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.
Advisor: David Ridley, Henry Grabowski | JEL Codes: I23, L31, O31, O32, O38 | Tagged: Innovation, Research Expenditures, Science Policy, Technology Transfer
Effects of Wages of Government Officials on Corruption in Developing Countries
By Vansh Muttreja
In a world where a majority of countries are suffering from corruption, it is important to study the causes of corruption and how it can be removed. There are many factors that affect corruption, and the one that this thesis focuses on is wages. The goal of this thesis is to understand the effects of wages of government officials on corruption levels in developing countries over time. The reason for looking particularly at developing countries is that corruption is higher and a bigger concern in such countries. The results of the analysis show that in order for developing countries to decrease corruption levels to those of the least 50 corrupt nations, there needs to be an increase of 422.51% in their government wages. The results are not suggestive for all developing countries because only a limited amount of developing countries were analyzed in this thesis. However, they do give us a glimpse into the negative relationship between corruption and wages.
Advisor: Edward Tower, Kent Kimbrough | JEL Codes: N4, O38
