In 2014 Aruoba and Fernández-Villaverde published A Comparison of programming languages in (macro)economics (official Elsevier link here, codes on GitHub, recently updated computations here). The article also mentions QuantEcon in [5]. Both Python and Julia were included in the review.

There, the authors announced a follow-up titled “Functional Programming in Economics” [1] where (more purely) functional languages would be discussed. As far as I could see, this article did not appear (yet). Of course I could try to send an email to the authors - and perhaps I will - but I would also appreciate your opinions very much.

For definiteness, let us restrict ourselves to discrete-time (deterministic or stochastic) dynamical systems such as those studied in Stachurski’s “Economic Dynamics”. Apart from the clear scarcity of purely functional software libraries, is there a fundamental reason why a functional language would *not* be well suited for this context, or is this indeed a very practical matter: Presently, the role of such languages in numerical computation as a whole is simply too marginal?

My question is not meant as any form of criticism, nor do I want to start a pointless “which language / paradigm is better” discussion. Indeed, like many others I hold QuantEcon in high regard. Yet, it seems to me that features such as function composition, currying and higher-order functions could allow for a very natural translation from mathematics to software in the specific field of discrete dynamical systems, perhaps even more so when considering their actions on metric spaces consisting of functions (or: measures) themselves.

I hope this thread does not take us too far off-topic. In any case I thank you very much in advance for your insights. They are much appreciated!