Part 4: The law of logarithmic returns

Abstract

The returns in an area of endeavor with many disparate problems are predicted to increase logarithmically with the invested resources. This ‘law of logarithmic returns’ applies to fields such as research, lobbying for policy changes, or industrial innovation, where the individual problems are one-off and not similar to another. Empirical data from various fields, including drug approvals, experience curves, quality of life, and historical research progress support this prediction. The logarithmic relationship between resources and returns has consequences for estimating the cost-effectiveness of research and prioritizing resource allocation. Overall, this work provides a predictive model for decision-making in resource allocation and highlights the importance of considering the distribution of problems within a field to accurately assess the returns on investment. – AI-generated abstract.