A comparison of four model specifications for describing small heterogeneous space-time datasets: Sugar cane production in Puerto Rico, 1958/59-1973/74

Data forming a short space-time series - too short to utilize a STARIMA model - can include a random effects term that is spatially structured in order to account for both serial and spatial autocorrelation. In this context, space-time heterogeneity can be accounted for in various ways, including specifications involving spatial filtering methodology. This paper summarizes comparisons of four model specifications - simple pooled space-time; sequential, comparative statics; temporally varying coefficients with a spatially unstructured random effects term; and, temporally varying coefficients with a spatially structured random effects term. Implementations are illustrated with annual sugar cane production data for Puerto Rico during 1958/59-1973/74. Copyright (c) 2008 the author(s). Journal compilation (c) 2008 RSAI.