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International trade is one of the key spheres of economic policy. It is crucial for a country to understand the dynamics of its export markets to create a coherent strategy to improve its position in global markets. Research in this field is particularly interesting for both economists and policy makers. However, due to a lack of data, most of the well-established literature is focused on the national level. Therefore, there is little evidence on the influence of local characteristics on export markets. This research aims to evaluate the influence of regional factors on the competitiveness of firms in international markets, focussing on the importance of agglomeration economies and location, among other local factors. To identify this influence, this paper studies the case of Brazil. This country offers rich disaggregated information that allows this type of research and displays enormous differences across rural and urban areas. Given these differences, the assumption of homogeneous effects is too restrictive. Therefore, to study the patterns across different territories around the country, Geographically Weighted Generalized Linear Model (GWGLM) method is applied. The results indicate an interaction between location and the influence of several local characteristics such as human capital, the degree of development and the local economic structure. This relationship creates virtuous circles in a few locations where urban agglomerations create a suitable environment for firms, while opposite patterns appear in other locations. JEL codes: F14, R11 and R12 [ABSTRACT FROM AUTHOR]

The β-convergence model is based on the neoclassical framework in which the spatial level of analysis is not relevant. These levels will result in decreasing returns. However, local processes of agglomeration, spillover effects, or other forces could operate differently depending on the level of spatial disaggregation. The primary objective of this article is to observe whether different local, regional, and national convergence behaviors are possible in the European Union (EU). To capture the differences among spatial scales, a multilevel and spatial effects extension of the Solow–Swan theoretical growth model is proposed. The estimations of this model are made using consistent information from Eurostat and Cambridge Econometrics for the period of 2000–2014. A multilevel spatial Durbin model estimator is applied to evaluate the spatial interactions of the regions. The results indicate that a general process of convergence in the EU coexists with intranational processes of divergence, highlighting the relevance of the spatial level of analysis. A final analysis of the impact of the economic crisis over the general behavior has been included verifying that the economic crisis strongly reinforce the weakness of the EU convergence. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, Ciccone's ( ) approach is applied to the Spanish case in 2011 but by estimating it using local labor markets (LLMs) instead of NUTS‐2 or NUTS‐3 regions. It is especially relevant in the case of Spain because the NUTS‐3 (provinces) are large regions in comparison with other cases in Europe. From a sample of income taxpayers published by the Spanish Fiscal Studies Institute, we derive figures on average wages by worker on the scale of LLMs. We argue that working at this level of spatial disaggregation is more in line with the idea of externalities from agglomerations, which are generated on a local scale. We can also observe intra‐regional heterogeneity and how the urban wage premium changes along the entire distribution of cities, including small‐medium size urban areas or rural areas. The empirical analysis is based on several estimation strategies, namely, ordinary least squares, two‐stages least squares, quantile regressions (QR), and instrumental variable quantile regressions (IVQR) estimators; they all find a significantly positive effect of agglomeration in the conditional mean of wages. This result can be estimated along the conditional distribution of wages. According to the QR and IVQR estimates, important variations are found along the distribution. [ABSTRACT FROM AUTHOR]

Background: Regional Economics and Economic Growth focus on the question of whether trade leads to a greater concentration of economic activity. Nevertheless, little empirical work has assessed the impact of trade on regional convergence. Therefore, this paper studies the regional convergence that has occurred in Mexico since NAFTA came into effect. Unlike previous papers, working with municipal-level data allows us to both observe the convergence patterns across space more clearly and to identify the effect of NAFTA. Methods: A conditional β-convergence model and conditional club β-convergence model were performed. However, in contrast to previous empirical studies, we use municipal panel data to identify more clearly the relationship between trade and regional convergence, and include the 2009 economic census to observe whether, after fifteen years of NAFTA, the economy has decentralized away from Mexico City to the US border regions. Results: The result shows that after NAFTA came into effect, the convergence in regions near the US border grew faster than it did in those further from it. However, there is a significant reduction in the β coefficient after NAFTA, indicating a slowdown in the rate of convergence. Furthermore, we find that rather than becoming integrated into world markets, municipalities in the south have instead lagged behind their counterparts since the signing of NAFTA. Conclusions: Even though centrifugal forces are starting to function, there is a significant reduction in the β coefficient after NAFTA came into effect. This suggests that better policies will be needed in order to control the increase in regional disparities. [ABSTRACT FROM AUTHOR]