The role of manipulation and intervention in theories of causality

8 May, 2021 at 11:52 | Posted in Theory of Science & Methodology | 2 Comments

largepreviewAs X’s effect on some other variable in the system S depends on there
being a possible intervention on X, and the possibility of an intervention in
turn depends on the modularity of S, it is a necessary condition for something to be a cause that the system in which it is a cause is modular with respect to that factor. The requirement that all systems are modular with respect to their causes can, in a way, be regarded as an interventionist addition to the unmanipulable causes problem … This implication has also been criticized in particular by Nancy Cartwright. She has proposed that many causal systems are not modular … Pearl has responded to this in 2009 (sect. 11.4.7), where he proposes, on the one hand, that it is in general sufficient that a symbolic intervention can be performed on the causal model, for the determination of causal effects, and on the other hand that we nevertheless could isolate the individual causal contributions …

It is tempting—to philosophers at least—to equate claims in this literature,
about the meaning of causal claims being given by claims about what would
happen under a hypothetical intervention—or an explicit definition of causation to the same effect—with that same claim as it would be interpreted in a philosophical context. That is to say, such a claim would normally be understood there as giving the truth conditions of said causal claims. It is generally hard to know whether any such beliefs are involved in the scientific context. However, Pearl in particular has denied, in increasingly explicit terms, that this is what is intended … He has recently liked to describe a factor Y , that is causally dependent on another factor X, as “listening” to X and determining “its value in response to what it hears” … This formulation suggests to me that it is the fact that Y is “listening” to X that explains why and how Y changes under an intervention on X. That is, what a possible intervention does, is to isolate the influence that X has on Y , in virtue of Y ’s “listening” to X. Thus, Pearl’s theory does not imply an interventionist theory of causation, as we understand that concept in this monograph. This, moreover, suggests that the intervention that is always available, for any cause that is represented by a variable in a causal model, is a formal operation. I take this to be supported by the way he responds to Nancy Cartwright’s objection that modularity does not hold of all causal systems: it is sufficient that a symbolic intervention can be performed. Thus, the operation alluded to in Pearl’s operationalization of causation is a formal operation, always available, regardless of whether it corresponds to any possible intervention event or not.

Interesting dissertation well worth reading for anyone interested in the ongoing debate on the reach of interventionist causal theories.

Framing all causal questions as questions of manipulation and intervention runs in to many problems, especially when we open up for “hypothetical” and “symbolic” interventions. Humans have few barriers to imagining things, but that often also makes it difficult to value the proposed thought experiments in terms of relevance. Performing “well-defined” interventions is one thing, but if we do not want to to give up searching for answers to the questions we are interested in and instead only search for answerable questions, interventionist studies is of limited applicability and value. Intervention effects in thought experiments are not self-evidently the causal effects we are looking for. Identifying causes (reverse causality) and measuring effects of causes (forward causality) is not the same. In social sciences, like economics, we standardly first try to identify the problem and why it occurred, and then afterwards look at the effects of the causes.

Leaning on the interventionist approach often means that instead of posing interesting questions on a social level, focus is on individuals. Instead of asking about structural socio-economic factors behind, e.g., gender or racial discrimination, the focus is on the choices individuals make (which — as I maintain in my book Ekonomisk teori och metod — also tends to make the explanations presented inadequately ‘deep’).  A typical example of the dangers of this limiting approach is ‘Nobel prize’ winner Esther Duflo , who thinks that economics should be based on evidence from randomised experiments and field studies. Duflo et consortes want to give up on ‘big ideas’ like political economy and institutional reform and instead go for solving more manageable problems the way plumbers do. Yours truly is far from sure that is the right way to move economics forward and make it a relevant and realist science. A plumber can fix minor leaks in your system, but if the whole system is rotten, something more than good old fashion plumbing is needed. The big social and economic problems we face today are not going to be solved by plumbers performing interventions or manipulations in the form of RCTs.


  1. Please do not take this as saying all causation discussion must be in terms of intervention, but the plumber analogy does not work against that idea. If the whole system is failing, that only says the intervention needed is on that system. That system intervention may involve multiple individual interventions (e.g., programs to subsidize replaceing aging water-inefficient toilets with better units) or only a singular intervention on the public part of the system (e.g., repairing a main sewer line).
    Any policy decision must correspond to an intervention and so intervention models of causation (with their precise conceptualizations regarding transportability, feasibility etc.) must be a central tool for any policy-oriented research.

    • I’ve had a similar discussion with Judea Pearl, who thinks I am — as are Nancy Cartwright & David Freedman — too “pessimistic” on the reach of the manipulation/intervention approach. I do concede, of course, that it is possible (more or less, depending on context) to retrofit causal questions into a manipulation/intervention framework, but before we are there, we have to agree on having identified the causal problem we try to deal with when recommending different policies. Before we can calculate causal effects we have to identify the causes, and as especially Cartwright has argued for years now, that is is perhaps not always best done within a manipulation/intervention framework. One problem — which I tried to highlight in the post — is that the manipulation/intervention approach in broader social and economic contexts (as also the Hernán-Pearl discussion on obesity showed) requires a reframing of the questions we pose (as in Duflo et consortes “plumber RCTs”), which often means that we get “well-defined” causal answers, but not necessarily answers to the questions we really are interested at finding answers to. The manipulation/intervention framework is one way to do causal analysis. But it is not the way to do it. Being myself an advocate of “inference to the best explanation” I think we also have to more carefully consider explanatory considerations when estimating and identifying causal relations.

Sorry, the comment form is closed at this time.

Blog at
Entries and Comments feeds.