Stability of the World Trade Web over time – An extinction analysis

The World Trade Web (WTW) is a weighted network whose nodes correspond to countries while edge weights reflecting the value of imports and/or exports between countries. In this paper we introduce to this macroeconomic system the notion of extinction analysis, a technique often used in the analysis of ecosystems, for the purpose of investigating the robustness of this network. In particular, we subject the WTW to a principled set of in silico “knockout experiments,” akin to those carried out in the investigation of food webs, but suitably adapted to this macroeconomic network. Informed by results in network theory as well as studies of contagion in economic networks, we seek to understand the role of connectance in the robustness of the system. We interpret increasing connectance as one aspect of a move towards globalization and liberalized trade policy. Broadly, our experiments confirm two conjectures. First, that the WTWs are “robust yet fragile” networks — robust to random failures but fragile under targeted attack. Second, that growing connectance has both positive and negative impacts on robustness. More specifically, we find that increasing connectance corresponds to increasing robustness for small shocks but to decreasing robustness in the face of large, cascading shocks up to the system. This yields evidence in support of the view that globalization, as witnessed by increasing connectance, increases the ability of a system to absorb shock up until a certain size, whereupon the shock overwhelms the system and sparks a broader contagion. We anticipate that experiments and measures like these can play an important role in the evaluation of the stability of economic systems.     

Modeling the International-Trade Network: a gravity approach

We investigate whether the gravity model (GM) can explain the statistical properties of the International Trade Network (ITN). We fit data on trade flows with a GM using alternative estimation techniques and we build GM-based predictions for the weighted topological properties of the ITN, which are then compared to the observed ones. Our exercises show that the GM: (i) may replicate part of the weighted-network structure only if the observed binary architecture is kept fixed; (ii) is not able to explain higher-order statistics that, like clustering, require the knowledge of triadic link-weight topological patterns, even if the binary structure perfectly replicates the observed one; (iii) performs very badly when asked to predict the presence of a link, or the level of the trade flow it carries, whenever the binary structure must be simultaneously estimated.     

Global networks of trade and bits

Considerable efforts have been made in recent years to produce detailed topologies of the Internet, but so far these data have been overlooked by economists. In this paper, we suggest that such information could be used to characterize both the size of the digital economy and outsourcing at country level. We analyse the topological structure of the network of trade in digital services (trade in bits) and compare it with the more traditional flow of manufactured goods across countries. To perform meaningful comparisons across networks with different characteristics, we define a stochastic benchmark for the number of connections among each country-pair, based on hypergeometric distribution. Original data are filtered so that we only focus on the strongest, i.e. statistically significant, links. We find that trade in bits displays a sparser and less hierarchical network structure, which is more similar to trade in high-skill manufactured goods than total trade. Moreover, distance plays a more prominent role in shaping the network of international trade in physical goods than trade in digital services.     

A dynamic analysis of collusive networks

This paper investigates the strategic formation of collusive networks in a dynamic framework. A collusive network is a set of market sharing agreements between firms in oligopolistic markets and auctions. Belleflamme and Bloch (Int Econ Rev 45(2):387–411, 2004) fully characterize the pairwise stable collusive networks in their symmetric model. In contrast, we characterize the collusive networks to which a dynamic network formation process converges with positive probability in the symmetric model. We provide a complete characterization for the case of the process that starts from a network with sufficiently few links. Moreover, we show that the process never cycles but always converges to a stable network. In addition, we discuss an asymmetric model where firms enjoy a home country advantage. We show that the expected number of collusive agreements may be reduced by an increase in the degree of the home country advantage. This implies that policies for discouraging entry may fail, and may lead to a decrease in expected social surplus.     

Social capital and cultural adjustment of international assignees in NGOs: do support networks really matter?

International assignees face cultural adjustment challenges in their host countries in work and nonwork situations. At the same time, social capital theory suggests that individuals can access and mobilize resources from their social networks. We explore the use of social networks by international assignees from a non-governmental organization in their cross-cultural adjustment to the host country. Specifically, we are interested in the individuals who directly provided support to the expatriate, a network that we term the ‘current assignment support network’. We focus on the size, type and frequency of contact of the international assignee's support network, and investigate to what extent these variables can predict overall cultural adjustment to the host country, or separate dimensions of cultural adjustment such as interaction adjustment, general adjustment and work adjustment. Our findings indicate that certain characteristics of the international assignee's current assignment support network do impact their cultural adjustment to the host country, but that the effects are moderated by whether the assignee has prior international experience.     

