Response to Henschen: causal pluralism in macroeconomics

ABSTRACT

In his recent paper in the Journal of Economic Methodology, Tobias Henschen puts forth a manipulationist definition of macroeconomic causality that strives for adequacy. As the notion of ‘adequacy’ remains underdeveloped in that paper, in this study we offer a discussion of what it means for a definition of causality to be adequate to macroeconomics. One of the meanings of adequacy is that the definition of causality describes the types of relations for which macroeconomic causal models stand for. On this understanding of adequacy, we take issue with Henschen’s claim. We argue that his manipulationist definition is only applicable to a sample of causal models used by macroeconomists. There are other sets of macroeconomic causal models to which probabilistic and mechanistic definitions seem more adequate. We show relevant examples to support this claim and conclude that a moderate causal pluralism is an adequate stance with respect to macroeconomic causal models.

KEYWORDS:

• Causal inference
• macroeconomics
• causal pluralism
• probabilistic causality
• mechanistic causality

Acknowledgment

The authors acknowledge the comments received from the two anonymous reviewers and the participants in Brown Bag Seminar taking place on the 13th December 2018 organized by the Centre for Philosophy of Social Science (TINT) at the University of Helsinki. The input of work of both authors is equal.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Mariusz Maziarz is a Ph.D. candidate at the Wrocław University of Economics and an assistant researcher at the Interdisciplinary Centre for Ethics, Jagiellonian University. His research interests focus on philosophy and methodology of economics; causality, philosophy of econometrics, and philosophy of medicine.

Robert Mróz is a Ph.D. student at the Faculty of Economic Sciences at the University of Warsaw. His research is concerned with causal inference in economics and econometrics, as well as economic models and modeling practices in economics.

ORCID

Mariusz Maziarz http://orcid.org/0000-0003-1979-0746

Robert Mróz http://orcid.org/0000-0002-3180-3151

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1 We do think it is intuitive to connect policy (manipulating one variable to influence another) and the manipulationist account. Our argument presented here means that other accounts of causality underpin other types of models that are used in economics to produce causally interpreted results, but we think some such intuition might putatively explain why accounts such as Henschen’s or Hoover’s are popular in the philosophy of macroeconomics. For our current purposes, as it is not a crucial part of the argument, we are content to leave this issue at the level of intuitions.

2 The numbers refer to the order of appearance in Henschen’s (2018a) paper and Table 1.

3 Contrary to Henschen’s (2018a) remark that the manipulationist theory of causality raises the problem of circularity, it is sometimes interpreted as a reductionist enterprise (Carroll, 2009; Menzies & List, 2010).

4 As this definition is taken directly from Henschen (2018a), we follow the notation proposed there, in which upper-case letters denote variables and lower-case letters denote the values of these variables.

5 Henschen himself seems to admit as much in his companion paper (2018b). In this paper, he argues that methods such as instrumental variables or econometric causality tests, which make up the standard arsenal of macroeconomic causality research, do not provide conclusive evidence for causal relations, where causality is understood in line with the interventionist account. The contribution of our paper is, thus, to show that some of the models and methods fit well with other understandings of causality. Consequently, the answer to the question “What is macroeconomic causality?” (the title of Henschen’s, 2018a paper) cannot consist in specifying a definition based on only one of many philosophical approaches to causality.

6 We label ‘contemporary DSGE’ the models populated by heterogeneous agents. The move from the homogeneous rational agent, accused of unrealisticness, to agents differing in their decision processes was started by Iacoviello (2005). Earlier, the realistic treatment of the customer decision process was hampered by steep requirements in terms of computational power.

7 When discussing mechanisms it is also worth noticing that the presence of multiple interacting mechanisms in the economy is an epistemic obstacle to deriving actual causal knowledge that would fit the manipulationist definition. (Similarly, the estimation of VAR models on purely observational data that was discussed in section 4.1 was also such an epistemic obstacle.) The presence of several mechanisms produces a situation in which estimating the effect of an intervention under consideration is only possible within a model. As Reiss (2013, p. 108) puts it, “it is not normally possible to predict an outcome upon observing that this or that mechanism has been triggered.” Even if there was a possible intervention justified by such models, its results could not be foreseen without additional assumptions and/or further evidence (such as, for instance, natural experiments). This complexity of the economy is of course an obstacle to producing causal knowledge on the basis of data regardless of the account of causality that one ascribes to.

8 We label this stance ‘moderate’ to distinguish it from radical causal pluralism (cf. Reiss, 2015, p. 16).

Additional information

Funding

The research was partially financed by the National Science Centre, Poland under grant number 2015/19/N/HS1/01066. Mariusz Maziarz received a Ph.D. scholarship from the National Science Centre, Poland under grant number 2018/28/T/HS1/00007. The preparation of this article was partially supported by the National Programme for the Development of Humanities in Poland (grant number 0266/NPRH4/H2b/83/2016).