Assessing the Cluster Correspondence between Paired Point Locations

Some complex geographic events are associated with multiple point locations. Such events include, but are not limited to, those describing linkages between and among places. The term multi‐location event is used in the paper to refer to these geographical phenomena. Through formalization of the multi‐location event problem, this paper situates the analysis of multi‐location events within the broad context of point pattern analysis techniques. Two alternative approaches (Vector autocorrelation analysis and cluster correspondence analysis) to the spatial dependence of paired‐location events (i.e., two‐location events) are explored, with a discussion of their appropriateness to general multi‐location event problems. The research proposes a framework of cluster correspondence analysis for the detection of local non‐stationarities in the spatial process generating multi‐location events. A new algorithm for local analysis of cluster correspondence is proposed. It is implemented on a large‐scale dataset of vehicle theft and recovery location pairs in Buffalo, New York.     

A HARMONIZATION OF FIRST AND SECOND NATURES*

ABSTRACT This paper investigates the joint impact of the first nature and the second nature forces on industry location. Toward this aim, we develop a two‐region new economic geography model where local factor congestion and location advantages compete with demand linkages and product market crowding. In particular, we study the case of absolute location advantage in a single industry model and the case of comparative advantages in a two‐industry model. We characterize the structure of industries and discuss the possibilities of catastrophic changes, endogenous industrial asymmetries and specialization. We find that absolute location advantage are associated with a smooth agglomeration process and comparative advantages with a catastrophic process.     

INFERENCE BASED ON ALTERNATIVE BOOTSTRAPPING METHODS IN SPATIAL MODELS WITH AN APPLICATION TO COUNTY INCOME GROWTH IN THE UNITED STATES*

ABSTRACT This study examines aggregate county income growth across the 48 contiguous states from 1990 to 2005. To control for endogeneity, we estimate a two‐stage spatial error model and implement a number of spatial bootstrap routines to infer parameter significance. Among the results, we find that outdoor recreation and natural amenities favor positive growth in rural counties and property taxes correlate negatively with rural growth. Comparing bootstrap inference with other models, including the recent General Moment heteroskedastic‐robust spatial error estimator, we find similar conclusions suggesting bootstrapping can be effective in spatial models where asymptotic results are not well established.     

A NON-GAUSSIAN TIME SERIES ANALYSIS OF RURAL RETAIL BUSINESS COUNTS*

ABSTRACT. Determinants of the number of retail firms serving a rural area have been investigated by drawing on demand threshold analysis to analyze cross-sectional data. The relevance of such studies to an individual community may be limited if it is characterized by differential levels or unique types of economic activity. Alternatively, conducting the analysis using time-series data on an individual community may lead to problems associated with non-normal and nonstationary data. These problems are addressed by formulating a state-space model of time-series count data. The discrete, nonnegative nature of count data is accommodated by using a conjugate prior for the Poisson location parameter. A guide function is used to link the prior to the state vector and Bayes rules are used for updating.     

GRAVITY AND SPATIAL STRUCTURE: THE CASE OF INTERSTATE MIGRATION IN MEXICO*

ABSTRACT The estimation of gravity models of internal (aggregate) place‐to‐place migration is plagued with endogeneity (omitted‐variable) biases if the unobserved effects of spatial structure are not accounted for. To address this econometric problem, this paper presents a more general specification of the gravity model, which allows for (bilateral) parameter heterogeneity across individual migration paths—along with (unilateral) origin‐ and destination‐specific effects. The resultant “three‐way fixed‐effects” (3FE) model is applied for an analysis of interstate migration in Mexico based on cross‐sectional data. To overcome parameter‐dimensionality problems (due to limited or incomplete information), the 3FE model is estimated using the Generalized Maximum Entropy (GME) estimator. The empirical implications of this new modeling strategy are illustrated by contrasting the 3FE‐GME estimates with those for the traditional and two‐way fixed‐effects (2FE) models. The former are far more plausible and intuitively interpretable than their traditional and 2FE counterparts, with parameter estimates changing in expected directions. The (average) effect of the migrant stock is markedly smaller than usually estimated, providing a more realistic measure of network‐induced migration. Migration outflows from centrally located origins have significantly steeper distance decay. Path‐specific distance effects exhibit directional asymmetries and spatial similarities.     

