The Research Space: using the career paths of scholars to predict the evolution of the research output of individuals, institutions, and nations

In recent years scholars have built maps of science by connecting the academic fields that cite each other, are cited together, or that cite a similar literature. But since scholars cannot always publish in the fields they cite, or that cite them, these science maps are only rough proxies for the potential of a scholar, organization, or country, to enter a new academic field. Here we use a large dataset of scholarly publications disambiguated at the individual level to create a map of science-or research space-where links connect pairs of fields based on the probability that an individual has published in both of them. We find that the research space is a significantly more accurate predictor of the fields that individuals and organizations will enter in the future than citation based science maps. At the country level, however, the research space and citations based science maps are equally accurate. These findings show that data on career trajectories-the set of fields that individuals have previously published in-provide more accurate predictors of future research output for more focalized units-such as individuals or organizations-than citation based science maps

Platform for democratizing access to government budget and expenditure data

Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 76-77).Budgeting and expenditure data is the clearest expression of a government's priorities. Despite its importance, making it available to the public imposes hard challenges that not every administration is ready to undertake. The lack of IT capabilities and constrained resources of government agencies -regardless of size or budget- make it difficult for them to respond to the demands of information from their constituencies, transparency advocates, the press and central governments. Moreover, these administrations don't usually have access to analysis tools that help them view how the resources are being used and to detect potential risks of misspending -a critical need of elected officials, who are under everyday scrutiny. Responding to these needs, I propose the design, implementation, impact and usability studies of a software platform for analysis and visualization of government budget and expenditure data.by Manuel Aristarán.S.M

Linking Economic Complexity, Institutions, and Income Inequality

A country's mix of products predicts its subsequent pattern of diversification and economic growth. But does this product mix also predict income inequality? Here we combine methods from econometrics, network science, and economic complexity to show that countries exporting complex products-as measured by the Economic Complexity Index-have lower levels of income inequality than countries exporting simpler products. Using multivariate regression analysis, we show that economic complexity is a significant and negative predictor of income inequality and that this relationship is robust to controlling for aggregate measures of income, institutions, export concentration, and human capital. Moreover, we introduce a measure that associates a product to a level of income inequality equal to the average GINI of the countries exporting that product (weighted by the share the product represents in that country's export basket). We use this measure together with the network of related products-or product space-to illustrate how the development of new products is associated with changes in income inequality. These findings show that economic complexity captures information about an economy's level of development that is relevant to the ways an economy generates and distributes its income. Moreover, these findings suggest that a country's productive structure may limit its range of income inequality. Finally, we make our results available through an online resource that allows for its users to visualize the structural transformation of over 150 countries and their associated changes in income inequality during 1963-2008. (C) 2017 Elsevier Ltd. All rights reserved