Interpreting dynamic space-time panel data models

Mardi | 2010-11-16

Nicolas DEBARSY (CERPE De Namur) – Cem ERTUR – James P. LeSAGE – libre

There is a great deal of literature regarding the asymptotic properties ofvarious approaches to estimating simultaneous space-time panel models, butlittle attention has been paid to how the model estimates should be interpreted.The motivation for use of space-time panel models is that they canprovide us with information not available from cross-sectional spatial regressions.[8] show that cross-sectional simultaneous spatial autoregressivemodels can be viewed as a limiting outcome of a dynamic space-time autoregressiveprocess. A valuable aspect of dynamic space-time panel data modelsis that the own- and cross-partial derivatives that relate changes in the explanatoryvariables to those that arise in the dependent variable are explicit.This allows us to employ parameter estimates from these models to quantifydynamic responses over time and space as well as space-time diffusion impacts.We illustrate our approach using the demand for cigarettes over a 30year period from 1963-1992, where the motivation for spatial dependence isa bootlegging effect where buyers of cigarettes near state borders purchase