Concurrent assessment of urban environment and cardiometabolic risk over 10 years in a middle‐aged population‐based cohort

Inference regarding the impact of urban areas on health is limited by cross‐sectional studies assessing few dimensions and ignoring area‐level socio‐economic status. This study simultaneously assessed several dimensions of the built environment against incident cardiometabolic risk (CMR) arising over 10 years. It tested the hypothesis that, accounting for local area relative wealth, features of the built environment would not predict incident CMR. Initially, disease‐free adults in a biomedical cohort in Adelaide, Australia, provided address and clinical data over three waves of follow‐up. CMR was defined as the count of five clinical CMR factors. Built environment measures were derived for urban form, and natural, and food environments. Local area wealth was expressed using the relative location factor index. Poisson growth models accounting for within‐suburb clustering, age, sex, and education were used to estimate associations between built environment measures and increasing CMR. Fitted linear trajectories had statistically significant mean values of intercepts and slopes. CMR trajectories were associated with age, male sex, and low education. In models including measures of the food, natural, and urban form environments, per standard deviation increase, only POS count predicted incident CMR, which was more strongly predicted by relative location factor. Not accounting for local area socio‐economic status may overestimate the strength of relationships between health and the built environment. Inequity in accessible POS is robustly related to incident CMR.     

TRAFFIC CONGESTION,POLYCENTRICITY, AND INTRAURBAN FIRM LOCATION CHOICES: A NESTED LOGIT MODEL FOR THE LOS ANGELES METROPOLITAN AREA

This study empirically investigates traffic congestion effects on agglomeration through the lens of firm location decisions. A discrete choice model is applied to examine new establishments’ location choices within the Los Angeles metropolitan area. Employment centers are defined as the choice set to explore the nature and role of intraurban agglomerations. The results show that metro‐wide congestion negatively affects the location choices of firms in the high‐order office‐related activities, while local congestion have positive impacts on those firms’ location decisions. In contrast, firms in production‐related activities are positively influenced by regional congestion but are negatively affected by local congestion levels.     

Accuracy of Count Data Estimated by the Point‐in‐Polygon Method

This paper analyzes the accuracy of count data estimated by the point‐in‐polygon method. A point‐in‐polygon interpolation model is proposed, based on a stochastic distribution of points and the target zone, in order to represent a variety of situations. The accuracy of estimates is numerically investigated in relation to the size of the target zone and the distribution of points, and the optimal location of representative points is discussed. The major findings of this paper are as follows: (1) though the relative accuracy of estimates generally increases monotonously with the size of the target zone, the monotoneity is often disturbed by the periodicity in the spatial configuration of source zones and the point distribution; (2) the point‐in‐polygon and the areal weighting interpolation methods have the same accuracy of estimates when points are concentrated in less than 12–15 percent area around the representative point in source zones; (3) the point‐in‐polygon method is not so robust against the locational gap between points and the representative point; (4) the optimal location of representative points is given by the spatial median of points.     

Model Uncertainty in Matrix Exponential Spatial Growth Regression Models

This article considers the most important aspects of model uncertainty for spatial regression models, namely, the appropriate spatial weight matrix to be employed and the appropriate explanatory variables. We focus on the spatial Durbin model (SDM) specification in this study that nests most models used in the regional growth literature, and develop a simple Bayesian model‐averaging approach that provides a unified and formal treatment of these aspects of model uncertainty for SDM growth models. The approach expands on previous work by reducing the computational costs through the use of Bayesian information criterion model weights and a matrix exponential specification of the SDM model. The spatial Durbin matrix exponential model has theoretical and computational advantages over the spatial autoregressive specification due to the ease of inversion, differentiation, and integration of the matrix exponential. In particular, the matrix exponential has a simple matrix determinant that vanishes for the case of a spatial weight matrix with a trace of zero. This allows for a larger domain of spatial growth regression models to be analyzed with this approach, including models based on different classes of spatial weight matrices. The working of the approach is illustrated for the case of 32 potential determinants and three classes of spatial weight matrices (contiguity‐based, k‐nearest neighbor, and distance‐based spatial weight matrices), using a data set of income per capita growth for 273 European regions.     

