Two econometric issues arise in the estimation of complete systems of producer or consumer demands when many non-negativity constraints are binding for a large share of observations, as frequently occurs with micro-level data. The first is computational. The econometric model is essentially an...

In this paper, I show that the "Bayesian inversion" of demand, which is defined as the posterior distribution of random utilities given realized choices, can replace Berry, Levinsohn, and Pakes (1995)’ "mean utility inversion" and radically simplify the estimation of discrete choice models...

The paper introduces Bayesian inference into a demand model. This allows us to test for the negativity condition of the substitution matrix which is difficult to handle directly in the traditional approach. To illustrate the Bayesian inference procedures, we estimate the Rotterdam model and test...

This article discusses the use of Bayesian methods for estimating logit demand models using aggregate data, i.e. information solely on how many consumers chose each product. We analyze two different demand systems: independent samples and consumer panel. Under the first system, there is a...