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Category Archives: R11

Deciphering Chinese Financing To African Countries

By Gwen Geng

The paper considers what attracts Chinese aid and Chinese investment to African countries and what kinds of Chinese financing projects are more likely to have unrevealed financing amount. The main database used is AidData: China’s Official Finance to Africa 2000-2012. It contains 2356 Chinese financing projects to 50 African countries. The results suggest that Chinese aid supports less developed economies, while Chinese investment favors countries with resource abundance and political conditions conducive to profit-making. The findings show that projects with unrevealed funding amounts tend to fall under investment and the government sector among other categories, raising questions on financing secrecy.

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Advisors: Robert Garlick and Michelle Connolly | JEL Codes: F13, F54, N47, N57, O24, R11, R15

Entrepreneurial Attractiveness: Amazon, Google, and the Search for Innovative Hot Spots

By Anna Katherine Kropf

Recent economic literature suggests that entrepreneurship in technological fields can spur economic growth, making it a popular topic for city development officials. Yet, this increasingly popular phenomenon is met by many economic questions. One of those questions is which characteristics of metropolitan areas are attractive to entrepreneurs. To answer the question of attractiveness on both the small business and corporate levels, I compare across two case studies: Amazon’s search for a second headquarters and Google’s tech hub network. Using principal component analysis, I statistically deduce seven components of attractiveness from an original 34 variables. These components are then weighted using three methods—a case study, a survey, and an empirical method—to produce comparable indices of attractiveness. Generally, I find that sizeable population and healthy economy are the strongest components. However, the statistically insignificant components that can change an urban area’s ranking considerably are talent and geographic network effects. Ultimately, creating policy to maximize these aspects can change a city’s innovative
trajectory.

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Advisor: Dr. Charles Becker | JEL Codes: O, O3, R, R1, R11

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