One of the central research questions in modelling space-time data is the right econometric model. At least three problems must be tackled: (i) The observations on each spatial unit might be correlated over time, (ii) The observations at each point in time might be correlated over space, and (iii) The omission of time-invariant and/or spatial-invariant background variables could bias the regression coefficients in a typical cross-section or time-series model. As we have no a priori reasons to believe that one problem is more important than another, this paper presents a general model that encompasses a wide series of simpler models frequently used in the time-series econometrics, spatial econometrics and panel data econometrics literature. A framework is developed to determine which model is the most likely candidate to study space-time data.
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Paper provided by European Regional Science Association in its series ERSA conference papers with number
ersa05p81.
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