Giorgio Fagiolo

Clustering in complex directed networks

Many empirical networks display an inherent tendency to cluster, i.e., to form circles of connected nodes. This feature is typically measured by the clustering coefficient (CC). The CC, originally introduced for binary, undirected graphs, has been recently generalized to weighted, undirected networks. Here we extend the CC to the case of (binary and weighted) directed networks and we compute its expected value for random graphs. We distinguish between CCs that count all directed triangles in the graph (independently of the direction of their edges) and CCs that only consider particular types of directed triangles (e.g., cycles). The main concepts are illustrated by employing empirical data on world-trade flows.

On the topological properties of the world trade web: A weighted network analysis

This paper studies the topological properties of the World Trade Web (WTW) and its evolution over time by employing a weighted-network analysis. We show that the WTW, viewed as a weighted network, displays statistical features that are very different from those obtained by using a traditional binary-network approach. In particular, we find that: (i) the majority of existing links are associated to weak trade relationships; (ii) the weighted WTW is only weakly disassortative; (iii) countries holding more intense trade relationships are more clustered.

Exploitation, exploration and innovation in a model of endogenous growth with locally interacting agents

The paper presents a model of endogenous growth in which firms are modeled as boundedly-rational, locally interacting, agents. Firms produce a homogeneous good employing technologies located in an open-ended technological space and are allowed to either imitate existing, similar practices or to locally explore the technological space to find new, more productive techniques. We first identify sufficient conditions for the emergence of empirically plausible GNP time-series characterized by self-sustained growth. Then, we study the trade-off between individual rationality and collective outcomes by providing an example in which more rational agents systematically perform worse than less rational ones.

International trade and financial integration: a weighted network analysis

The authors analyse patterns of international trade and financial integration using complex network analysis. The combination of both binary and weighted approaches delivers more precise and thorough insights into the topological structure and properties of international trade and financial networks (ITN and IFN). It is found that the ITN is more densely connected than the IFN, while both types of network display a core–periphery structure. This hierarchical organization is more pronounced in financial markets, suggesting that the bulk of trade in financial assets occurs through a handful of countries acting as hubs. High-income countries are better linked and form groups of tightly interconnected nodes. This kind of structure can explain why the recent financial crisis has spread rapidly among advanced countries while reaching emerging markets only in a second phase.

MATCHING, BARGAINING, AND WAGE SETTING IN AN EVOLUTIONARY MODEL OF LABOR MARKET AND OUTPUT DYNAMICS

In this paper, we present an agent-based, evolutionary, model of output- and labor-market dynamics. Firms produce a homogeneous, perishable good under constant returns to scale using labor only. Labor productivities are firm-specific and change stochastically due to technical progress. The key feature of the model resides in an explicit microfoundation of the processes of : (i) matching between firms and workers, (ii) job search, (iii) wage setting, (iv) endogenous formation of aggregate demand, and (v) endogenous price formation. Moreover, we allow for a competitive process entailing selection of firms on the basis of their revealed competitiveness. Simulations show that the model is able to robustly reproduce Beveridge, Wage and Okun curves under quite broad behavioral and institutional settings. The system generates endogenously an Okun coefficient greater than one even if individual firms employ production functions exhibiting constant returns to labor. Monte Carlo simulations also indicate that statistically detectable shifts in Okun and Beveridge curves emerge as the result of changes in institutional, behavioral, and technological parameters. Finally, the model generates sharp predictions about how system parameters affect aggregate performance (i.e. average GDP growth) and its volatility.

Identifying the community structure of the international-trade multi-network

We study the community structure of the multi-network of commodity-specific trade relations among world countries over the 1992–2003 period. We compare structures across commodities and time by means of the normalized mutual information index (NMI). We also compare them with exogenous community structures induced by geography and regional trade agreements. We find that commodity-specific community structures are very heterogeneous and much more fragmented than that characterizing the aggregate ITN. This shows that the aggregate properties of the ITN may result (and be very different) from the aggregation of very diverse commodity-specific layers of the multi-network. We also show that commodity-specific community structures, especially those related to the chemical sector, are becoming more and more similar to the aggregate one. Finally, our findings suggest that geography-induced partitions of our set of countries are much more correlated with observed community structures than partitions induced by regional-trade agreements. This result strengthens previous findings from the empirical literature on trade.

Agent-Based Modelling: A Methodology for Neo-Schumpeterian Economics

Modellers have had to wrestle with an unavoidable trade-off between the demand of a general theoretical approach and the descriptive accuracy required to model a particular phenomenon. A new class of simulation models has shown to be well adapted to this challenge, basically by shifting outwards this trade-off: So-called agent-based models (ABMs henceforth) are increasingly used for the modelling of socio-economic developments. Our paper deals with the new requirements for modelling entailed by the necessity to focus on qualitative developments, pattern formation, etc. which is generally highlighted within Neo-Schumpeterian Economics and the possibilities given by ABMs.

Macroeconomic Policy in DSGE and Agent-Based Models

The Great Recession seems to be a natural experiment for macroeconomics showing the inadequacy of the predominant theoretical framework—the New Neoclassical Synthesis—grounded on the DSGE model. In this paper, we present a critical discussion of the theoretical, empirical and political-economy pitfalls of the DSGE-based approach to policy analysis. We suggest that a more fruitful research avenue to pursue is to explore alternative theoretical paradigms, which can escape the strong theoretical requirements of neoclassical models (e.g., equilibrium, rationality, representative agent, etc.). We briefly introduce one of the most successful alternative research projects—known in the literature as agent-based computational economics (ACE)—and we present the way it has been applied to policy analysis issues. We then provide a survey of agent-based models addressing macroeconomic policy issues. Finally, we conclude by discussing the methodological status of ACE, as well as the (many) problems it raises.

Randomizing world trade. I. A binary network analysis.

The international trade network (ITN) has received renewed multidisciplinary interest due to recent advances in network theory. However, it is still unclear whether a network approach conveys additional, nontrivial information with respect to traditional international-economics analyses that describe world trade only in terms of local (first-order) properties. In this and in a companion paper, we employ a recently proposed randomization method to assess in detail the role that local properties have in shaping higher-order patterns of the ITN in all its possible representations (binary or weighted, directed or undirected, aggregated or disaggregated by commodity) and across several years. Here we show that, remarkably, the properties of all binary projections of the network can be completely traced back to the degree sequence, which is therefore maximally informative. Our results imply that explaining the observed degree sequence of the ITN, which has not received particular attention in economic theory, should instead become one the main focuses of models of trade.

Randomizing world trade. II. A weighted network analysis

Based on the misleading expectation that weighted network properties always offer a more complete description than purely topological ones, current economic models of the International Trade Network (ITN) generally aim at explaining local weighted properties, not local binary ones. Here we complement our analysis of the binary projections of the ITN by considering its weighted representations. We show that, unlike the binary case, all possible weighted representations of the ITN (directed and undirected, aggregated and disaggregated) cannot be traced back to local country-specific properties, which are therefore of limited informativeness. Our two papers show that traditional macroeconomic approaches systematically fail to capture the key properties of the ITN. In the binary case, they do not focus on the degree sequence and hence cannot characterize or replicate higher-order properties. In the weighted case, they generally focus on the strength sequence, but the knowledge of the latter is not enough in order to understand or reproduce indirect effects.