Publish or Patent: Bibliometric evidence for empirical trade-offs in national funding strategies

TL;DR

This study uses multivariate regression to analyze how different national R&D funding allocations influence publication and patent outputs, revealing trade-offs and providing predictive models for future research and policy decisions.

Contribution

It introduces empirical models linking R&D funding components to publication and patent outputs, explaining international differences and enabling future output predictions.

Findings

Government funding boosts publications but reduces high-quality patents.

Industrial funding correlates with increased patenting activity.

US focuses on industrial funding, explaining its publication and patenting patterns.

Abstract

Multivariate linear regression models suggest a trade-off in allocations of national R&D investments. Government funding, and spending in the higher education sector, seem to encourage publications, whereas other components such as industrial funding, and spending in the business sector, encourage patenting. Our results help explain why the US trails the EU in publications, because of its focus on industrial funding - some 70% of its total R&D investment. Conversely, it also helps explain why the EU trails the US in patenting. Government funding is indicated as a negative incentive to high-quality patenting. The models here can also be used to predict an output indicator for a country, once the appropriate input indicator is known. This usually is done within a dataset for a single year, but the process can be extended to predict outputs a few years into the future, if reasonable forecasts can be made of the input indicators. We provide new forecasts about the further relationships of the US, the EU-27, and the PRC in the case of publishing. Models for individual countries may be more successful, however, than regression models whose parameters are averaged over a set of countries.