Multilevel Multiprocess Modeling with Gsem

Multilevel multiprocess models are simultaneous equation systems that include multilevel hazard equations with correlated random effects. Demographers routinely use these models to adjust estimates for endogeneity and sample selection. In this article, I demonstrate how multilevel multiprocess models can be fit with the gsem command. I distinguish between two classes of multilevel multiprocess models: nonrecursive systems of hazard equations without observed endogenous variables and recursive systems that include a hazard equation with observed endogenous qualitative variables. I illustrate the estimation of both classes of models using sample datasets shipped with the statistical software aML. I pay special attention to identifying structural coefficients in nonrecursive simultaneous systems.

Estimating the Supply Elasticity of California Wine Grapes Using Regional Systems of Equations

This article is the first of its kind to estimate econometrically the supply elasticity of California wine grapes. Wine grapes constitute the single largest crop in the state of California in terms of total receipts. Allowing for the dynamic adjustments of quasi-fixed inputs, we estimate simultaneous systems of equations for California's four major wine grape growing regions and eight of the most widely grown varieties. We find that California wine grape production is, on the whole, inelastic with respect to prices received. The variety showing the most price responsiveness is Chardonnay. There appears to be no significant difference in price responsiveness between the coastal and inland growing regions, or between red and white grape varieties. (JEL Classification: Qll, Q13, R14)