Causal structure and hierarchies of models.

Published

Journal Article

Economics prefers complete explanations: general over partial equilibrium, microfoundational over aggregate. Similarly, probabilistic accounts of causation frequently prefer greater detail to less as in typical resolutions of Simpson's paradox. Strategies of causal refinement equally aim to distinguish direct from indirect causes. Yet, there are countervailing practices in economics. Representative-agent models aim to capture economic motivation but not to reduce the level of aggregation. Small structural vector-autoregression and dynamic stochastic general-equilibrium models are practically preferred to larger ones. The distinction between exogenous and endogenous variables suggests partitioning the world into distinct subsystems. The tension in these practices is addressed within a structural account of causation inspired by the work of Herbert Simon's, which defines cause with reference to complete systems adapted to deal with incomplete systems and piecemeal evidence. The focus is on understanding the constraints that a structural account of causation places on the freedom to model complex or lower-order systems as simpler or higher-order systems and on to what degree piecemeal evidence can be incorporated into a structural account.

Full Text

Duke Authors

Cited Authors

  • Hoover, KD

Published Date

  • December 2012

Published In

Volume / Issue

  • 43 / 4

Start / End Page

  • 778 - 786

PubMed ID

  • 22727127

Pubmed Central ID

  • 22727127

Electronic International Standard Serial Number (EISSN)

  • 1879-2499

International Standard Serial Number (ISSN)

  • 1369-8486

Digital Object Identifier (DOI)

  • 10.1016/j.shpsc.2012.05.007

Language

  • eng