Davide Luzzati from the Sant’Anna School of Advanced Studies is giving a talk on Friday, May 5, 2023 at 3 PM.
If you would like to join the talk, please send an email to firstname.lastname@example.org.
Title: “Centrality in the Macroeconomic Multi-Network and Spatio-Temporal Evolution of Country Per-Capita GDP”
Empirical testing of the income-enhancing effect of technology diffusion has been traditionally carried out using aggregate measures of country openness as a proxy of the extent to which a country is exposed to foreign markets and migration flows. For example, to account for countries’ exposure to international trade, it is customary to employ a simple measure of trade openness computed as the ratio between a country’s total trade and its gross-domestic product (GDP). However, these measures are essentially local, as they only account for direct interactions with neighboring countries. Indeed, it may be the case that such openness proxies are not perfectly correlated with indicators accounting for the global embeddedness of a country in the networks of international relations, which instead fully account for the overall position of a country within the complex web of interconnections in which it is entrenched. If that is the case, standard measures of openness are not able to capture the income-enhancing effects of international technology diffusion, which may be instead better proxied if one employs tools and concepts borrowed from complex-network theory.
In this work, we present indeed a simple theoretical country-growth model predicting that, net of country-specific spatio-temporal characteristics (including traditional openness proxies), country per-capita income should positively depend on its global importance (i.e., by her Bonacich or Katz centrality) in the macroeconomic networks wherein she is embedded. Next, we take to the data the implications of the theoretical model, using data on the international networks of merchandise trade, finance, migration and ideas’ flows. We build a multi-layer network and we employ different measures of country centrality in such a network as a covariate in panel regressions explaining country per-capita income. The empirical exercises strongly support the predictions of the model, robustly across a number of alternative specifications of the empirical model and controlling for possible endogeneity issues and spatial effects.
Davide Luzzati is a PhD candidate in economics at Sant’Anna School of Advanced Studies in Pisa, Italy. After completing an MSc in statistics at the ETH Zurich, he became interested in the connections between complexity science and economics. After spending time at the École Polytechnique in France and the Weizmann Institute of Science in Israel, he is now focusing his research on how shocks propagate in firm-to-firm production networks, with a particular focus on climate change and natural disasters.