Metrics capturing the degree to which individual economies are globalized

We discuss metrics of globalization for individual economies as distance measures between fully integrated and trade restricted equilibria in economies initially operating under less than full integration with the global economy. Such metrics can be used to construct country globalization metrics reflecting the distance of economies from full global integration due to trade barriers, barriers to factor flows, barriers to international financial intermediation, solved technological diffusion and other economy-specific features yielding less than full integration into the global economy. Many distance metrics present themselves and none are wholly satisfactory since they each behave differently across various displacements from integration. Distance measures can, for instance, be small in goods space but large in price space. We present alternative measures constructed for eight OECD economies and comment in a concluding section on other measures used elsewhere in the literature such as trade/GDP ratios.     

The Division and Size of Gains from Liberalization in Service Networks*

If two disjoint country service networks involving a small and large country are connected as part of international liberalization in the presence of network externalities, the per capita gain for the small country from access to a large network will be large, and the per capita gain for the large country will be small. In contrast to goods, the benefits of liberalization in network‐related services are more likely to be approximately equally divided between large and small countries than is true of trade in goods, where benefits accrue disproportionately to the small country. We also argue that non‐cooperation in network‐related services trade may involve more extreme retaliation than suggested for trade in goods by the optimal tariff literature, so that relative to a non‐cooperative outcome, gains from liberalization in network‐related services become larger than from liberalization in goods. We develop simple models which we use for numerical examples showing these points, along with an empirical implementation for global telecoms liberalization for the US, Europe, Canada, and the rest of the world using the framework developed in the paper. This shows similar proportional gains to regions, consistent with the theme of the paper that goods and services liberalization differ.     

The potential trade effects of an FTA between the EU and Russia

The Potential Trade Effects of an FTA between the EU and Russia.- This paper analyzes some of the potential economic effects of free trade agreements between the EU and Russia and the other European CIS countries using standard indicators of trade patterns. It confirms that it would not be feasible for the EU to conclude such an agreement with Russia alone. It is also shown that, if the current high tariff levels are maintained in the CIS countries, they may not benefit from an agreement with the EU. More generally, the authors question the economic motivation for countries such as Russia in seeking free trade agreements with industrial countries which already have low levels of external protection.     

Are developed country multilateral tariff reductions necessarily beneficial for the U.S.?

Since the formation of the GATT in 1947, the belief underlying U.S. participation in GATT multilateral tariff reductions has been that they are beneficial to the U.S. This paper reports general equilibrium computations of the welfare effects of a 50% multilateral tariff reduction among developed countries using a seven region world trade model due to Whalley (1982).     

Home and regional biases and border effects in Armington type models

We discuss biases in preferences and their trade effects in terms of impacts on non-neutral trade flows motivated by recent literature on both home bias and the border effect. These terms take on multiple definitions in the literature and are often used interchangeably even though they differ. The border effect refers to a higher proclivity to trade behind rather than across national borders and is usually defined by the coefficients of regional dummies from an estimated gravity model. It can be present both in data and in counterfactual model solutions. Sometimes the reduced form of the gravity model used is asserted to reflect an Armington type model. For the border effect to occur as a model outcome, a structural model with at least 2 home regions and 1 country abroad is needed. In contrast to current literature, we offer a characterization of various forms of preference bias in trade models and measures of their associated trade effects based on a concept we term trade neutrality. These effects go beyond conventional border effects, and can be both across and within borders. Home bias is typically specified as an Armington preference for domestic over comparable foreign products in a trade model where goods are heterogeneous across countries. It is reflected in both model structure and parameterization, but defined in several different ways in the literature. We assess the contribution of each form of bias to the set of possible trade effects using a calibrated model with 3 Canadian regions, the U.S., and the rest of the world using 2001 data. We also evaluate how much of the conventional border effect is accounted for when model biases are modified in various ways.     

Mapping worldwide mobile networks: Some problems and indicative solutions

Mobile telecommunications is a global and complex industry containing many actors. However, relatively little research has been undertaken into explaining its structure. With this in mind, the objective of this paper is twofold: first, to map the structure of the mobile telecommunications industry and, second, to use this mapping exercise to highlight the data collection issues that are frequently encountered. Through outlining one particular approach to data collection, the paper argues that researchers need to be careful when constructing datasets and wary when relying on those provided by others. By mapping the structure of the mobile industry, the paper highlights a series of key issues in data collection and trends in operator and market structure.