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. 2024 Jan 4:6:e9.
doi: 10.1017/ehs.2023.35. eCollection 2024.

Identifying culture as cause: Challenges and opportunities

Sirio Lonati  1 , Rafael Lalive  2 , Charles Efferson  2
Affiliations

Identifying culture as cause: Challenges and opportunities

Sirio Lonati et al. Evol Hum Sci. .

Abstract

Causal inference lies at the core of many scientific endeavours. Yet answering causal questions is challenging, especially when studying culture as a causal force. Against this backdrop, this paper reviews research designs and statistical tools that can be used - together with strong theory and knowledge about the context of study - to identify the causal impact of culture on outcomes of interest. We especially discuss how overlooked strategies in cultural evolutionary studies can allow one to approximate an ideal experiment wherein culture is randomly assigned to individuals or entire groups (instrumental variables, regression discontinuity design, and epidemiological approach). In doing so, we also review the potential outcome framework as a tool to engage in causal reasoning in the cultural evolutionary field.

Keywords: Causal inference; culture; potential outcomes; treatment effects.

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Conflict of interest statement

CE is on the editorial board of Evolutionary Human Sciences.

Figures

None
Graphical abstract
Figure 1.
Figure 1.
Selection on observables and omitted common causes. Note: A box around a variable means that this variable is conditioned on in the analysis; a dashed arrow represents a spurious relationship. (a) A case where conditioning is enough to correctly identify the null causal effect of Di; (b) a conditioning strategy that does not completely solve issues of unobserved common causes, because only the common cause X1i is observed, while the common cause X2i is unobserved.
Figure 2.
Figure 2.
Conditioning on a common effect and M-bias. Note: A box around a variable means that this variable is conditioned on in the analysis; a dashed arrow represents a spurious relationship. (a) Conditioning on the common effect Xi engenders a spurious relation between the treatment Di and the outcome Yi. (b) Conditioning on the variable X1i engenders a spurious relation between the treatment Di and the outcome Yi.
Figure 3.
Figure 3.
Instrumental variables (see Huntington-Klein, 2021). Note: All panels display the relationship between a valid or invalid instrument Zi, a cultural trait Di, an outcome Yi and two potentially omitted common causes, Qi and Ci.
Figure 4.
Figure 4.
Regression discontinuity: a representation (see Cattaneo et al., 2023). Note: The solid curves represent observed outcomes; the dotted curves represent unobserved outcomes.
Figure 5.
Figure 5.
Regression discontinuity: an alternative representation (see Huntington-Klein, 2021).
Figure 6.
Figure 6.
Epidemiological approach using immigrants’ data: a representation (see Luttmer & Singhal, 2011). Note: Each circle represents the average observations of immigrants coming from a given country. The dimensions of circles represent a different number of migrants observed.
See this image and copyright information in PMC

References

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