With the implementation of regional development policies in recent years, transportation infrastructure has greatly promoted regional economic development, but what impact it has on the construction of market integration in the local and surrounding regions has not been specifically answered. Based on the provincial panel data of China from 2010 to 2021, this paper uses the spatial panel method to study the impact of transportation infrastructure development and the construction of national unified market and its spatial spillover effects. The empirical results show that there is significant spatial auto-correlation between inter-provincial transport infrastructure and market integration. Railway density plays a greater role in promoting the national unified market. The government expenditure and foreign direct investment play a positive role in promoting the construction of a unified national market, while the dependence of foreign trade inhibits the development of market integration. In the analysis of spatial spillover effects, the direct effect of railway density is significantly higher than that of highway. The government should strengthen the quality and efficiency of railway transportation, promote the scale of foreign direct investment of enterprises, and actively promote the construction of national unified market.
Artificial intelligence (AI) is rapidly transforming the global economy, and Latin America is no exception. In recent years, there has been a growing interest in AI development and implementation in the region. This paper presents a ranking of Latin American (LATAM) countries based on their potential to become emerging powers in AI. The ranking is based on three pillars: infrastructure, education, and finance. Infrastructure is measured by the availability of electricity, high-speed internet, the quality of telecommunications networks, and the availability of supercomputers. Education is measured by the quality of education and the research status. Finance is measured by the cost of investments, history of investments, economic metrics, and current implementation of AI. While Brazil, Chile, and Mexico have established themselves as major players in the AI industry in Latin America, our ranking demonstrates the new emerging powers in the region. According to the results, Argentina, Colombia, Uruguay, Costa Rica, and Ecuador are leading as new emerging powers in AI in Latin America. These countries have strong education systems, well-developed infrastructure, and growing financial resources. The ranking provides a useful tool for policymakers, investors, and businesses interested in AI development in Latin America. It can help to identify emerging LATAM countries with the greatest potential for AI growth and success.
This paper reports research results on Science Technology Engineering and Mathematics – STEM – wage premium in 10 main Brazilian technologic clusters: Manaus, Ilhéus-Itabuna, Belo Horizonte, Pouso Alegre, Curitiba, Porto Alegre, Florianópolis, Campinas, São Carlos and São Paulo. The study adjusts the Oaxaca decomposition method – which allows using the workers’ occupation as a categorical variable – to estimate the median of the STEM wage premium in each of the clusters. The control variables are age, educational level, and experience, which are proxy variables for human capital. Inspection of data reveals that the STEM workforce is more educated and has more stability in the job. The statistical analysis suggests that the median of the STEM wage premium obtained by workers in the ten clusters is higher than observed in development countries. This may indicate that Brazilian STEM labor force should will is still grow to meet demand.
Financial technology companies in Latin America and the world, typically known as Fintech, are growing at a significant rate. However, a detailed analysis on the main influencers on the success or survival of these technologies remains to be discussed. This research determines the variables and social actors that characterize the Fintech ecosystem. For this purpose, a descriptive design was employed under the methodology of structural analysis, making use of tools such as a panel of experts and the MICMAC software (Matrix of Crossed Impacts Multiplication Applied to a Classification). The results suggest that investment, customer management and behavior due to COVID-19 are considered key variables in the current Fintech market. While the SBS (Superintendency of Banking, Insurance and AFP), Peruvian Fintech companies and clients are considered as the preponderant social actors. The findings constitute a basis for the design and strategic planning of future scenarios aimed at minimizing risks and making the most of the opportunities offered by this industry 4.0 new market.
