On dual approaches to demand systems estimation in the presence of bindingquantity constraints

Binding quantity constraints, especially non-negativity constraints, appear frequently in micro-level data sets. Two dual approaches to demand systems estimation in the presence of binding non-negativity constraints are revie wed. It is demonstrated that, in a demand systems context, the more commonl y used approach for treating binding non-negativity constraints is incompat ible with economic theory and thus produces inconsistent estimates of price response. Furthermore, Monte Carlo experiments indicate that bias can be s ubstantial even if limit observations comprise a relatively small portion o f the sample. The alternative, a direct maximum likelihood estimation appro ach, has desirable properties; however, analytical and computational diffic ulties severely hamper application. The numerical integration approach, emp loyed here for direct maximum likelihood estimation, is presented. It is be lieved that this integration approach facilitates direct maximum likelihood estimation for some problems. Nevertheless, the ability to estimate comple x demand systems remains constrained.