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Category Archives: O32

What Fosters Innovation? A CrossSectional Panel Approach to Assessing the Impact of Cross Border Investment and Globalization on Patenting Across Global Economies

By Michael Dessau and Nicholas Vega

This study considers the impact of foreign direct investment (FDI) on innovation in high income, uppermiddle  income and lowermiddle income countries. Innovation matters because it is a critical factor for economic growth. In a panel setting, this study assesses the degree to which FDI functions as a vehicle for innovation as proxied by scaled local resident patent applications. This study considers research and development (R&D), domestic savings, imports and exports, and quality of governance as factors which could also impact the effectiveness of FDI on innovation. Our results suggest FDI is most effective as inward direct investment in countries outside the technological frontier possessing adequate existing domestic investment capital and R&D spending to convert foreign investment capital and technological spillover into innovation. Nonetheless, FDI was not a consistent indicator for innovation; rather, the most consistent indicators across this study were R&D and domestic savings. Differences amongst income groups are highlighted as well as their varying responses to our array of causal factors.

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Advisor: Lori Leachman | JEL Codes: A10, B22, C82, E00, E02, O10, O11, O30, O31, O32, O33, O34, O43

Federal and Industrial Funded Research Expenditures and University Technology Transfer licensing

By Trent Chiang

In this paper I relate the numbers of university licenses and options to both university research characteristics and research expenditures from federal government or industrial sources. I apply the polynomial distributed lag model for unbalanced panel data to understand the effects of research expenditures from different sources on licensing activity. We find evidence suggesting both federal and industrial funded research expenditures take 2-3 years from lab to licenses while federal expenditures have higher long-term dynamic effect. Break down licenses by different types of partners, we found that federal expenditures have highest effect with small companies and licenses generating high income. Further research is necessary to analyze the reason for such difference.

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Advisor: David Ridley, Henry Grabowski | JEL Codes: I23, L31, O31, O32, O38 | Tagged: Innovation, Research Expenditures, Science Policy, Technology Transfer

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