Abstract: In my talk, I will go into the standard model of percolation and how this model can be used to analyse innovation diffusion processes through word-of-mouth. We will do so distinguishing different network topologies (random, small-world, regular), between simple versus complex propagation, and between different preference distribution reflecting economic inequality levels. This work is based on collaborations with dr. Elena Mas Tur (Eindhoven University of Technology) and dr. Paolo Zeppini (Bath University).?

Abstract: Recent results of a new branch - Economic Complexity - set basis for a framework to interpret and explain the extreme heterogeneity of the dynamics of development of nations. The idea behind the concept of Economic Complexity is to use the output of a country to determine how fertile the economic system is. In other words, to go from the observable exported products to a synthetic estimate (fitness) of the level of endowments present in the country, that automatically takes their relationships into account. We will discuss the main results and achievements of Economic Complexity. As an example of them, the metrics for country intangibles allows for quantifying the hidden growth potential of countries by comparing it with money-based figures such as the GDP per capita. The analysis of the economic evolution in the plane defined by fitness and GDP per capita pinpoints strongly heterogeneous patterns of evolution and allows to cast economic forecast into the framework of forecasting the evolution of a dynamical system as in the case of weather dynamics. We also observe a strong heterogeneity in the predictability of the economic dynamics. In such a framework, the usual tool used in Economics (i.e regressions) is no more the appropriate one to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are needed. We will also discuss how it is possible to track and define trajectories of growth and development at single product level by defining a suitable network, named Product Progression, linking products on a technological hierarchical basis.?

Abstract: Economic theory has developed in such a way as to be consistent with the socio-political liberalism which became dominant after the Enlightement. The doctrine of "laissez faire", and the argument that leaving people insofar as possible to their own devices would lead to a socially desirable state was based on the conviction that an Invisible Hand would lead society to such a state. As economic theory developed it was never able to give a formal justification for this assertion. It was claimed that this would happen but the discipline was confined to study the welfare properties of equilibrium states without explaining how they were attained. Thus crises were said to be generated by exogenous shocks and did not come from within the system. Changing our two hundred year old paradigm to thinking of the economy as a complex adaptive system allows us to consider economies out of equilibrium and the fact that they may self organise into states which are far from optimal. Such systems with their feedbacks are unpredictable and policy measures can generate unexpected consequences. Accepting this may lead to more realistic and more modest economic theory

Abstract: This paper examines whether propagation of idiosyncratic, firm-level shocks through input-output linkages can lead to sizable fluctuations at the aggregate level. Using a large-scale dataset on supply chain linkages among Japanese firms together with information on firm-level exposures to a large, but localized, natural-disaster?the Great East Japan Earthquake in 2011?we quantify the earthquake?s impact on firms that were (directly or indirectly) linked to affected firms. We find that having a supplier in the earthquake-hit region led to a 3% loss in terms of sales growth compared to firms with no such suppliers. We also find evidence for smaller but nevertheless significant upstream propagation from affected firms to their suppliers. Furthermore, we show that these losses do not remain confined to the disrupted firms? immediate customers and suppliers. Rather, firms that were only indirectly related to the firms in the affected areas (such as their customers? customers) were also negatively impacted. Even though our results suggest that such cascade effects decay with supply chain distance, the number of firms affected is large enough for this localized disruption to have a meaningful macroeconomic impact: the propagation of the earthquake shock over input-output linkages led to a 1% drop in Japan?s aggregate output in the year following the earthquake.

Abstract: We study how to optimally schedule production in technologies following experience curves under uncertainty to meet a known demand schedule. Experience effects encourage specialization but in an uncertain world a risk-averse decision maker may prefer to diversify. This is relevant for planning investment strategies for the transition to a sustainable energy system. We develop a stochastic model and characterize the optimal degree of diversification as a function of relative progress rates, initial conditions, time horizon, discount rate and variability. Due to feedback effects from learning, solutions depend sensitively on underlying model parameters, and we observe instantaneous switching between local optimums of the objective function. This differs sharply from portfolios of standard financial assets. Technological lock-in may be characterised in this framework. When the planning horizon is long, we find that it is optimal to specialize more in the short term than the long term, where uncertainty dominates the utility function.

Abstract: We develop a behavioral model for housing prices with heterogeneous expectations, with fundamental buying prices linked to housing rental levels to fundamental buying prices. Using quarterly data we estimate the model parameters for eight different countries, US, UK, NL, JP, CH, ES, SE and BE. We find that the data support heterogeneity in expectations, with temporary endogenous switching between fundamental mean-reverting and trend-following beliefs based on their relative performance. For all countries we identify temporary, long lasting house price bubbles, amplified by trend extrapolation, and crashes reinforced by mean-reverting expectations. The qualitative predictions of such non-linear models are very different from standard linear benchmarks, with important policy implications. The fundamental price becomes unstable, e.g. when the interest rate is set too low or mortgage tax deductions too high, giving rise to multiple non-fundamental equilibria and/or global instability. We also discuss estimation of similar non-linear switching models to other time series, such as stock? prices, commodity prices, exchange rates and inflation.

