Bayesian inference of a smooth transition dynamic almost ideal model of food demand in the US
A dynamic ‘smooth transition’ Almost Ideal model is estimated for food consumption in the US. A Metropolis-Hastings algorithm is employed to map the posterior distributions and rejection sampling is used to evaluate and impose curvature restrictions at more than one point in the sample. The findings support the contention of structural change of a ‘smooth transition’ nature. Notably, the income food elasticity of demand becomes smaller through time, and the own price elasticities for food and non food become more elastic.
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