ALBERT

Description: Within a number of disciplines, the terms “city” and “region” are frequently referred to in combination, raising the obvious question as to the relationship between two. The central focus of the paper involves an attempt to identify the more significant differences between the city and the region in terms of their respective modes of spatial organization. This is undertaken from three broad perspectives. The first compares the individual city and the individual region as independent entities, while the second perspective considers the city in relation to the region in which it is located. A third perspective is concerned with a system of cities in comparison with a system of regions. The latter part of the discussion examines alternative definitions of the city, and the extent to which these may be regarded as satisfactory.

Description: This paper explores a linear and circular model with spatial Cournot competition. It is shown that agglomeration of firms at the center of the main street is the equilibrium when the demand density on the main street (linear market) is high, and there exists a unique separated location equilibrium when the density is moderate. Moreover, the socially desirable interior locations are more dispersed than the equilibrium ones. Finally, extensions on tax policies, nonlinear demand, non-uniform distribution, and others are also discussed.

Description: This study investigates the spatial distribution of economic benefits and costs of an ecological restoration project for an urban branch stream, namely Yeocheon-Cheon in Nam-Gu, Ulsan metropolitan city, South Korea. A contingent valuation method with the one and one-half bounded dichotomous choice model was applied, and a spike model was employed to address zero-WTP responses. First, benefits of the project were not limited to the project site jurisdiction (Nam-Gu) but extended to the whole metropolitan city. Second, the significant negative coefficient of the distance variable indicates the distance decay of WTP for the project. Third, respondents who visited the site showed a significantly higher willingness to pay for the project. Finally, the project was economically profitable and socially desirable from the benefit–cost perspective. However, the cost allocation between jurisdictions was fiscally nonequivalent in terms of the spatial benefit distribution.

Description: We analyze the determinants and regional implications of internal migration flows across Danish municipalities in 2006–2012. Besides assessing the role of labor market and housing market factors in driving a region’s net migration rate, we particularly focus on agglomeration factors identified by “new” migration theories related to regional growth models and the new economic geography. The work contributes to the field in the following way: we extend the scarce literature on the different channels through which agglomeration economies act as an attractor for mobile labor. Moreover, we account for the role of space–time dynamic adjustment processes and simultaneity among migration and labor market variables and finally test for heterogeneity in the migration response to regional labor market disparities among low- and high-skilled migrants. Our results support the view that agglomeration economies are indeed key drivers of internal migration flows in Denmark. That is, while we obtain mixed evidence with regard to the role of traditional labor and housing market variables, most of the included proxies for agglomeration economies such as the region’s population density, patent intensity, endowment with human capital as well as the region’s employment share of knowledge-intensive services are positively correlated with the region’s net in-migration rate. Regarding the regional implications of internal migration flows, the results hint at a process of cumulative causation for the time period of analysis running from agglomeration economies to the inflow of mobile labor and subsequent regional income development.

Description: This paper presents a new method for estimating regional trade flows using transportation survey data describing commodity origin–destination flows. Explicit attention is paid to the difference between commodity flows and trade flows that arises from the presence of transhipment points. Observed commodity flows in the transportation survey data are converted to production–consumption trade flows that are consistent with the multi-regional input–output framework. Regional trade flow estimates are then reconciled with regional production and consumption estimates using a mathematical program that aims to make minimal adjustments while imposing known multi-regional input–output accounting identities. It is shown that commodities originating or terminating at a transhipment point should be reassigned to their probable production origins or consumption destinations as long as an unbiased sample of previous observations is available. As the number of observations increases, the prediction error of the production origin or consumption destination decreases exponentially. A real-world case study in the Province of Ontario in Canada demonstrates the feasibility of estimating interregional trade flows from commercial vehicle survey data and shows that the estimated pattern of trade flows is maintained after adjustments are made to satisfy accounting constraints. Therefore, it is possible to create a balanced multi-regional input–output model based on a commercial vehicle survey and the limited supplementary data available at the regional level.