Abstract: The Netherlands has generally been a laggard in tackling the energy transition, to the extent that a judge Dutch State is acting unlawfully by not contributing its proportional share to preventing a global warming. A 2015?report (in Dutch)?co-authored with the?Netherlands Scientific Council for Government Policy (WRR) argues that a contributing cause to this state of affairs is from policy makers looking at the energy system in too much isolation. The report is a practical case study how taking a complex systems lens to the problem, may open the path to different and innovative approaches to Dutch energy transition policy.

Abstract: Network-based metrics are commonly applied in a wide range of real-world problems, such as ranking, recommendation, and information spreading. Classical methods inspired by physical processes (like diffusion) often neglect the temporal order of interactions and, as a consequence, turn out to be highly ineffective when applied to systems evolving in time which is particularly worrying as most real systems fall in this category. To devise improved and well founded metrics, it is critical to understand the nature of the shortcomings of classical methods in evolving systems. In this presentation, we focus on the problems of ranking and recommendation in growing complex networks. For both problems, we show that by understanding the temporal patterns of the studied systems and unveiling the consequent lack of performance of classical metrics, we are able to design time-dependent methods that significantly outperform their static counterparts in singling out the most valuable items in the system. In the case of ranking, we use growing network models to show that PageRank centrality metrics systematically exhibit a temporal bias towards old or recent nodes depending on the temporal scales of node aging. We introduce a rescaled score which is built on the PageRank score and at the same time it is not biased by node age. We use real and model data and show that the rescaled score allows us to identify high-quality nodes earlier than with other metrics. In the case of recommendation, we use data from Netflix, Yelp and Digg to show that classical methods tend to favor old nodes and, as a consequence, systematically fail to identify recent items that will be collected by users in the future. We design a new time-aware method built on network growth patterns and show that it markedly outperforms its static counterpart. The findings presented here support the idea that time-aware modifications of existing metrics can lead to improved results in finding the most valuable information in diverse real systems.

Abstract: In animal collective behavior, interactions between individuals and between an agent and the environment are usually seen to be ?through information?propagation. Cooperations can emerge with or without information sharing.? The information propagation in ants, fish and birds seems to be the?crucial?mechanism that regulates the global behavior of the crowd. This talk will introduce the research related to?information?functioning in collective?groups?and several recent works that demonstrate interesting collective patterns with information sharing playing pivotal roles.

Abstract: In this work we analyze the short- and long-run effects of fiscal austerity policies, employing an agent-based?model populated by heterogeneous, boundedly-rational firms and banks. The model, in line with the family of?"Keynes+Schumpeter" formalism, is able to account for a wide array of macro and micro empirical regularities.?In particular, it endogenously generates self-sustained growth patterns together with persistent economic?fluctuations punctuated by deep downturns. On the policy side, we find that austerity policies considerably?harm the economy, by increasing output volatility, unemployment, and the incidence of crises. In addition, they?depress innovation and the diffusion of new technologies, thus reducing long-run productivity and GDP growth.?Finally, we show that "discipline-guided" fiscal rules are self-defeating, as they do not stabilize public finances,?but, on the contrary, they disrupt them.

Abstract: We use citation data of scientific articles produced by individual nations in different scientific domains to build a bipartite country - scientific domains network to determine the structure and efficiency of national research systems. We characterize the scientific fitness of each nation ?that is, the competitiveness of its research system?and the complexity of each scientific domain by means of a non-linear iterative algorithm able to assess quantitatively the advantage of scientific diversification. We find that technological leading nations, beyond having the largest production of scientific papers and the largest number of citations, do not specialize in a few scientific domains. Rather, they diversify as much as possible their research system. On the other side, less developed nations are competitive only in scientific domains where also many other nations are present. Diversification thus represents the key element that correlates with scientific and technological competitiveness. A remarkable implication of this structure of the scientific competition is that the scientific domains playing the role of ?markers? of national scientific competitiveness are those not necessarily of high technological requirements, but rather addressing the most ??sophisticated?? needs of the society. We complement this analysis with a correlation study between the scientific impact of a nation with a normalized measure of RD funds and the level of internationalization.

Abstract: Systemic risk in financial markets arises largely through the interconnectedness of agents through financial contracts. We show that the systemic risk level of every agent in the system can be quantified by simple network measures. With actual central bank data for Austria and Mexico we are able to compute the expected systemic losses of the economy, a number that allows us to estimate the true cost of a financial crises. We can further show with real data that it is possible to compute the systemic risk contribution of every single financial transaction to the financial system. Based on these findings, we suggest a smart financial transaction tax that taxes the systemic risk contribution of individual transactions. This tax provides an incentive for market participants to trade financial assets in a way that effectively restructures financial networks so that contagion events become impossible.?It is possible to show the existence of a systemically risk-free equilibrium under this smart tax. More intuitively, with the help of an agent based model we can demonstrate that the Systemic Risk Tax practically eliminates the network-driven systemic risk in a system.

Abstract: We introduce a model of innovation in which products are composed of distinct components and new components are adopted one at a time. We show that the number of products we can make now gives a distorted view of the number we can make in the future: simple products get over-represented, and complex products under- represented. By applying this at the component level, we derive a strategy for making far-sighted innovation choices that increase the rate of innovation. We apply our strategy to real data from three different sectors?language, gastronomy and mobile technology.?