Spatial collocation and venture capital in the US biotechnology industry
AbstractBiotechnology firms operate in a high-risk and high-reward environment and are in a constant race to secure venture capital (VC) funds. Previous contributions to the literature show that the VC firms tend to invest locally in order to monitor their investments and to provide operating assistance to their target firms. Further, biotechnology is a knowledge-based industry that tends to exhibit spatial clusters, and the firms in such industries may collocate to benefit from gaining access to local markets for specialized inputs (e.g., skilled researchers) and from local knowledge spillovers and network externalities. If such gains exist, we expect that the collocated firms should exhibit positively correlated performance, including in their ability to attract venture capital funds. The purpose of this paper is to empirically measure the strength and spatial extent of the relationships among the amount of funds raised by proximate biotechnology firms. We model these relationships with a spatial autoregression (SAR) model, and we control for characteristics of the biotechnology firms and the VC firms that provide their funds as well as site-specific factors. Based on our fitted SAR model, we find that the amount of venture capital raised by a particular biotechnology firm is significantly influenced by the number of VC firms and the VC funding levels raised by biotechnology firms located within a 10-mile radius, but these relationships are not statistically significant beyond this range.
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Bibliographic InfoArticle provided by Elsevier in its journal Research Policy.
Volume (Year): 40 (2011)
Issue (Month): 9 ()
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Web page: http://www.elsevier.com/locate/respol
Venture capital; Biotechnology; Cluster scope; Knowledge spillovers; Network externalities; Dedicated biotechnology firms; Spatial externalities;
Find related papers by JEL classification:
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
- O3 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights
- R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
- L65 - Industrial Organization - - Industry Studies: Manufacturing - - - Chemicals; Rubber; Drugs; Biotechnology
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