The dissertation consists of two chapters on measuring firms technological profile. Patent data can be grouped into two primary generations. The first generation lead by the work of Schmookler (1966), Scherer (1982), and Griliches (1984), and the second generation led by Trajtenberg, Jaffe, and Henderson (1997) and Kogan et al. (2016). When combined, both generations data spans from nearly 1926-2010 and has made a meaningful impact on innovation research. In the first chapter, I propose a third generation of patent data. The third generation of patent data has two distinct contributions. First, it extends patent-firm ownership information beyond 2010 to 2016. The new dataset uses the established connections of previous datasets and builds on that information with additional data on firm names gathered from EDGAR. Second, it takes advantage of the information contained in the text of patents using text analysis. Using text analysis allows for greater flexibility over traditional measures. The second chapter investigates how ownership structure affects firm value. The previous literature has assumed more innovation is better, meaning the more innovation a business creates; the better off it is in the long-run. However, not all innovations are created equal. We contribute to the literature by investigating how institutional investors change future innovation, not in quantity, but diversity. Using several unique measures of technological diversification created from firm-level patent data, we show that institutional investors increase the focus on a firm’s future innovation. Our results are robust to the classification scheme. Ultimately, our results indicate institutional investors create value by encouraging firms to build on prior knowledge.
| Identifer | oai:union.ndltd.org:uno.edu/oai:scholarworks.uno.edu:td-3641 |
| Date | 18 May 2018 |
| Creators | Rayfield, Blake K |
| Publisher | ScholarWorks@UNO |
| Source Sets | University of New Orleans |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | University of New Orleans Theses and Dissertations |
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