Conditioning in dynamic models
(1985) Journal of Time Series Analysis — Vol. 6, n° 1, p. 15-34 (1985)
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- Abstract
- A statistical model is generally defined through a probability on some variables conditionally on other variables and refers to some parameters of interest. Therefore, it seems natural to ask under which conditions such a model does not lose information with respect to a model describing more variables and implying more parameters. Admissibility conditions for reductions by conditioning are investigated both in one-shot and in dynamic models. By so doing, concepts of ‘exogeneity’ and of ‘non-causality’ are integrated into a general framework. This paper is essentially a non-technical introduction to the theory of reduction developed more formally in other papers. It also supplies various examples of the concepts introduced in that theory.
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Florens, J.-P., & Mouchart, M. (1985). Conditioning in dynamic models. Journal of Time Series Analysis, 6(1), 15-34. https://doi.org/10.1111/j.1467-9892.1985.tb00395.x (Original work published 1985)