TY - UNPB
T1 - Individual Determinants of Inventor Productivity
T2 - Report and Preliminary Results with Evidence from Linked Human Capital and Patent Data
AU - Frosch, Katharina
AU - Harhoff, Dietmar
AU - Hoisl, Karin
AU - Steinle, Christian
AU - Zwick, Thomas
PY - 2015
Y1 - 2015
N2 - This report offers new insights into the drivers of inventor productivity at the individual level. It includes well-known drivers, such as inventor age and education, and controls for inventor team size, and firm/applicant information, as well as period and technology field effects derived from patent data. In addition, it adds inventor characteristics that have been largely neglected in existing studies on inventor productivity, such as the breadth of work experience, divergent thinking skills, cognitive problem-solving skills, the use of knowledge sourced from networks within and outside of the inventors’ field of expertise, and personality traits. The empirical model draws on a new dataset that matches information about inventors’ human capital, such as creative skills, personality traits, networks, and career biographies (collected with a self-administered survey) with patenting histories for 1932 German inventors between the years 1978 and 2012 for clean technology, nanotechnology, and mechanical elements. Our results indicate that the additional inventor characteristics double the proportion of total variation of productivity explained by individual characteristics. Furthermore, we find differences in the importance of individual characteristics across industries and along the productivity distribution, between more and less productive inventors.
AB - This report offers new insights into the drivers of inventor productivity at the individual level. It includes well-known drivers, such as inventor age and education, and controls for inventor team size, and firm/applicant information, as well as period and technology field effects derived from patent data. In addition, it adds inventor characteristics that have been largely neglected in existing studies on inventor productivity, such as the breadth of work experience, divergent thinking skills, cognitive problem-solving skills, the use of knowledge sourced from networks within and outside of the inventors’ field of expertise, and personality traits. The empirical model draws on a new dataset that matches information about inventors’ human capital, such as creative skills, personality traits, networks, and career biographies (collected with a self-administered survey) with patenting histories for 1932 German inventors between the years 1978 and 2012 for clean technology, nanotechnology, and mechanical elements. Our results indicate that the additional inventor characteristics double the proportion of total variation of productivity explained by individual characteristics. Furthermore, we find differences in the importance of individual characteristics across industries and along the productivity distribution, between more and less productive inventors.
M3 - Working paper
T3 - ZEW Discussion Papers
BT - Individual Determinants of Inventor Productivity
PB - Leibnitz Centre for European Economic Research (ZEW)
CY - Mannheim
ER -