The quaids ado files written by Brian Poi provide a good template for constructing alternative ado files for maximum likelihood estimation of demand systems. I describe how I used the template to construct ado files to estimate a five commodity almost ideal demand system with demographic scaling. The system is applied to USDA national food consumption survey data. The estimation is used as an exercise in a PhD level micro theory course that aims to connect the empirical implications of theory with econometric estimation. I report on how maximum likelihood estimation of demand systems contributes to student learning of both consumer theory and nonlinear estimation. I include a discussion of how mata is used to recover coefficients from maximum likelihood estimation to perform post estimation processing like calculation of elasticities.
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