From network ties to network structures: Exponential Random Graph Models of interorganizational relations

Theoretical accounts of network ties between organizations emphasize the interdependence of individual intentions, opportunities, and actions embedded in local configurations of network ties. These accounts are at odds with empirical models based on assumptions of independence between network ties. As a result, the relation between models for network ties and the observed network structure of interorganizational fields is problematic. Using original fieldwork and data that we have collected on collaborative network ties within a regional community of hospital organizations we estimate newly developed specifications of Exponential Random Graph Models (ERGM) that help to narrow the gap between theories and empirical models of interorganizational networks. After controlling for the main factors known to affect partner selection decisions, full models in which local dependencies between network ties are appropriately specified outperform restricted models in which such dependencies are left unspecified and only controlled for statistically. We use computational methods to show that networks based on empirical estimates produced by models accounting for local network dependencies reproduce with accuracy salient features of the global network structure that was actually observed. We show that models based on assumptions of independence between network ties do not. The results of the study suggest that mechanisms behind the formation of network ties between organizations are local, but their specification and identification depends on an accurate characterization of network structure. We discuss the implications of this view for current research on interorganizational networks, communities, and fields.     

Patterns of dominant flows in the world trade web

The large-scale organization of the world economies is exhibiting increasing levels of local heterogeneity and global interdependency. Understanding the relation between local and global features calls for analytical tools able to uncover the global emerging organization of the international trade network. Here we analyze the world network of bilateral trade imbalances and characterize its overall flux organization, unraveling local and global high-flux pathways that define the backbone of the trade system. We develop a general procedure capable to progressively filter out in a consistent and quantitative way the dominant trade channels. This procedure is completely general and can be applied to any weighted network to detect the underlying structure of transport flows. The trade fluxes properties of the world trade web determine a ranking of trade partnerships that highlights global interdependencies, providing information not accessible by simple local analysis. The present work provides new quantitative tools for a dynamical approach to the propagation of economic crises.     

Tempus volat,hora fugit: A survey of tie-oriented dynamic network models in discrete and continuous time

Given the growing number of available tools for modeling dynamic networks, the choice of a suitable model becomes central. The goal of this survey is to provide an overview of tie-oriented dynamic network models. The survey is focused on introducing binary network models with their corresponding assumptions, advantages, and shortfalls. The models are divided according to generating processes, operating in discrete and continuous time. First, we introduce the temporal exponential random graph model (TERGM) and the separable TERGM (STERGM), both being time-discrete models. These models are then contrasted with continuous process models, focusing on the relational event model (REM). We additionally show how the REM can handle time-clustered observations, that is, continuous-time data observed at discrete time points. Besides the discussion of theoretical properties and fitting procedures, we specifically focus on the application of the models on two networks that represent international arms transfers and email exchange, respectively. The data allow to demonstrate the applicability and interpretation of the network models.     

What Does Trade Openness Measure?

An empirical measure of trade openness is defined as the ratio of total trade to GDP, and represents a convenient variable routinely used for cross‐country studies on a variety of issues. However, the effects that the crude measure captures remain ambiguous, making it difficult to interpret the empirical results. Drawing on several strands of the literature, this study examines the informational content of the trade openness measure using intranational and international data. We find that, even for fully integrated economies within a country, trade openness is approximately half as variable as it is for segmented diverse countries around the world. The information it conveys is better characterized as the extent of the economic remoteness and idiosyncratic distribution of sectoral production. The cross‐country variation of trade openness derives more from the variability in GDP than trade.     

