# CAUSAL ANALYSIS AFTER HAAVELMO

@article{Heckman2014CAUSALAA, title={CAUSAL ANALYSIS AFTER HAAVELMO}, author={James Heckman and Rodrigo R. Pinto}, journal={Econometric Theory}, year={2014}, volume={31}, pages={115 - 151} }

Haavelmo’s seminal 1943 and 1944 papers are the first rigorous treatment of causality. In them, he distinguished the definition of causal parameters from their identification. He showed that causal parameters are defined using hypothetical models that assign variation to some of the inputs determining outcomes while holding all other inputs fixed. He thus formalized and made operational Marshall’s (1890) ceteris paribus analysis. We embed Haavelmo’s framework into the recursive framework of…

## 98 Citations

Trygve Haavelmo and the Emergence of Causal Calculus

- Economics
- 2013

Haavelmo was the first to recognize the capacity of economic models to guide policies. This paper describes some of the barriers that Haavelmo’s ideas have had (and still have) to overcome and lays…

TRYGVE HAAVELMO AND THE EMERGENCE OF CAUSAL CALCULUS

- EconomicsEconometric Theory
- 2014

Haavelmo was the first to recognize the capacity of economic models to guide policies. This paper describes some of the barriers that Haavelmo’s ideas have had (and still have) to overcome and lays…

Causality and Econometrics

- Economics
- 2022

of the of IZA. on policy, but IZA takes no institutional policy positions. The IZA research network is committed to the IZA Guiding Principles of Research Integrity. of Our key between policymakers…

Reflections on Heckman and Pinto's Causal Analysis After Haavelmo

- Philosophy
- 2013

Working paper. TECHNICAL REPORT R-420 November 2013 Reflections on Heckman and Pinto’s “Causal Analysis After Haavelmo” Judea Pearl University of California, Los Angeles Computer Science Department…

Graphical Causal Modeling in Econometrics

- Economics
- 2020

Causal Bayesian nets (Pearl, 2000; Spirtes et al., 2000) have been employed fruitfully in computer science, epidemiology and political science. Thus far, the applications in research in economics…

2 An oracle for policies or an aid to forecasters ?

- Economics
- 2014

Haavelmo was the first to recognize the capacity of economic models to guide policies. This paper describes some of the barriers that Haavelmo’s ideas have had (and still have) to overcome, and lays…

Implementation-Neutral Causation in Structural Models

- Economics
- 2018

The Cowles Commission insight that causal relations are shown to depend on parameter restrictions that are explicit in the structural form, but not in the reduced form when the coefficients are interpreted as unrestricted constants is shown to be correct.

Causality: a decision theoretic approach

- Economics, Computer Science
- 2019

A decision-theoretic model akin to Savage (1972) that is useful for defining causal effects is proposed and axioms on preferences are provided that are equivalent to the existence of a Directed Acyclic Graph that represents the DM's preference.

In Defense of Unification (Comments on West and Koch's review of Causality)

- Philosophy
- 2014

A new review of Causality has appeared in the Journal of Structural Equation Modeling, and the reviewers seem reluctant, and tend to cling to traditions that lack the language, tools and unifying perspective to bene t from the chapters reviewed.

Causal Inference and Data-Fusion in Econometrics

- Computer Science
- 2019

Recent advances in this literature that have the potential to contribute to econometric methodology along three dimensions provide a unified and comprehensive framework for causal inference, in which the aforementioned problems can be addressed in full generality.

## References

SHOWING 1-10 OF 115 REFERENCES

Discussion: ‘The Scientific Model of Causality’

- Economics
- 2005

Heckman advocates an approach to causal inference that draws upon structural modeling of the outcome(s) of interest (which he calls scientific), and he contrasts this approach sharply with that…

Alternative Graphical Causal Models and the Identification of Direct E!ects

- Computer Science
- 2010

This paper analyzes various measures of the ‘direct’ causal effect, focussing on the pure direct effect (PDE), and introduces the Minimal Counterfactual Model (MCM) which is referred to as ‘minimal’ because it imposes the minimal counterfactual independence assumptions.

Comment: Graphical Models, Causality and Intervention

- Computer Science
- 2016

I will focus on the connection between graphical models and the notion of causality in statistical analysis, and supplement the discussion with an ac'count of how causal models and graphical models are related.

1. The Scientific Model of Causality

- Economics
- 2005

Causality is a very intuitive notion that is difficult to make precise without lapsing into tautology. Two ingredients are central to any definition: (1) a set of possible outcomes (counterfactuals)…

Settable Systems: An Extension of Pearl's Causal Model with Optimization, Equilibrium, and Learning

- EconomicsJ. Mach. Learn. Res.
- 2009

The settable systems framework is offered as an extension of the Pearl Causal Model that permits causal discourse in systems embodying optimization, equilibrium, and learning and may prove generally useful for machine learning.

A Study Of Identifiability In Causal Bayesian Networks 1 Version 0 . 3

- Computer Science
- 2006

It is shown that the identify algorithm that Tian and Pearl define and prove sound for semi-Markovian models can be transfered to general causal graphs and is not only sound, but also complete, effectively solving the identifiability question for causal Bayesian networks.

Econometric Evaluation of Social Programs, Part I: Causal Models, Structural Models and Econometric Policy Evaluation

- Economics
- 2007

Causality, Conditional Independence, and Graphical Separation in Settable Systems

- Computer ScienceNeural Computation
- 2012

The conditional Reichenbach principle is applied to show that the useful tools of d-separation and D- separation can be employed to establish conditional independence within suitably restricted settable systems analogous to Markovian PCMs.

Causation, prediction, and search

- Computer Science
- 1993

The authors axiomatize the connection between causal structure and probabilistic independence, explore several varieties of causal indistinguishability, formulate a theory of manipulation, and develop asymptotically reliable procedures for searching over equivalence classes of causal models.

Mostly Harmless Econometrics: An Empiricist's Companion

- Economics
- 2008

The core methods in today's econometric toolkit are linear regression for statistical control, instrumental variables methods for the analysis of natural experiments, and differences-in-differences…