Final Report Summary - CONNECTING-EU! (Network analysis of economic development and social cohesion in Europe)
The Connecting_EU! project has applied cutting-edge methods from network analysis, econometrics and data visualization to analyze the network structure of economic development and social cohesion in Europe and around the world. We analyzed data from millions of publications and patents, as well as trade data from hundreds of countries between 1962 and 2010. Additionally, we explored within case studies the structural drivers of the innovation networks and knowledge migration between Turkey, Germany and the European Union.
Results
In our work on “Linking economic complexity, institutions and income inequality” (Hartmann, Guevara, Jara-Figueroa, Aristarán and Hidalgo, 2015; http://arxiv.org/abs/1505.07907) we show that countries exporting complex products have less income inequality than countries exporting simpler products and that increases in economic complexity are accompanied by decreases in income inequality. Multivariate regression analysis illustrates that the connection between economic complexity and income inequality is robust to controlling for measures of income, institutions, and human capital. Moreover, we introduce a measure that associates products to the average GINI level of the countries exporting these products and use this measure together with the network of related products—or product space—to illustrate how changes in a country’s productive structure translate into changes in income inequality. These findings suggest that social policies alone might lack the strength required to fully modify income inequality in absence of changes to a country’s productive structure. Thus, countries need to combine industrial and social policies for sustained income inequality.
A significant methodological outcome of the project is the R package “diverse” (https://cran.rstudio.com/web/packages/diverse/diverse.pdf; Guevara, Hartmann and Mendoza, 2016). The package allows researchers from any scientific field to analyze the evolution of a varied set of diversity and similarity measures in complex systems—like financial markets, migration patterns, science collaborations, or economic production systems in Europe and across the world. The R package “diverse” provides a toolkit for social scientists, interdisciplinary researcher and beginners in ecology to (i) import data, (ii) calculate different data transformations and normalization like revealed comparative advantages, (iii) calculate different diversity measures, and (iv) connect to other specialized R packages.
Moreover, our book on “International Innovation Networks and Knowledge Migration: The German-Turkish nexus” (Pyka, Kustepeli and Hartmann, Routledge, 2016) confronts traditional views on migration with modern theories of brain circulation and innovation networks, showing that migration leads to mutual benefits for both the home and host countries. Bringing together over 20 international contributors, our book highlights that knowledge migration and cultural diversity can strongly stimulate entrepreneurial activities, competence acquisition and economic development of countries and regions. We show that commuting entrepreneurs and international research networks can lead to economic win-win situations for all participants; however, constructive cultural diversity management is necessary to unfold the full potential of interdisciplinary and intercultural innovation networks. Our results also highlight the considerable scope for improvement of European migration policies to be better prepared for the structural changes stemming from an aging society in Europe, and an increasing international division of labor.
In our work on the “The Research Space” (Guevara, Hartmann Aristarán, Mendoza, and Hidalgo, Scientometrics, 2016), we use 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. Therefore, 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. Thus, the research space can be a useful tool for research policy makers in Europe and elsewhere to analyze the comparative advantages and diversification path of their scholars, universities and countries. For instance, preliminary analysis of the research portfolios of leading European Universities in the field of Bioeconomics, suggest comparative strengths in biological sciences and business administration, but weaknesses in the connection with informatics compared to other leading universities in agriculture, for instance in the US or Brazil.
In summary, the results of our project show that the capabilities of economic agents to diversify their knowledge, create inclusive institutions and grow their economy is strongly conditioned by the network structure of their capability portfolio and their ability to exchange knowledge within and across national, sectoral or disciplinary boundaries. Moreover, the results of the project also imply that neither austerity measures nor macroeconomic policies will be sufficient to overcome structural constraints of economic development and to create jobs and inclusive growth in Europe. Instead, especially in regions with structural economic problems, deliberate emphasis on innovation networks and economic diversification and sophistication is necessary.
Results
In our work on “Linking economic complexity, institutions and income inequality” (Hartmann, Guevara, Jara-Figueroa, Aristarán and Hidalgo, 2015; http://arxiv.org/abs/1505.07907) we show that countries exporting complex products have less income inequality than countries exporting simpler products and that increases in economic complexity are accompanied by decreases in income inequality. Multivariate regression analysis illustrates that the connection between economic complexity and income inequality is robust to controlling for measures of income, institutions, and human capital. Moreover, we introduce a measure that associates products to the average GINI level of the countries exporting these products and use this measure together with the network of related products—or product space—to illustrate how changes in a country’s productive structure translate into changes in income inequality. These findings suggest that social policies alone might lack the strength required to fully modify income inequality in absence of changes to a country’s productive structure. Thus, countries need to combine industrial and social policies for sustained income inequality.
A significant methodological outcome of the project is the R package “diverse” (https://cran.rstudio.com/web/packages/diverse/diverse.pdf; Guevara, Hartmann and Mendoza, 2016). The package allows researchers from any scientific field to analyze the evolution of a varied set of diversity and similarity measures in complex systems—like financial markets, migration patterns, science collaborations, or economic production systems in Europe and across the world. The R package “diverse” provides a toolkit for social scientists, interdisciplinary researcher and beginners in ecology to (i) import data, (ii) calculate different data transformations and normalization like revealed comparative advantages, (iii) calculate different diversity measures, and (iv) connect to other specialized R packages.
Moreover, our book on “International Innovation Networks and Knowledge Migration: The German-Turkish nexus” (Pyka, Kustepeli and Hartmann, Routledge, 2016) confronts traditional views on migration with modern theories of brain circulation and innovation networks, showing that migration leads to mutual benefits for both the home and host countries. Bringing together over 20 international contributors, our book highlights that knowledge migration and cultural diversity can strongly stimulate entrepreneurial activities, competence acquisition and economic development of countries and regions. We show that commuting entrepreneurs and international research networks can lead to economic win-win situations for all participants; however, constructive cultural diversity management is necessary to unfold the full potential of interdisciplinary and intercultural innovation networks. Our results also highlight the considerable scope for improvement of European migration policies to be better prepared for the structural changes stemming from an aging society in Europe, and an increasing international division of labor.
In our work on the “The Research Space” (Guevara, Hartmann Aristarán, Mendoza, and Hidalgo, Scientometrics, 2016), we use 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. Therefore, 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. Thus, the research space can be a useful tool for research policy makers in Europe and elsewhere to analyze the comparative advantages and diversification path of their scholars, universities and countries. For instance, preliminary analysis of the research portfolios of leading European Universities in the field of Bioeconomics, suggest comparative strengths in biological sciences and business administration, but weaknesses in the connection with informatics compared to other leading universities in agriculture, for instance in the US or Brazil.
In summary, the results of our project show that the capabilities of economic agents to diversify their knowledge, create inclusive institutions and grow their economy is strongly conditioned by the network structure of their capability portfolio and their ability to exchange knowledge within and across national, sectoral or disciplinary boundaries. Moreover, the results of the project also imply that neither austerity measures nor macroeconomic policies will be sufficient to overcome structural constraints of economic development and to create jobs and inclusive growth in Europe. Instead, especially in regions with structural economic problems, deliberate emphasis on innovation networks and economic diversification and sophistication is necessary.