THE MOSES-PREDOHL PULL AND THE LOCATION DECISION OF THE FIRM*

ABSTRACT This paper exploits the two-stage approach and the envelope theorem to examine the role of the Moses-Predhol pull in the cost-minimizing location theory of the firm. It shows that the two-stage approach introduces the Moses-Predohl pull into the first-order conditions. The Moses-Predohl pull is shown to be equal to zero through the envelope theorem. These results show why the assertions of Bossert and Buhl (1986) concerning Kusumoto (1984,1985) are incorrect.     

GEOGRAPHICAL MOBILITY OF DANISH DUAL‐EARNER COUPLES—THE RELATIONSHIP BETWEEN CHANGE OF JOB AND CHANGE OF RESIDENCE*

ABSTRACT We analyze the relationship between geographical residence and job mobility for Danish dual‐earner couples. We estimate the probability of moving residence and changing job, taking the interdependence between the events into account. The results point to the importance of addressing the interrelationship between residence and jobs. Furthermore, the change of residence matter more than change of job and women respond relatively more to changes in their husbands’ job region. The findings imply that mobility promoting initiatives must focus on families rather than individuals and recognize that for most families the choice of residence location dominates the choice of job location.     

Growth and Convergence in a Multiregional Model with Space–Time Dynamics. 多区域时空动态模型的增长与收敛

The goal of this article is to test four distinct hypotheses about whether the relative location of an economy affects economic growth and economic well‐being using an extended Solow–Swan neoclassical growth model that incorporates both space and time dynamics. We show that the econometric specification takes the form of an unconstrained spatial Durbin model, and we investigate whether the results depend on some methodological issues, such as the choice of the time span and the inclusion of fixed effects. To estimate the fixed effects spatial Solow–Swan model, we adjust the Arrelano and Bond (1991) generalized method‐of‐moments (GMM) estimator to deal with endogeneity not only arising from the initial income level, as in the basic model, but also from the initial income levels and economic growth rates observed in neighboring economies.     

MIGRATION AS A WAY TO DIVERSIFY: EVIDENCE FROM RURAL TO URBAN MIGRATION IN THE U.S.

This paper extends the utility maximization model of migration by introducing income and unemployment‐related uncertainties as determinants of utility, and analyzes the effects of the informational advantages of migrants. The paper maintains that migration would expand an individual's economic choices and opportunities and allow diversification. Consequently, diversification advantages influence the location decisions of migrants, an effect captured by the correlation of incomes at the origin and potential destinations. We use the discrete choice model based on random utility maximization as the framework for our empirical investigation of migration from the United States rural to urban counties. This paper takes advantage of an equivalent relation between the conditional logit model and Poisson regression to study the migration decisions using aggregate data among a large set of spatial alternatives. The results show that the diversification concerns have significant effects on location decisions of the rural‐urban migrants in the United States.     

HEGEL AND PATHOLOGIZED MODERNITY,OR THE END OF SPIRIT IN THE ANTHROPOCENE

This article has two broad concerns, both of which are pursued primarily with reference to Hegel's philosophy of history. First, it examines whether Hegel can help explain the difficulty we have in modernity in responding to climate change and ecological crisis. It argues that Hegel provides a useful analysis of this problem, since the model of self‐determination that he appeals to is comprehensively embedded in embodied forms of culture. This helps explain why even a self‐correcting worldview like modernity is obdurate in the face of this crisis. Second, Hegel claims that the defining attribute of spirit is its capacity for self‐production. Modernity is characterized by the emerging and widespread knowledge that spirit is self‐producing. Modernity develops institutions that facilitate and provide an objective reality for spirit's self‐production and its freedom. This aspect of the article examines whether the distinctive capacity of spirit for self‐determination, which is realized in modernity, is subject to the same atrophying conditions by which Hegel says all other historical shapes of spirit are characterized. It asks if the present ecological crisis, something that is directly attributable to spirit itself, represents the limits of self‐producing spirit. The article concludes by examining the difficult position of those countries that cannot be considered to be responsible for the emergence of the Anthropocene but whose actions in the present will amplify its impact.     

