Demand System estimation with Stata: Multivariate censoring and other econometric issues
This presentation provides a Stata application for the estimation of Blundell, Banks and Lewbel’s (1997) demand system, dealing with the zero problem which is in the heart of many expenditure survey analysis. Starting from Poi’s (2008) routine, our main contribution is the multivariate censoring correction, implementing Tauchman (2010) theoretical framework which relies on including correction terms in the system. These latters are computed from a multivariate probit estimated with Simulated Maximum Likelihood using Cappellari and Jenkins’ (2007) mvnp routine. We also discuss how to deal with several econometric issues related to the demand system estimation literature: Total budget endogeneity, the conditional linearity and the symmetry restriction (using Minimum Distance estimator).
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