Causality in Econometric Modeling. From Theory to Structural Causal Modeling

Mouchart, Michel ; Orsi, Renzo ; Wunsch, Guillaume (2020) Causality in Econometric Modeling. From Theory to Structural Causal Modeling. Bologna: Dipartimento di Scienze economiche, p. 33. DOI 10.6092/unibo/amsacta/6337. In: Quaderni - Working Paper DSE (1143). ISSN 2282-6483.
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Abstract

This paper examines different approaches for assessing causality as typically followed in econometrics and proposes a constructive perspective for improving statistical models elaborated in view of causal analysis. Without attempting to be exhaustive, this paper examines some of these approaches. Traditional structural modeling is first discussed. A distinction is then drawn between model-based and design-based approaches. Some more recent developments are examined next, namely history-friendly simulation and information-theory based approaches. Finally, in a constructive perspective, structural causal modeling (SCM) is presented, based on the concepts of mechanism and sub-mechanisms, and of recursive decomposition of the joint distribution of variables. This modeling strategy endeavors at representing the structure of the underlying data generating process. It operationalizes the concept of causation through the ordering and role-function of the variables in each of the intelligible sub-mechanisms.

Abstract
Document type
Monograph (Working Paper)
Creators
CreatorsAffiliationORCID
Mouchart, MichelUniversité catholique de Louvain0000-0001-9021-232X
Orsi, RenzoUniversità di Bologna0000-0001-7770-1014
Wunsch, GuillaumeUniversité catholique de Louvain0000-0002-2344-5251
Keywords
structural modeling, exogeneity, causality, model-based and design-based approaches, recursive decomposition, history- friendly simulation, transfer entropy
Subjects
ISSN
2282-6483
DOI
Deposit date
24 Feb 2020 14:36
Last modified
24 Feb 2020 14:36
URI

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