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This paper evaluates the potential responses of international labor mobility to the recent COVID-19 health shocks, using a New Economic Geography model inspired by recent events in Central and North America. The model suggests that the restraining impact of COVID-19 on migratory flows may retain potential emigrants in Mexico and Central America, enlarge the home market in the region, attract foreign and local businesses, and increase real wages. Moreover, this prediction unveils opportunities for the future from the opening of new, regular migratory pathways between Central America and Mexico. These would concentrate population and industry in Mexico, raise the market potential in the area and boost real wages in Mexico – and possibly in Central America as well – despite the partial deindustrialization of the Central American hinterland. [ABSTRACT FROM AUTHOR]

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]

Subnational input–output (IO) tables capture industry- and region-specific production, consumption, and trade of commodities and serve as a common basis for regional and multi-regional economic impact analysis. However, subnational IO tables are not made available by national statistical offices, especially in the United States (US), nor have they been estimated with transparent methods for reproducibility or updated regularly for public availability. In this article, we describe a robust StateIO modeling framework to develop state and two-region IO models for all 50 states in the US using national IO tables and state industry and trade data from reliable public sources such as the US Bureau of Economic Analysis. We develop 2012-2017 state IO models and two-region IO models at the BEA summary level. The two regions are state of interest and rest of the US. All models are validated by a series of rigorous checks to ensure the results are balanced at state and national levels. We then use these models to calculate a 2012–2017 time series of macro economic indicators and highlight results for 11 states that have distinct economies with respect to size, geography, and industry structure. We also compare selected indicators to state IO models created by popular licensed and open-source software. Our StateIO modeling framework is consolidated in an open-source R package, stateior, to ensure transparency and reproducibility. Our StateIO models are US-focused, which may not be transferrable to international accounts, and form the economic base of state versions of the US environmentally-extended IO models. [ABSTRACT FROM AUTHOR]