Papers in Regional Science最新文献

Most papers on creative industries ask whether they are a source of Marshallian or Jacobian effects, inasmuch as a stronger creative sector is a direction of diversification that could have positive spillovers onto the rest of the economy. While most works have focused on developed economies, I contribute evidence from a middle-income Latin American country and study both creative occupations and creative sectors. I find that specialisation in creative sectors is associated with higher sales and a larger number of firms in those sectors, albeit at a decreasing rate. A similar relationship is found between specialisation in creative occupations and the income of those workers. I find no evidence of effects of creative specialisation on other sectors.

The paper investigates the effects of internal migration on green growth in Italian regions. We use employment in "sustainable" sectors to measure green growth, resorting to a novel measure based on the EU taxonomy for sustainable activities. Using data from 103 Italian regions (NUTS3) from 2008 to 2018, we find that highly skilled interregional migrants are positively related to green employment in their destinations. The effect is possibly due to return migrants to the Southern regions. Overall, the evidence emphasizes the importance of human capital migration in sustainable development.

This study investigates the dynamics of human capital in borderlands, focusing on the case of the Minho River border between Spain and Portugal. We examine how this capital influences company sales in these culturally and economically intertwined regions. The problem is critical due to the unique nature of borderlands in global trade and cultural exchange. Our novel approach uses hierarchical linear models for comparative analysis between municipalities in the border regions and those in the wider province (NUT III UE). This allows a deeper understanding of the localized effects of human capital. Empirical results reveal significant country and border effects on company sales in the examined case. Spanish companies face disadvantages compared to Portuguese ones, likely due to lower industrial land costs, cheaper labor, and different tax systems in Portugal. The analysis indicates a positive border effect on sales, attributed to geographical and cultural proximity, outweighing the disadvantages of smaller firm size and lower agglomeration in border territories. This research not only highlights the specific context of the Minho River borderlands but also offers broader insights into the role of human capital in regional economic development. This case study provides a foundation for future research and policy formulation in similar border regions worldwide, emphasizing the significance of human capital and its varied impact across different geographical and political contexts.

Location analytics have been a mainstay in regional science since its inception. Why? Perhaps the biggest reason is the ability to tease out important spatial heterogeneity nuances, but also to communicate geographically oriented analysis, planning, management and policy issues in rigorous ways, often as mathematical models, that can be subjected to further scrutiny and evaluation. Further, addressing broad challenges facing emergency response, food production, risk mitigation, transportation, public health, crime, housing and other issues through such approaches has proven an immense benefit to society. This paper focuses on the evolving subfield within regional science of location analysis and modeling, highlighting contributions to date but also detailing exciting areas of advancement involving spatial optimization and geographic information science. The paper includes a reflection on regional science journal publication trends, but also broader patterns of location analytics activity. It is hoped that this review will lead to a reassessment of regional science priorities, and consideration of the role that our specialty areas have in maintaining core strengths as well as potential for growing the discipline in the coming years.

We investigate the hypothesis of regional convergence in the per-capita GDP in 242 European regions (NUTS2) during the 2000–2021 period. The literature shows mixed results, from absolute convergence towards a joint long-run distribution to multiple regimes (convergence club). Our results show a broad convergence to an unimodal distribution. Although the GDP distribution was characterized by a twin-peak property in 2000, it tends to disappear over time, bringing, in 2021, to an unimodal distribution. Physical and human capital is the most responsible for the convergence process and the EU cohesion funds. To empirically investigate the question, we first apply alternative techniques of cluster identification. Later, we assess whether clusters and covariates affect the per-capita GDP. We use a novel machine learning algorithm (GPBoost) instead of the more traditional techniques used in the current literature. The results show that a convergence process is at work; physical and human capital are mainly responsible for the gdp explanation. but eu funds play a relevant role as well. moreover, complementarities do exist among these variables.