Judea Pearl on regression and causation

28 Sep, 2013 at 11:35 | Posted in Statistics & Econometrics | 6 Comments

Judea Pearl was kind enough to send yours truly his article (co-authored with Bryant Chen) Regression and causation: a critical examination of six econometrics textbooks a while ago. It has now been published in real-world economics review  issue no. 65.

causation

The article addresses two very important questions in the teaching of modern econometrics and its different textbooks – how is causality treated in general, and more specifically, to what extent they use a distinct causal notation.

The authors have for years been part of an extended effort of advancing explicit causal modeling (especially graphical models) in applied sciences, and this is a first examination of to what extent these endeavours have found their way into econometrics textbooks.

Although the text partly is of a rather demanding “technical” nature, I would definitely recommend it for reading, especially for social scientists with an interest in these issues.

Pearl’s seminal contribution to this research field is well-known and indisputable, but on the “taming” and “resolve” of the issues, I however have to admit that — under the influence of especially David Freedman and Nancy Cartwright — I still have some doubts on the reach, especially in terms of “realism” and “relevance,” of these “solutions” for social sciences in general and economics in specific (see here, here, here and here). And with regards to the present article I think that since the distinction between the “interventionist” E[Y|do(X)] and the more traditional “conditional expectationist” E[Y|X] is so crucial for the subsequent argumentation, a more elaborated presentation had been of value, not the least because then the authors could also more fully explain why the first is so important and if/why this (in my, Freedman’s and Cartwright’s view) can be exported from “engineer” contexts where it arguably easily and universally apply, to “socio-economic” contexts where “manipulativity” and “modularity” are not perhaps so universally at hand.

6 Comments

  1. Can you provide an introductory reading list for this topic? I could understand the text of Pearl/Chen; but a series of articles (or books) that give more elementary background would be appreciated. I am a government-employed economist; and I would assume that a number of these issues have policy-related implications. Great web site!

    • The topic is rather complicated, but maybe these works could function as an “introduction”:

      Kevin Hoover: The Methodology of Empirical Macroeconomics (especially chapter 4) (CUP 2001)
      Nancy Cartwright: Hunting Causes and Using Them: Approaches in Philosophy and Economics (CUP 2007)
      Judea Pearl: Causality (CUP 2000)
      Stephen Morgan & Christopher Winship: Counterfactuals and Causal Inference (CUP 2007)

      • Thanks very much — these will go on my reading list!

  2. […] of Six Econometrics Textbooks. Lars Syll, who was earlier sent the paper, has weighed in here. It is a heavy and technical paper, but I think that the underlying results are of great interest […]

  3. I find it helpful to compare E(It will rain | people are carrying umbrellas) with E(It will rain | I will make everyone carry umbrellas). Or E(The economy is good | interest rates are naturally low) with E(The economy is good | I will artificially force interest rates to be low).

  4. […] of Six Econometrics Textbooks. Lars Syll, who was earlier sent the paper, has weighed in here. It is a heavy and technical paper, but I think that the underlying results are of great interest […]


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