We use daily data on bilateral interbank exposures and monthly bank balance sheets to study network characteristics of the Russian interbank market over Aug 1998 – Oct 2004. Specifically, we examine the distributions of (un)directed (un)weighted degree, nodal attributes (bank assets, capital and capital-to-assets ratio) and edge weights (loan size and counterparty exposure). We search for the theoretical distribution that fits the data best and report the “best” fit parameters. We observe that all studied distributions are heavy tailed. The fat tail typically contains 20\% of the data and can be systematically described by a truncated power law. In most cases, however, separating the bulk and tail parts of the data is hard, so we proceed to study the full range of the events. We find that the stretched exponential and the log-normal distributions fit the full range of the data best. These conclusions are robust to 1) whether we aggregate the data over a week, month, quarter or year; 2) whether we look at the “growth” versus “maturity” phases of interbank market development; and 3) with minor exceptions, whether we look at the “normal” versus “crisis” operation periods. In line with prior research, we find that the network topology changes greatly as the interbank market moves from a “normal” to a “crisis” operation period.
Debates about holism versus reductionism and ideas about chaos, synergetics and self-organized criticality have been around for decades. What prompted the revolution in network theory in recent years was the sudden and abundant availability of data. Mobile-phone records capture the communication and mobility patterns of whole countries, import-export and stock data condense economic activity into easily accessible databases. From social media to cell biology, cheap sensors and high-throughput technologies are fueling a data explosion that offers unparalleled opportunities to document the inner workings of many complex systems.
We argue that the present crisis and stalling economy continuing since 2007 have clear origins, namely in the delusionary belief in the merits of policies based on a “perpetual money machine” type of thinking. Indeed, we document strong evidence that, since the early 1980s, consumption has been increasingly funded by smaller savings, booming financial profits, wealth extracted from house price appreciation and explosive debt.
Here we show that the interactions between individual scientists trying to find a local balance between exploration and exploitation results in an aggregate pattern characterized by a succession of tradition-bound periods punctuated by non-cumulative breaks. This result is remarkably robust.