Regional Science Policy and Practice最新文献

Although multiple studies on structural change can be found at the national level, the definition of structural change is far from univocal and its subnational manifestations remain underexplored. This paper empirically examines the patterns of regional structural change in Argentina according to the four main definitions used in the literature (not only productive diversification, predominant in the economic geography field), highlighting the differences that arise when applying these concepts. Based on employment data for 85 labor market areas (LMAs) throughout the 1996–2019 period, we propose different criteria to apply and measure the four definitions and to classify the heterogeneous trajectories of structural change in LMAs, including cluster analysis. As the business cycle is a critical dimension in such an unstable economy, we examine the entire period and compare two sub-periods with very different economic dynamics. The results show that the identification of structural change depends on the concepts and measures used, the unit of analysis (national versus regional) and the type of economic cycle. These findings call for context- and place-based policies.

Using structural impact analysis, this paper investigates the economic implications of road transport infrastructure investments on the Latin American Integration Route (LAIR) in the state of Mato Grosso do Sul (MS), Brazil. We aim to determine whether these investments can drive short-term local economic growth, identify sectors that benefit the most from the investments, and analyze the distribution of effects among MS municipalities. Based on three comparative scenario simulations, the findings indicate that infrastructure investments are likely to yield positive short-term impacts on MS's GDP. The intensity of these impacts varies across industries and municipalities, with Campo Grande (state capital) being a key beneficiary. Compared to other types of investments, those in transport infrastructure have a lower dispersion capacity in space. The main contribution lies in utilizing the S-curve to model the financial progress of each investment project, as this information is frequently unavailable. Additionally, adopting the Spatial Location Quotient (SLQ) estimates the spatial distribution of investments impacts. Lastly, the guided simulation of investments is a methodology to enhance the efficacy of formulating and executing public investment policies, considering the local spatial consequences of these investments.

The study of crime and its associated factors is fundamental to improving the well-being of a society. In this context, this study aimed to understand the influence of amenities on crime in the urban areas of Cuenca (Ecuador). To this purpose, data was obtained from public entities and Google Places API. The empirical strategy employed involved the estimation of a set of spatial econometric models. The results show that amenities have an attractor effect on crime, thus reflecting that criminals act in places where there is a large accumulation of people. It was also found that the presence of government entities has no effect on crime.

There remains a dearth of literature dedicated to urban core-to-core cross-border regions, especially ones described as highly innovative. Hence, there is a growing need to advance the concept of a cross-border region, especially through the lens of clusters and smart system innovation policy by considering what might be the role of social entrepreneurship regarding its development. Thus, this article focuses on how an innovative cross-border region may be emerging between the bi-national Cascadia region, and analyzes the role of corporate driven social entrepreneurship in its advancement.

The COVID-19 pandemic was one of the biggest global crises of the 21st century, affecting all economic sectors, and Russia was no exception. Russian researchers have shown that the losses from the pandemic varied widely across sectors and regions: the service sector and large cities with high population density suffered the most. However, spatial and agglomeration effects at the micro level have been little studied in the context of COVID-19. Here, we show that during the pandemic, the influence of neighbouring firms on each other decreased, but the positive impact of agglomeration effects on firm performance increased. Using multilevel models and geographically weighted regressions, we constructed separate regressions for 2019 and 2020 explaining the sales margin of South Siberian firms by their individual, spatial and regional characteristics. Entertainment, service and transport companies were the most affected, which is consistent with the results of other studies. We also obtained new results: neighbours’ performance affected positively the firm performance in 2019, but during the pandemic the influence of neighbours became insignificant, a high level of digitalisation helped firms to survive the pandemic, and quarantine restrictions in the region had little impact on business performance. The findings can help develop an effective strategy to combat the economic impact of the pandemic and support businesses. We expect our study to improve understanding of what happens to firms during a pandemic and quarantine. The results may be useful outside the COVID-19 context: spatial and agglomeration effects also operate for firms outside the pandemic.

This study aims to bridge the gap in the existing literature by examining the impact of prevailing traditional slavery institutions and democratization processes on human capital development. In our pursuit, we conducted a residential survey in Sumba Island, Indonesia. Notably, despite democratization efforts since the 1950s, the traditional slavery institution, deeply entrenched in the ancient Austronesian ranking system, remains prevalent. This system classifies individuals into three hereditary tiers: nobles, commoners, and slaves. Based on the premise that caste designation is random and exogenous, we utilized an ordinary least squares (OLS) estimation approach, incorporating natal clan and cohort fixed effects. Our findings underscore the distinct advantage in human capital that individuals of the noble rank hold over their counterparts in the lower ranks, i.e. commoners and slaves. However, we also highlight the promise of ongoing democratization in bridging the human capital gaps between nobles and slaves, while simultaneously enhancing the potential for commoners to improve their human capital outcomes.

This study investigates the impacts of the minimum wage on U.S. regional labor markets. Using ten years of county-level data, we examine the relationship between the minimum wage and several key components of the labor market. Following past research, the number of people in the labor force is used to measure labor supply, but—as an extension to the literature—job postings data are included to measure labor demand. Consistent with previous studies, we find a positive relationship between labor force participation and a county’s minimum wage. The results are mixed, however, when examining the effects of the minimum wage on job postings.