Migrant Networks and the Spread of Information

Diaspora networks provide information to future migrants, which affects their success in the host country. While the existing literature explains the effect of networks on the outcomes of migrants through the size of the migrant community, we show that the quality of the network is an equally important determinant. We argue that networks that are more integrated in the society of the host country can provide more accurate information to future migrants about job prospects. In a decision model with imperfect signalling, we show that migrants with access to a better network are more likely to make the right decision, that is, they migrate only if they gain. We test these predictions empirically using data on recent Mexican migrants to the United States. To instrument for the quality of networks, we exploit the settlement of immigrants who came during the Bracero program in the 1950s. The results are consistent with the model predictions, providing evidence that connections to a better integrated network lead to better outcomes after migration.     

Religion and International Trade: Does the Sharing of a Religious Culture Facilitate the Formation of Trade Networks?

A bstract .   Despite interest in the influence of religion on economic activity by early economists like Adam Smith, modern economists have done little research on the subject. In light of the apparent religious fervor in many parts of the global economy, economists' seeming lack of interest in studying how religious cultures enhance or retard the globalization of economic activity is especially surprising. This article makes a contribution toward filling this void by examining how religion affects international trade. Specifically, we examine whether the sharing of religious cultures enables the formation of exchange networks that can overcome the failure or nonexistence of other social and economic institutions necessary for completing complex international transactions. We apply an expanded gravity model of international trade to control for a variety of factors that determine trade, and we use two recently developed regression methods, scaled OLS and nonlinear least squares, to exploit the model to its fullest. We find that the sharing of Buddhist, Confucian, Hindu, Eastern Orthodox Catholic, and Protestant cultures by people in different countries has a significantly positive influence on bilateral trade, all other things equal. The sharing of Roman Catholic culture has a significantly negative influence on bilateral trade, and the sharing of Islamic and Judaic cultures neither promotes nor discourages international exchange. These results suggest that some religious cultures are more conducive than others for forming international trade networks.     

The motifs of risk transmission in multivariate time series: Application to commodity prices

In this article we propose to exploit topological information embedded in forecast error variance decomposition derived from large Bayesian vector autoregressive models (VAR) to study network connectedness and risk transmission of multivariate time series observations. Firstly, we design a robust link classification procedure based on shortest paths, so to identify salient directional spillovers in a high-dimensional framework. Secondly, we study recurrent and statistically significant sub-graphs, i.e. network motifs, on the induced network backbone by means of null models which account for local node heterogeneity. The methodology is applied to analyze spillover networks of a set of global commodity prices. We demonstrate that spillovers become key drivers of the system variance during commodity price bubbles and bursts, giving raise to complex triadic structures which do not manifest during normal business periods. By accounting for local node connectivity, we observe a departure from the null models due to the high participation of Crude Oil, Food and Beverages and Raw Materials in complex recurrent sub-graphs.     

Integration, agglomeration and welfare

This paper studies the social desirability of agglomeration, and the efficiency arguments for policy intervention in a simple, analytically tractable new economic geography model. The location pattern emerging as market equilibrium is ‘bubble-shaped’, i.e. it features dispersion both at high and low trade costs and stable equilibria with partial and full agglomeration for intermediate levels of trade costs. We show that the market equilibrium is characterized by over-agglomeration for high trade costs and under-agglomeration for low trade costs, and we work out analytically that a net pecuniary externality is the underlying cause of this market failure. One particularly noteworthy result is that the net pecuniary externality is positive at high levels of trade freeness. However, there is no market under-agglomeration unless this positive net pecuniary externality interacts with an additional congestion force originating in the (per se efficient) competitive housing market.     

Trade networks and economic fluctuations in Asian countries

The paper presents a new methodology, based on tensor decomposition, to map dynamic trade networks and to assess its strength in forecasting economic fluctuations at different periods of time in Asia. Using the monthly merchandise import and export data across 33 Asian economies, together with the US, EU and UK, we detect the community structure of the evolving network and we identify clusters and central nodes inside each of them. Our findings show that data are well represented by two communities, in which People's Republic of China and Japan play the major role. We then analyze the synchronisation between GDP growth and trade. Furthermore we apply our model to the prediction of economic fluctuations. Our findings show that the model leads to an increase in predictive accuracy, as higher order interactions between countries are taken into account.     

Discrete Dynamics for the Core-periphery Model

Abstract

It is known that the discretisation of continuous-time models can introduce chaotic behaviour, even when this is not consistent with observations or even the model's assumptions. We propose generic dynamics describing discrete-time core-periphery models that comply with the established assumptions in the literature and are consistent with observed behaviour. The desired properties of the dynamics are proved analytically in the general case. We also give particular forms for the dynamics for those interested in applying our model.     

