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The NBER-Rensselaer Scientific Papers Database: Form, Nature, and Function
Abstract
This article is a guide to the NBER-Rensselaer Scientific Papers Database, which includes more than 2.5 million scientific publications and over 21 million citations to those papers. The data cover an important sample of 110 top U.S. universities and 200 top U.S.-based R&D-performing firms during the period 1981-1999. This article describes the file system which comprises the database, explains the variables included in the files, and discusses the functions of the various files. It includes numerous descriptive tables, as well as graphs of the data in the time series dimension. In addition, it discusses limitations and strengths of the data as well as some questions that the data might be used to address.
... While much of the previous research has centered on exploration as more sciencebased and exploitation as more technology-based, this current research effort seeks to separate the scientific activities into both exploration and exploitation. Utilising a unique database, the NBER-Rensselaer Scientific Papers Database (Adams and Clemmons, 2008), this research effort uses citations to and from scientific publications to separate the two phenomena, exploration and exploitation. ...
... The primary independent or predictor variables are constructed from the citation patterns that firm publications have. These data were obtained using the NBER-Rensselaer Scientific Papers Database (Adams and Clemmons, 2008). This database contains the scientific publications of the top 110 U.S. universities and the top 200 U.S. R&D-performing firms for the years 1981 to 1999. ...
Since March's 1991 seminal article, exploration and exploitation have been extensively studied in the areas of organisational learning, strategic renewal, and technological innovation [Li et al.(2008)]. However, much of the research has focused on exploration as science-based and exploitation as technology-based. This current research effort utilises a unique database to examine the phenomena only in the science arena. The results are that exploration efforts lead to science outcomes, and that both exploration and exploitation efforts have a positive impact on technological outcomes. The managerial implications of these findings are discussed.
... The primary independent or predictor variable is the number of scientific publications a firm has per year. These data were obtained using the NBER-Rensselaer Scientific Papers Database, which contains the scientific publications of the top 110 U.S. universities and the top 200 U.S. R&D-performing firms for the years 1981 to 1999 [46]. These data were extracted from the Institute for Scientific Information (ISI) databases including the Web of Science. ...
Open innovation has been examined a great deal in the last few years in the technology management and innovation literature, but its critical aspect – scientific openness – has been debated for centuries. The purpose of this paper is to elucidate the arguments for and against scientific openness. Using concepts from game theory, we develop the Scientific Openness Decision Model linking the strategic decision for openness/secrecy and the resultant business environment. We then empirically test that model using data from 118 companies across 54 industries. Openness, measured by scientific publications, is found to be a strong predictor of both positive technological and scientific outcomes for firms. These findings are examined to determine the relative merits of a strategy of scientific openness versus secrecy, and future research possibilities are discussed.
... To conduct our analysis, we use a previously under-explored data on university research spending and knowledge production covering the 96 leading research universities from 1981 to 1996. We use newly available data on the basic knowledge production of leading research universities compiled by Adams and Clemmons (2008) together with university spending, income, and endowment data from the Higher Education General Information Survey (HEGIS) and Integrated Post-Secondary Education Data System (IPEDS) collected by the US Department of Education. ...
Every year billions of dollars are spent on research grants to produce new knowledge in universities. However, as grants may also affect other research funding, the effects of financial resources on knowledge production remain unclear. To uncover how financial resources affect knowledge production, we study the effects of research spending itself. Utilizing the legal constraints on university spending from an endowment we develop an instrumental variables approach. Our approach instruments for university research spending with time-series variation in stock prices interacted with cross-sectional variation in initial endowment market values for research universities in the United States. Our analysis reveals that research spending has a substantial positive effect on the number of papers produced, but not their impact. We also demonstrate that research spending effects are quite similar at private and public universities. (JEL H5, I2, O3)
... Empirical validation of such network e¤ects is di¢ cult, but must be explored as sources of data become less scarce. The recently released NBER-Rennsellear scienti…c papers dataset ( Adams and Clemmons, 2008) contains a wealth of information on research partnerships, thus it opens up promising areas for research on these topics. As an informal support for the importance of such mechanisms, anyone who has a Ph.D. would testify that learning from the papers of an academician, and learning directly from the academician can often be two very di¤erent things. ...
