasticities estimates of the beef demand in Colombia using quarterly data since 1998 until 2007. However, complexity on the decision process of consumption should be taken into account, since expenditure on a particular good is sequential. In the case of beef demand in Colombia, a Multi-Stage process is proposed based on an Almost Ideal Demand System (AIDS). The econometric novelty in this paper is to estimate simultaneously all the stages by the Generalized Method of Moments to obtain a joint covariance matrix of parameter estimates in order to use the Delta Method for calculating the standard deviation of the long-term elasticities estimates. Additionally, this approach allows us to get elasticity estimates in each stage, but also, total elasticities which incorporate interaction between stages. On the other hand, the short-term dynamic is handled by a simultaneous estimation of the Error Correction version of the model; therefore, Monte Carlo simulation exercises are performed to analyse the impact on beef demand because of shocks at different levels of the decision making process of consumers. The results indicate that, although the total expenditure elasticity estimate of demand for beef is 1.78 in the long-term and the expenditure elasticity estimate within the meat group is 1.07, the total short-term expenditure elasticity is merely 0.03. The smaller short-term reaction of consumers is also evidenced on price shocks; while the total own price elasticity of beef is -0.24 in the short-term, the total and within meat group long-term elasticities are -1.95 and -1.17, respectively.

Keywords : Cointegration; Delta method; Demand system; Generalized method of moments; Monte Carlo Simulation.

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