From Trade Among Nations to Trade Within Firms Across National Borders

SUMMARY

Based on international economics, evolutionary economics, and organizational theories, this paper discusses the evolution of the multinational corporation's intra-organizational cross-border trade and production network. The paper suggests that firms are social and economic entities, whose intra-organizational, cross-border trade and production networks coevolve with their multilocal competitive environments. Since organizational evolution, technological innovation, and organizational learning are path-dependent, a firm-specific inertia makes it to differentiate itself from its competitors in both its intra-organizational network and market outcome. The growing trends in intra-firm transactions and intra-firm division of labor on global basis present a challenge to national governments. This paper discusses intra-firm cross-border trade versus arm's-length international trade and the implications for national-based policies.     

Is China uniform? Intra-country differences in the takeoff of new products

Multi-national corporations (wrongly) introduce new products in China rather late. Such a strategy arises because research treats all of China as one monolithic country, thus, finding that takeoff occurs quite late. However, for large or multi-ethnic countries, intra country diversity may be quite high, rivaling or exceeding that among inter country differences of some continents (e.g., Europe). This study examines the takeoff of new products among provinces of China based on data of 30 Chinese provinces on 10 categories over 34 years. Rooted in the theory of institutions and product network externalities, this study tests the drivers of new product takeoff using a discrete time hazard model. The major results are as follows: First, time to takeoff varies dramatically across provinces in China. Second, the average time to takeoff varies substantially between products with strong and weak network externalities. Third, time to takeoff is converging across provinces. Fourth, the intra-country differences in time-to-takeoff are explained by economic institutional variables: economic wealth, trade openness, education, media and transportation infrastructure; and product characteristics: network externalities and year of introduction. Fifth, the vast differences in takeoff of new products across provinces suggest that a waterfall strategy within China might be more profitable.     

Network effects,trade, and productivity

We consider network effects in the monopolistically competitive model of trade developed by Melitz and Ottaviano (2008). We show that a larger network effect intensifies competition by allowing more‐productive firms to raise prices and earn higher profits, but forcing less‐productive firms to reduce prices and earn lower profits. As a result, low‐productivity firms are driven out of the market. We also show that when network effects are asymmetric, it may be difficult for firms from a country with a small network effect to compete with firms from a country with a large network effect.     

Analysis of technological innovation based on citation information

The paper discusses the dynamic properties of the patent network. Technological innovation occurs frequently, and predicting where it will happen is difficult because an economic system can adapt to changing technology. We construct a patent network based on the cited relations between patents and analyze the properties of the patent network from January 1976 to December 2005 by using USPTO patent data. We find that technology trends, which are calculated by our measures, are similar with historical trends of technology, showing that our measures would be useful to predict future technology relations. Also, we find that the change of similarity between patents shows meaningful results in terms of technological innovation.     

Probabilistic forecasting of output growth,inflation and the balance of trade in a GVAR framework

We apply a global vector autoregressive (GVAR) model to the analysis of inflation, output growth and global imbalances among a group of 33 countries (26 regions). We account for structural instability by use of country‐specific intercept shifts, the timings of which are identified taking into account both statistical evidence and our knowledge of historic economic conditions and events. Using this model, we compute both central forecasts and scenario‐based probabilistic forecasts for a range of events of interest, including the sign and trajectory of the balance of trade, the achievement of a short‐term inflation target, and the incidence of recession and slow growth. The forecasting performance of the GVAR model in relation to the ongoing financial crisis is quite remarkable. It correctly identifies a pronounced and widespread economic contraction accompanied by a marked shift in the net trade balance of the Eurozone and Japan. Moreover, this promising out‐of‐sample forecasting performance is substantiated by a raft of statistical tests which indicate that the predictive accuracy of the GVAR model is broadly comparable to that of standard benchmark models over short horizons and superior over longer horizons. Hence we conclude that GVAR models may be a useful forecasting tool for institutions operating at both the national and supra‐national levels. Copyright © 2010 John Wiley & Sons, Ltd.