INTRODUCTIONT HE new economic geography literature explores the importance of technology and geography in determining specialisation patterns and comparative advantage of countries. In particular, Eaton and Kortum (2002), henceforth referred to as EK, provide a general equilibrium model to analyse the relative importance of technology and geography. Fieler (2011) extends the model by assuming that technology (productivity) varies more widely across countries for high income elasticity goods. 1 This implies that the composition of exports is directly related to the level of productivity that exists in a country. Similarly, the composition of exports also determines the level of export sophistication, which indicates the similarity of export bundles of a country with exports of high income countries (Hausmann et al., 2007).This paper explores the relative importance of technology and trade costs on export sophistication and welfare in a general equilibrium framework. It uses an estimation strategy developed by Balistreri and Hillberry (2007) that employs a structural estimation technique to calibrate a general equilibrium model. It also incorporates non-homothetic preferences using a Stone-Geary utility function. The tradable sector is modelled using a disaggregated EK framework that estimates bilateral trade at commodity level. 2 Key parameters of the model are calibrated.The result shows that the marginal expenditure shares exhibit substantial variation across commodities, with the highest share in services. Moreover, the efficiency dispersion parameter varies moderately across commodities consistent with their expected spread of efficiency. That is, more (less) sophisticated commodities have larger (smaller) spread of efficiency. Similarly, there is variation in the trade costs parameter across commodities, which indicates a difference in sensitivity. For example, commodities such as machinery and electrical equipment are less sensitive than others. Furthermore, the implied distance elasticities from the calibrated model are similar to estimates from a log-linear regression for most of the commodities.With regard to the country-specific technology parameter, the result shows that it varies across commodities within a country and also across countries. A country can have a large value in some commodities, but not in others. The overall pattern indicates that low-income countries are at the bottom end in the ranking. Similarly, the average weighted income of a commodity (PRODY) varies consistently with its level of sophistication. Moreover, export sophistication shows a clear upward trend with GDP per capita. Further, counterfactual experiments are also conducted to assess the effects of changes in technology and trade costs for the bottom quinitile countries. The findings indicate that these countries relatively have a I thank the associate editor, anonymous referee, Russell Hillberry, Roland Hodler, Michael Coelli, Philip McCalman, Reshad Ahsan, and various seminar and conference participants for helpful comment...
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