Peer-reviewed publications

Science quality and the value of inventions

Science Advances 11 Dec 2019: Vol. 5, no. 12, eaay7323 DOI: 10.1126/sciadv.aay7323

Coverage Research Europe

with Dietmar Harhoff, Fabian Gaessler and Stefano Baruffaldi

SNPL references by science quality Patent value by SNPL science quality Patent value by distance to the scientific frontier and SNPL science quality.
Abstract Despite decades of research, the relationship between the quality of science and the value of inventions has remained unclear. We present the result of a large-scale matching exercise between 4.8 million patent families and 43 million publication records. We find a strong positive relationship between the quality of the scientific contributions referenced in patents and the value of the respective inventions. We rank patents by the quality of the science to which they are linked. Strikingly, high-ranking patents are twice as valuable as low-ranking patents, which, in turn, are about as valuable as patents without a direct science link. We show this core result for various science quality and patent value measures. The effect of science quality on patent value remains relevant even when science is linked indirectly through other patents. Our findings imply that what is considered excellent within the science sector also leads to outstanding outcomes in the technological and commercial realms.

Estimating measures of multidimensional poverty with Stata

The Stata Journal (2017) 17, Number 3, pp. 687–703 URL: Stata Journal

with Daniele Pacifico

Abstract In this article, we describe the multidimensional poverty measures developed by Alkire and Foster (2011, Journal of Public Economics 95: 476–487) and show how they can be computed with Stata by using the mpi command.

Other publications

Linked Inventor Biography Data 1980-2014 (INV-BIO ADIAB 8014)

FDZ Data Report, No. 03/2018 URL: Report

with Matthias Dorner, Dietmar Harhoff, Fabian Gaessler and Karin Hoisl

SNPL references by science quality Patent value by SNPL science quality
Abstract This data report describes the Linked Inventor Biography Data 1980-2014 (INV-BIO ADIAB8014), its generation using record linkage and machine learning methods as well as how to access the data via the FDZ.

Used in project Filling the Gap - Firm Strategies for Human Capital Loss.