Journal of Regional Science最新文献

The literature has produced mixed findings on the relationship between industry agglomeration and firm-level productivity where it concerns the self-selection of productive firms into locations characterized by different levels of industry agglomeration. We argue that the nature of this self-selection crucially depends on whether incumbent and entrant firms compete on the same market. Adverse selection of less productive firms into a location only dominates if knowledge spillovers in agglomerated locations are harmful to productive entrants: when the entrant and local incumbents target the same (domestic) product market and the entrant risks losing market share and profits. We find evidence for this notion in analysis of location decisions for new plants at the fine-grained geographical level in Japan by firms with known productivity records in the industry (multi-plant firms). We conclude that sorting processes do occur, but that the nature of these processes can only be uncovered in analysis that considers competition on product markets and accurate measures of firm heterogeneity in productivity.

In the immediate aftermath of the invasion of Ukraine, over 6 million Ukrainians fled their country to various European countries, including Italy. Various entities in the country, ranging from third-sector organizations to private citizens, expressed their interest in hosting these refugees, with significant subnational heterogeneity. What influenced this varying willingness to be hosts? We aim to provide some preliminary answers to this question by investigating the role of social capital in this heterogeneous response, using a quantitative framework. Our results, obtained through a set of regressions using Fractional Probit estimators, suggest that bonding social capital is associated with greater willingness to host, whereas the opposite is true for bridging social capital. The implications of these findings are discussed.

Given the relevance of spatial and sectoral interactions in shaping the productivity performance of economic systems and filières, in this study, we suggest addressing both aspects by estimating a system of simultaneous dynamic spatial panel data models. This approach allows to consider how the production level of a specific sector is influenced by the performance of other interconnected sectors in the same area (cross-sectoral spillovers) as well as the role of productivity spillovers originating from the same or other sectors in neighbouring territories (inter and intra sectoral spatial effects). The validity of the proposed approach is confirmed through the estimation of a simultaneous system for the production process of the Italian agribusiness filière. The results indicate the existence of meaningful inter-dependences within and between sectors and territories that materialises in spillovers of different natures (input factors, internal and external features), offering valuable policy implications for the overall economic growth of the agriculture filière.

A region's growth trajectory is influenced by the economic circumstances of other regions in its proximity. While proximity is often understood in a geographic sense, economic connectivity can take many different forms. In particular, shock transmission processes between regions are inherently asymmetric and heterogeneous, which is not captured by geographic proximity measures. As a potential channel for economic dependencies, we consider cross-regional commuter flows. Commuters, who spend a substantial portion of their income in a different place from where they earn it, connect peripheral regions to economic centers. In an econometric framework, we estimate time-space dynamic panel models with German county-level data. Given those estimates, we demonstrate a considerable variation in the spatial distribution of shock responses from using alternative proxies for spatial dependency, which is hidden by the traditional focus on average marginal effects. Local spatial multipliers differ depending on the nature and origin of the shock and the assumed network structure.

In this paper, we study the relationship between organized crime, corruption, and economic growth on a data set from Italian regions for the period 1996–2013. Our working hypothesis is that organized crime can embezzle part of the public expenditure aimed at productive uses by threatening and bribing public officers. To assess the consequences for regional growth we estimate a finite mixture covariate measurement model and find that the relationship between public expenditure and per capita GDP is characterized by parameter heterogeneity. Specifically, regions are partitioned in clusters identified by the initial level of organized crime. The effect of public expenditure on per capita GDP differs across clusters of regions: in the regions with the higher levels of organized crime public expenditure has a negative effect on per capita GDP, and the estimated share of embezzled public expenditure is higher, amounting to approximately 10% of its book value. Differently, in the regions with lower levels of organized crime the effect of public expenditure on per capita GDP is positive and the estimated share of embezzled public expenditure is lower. The empirical analysis is shown to be consistent with a theoretical growth model à la Barro (1990) augmented by corruption orchestrated by organized crime.

Residents' personal identification with places (regions, cities, towns, and so on) and with what places are supposed to stand for often determines their place-supportive attitudes and behaviors. However, little is known about how residents' identification with the characteristics of places and their adoption of place-related norms and values specifically affect residential mobility intentions and pro-local consumption tendencies, which are key topics in many spatial development plans and place marketing. The present study addresses this gap in the literature by using a structural equation modeling approach and a cross-place survey in Germany with 612 residents. The findings show that resident-place identification, on the basis of residential need satisfaction, increases residents' intentions to stay in a place and pro-local consumption preferences. These findings suggest that spatial planners and public managers can support the socioeconomic development of cities and regions and increase residents' willingness to stay in a place by strengthening their individual identification with places. We discuss the implications of our findings for the marketing and branding of places.