CAUSAL REASONING IN ECONOMETRIC-MODELS

被引:3
|
作者
LIN, KP [1 ]
FARLEY, AM [1 ]
机构
[1] UNIV OREGON,DEPT COMP & INFORMAT SCI,EUGENE,OR 97403
关键词
CAUSAL REASONING; CAUSAL ORDERING; QUALITATIVE REASONING; QUANTITATIVE MODELS;
D O I
10.1016/0167-9236(94)00035-Q
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Propagation of change based on causal ordering is a central element of causal reasoning in economic models. While causal reasoning has most often been applied in qualitative models, we demonstrate a technique for causal reasoning that offers explanations of structure and behaviour in quantitative, econometric contexts. Given a matching of equations with endogenous variables, causal reasoning can be applied to both static and dynamic system models. By propagating the disturbance of one or more exogenous variables, impact or static multipliers of the model can be derived along with a causal explanation. Dynamic analysis is achieved by propagation of lagged endogenous variables carried from the previous time periods. Two versions of Keynesian macro-econometric models, Klein's Model I, and the Klein-Goldberger Model are used as examples.
引用
收藏
页码:167 / 177
页数:11
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