Russo, Federica
(2009)
Causal Arrows in Econometric Models.
In: UNSPECIFIED.
Abstract
Econometrics applies statistical methods to study economic phenomena. Roughly, by means of equations, econometricians typically account for the response variable in terms of a number of explanatory variables. The question arises under what conditions econometric models can be given a causal interpretation. By drawing the distinction between associational models and causal models, the paper argues that a proper use of background knowledge, three distinct types of assumptions (statistical, extra-statistical, and causal), and the hypothetico-deductive methodology provide sufficient conditions for a causal interpretation of econometric models.
Monthly Views for the past 3 years
Monthly Downloads for the past 3 years
Plum Analytics
Actions (login required)
 |
View Item |
![[img]](https://philsci-archive.pitt.edu/style/images/fileicons/doc.png)
![[feed]](http://philsci-archive.pitt.edu/style/images/feed-icon-32x32.png){kind=icon}