In this thesis, I propose that international trade and financial networks may shed light on the determinants of country-level economic growth. I created yearly adjacency matrices for 90 countries' trade and capital flows to generate time-series centrality measurements which serve as proxies for a country's level of embeddedness within the global economic system. I then used these centrality measurements as independent variables in cross-country growth regressions. Through this, I was able to determine how well centrality measurements predict growth patterns, as well as how centrality measurements compare to traditional growth variables. I found that there is a statistically significant relationship for both trade centrality and financial centrality in these regressions, with and without the inclusion of standard growth-variables. Furthermore, I observed that both trade and financial networks exhibit core-periphery behavior, which decreased in structural intensity in the period studied. These findings contribute to the burgeoning literature that makes use of network analysis in a macroeconomic context.