Estimating a global MAIDADS demand system considering demography, climate and norms

Based on data mainly from the International Comparison Program for 156 countries, we conduct a global cross-sectional estimation of an extended rank-3 MAIDADS demand system for nineteen commodity groups including agri-food detail for integration in a Computable General Equilibrium model. We render both marginal budget shares and commitment terms depending on the implicit utility level and consider age shares on the population, the Gini-Coefficient, the share of Islamic population, a sea access indicator and mean temperatures as further explanatory variables. We find that especially demographic factors, the share of Islamic population and mean temperature considerably improve model selection statistics and the fit of commodity groups with a low fit in a variant where prices and income only are used. Graphics of the estimated Engel curves, with details for agro-food commodity groups, highlight income dynamics of budget shares.

Automated summary

Based on data from 156 countries, a global cross-sectional estimation of a demand system for nineteen commodity groups shows that demographic factors, the share of Islamic population, and mean temperature significantly improve model selection and fit, especially when considering additional explanatory variables. The estimated Engel curves illustrate income dynamics of budget shares, with a focus on agro-food commodity groups.