Ignorability and other questionable assumptions in causal inference

15 Aug, 2022 at 15:38 | Posted in Statistics & Econometrics | 1 Comment

Causal inference (Part 1 of 3): Understanding the fundamentals | by Jane  Huang | Data Science at Microsoft | MediumMost attempts at causal inference in observational studies are based on assumptions that treatment assignment is ignorable. Such assumptions are usually made casually, largely because they justify the use of available statistical methods and not because they are truly believed.

Marshall Joffe et al.

An interesting (but from a technical point of view rather demanding) article on a highly questionable assumption used in ‘potential outcome’ causal models. It made yours truly come to think of how tractability has come to override reality​ and truth also in modern mainstream economics.

A ‘tractable’ model is of course great since it usually means you can solve it. But — using ‘simplifying’ tractability assumptions (rational expectations, common knowledge, representative agents, linearity, additivity, ergodicity, exchangeability, ignorability, etc.) because otherwise they cannot ‘manipulate’ their models or come up with ‘rigorous ‘ and ‘precise’ predictions and explanations, does not exempt scientists from having to justify their modelling choices. Being able to ‘manipulate’ things in models cannot per se be enough to warrant a methodological choice. Suppose economists do not really think their tractability assumptions make for good and realist models. In that case, it is certainly a just question to ask for clarification of the ultimate goal of the whole modelling endeavour.

Take for example the ongoing discussion on rational expectations as a modelling assumption in economics. Those who want to build macroeconomics on microfoundations usually maintain that the only robust policies are those based on rational expectations and representative actors models. As yours truly has tried to show in On the use and misuse of theories and models in mainstream economics there is really no support for this conviction at all. If microfounded macroeconomics has nothing to say about the real world and the economic problems out there, why should we care about it? The final court of appeal for macroeconomic models is not if we — once we have made our tractability assumptions — can ‘manipulate’ them, but the real world. And as long as no convincing justification is put forward for how the inferential bridging de facto is made, macroeconomic modelbuilding is little more than hand-waving that gives us rather a little warrant for making inductive inferences from models to real-world target systems. If substantive questions about the real world are being posed, it is the formalistic-mathematical representations utilized to analyze them that have to match reality, not the other way around.

1 Comment

  1. Here’s a link to the article (which is from 2010):

    P.S. Marshall Joffe (Ph.D. 1994) was a doctoral advisee of mine. Marshall was recognized as one of the finest our department had the pleasure of hosting.

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