Causal Inference

Novemver, 2013

Abstract

This paper reflects on a recent article by Heckman and Pinto (2013) in which they discuss a formal system, called do-calculus, that operationalizes Haavelmo’s conception of policy intervention. They replace the do-operator with an equivalent operator called “fix,” highlight the capabilities of “fix,” discover limitations in “do,” and inform readers that those limitations disappear in “the Haavelmo approach.” I examine the logic of HP’s paper, its factual basis, and its impact on econometric research and education.

September, 2013

Abstract

May, 2013

Abstract

This note reviews basic techniques of linear path analysis and demonstrates, using simple examples, how causal phenomena of non-trivial character can be understood, exemplified and analyzed using diagrams and a few algebraic steps. The techniques allow for swift assessment of how various features of the model impact the phenomenon under investigation. This includes: Simpson’s paradox, case–control bias, selection bias, missing data, collider bias, reverse regression, bias amplification, near instruments, and measurement errors.