This study uses the tools of network analysis to graphically and analytically represent the characteristics of world trade. The structure of the World Trade Network is compared over time, detecting and interpreting patterns of trade ties among countries. The results show that the trading system has become more intensely interconnected, and trade integration at the world level has been increasing, but it is still far from being complete, with the exception of a few areas. At the same time, we observed a strong and increasing heterogeneity in countries’ choice of trade partners, with countries holding very different positions within the network, so that it is very difficult to talk of a representative country in the international trade system. Network indices were also used in a gravity model regression, adding to the explanatory power of the model. Furthermore, the analysis shows that trade policies do play a role in shaping the trade network, and that WTO members are more closely connected than the rest of the world. The structural difference between the extensive and the intensive margin of trade is also highlighted. An important feature of these results is that they pertain to the trading system as a whole, giving a unified view of the system characteristics and complexity.
In this paper we investigate the causal effect of immigration on trade flows using Italian panel data at the province level. We exploit the exceptional characteristics of the Italian data (the fine geographical disaggregation, the very high number of countries of origin of immigrants, the high heterogeneity of social and economic characteristics of Italian provinces, and the absence of cultural or historical ties) and an empirical strategy based on the comparison of estimates at the NUTS-2 and NUTS-3 geographical level, on the use of a wide set of fixed effects, and on instrument based on immigrants' enclaves. The results are that immigrants have a significant positive effect on both exports and imports, much larger for the latter. The pro-trade effects of immigrants tend to decline in space, and even turn negative when large ethnic communities are located too far away from a specific province (via a trade-diversion effect). Finally, we give evidence of a substantial heterogeneity in the effects of immigrants: the impact on trade tends to be larger for immigrants coming from low-income countries, for earlier waves of immigrants and for the less advanced provinces of Southern Italy. AbstractIn this paper we investigate the causal effect of immigration on trade flows using Italian panel data at the province level. We exploit the exceptional characteristics of the Italian data (the fine geographical disaggregation, the very high number of countries of origin of immigrants, the high heterogeneity of social and economic characteristics of Italian provinces, and the absence of cultural or historical ties) and an empirical strategy based on the comparison of estimates at the NUTS-2 and NUTS-3 geographical level, on the use of a wide set of fixed effects, and on instrument based on immigrants' enclaves. The results are that immigrants have a significant positive effect on both exports and imports, much larger for the latter. The pro-trade effects of immigrants tend to decline in space, and even turn negative when large ethnic communities are located too far away from a specific province (via a trade-diversion effect). Finally, we give evidence of a substantial heterogeneity in the effects of immigrants: the impact on trade tends to be larger for immigrants coming from low-income countries, for earlier waves of immigrants and for the less advanced provinces of Southern Italy. JEL Classification
This paper provides evidence for an aspect of trade often disregarded in international trade research: countries' sectoral export diversification. The results of our semiparametric empirical analysis show that, on average, countries do not specialize; on the contrary, they diversify. Our results are robust for different statistical indices used to measure trade specialization, for the level of sectoral aggregation, and for the level of smoothing in the nonparametric term associated with per capita income. Using a generalized additive model (GAM) with countryspecific fixed effects it can be shown that, controlling for countries' heterogeneity, sectoral export diversification increases with income.
HighlightsThis paper explores the World Trade using the Network Analysis and introduces the reader to some of the techniques used to visualize, calculate and synthetically represent network trade data. The paper shows different visualizations of the network and describe its topological properties, producing and discussing some of the commonly used Network's statistics, and presenting some specific topics. All in all, this paper shows that Network Analysis is a useful tool to describe bilateral trade relations among countries when interdependence matters, and when trade relations are characterized by high dimensionality and strong heterogeneity. AbstractIn this paper we explore the BACI-CEPII database using Network Analysis. Starting from the visualization of the World Trade Network, we then define and describe the topology of the network, both in its binary version and in its weighted version, calculating and discussing some of the commonly used network's statistics. We finally discuss some specific topics that can be studied using Network Analysis and International Trade data, both at the aggregated and sectoral level. The analysis is done using multiple software (Stata, R, and Pajek). The scripts to replicate part of the analysis are included in the appendix, and can be used as an handson tutorial. Moreover,the World Trade Network local and global centrality measures, for the unweighted and the weighted version of the Network, calculated using the bilateral aggregate trade data for each country (178 in total) and each year (from 1995 to 2010,) can be downloaded from the CEPII webpage.JEL Classification: F10
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