This paper makes a contribution to the application of nonlinear simultaneous equations estimation and nonparametric Bootstrapping techniques. The nonlinear demand model estimation work in this paper is in the context of the newly developed Quadratic Almost Ideal Demand System (QUAIDS) model, and...

This paper motivates and applies a variant of the Bayesian Bootstrap Multivariate Regression by Heckelei and Mittelhammer (2003) to a Japanese meat demand specification with endogenous regressors. The methodology is first given an alternative and more elegants motivation and then extended to...

This paper presents an application of Bayesian analysis to an AIDS model of Japanese meat demand extending previous approaches in three ways: (1) The methodology employed is robust with respect to the likelihood function but retains the generic, easily programmable character of algorithms...

Replaced with revised version of paper 05/29/04.

This paper presents a Bayesian alternative to Generalized Maximum Entropy (GME) and Generalized Cross Entropy (GCE) methods for deriving solutions to econometric models represented by underdetermined systems of equations. For certain types of econometric model specifications, the Bayesian...

This paper introduces a semi-parametric bootstrapping approach to Bayesian analysis of structural parameters in simultaneous equation systems that extends the single and multivariate regression approaches of Heckelei and Mittelhammer (1996, 2002) to models with endogenous regressors. Monte Carlo...

This paper makes a contribution to the application of nonlinear simultaneous equations estimation and nonparametric Bootstrapping techniques. The nonlinear demand model estimation work in this paper is in the context of the newly developed Quadratic Almost Ideal Demand System (QUAIDS) model, and...