The relation between causal structure and cointegration and long-run weak exogeneity is explored using some ideas drawn from the literature on graphical causal modeling. It is assumed that the fundamental source of trending behavior is transmitted from exogenous (and typically latent) trending variables to a set of causally ordered variables that would not themselves display nonstationary behavior if the nonstationary exogenous causes were absent. The possibility of inferring the long-run causal structure among a set of time-series variables from an exhaustive examination of weak exogeneity in irreducibly cointegrated subsets of variables is explored and illustrated.

中文翻译：

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长期因果顺序的发现：初步调查

因果关系和协整关系与长期弱外生性之间的关系，是使用从图形因果模型的文献中得出的一些思想来探索的。假定趋势行为的基本来源是从外源（通常是潜在的）趋势变量传递到一组因果有序变量，如果不存在非平稳外因，则它们本身不会显示出非平稳行为。探究并说明了从穷举不可综合的变量子集中的弱外生性详尽检查中推断出一系列时间序列变量中长期因果结构的可能性。