Grant C. Black

WHO'S PATENTING IN THE UNIVERSITY? EVIDENCE FROM THE SURVEY OF DOCTORATE RECIPIENTS

We use the Survey of Doctorate Recipients to examine the question of who in US universities is patenting. Because standard methods of estimation are not directly applicable, we use a zero-inflated negative binomial model to estimate the patent equation, using instruments for the number of articles to avoid problems of endogeneity. We also estimate the patent model using the generalized method of moments estimation of count data models with endogenous regressors. We find work context and field to be important predictors of the number of patent applications. We also find patents to be positively and significantly related to the number of publications. This finding is robust to the choice of instruments and method of estimation. The cross-sectional nature of the data preclude an examination of whether a trade-off exists between publishing and patenting, holding individual characteristics constant over time. But the strong cross-sectional correlation that we find does not suggest that commercialization has come at the expense of placing knowledge in the public domain.

Doctoral Education and Economic Development: The Flow of New Ph.D.s to Industry

Doctoral education in science and engineering is critical to the university’s role in fostering economic development. One aspect of this is the placement of recent graduates with firms. Despite the role Ph.D.s play in this process, little work has documented and analyzed these firm placements. This article takes a first step at rectifying this deficiency, using data from the 1997-1999 Survey of Earned Doctorates administered by the National Science Foundation to all doctoral recipients in the United States. The authors show that knowledge sources, as measured by the training location of new Ph.D.s going to industry, are concentrated in different geographic centers from those that university R&Dexpenditure data would suggest. The authors also find significant outflows from the Midwest of Ph.D.s and significant inflows to the Pacific and northeast regions of the country. The authors’work suggests that many states fail to capture the economic development advantages that come from training a skilled work force.

The Knowledge Production Function for University Patenting

We estimate a knowledge production function for university patenting using an individual effects negative binomial model. We control for Research and Development expenditures, research field, and the presence of a Technology Transfer Office. We distinguish between three kinds of researchers: faculty, postdoctoral scholars (postdocs), and PhD students. For the latter two, we also distinguish by visa status. We find patent counts to relate positively and significantly to the number of PhD students and number of postdocs. Our results also suggest that not all graduate students and postdocs contribute equally to patenting but that contribution is mediated by citizenship and visa status. (JEL C25, O31, O32, O34, O38)

The small size of the small scale market: The early-stage labor market for highly skilled nanotechnology workers

We examine the labor market for the highly trained in nanotechnology and the response of universities toward providing training. We draw comparisons with the labor market and university response in bioinformatics. The demand analysis is based on position announcements in Science in 2002 compared to 2005. We also analyze online position announcements in late 2005 and early 2006. Our analysis leads us to conclude that at the present time the market is small and growing for positions in academe and at FFRDCs, small and stable for positions at firms. Our analysis of training leads to the conclusion that the pipeline is being filled primarily through a principal investigator approach, where a student is attached to one faculty members lab, rather than to a formal program. The fundamental difference between nanotechnology and bioinformatics in this respect may be due to differences in the opportunities available to universities and faculty.

Bioinformatics: Does the US system lead to missed opportunities in emerging fields? A case study

Although the field of bioinformatics/computational biology appears to be booming universities have been slow to start programs in this area. Four interrelated explanations are examined: individual faculty have no incentive to establish training programs; the educational system responds differently when demand is driven by industry rather than universities; the interdisciplinary nature of the field creates disincentives to establishing programs; and the ‘quick-fix’ to turn life scientists into computational biologists is not possible. Copyright , Beech Tree Publishing.

Bioinformatics training programs are hot but the labor market is not

Based on a survey of academic training programs and an analysis of advertised job openings, we conclude that the labor market in bioinformatics has changed dramatically from the 1990s to the early 2000s. The number of academic training programs, as well as enrollment in these programs, expanded rapidly during this period. The expansion has created a sizeable pipeline of students who will matriculate from these programs in the near future. Yet, at the same time that this expansion in training programs occurred, demand in the bioinformatics market declined and its origins have shifted largely from industry to academe. Unless conditions in industry change dramatically in the next few years, it is likely that trainees from these programs will have difficulty finding the expected jobs in industry.