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Estimation of Censored Demand Equations from Large Cross-Section Data
Authors:Federico Perali  & Jean-Paul Chavas
Institution:Universitàdegli Studi di Verona, Italy,;University of Wisconsin, Madison
Abstract:The article develops an alternative econometric methodology to estimate a system of censored demand equations using a large cross-section data from Colombian urban households. The approach preserves the behavioral information expressed by zero expenditures and conforms with the requirements imposed by consumer theory in a way consistent with the random utility hypothesis. We motivate the choice of the Tobit model as a statistical representation of consumer behavior and introduce the methodology by specifying the AIDS model modified according to both a translating and scaling demographic transformation. We propose to estimate each demand equation in unrestricted form using the jackknife technique. We then recover the demand parameters imposing the cross-equations restrictions by using minimum distance estimation. The empirical results of the censored demand system for specific households of policy relevance are reported.
Keywords:censored demand  jackknife  large cross-section data  minimum chi-squared estimator  scaling and translating
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