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Category Archives: C8

Redefining Resource Allocation in Computing Systems

By Jacob Chasan

A new kernel1 is in town. The current industry-standard for resource allocation on computers does not take the user’s preferences into account, rather programs are given access to resources based on the time that each requested to be run. Although this system can lead to solutions that minimize the time it takes for a program to receive an allocation, it often leads to an incentive misalignment between the programs and the user. This misalignment is exacerbated as the current queue based systems have no inherent mechanism to prevent a tragedy of the commons issue, whereby programs take more resources from the system than the value they provide to the user. By shifting to a market-based approach, where computing resources are allocated to programs based on how much utility the user receives from each program, the incentives of the programs and the users align. With inherent market mechanisms to keep the incentives aligned, this new paradigm leads to at least superior levels of utility for a user.

1As described in subsequent parts of this paper, the kernel is the core program within an operating system which is given the authority to allocate the hardware resources amongst the programs on the computer.

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Advisors: Professor Benjamin C. Lee, Professor Atila Abdulkadiroglu, Professor Michelle Connolly | JEL Codes: C8, C80

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

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