Trade costs in the first wave of Globalization

What drives globalization today and in the past? We employ a new micro-founded measure of bilateral trade costs based on a standard model of trade in differentiated goods to address this question. These trade costs gauge the difference between observed bilateral trade and frictionless trade. They comprise tariffs, transportation costs and all other factors that impede international trade but which are inherently difficult to observe. Trade costs fell on average by ten to Þfteen percent between 1870 and 1913. We also use this measure to decompose the growth of global trade over that period and Þnd that roughly 44 percent of the global trade boom can be explained by reductions in trade costs; the remaining 56 percent is attributable to economic expansion

Global Networks of Trade and Bits

Considerable efforts have been made in recent years to produce detailed topologies of the Internet. Although Internet topology data have been brought to the attention of a wide and somewhat diverse audience of scholars, so far they have been overlooked by economists. In this paper, we suggest that such data could be effectively treated as a proxy to characterize the size of the "digital economy" at country level and outsourcing: thus, we analyse the topological structure of the network of trade in digital services (trade in bits) and compare it with that of 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 thus filtered by means of different thresholds, so that we only focus on the strongest links, 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. Lastly, distance plays a more prominent role in shaping the network of international trade in physical goods than trade in digital services.Comment: 25 pages, 6 figure

Conditional Logit with one Binary Covariate: Link between the Static and Dynamic Cases

Disentangling state dependence from unobserved heterogeneity is a common issue in economics. It arises for instance when studying transitions between different states on the labor market. When the outcome variable is binary, one of the usual strategies consists in using a conditional logit model with an appropriate conditioning suitable for a dynamic framework. Although static conditional logit procedures are widely available, these procedures cannot be used directly in a dynamic framework. Indeed, it is inappropriate to use them with a lag dependent variable in the list of regressors. Moreover, reprogramming this kind of procedures in a dynamic framework can prove quite cumbersome because the likelihood can have a very high number of terms when the number of periods increases. Here, we consider the case of a conditional logit model with one binary regressor which can be either exogenous or the lagged dependent variable itself. We provide closed forms for the conditional likelihoods in both cases and show the link between them. These results show that in order to evaluate a conditional logit model with one lag of state dependence and no other covariate, it is possible to simply generate a two variable dataset and use standard procedures originally intended for models without state dependence. Moreover, the closed forms help reduce the computational burden even in the static case in which preimplemented procedures usually exist.conditional logit, state dependence, binary model, incidental parameter

Searching for superspreaders of information in real-world social media

A number of predictors have been suggested to detect the most influential spreaders of information in online social media across various domains such as Twitter or Facebook. In particular, degree, PageRank, k-core and other centralities have been adopted to rank the spreading capability of users in information dissemination media. So far, validation of the proposed predictors has been done by simulating the spreading dynamics rather than following real information flow in social networks. Consequently, only model-dependent contradictory results have been achieved so far for the best predictor. Here, we address this issue directly. We search for influential spreaders by following the real spreading dynamics in a wide range of networks. We find that the widely-used degree and PageRank fail in ranking users' influence. We find that the best spreaders are consistently located in the k-core across dissimilar social platforms such as Twitter, Facebook, Livejournal and scientific publishing in the American Physical Society. Furthermore, when the complete global network structure is unavailable, we find that the sum of the nearest neighbors' degree is a reliable local proxy for user's influence. Our analysis provides practical instructions for optimal design of strategies for "viral" information dissemination in relevant applications.Comment: 12 pages, 7 figure

Transaction Propagation on Permissionless Blockchains: Incentive and Routing Mechanisms

Existing permissionless blockchain solutions rely on peer-to-peer propagation mechanisms, where nodes in a network transfer transaction they received to their neighbors. Unfortunately, there is no explicit incentive for such transaction propagation. Therefore, existing propagation mechanisms will not be sustainable in a fully decentralized blockchain with rational nodes. In this work, we formally define the problem of incentivizing nodes for transaction propagation. We propose an incentive mechanism where each node involved in the propagation of a transaction receives a share of the transaction fee. We also show that our proposal is Sybil-proof. Furthermore, we combine the incentive mechanism with smart routing to reduce the communication and storage costs at the same time. The proposed routing mechanism reduces the redundant transaction propagation from the size of the network to a factor of average shortest path length. The routing mechanism is built upon a specific type of consensus protocol where the round leader who creates the transaction block is known in advance. Note that our routing mechanism is a generic one and can be adopted independently from the incentive mechanism.Comment: 2018 Crypto Valley Conference on Blockchain Technolog