Academic Knowledge: Does it Reflect the Combinatorial Growth of Technology?

TL;DR

This paper investigates whether academic knowledge, especially in economics, grows through recombination of ideas similar to technological growth, finding limited evidence of such growth due to institutional barriers.

Contribution

It adapts combinatorial growth theory to academia and provides empirical evidence that institutional structures hinder recombination-driven growth in research.

Findings

Limited topic recombination in economics research over three decades

Institutional career structures discourage idea recombination

Academic growth may not follow the same combinatorial patterns as technological growth

Abstract

I explore the concept of growth being rooted in the recombination of existing technology as an explanation for the remarkable growth witnessed during the Industrial Revolution as it was recently proposed by Koppl et al.(2023). I adapt their combinatorial growth theory to assess its applicability in generating academic knowledge within universities and research institutions, particularly in the field of economics. The central question is whether significant combinatorial growth can also be anticipated in academia. The current career structures discourage the recombination of ideas, theories, or methods, making it more advantageous for early career researchers to stick to the status quo. I employ machine-learning-based natural language analysis of the top 5 journals in economics. The analysis reveals limited correlations between topics over the past three decades, suggesting the presence of isolated topic islands rather than productive recombination. This confirms the theoretical considerations beforehand. Overall, the institutional order of academia makes combinatorial growth at the research frontier unlikely.