Scaling in economics: a reader's guide

TLDR

Scaling laws in economics and finance illustrate regularities that inform econometric goals such as estimating predictive distributions and impulse responses, offering insights into the underlying data‑generating process. The paper aims to highlight the challenges researchers face when using scaling law regularities to enhance econometric identification of causal data‑generating mechanisms. The study finds that scaling laws discipline theory formation and inspire speculative research projects.

Abstract

This paper discusses examples of scaling laws in economics and finance. It argues that these regularities in data are useful for disciplining theory formation. Estimation of the conditional predictive distribution and estimation of impulse response functions is a main goal of econometric work. Scaling type regularities give useful information on the underlying data generating process. The ability of scaling laws to suggest lines of potentially fruitful research was illustrated by the suggestion of several speculative research projects in this paper. Most importantly, the paper stresses the challenges that face empirical and theoretical researchers who wish to make use of scaling law type regularities to improve econometric identification of the underlying causal data generating mechanism.