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.Academic research productivity, Patenting, Publishing, Technology transfer, Count data models, Bayh-Dole Act,

No abstract

No abstract

No abstract

No abstract