Narrow Results

Over the past four decades, the high-performing Asian economies (HPAE) have followed a development strategy based on the exposure of their local markets to the presence of foreign competition and on outward-oriented production. In contrast, Latin American (LATAM) economies began taking steps in this direction only in the late 1980s and early 1990s, but before this period they were more focused on the implementation of import substitution policies. These divergent paths have led to sharply different growth performances in the two regions. Yet, standard trade openness indicators fall short of portraying the peculiarity of the Asian experience, and of explaining why other emerging markets with similar characteristics have been less successful over the last 25 years. We offer an alternative perspective on this issue by exploiting recently developed indicators based on weighted network analysis. We study the evolution of the core–periphery structure of the World Trade Network (WTN) and, more specifically, the evolution of the HPAE and LATAM countries within this network. Using random walk betweenness centrality, we show that the HPAE countries are more integrated into the WTN and many of them, which were on the periphery in the 1980s, are now in the core of the network. In contrast, the LATAM economies have at best maintained their position over the 1980–2005 period, and in some cases have fallen in the ranking of centrality.

In this work, we analyze gossip spreading on weighted networks. We try to define a new metric to classify weighted complex networks using our model. The model proposed here is based on the gossip spreading model introduced by Lind et al. on unweighted networks. The new metric is based on gossip spreading activity in the network, which is correlated with both topology and relative edge weights in the network. The model gives more insight about the weight distribution and correlation of topology with edge weights in a network. It also measures how suitable a weighted network is for gossip spreading. We analyze gossip spreading on real weighted networks of human interactions. Six co-occurrence and seven social pattern networks are investigated. Gossip propagation is found to be a good parameter to distinguish co-occurrence and social pattern networks. As a comparison some miscellaneous networks of comparable sizes and computer generated networks based on ER, BA and WS models are also investigated. They are found to be quite different from the human interaction networks.