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CONDITIONING IN DYNAMIC MODELS
Author(s) -
Florens J.P.,
Mouchart M.
Publication year - 1985
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.1985.tb00395.x
Subject(s) - mathematics , endogeneity , econometrics , mathematical economics , causality (physics) , reduction (mathematics) , physics , geometry , quantum mechanics
. 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.