Crop succession requirements in agricultural production planning
This paper hammers out the estimation of a fixed effects dynamic panel data model extended either to include spatial error autocorrelation or a spatially lagged dependent variable. To overcome the inconsistencies associated with the traditional least squares dummy estimator, the models are first-differenced to eliminate the fixed effects and then the unconditional likelihood function is derived taking into account the density function of the first-differenced observations on each spatial unit. When exogenous variables are omitted, the exact likelihood function of both models is found to exist. When exogenous variables are included, the presample values of these variables and thus the likelihood function must be approximated. Two leading cases are considered: the Bhargava and Sargan approximation and the Nerlove and Balestra approximation. As an application, a dynamic demand model for cigarettes is estimated based on panel data from 46 American states over the period 1963 to 1992.
Year of publication: |
2003
|
---|---|
Authors: | Klein Haneveld, W.K. ; Stegeman, A.W. |
Institutions: | Faculteit Economie en Bedrijfskunde, Rijksuniversiteit Groningen |
Saved in:
freely available
Saved in favorites
Similar items by person
-
Fast heuristics for a dynamic paratransit problem
Cremers, M.L.A.G., (2008)
-
Optimizing electricity distribution using two-stage integer recourse models
Klein Haneveld, W.K., (2000)
-
Asset liability management modeling using multi-stage mixed-integer stochastic programming
Vlerk, Maarten H. van der, (2000)
- More ...