This paper studies the relationship between a firm's market value and the mobility of scientific and technical personnel in its sectoral and geographic proximity. I uncover distinct positive and negative effects of mobility on market value that operate through various channels. I document a positive effect of scientific labor mobility on market value through knowledge assets embedded within technologically similar firms: firms having large stocks of external knowledge in their disposal benefit from increased mobility of scientific and technical personnel. On the other hand, firms that lack large external stocks of knowledge suffer a negative effect. The detrimental effect of mobility is larger for firms in more competitive industries, supporting the hypothesis that estimates capture the losses due to outbound knowledge and human capital. However, such losses are not significantly different for firms with different levels of R&D intensity. The positive and negative effects of scientific labor mobility, on average, are of similar magnitudes, making the average firm "break even" in terms of its net impact. These results are consistent with previous findings, and provide further insight into why innovative firms cluster in industrial districts.
This study highlights the effects of industry collaboration in enhancing academic innovation output. We exploit a unique longitudinal dataset on the 110 top U.S. research universities for the last 19 years. Our empirical findings confirm that the relationship between the number of industry collaborations and academic innovation is curvilinear. Moreover, we hypothesized and found that university contribution, collaboration breadth and knowledge capacity moderate the curvilinear relationship between the number of industry collaborations and academic innovation. Poisson, negative binomial and generalized negative binomial regressions are used to test the hypotheses in a panel data of 2090 university-year cases. Our results are robust to the three econometric methods, measures of variety of academic innovation and the findings support our prediction.
We study the contribution of doctoral students to innovation at 2,300 American science and engineering departments from 1973 to 1998. Macroeconomic and policy shocks in source countries that differentially affect enrollments across fields and universities isolate exogenous variation in the supply of students. Both US and international students contribute significantly to the production of knowledge at scientific laboratories, and their contributions are statistically comparable, consistent with an optimizing department. A theoretical model of scholarships helps us to infer the productivity effects of student quality. Visa restrictions limiting entry of high‐quality students are found to be particularly costly for academic innovation.
The tension between scientific openness versus secrecy has existed for centuries (Hull 1985). However, both academics and practitioners have recently argued that openness by private firms has many positive attributes. The purpose of this research effort is to review the extant literature on openness and to develop hypotheses regarding its impact on organizational outcomes. We then use a unique database to test the idea with 87 companies. Our findings are that openness is beneficial to the firm from a science, technological, and financial perspective and, perhaps, to the employees from an ethical viewpoint. The managerial and societal implications are also discussed.
Prior research shows long-run productivity growth in agriculture is associated with increases in the stock of public scientific knowledge and private patented inventions. However, private inventions may be a function of the stock of public knowledge. In this paper, we examine the possibility that public knowledge contributes to productivity through its relationship with private sector invention. Our analysis identifies connections between the stock of public knowledge and private firm R&D and examines whether the degree of “connectedness” to public science is associated with greater firm-level research productivity in agriculture. Bibliographic information identifies the nature and degree to which firms use public agricultural science through citations and collaborations on scientific papers. Fixed effects models show that greater citations and collaborations with university researchers are associated with greater private agricultural research productivity.
The make-or-buy decision is analyzed in a simple two-task principal-agent model. There is a cost-saving/quality tradeoff in effort provision. The principal faces a dichotomous choice between weak ("make") and strong ("buy") cost-saving incentives for the agent; the dichotomy is due to an incomplete-contracting limitation necessitating that one party be residual claimant. Choosing "buy" rather than "make" leads to higher cost-saving effort and -- in a plausible "main case" -- to lower quality effort; this in spite of stronger direct quality-provision incentives in the former case.
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