Description: It has been frequently argued that a firm’s location in the core of an industry’s innovation network improves its ability to access information and absorb technological knowledge. The literature has still widely neglected the role of peripheral network positions for innovation processes. In addition to this, little is known about the determinants affecting a peripheral actors’ ability to reach the core. To shed some light on these issues, we have employed a unique longitudinal dataset encompassing the entire population of German laser source manufacturers (LSMs) and laser-related public research organizations (PROs) over a period of more than two decades. The aim of our paper is threefold. First, we analyze the emergence of core–periphery (CP) patterns in the German laser industry. Then, we explore the paths on which LSMs and PROs move from isolated positions toward the core. Finally, we employ non-parametric event history techniques to analyze the extent to which organizational and geographical determinates affect the propensity and timing of network core entries. Our results indicate the emergence and solidification of CP patterns at the overall network level. We also found that the paths on which organizations traverse through the network are characterized by high levels of heterogeneity and volatility. The transition from peripheral to core positions is impacted by organizational characteristics, while an organization’s geographical location does not play a significant role.

Description: This paper discusses the current links between international business, economic geography and knowledge management. Despite the recent proliferation of papers dealing with knowledge transfer by multinational enterprises (MNEs) in China, there is limited work investigating the role of geographic space on knowledge transfer. Given the growing interest in knowledge transfer by MNEs, the lack of research on geographic space in the Chinese context is a significant gap in our knowledge. In response, we have conducted what we believe to be the first study on the relationship between geographic space and knowledge transfer by the Japanese MNEs to their subsidiaries in China. The paper reviews the relevant literature from which it develops a theoretical model which is then tested empirically. We then provide empirical results on the relationship between geographic space, perceived distance and knowledge transfer. A LISREL model is employed to study the impact of the latent variables associated with geographic space on knowledge transfer. Based on the results, this study provides useful insights for economic geographers who wish to study knowledge transfer between parent companies and their subsidiaries across geographic space.

Description: Applications of spatial probit regression models that have appeared in the literature have incorrectly interpreted estimates from these models. Spatially dependent choices frequently arise in various modeling scenarios, including situations involving analysis of regional voting behavior, decisions by states or cities to change tax rates relative to neighboring jurisdictions, decisions by households to move or stay in a particular location. We use county-level voting results from the 2004 presidential election as an illustrative example of some issues that arise when drawing inferences from spatial probit model estimates. Although the voting example holds particular intuitive appeal that allows us to focus on interpretive issues, there are numerous other situations where these same considerations come into play. Past work regarding Bayesian Markov Chain Monte Carlo estimation of spatial probit models from LeSage and Pace (Introduction to spatial econometrics. Taylor and Francis, New York, 2009 ) is used, as well as derivations from LeSage et al. (J R Stat Soc Ser A Stat Soc 174(4):1007–1027, 2011 ) regarding proper interpretation of the partial derivative impacts from changes in the explanatory variables on the probability of voting for a candidate. As in the case of conventional probit models, the effects arising from changes in the explanatory variables depend in a nonlinear way on the levels of these variables. In non-spatial probit regressions, a common way to explore the nonlinearity in this relationship is to calculate “marginal effects” estimates using particular values of the explanatory variables (e.g., mean values or quintile intervals). The motivation for this practice is consideration of how the impact of changing explanatory variable values varies across the range of values encompassed by the sample data. Given the nonlinear nature of the normal cumulative density function transform on which the (non-spatial) probit model relies, we know that changes in explanatory variable values near the mean may have a very different impact on decision probabilities than changes in very low or high values. For spatial probit regression models, the effects or impacts from changes in the explanatory variables are more highly nonlinear. In addition, since spatial models rely on observations that each represent a location or region located on a map, the levels of the explanatory variables can be viewed as varying over space. We discuss important implications of this for proper interpretation of spatial probit regression models in the context of our election application.

Description: In this study, we examine the vulnerability and resiliency of 10 tourism-based regional economies which include US national parks or seashores (situated on the Gulf of Mexico or Atlantic Ocean coastline) affected by several hurricanes over a 26-year period. The vulnerability of each economy to natural disasters was estimated using a panel linear model, while resilience was estimated by employing a negative binomial panel regression and a difference-in-difference model. Natural disaster damage, related to physical damage and human loss, was shown to have a negative effect on regional economies. Regions with stronger economies prior to natural disasters have lower disaster losses than regions with weaker economic characteristics. More effort to improve regional economic conditions before natural disasters is necessary to minimize disaster loss. Lessons learned from the economic impacts of past natural disasters, in particular in tourism-based regions, can help regional planners and policy makers predict problems related to disasters and more effectively prepare for future events.