Vulnerability to Bushfire Risk at Melbourne's Urban Fringe: The Failure of Regulatory Land Use Planning

The 7 February 2009 bushfires in the peri‐urban region to the north of metropolitan Melbourne heralded what many have called an entirely new epoch in terms of weather‐related disasters in Australia. A total of 173 people and 2000 properties were destroyed and, as with the 1939 fires in Victoria, a Royal Commission was subsequently instituted to inquire into the causes and responses to the fire. The Royal Commission has heard much evidence about alleged failings of fire response, communication and administration. It also considered land use planning issues and the associated regulatory framework. Using the Shire of Murrindindi as a case study, this paper argues that the location of population growth, and associated regulatory failure, are contributory, yet under‐researched, factors associated with life and property losses. The adoption of more robust planning tools which incorporate climate change considerations, we argue, is essential to anticipate and minimise the impacts of disastrous natural events such as bushfires. In the latter part of the paper, attention is drawn to a recent Victorian Civil and Administrative Tribunal decision which is groundbreaking in its use of the precautionary principle to prevent dwelling construction in an ‘inappropriate’ location as well as to some major inconsistencies between planning for flood and bushfire threats.     

Nonparametric Significance Test for Discovery of Network‐Constrained Spatial Co‐Location Patterns

Spatial co‐location patterns are useful for understanding positive spatial interactions among different geographical phenomena. Existing methods for detecting spatial co‐location patterns are mostly developed based on planar space assumption; however, geographical phenomena related to human activities are strongly constrained by road networks. Although these methods can be simply modified to consider the constraints of networks by using the network distance or network partitioning scheme, user‐specified parameters or priori assumptions for determining prevalent co‐location patterns are still subjective. As a result, some co‐location patterns may be wrongly reported or omitted. Therefore, a nonparametric significance test without priori assumptions about the distributions of the spatial features is proposed in this article. Both point‐dependent and location‐dependent network‐constrained summary statistics are first utilized to model the distribution characteristics of the spatial features. Then, by using these summary statistics, a network‐constrained pattern reconstruction method is developed to construct the null model of the test, and the prevalence degree of co‐location patterns is modeled as the significance level. The significance test is evaluated using the facility points‐of‐interest data sets. Experiments and comparisons show that the significance test can effectively detect network‐constrained spatial co‐location patterns with less priori knowledge and outperforms two state‐of‐the‐art methods in excluding spurious patterns.     

THE "CREATIVE CLASS" IN THE UK: AN INITIAL ANALYSIS

Richard Florida argues that regional economic outcomes are tied to the underlying conditions that facilitate creativity and diversity. Thus the Creative Class thesis suggests that the ability to attract creativity and to be open to diverse groups of people of different ethnic, racial and lifestyle groups provides distinct advantages to regions in generating innovations, growing and attracting high‐technology industries, and spurring economic growth. In this paper we investigate the extent to which there might be similar processes concerning the relationship between creativity, human capital, and high‐technology industries at work in the UK as in North America. The approach taken is broadly sympathetic to the Creative Class thesis; critical perspectives and reservations from the literature are introduced as appropriate research is focused around the three principal research questions: Where is the creative class located in the UK? What is the impact of quality of place upon this dispersion? What is the connection between the location of the creative class and inequalities in technical and economic outcomes within the UK? To this end, the creative class and its subgroups are defined and identified. We then construct quality of place indicators relating to tolerance, diversity, creativity and cultural opportunity. To these are added measures of public provision and social cohesion. Data are analysed by means of correlations and regression. In general we find that, although the distribution of the creative class is uneven and complex, our results are consistent with the findings of the North American research with the notable exception of technology‐based employment growth. Finally, priorities for further research are discussed. The need to further investigate causality, variations within the creative class itself, and the potential role of qualitative data in this are highlighted, as is the potential fate of “non‐creative” workers and places.     

HUMAN CAPITAL LOCATION CHOICE: ACCOUNTING FOR AMENITIES AND THICK LABOR MARKETS*

ABSTRACT A growing literature has found a positive association between human capital and long‐run employment growth across cities. These studies have increased interest in understanding the location choices of university degree holders, a group often used as a proxy measure of human capital. Based on data from the 2001 Canadian Census of Population, this paper investigates determinants of the location choices of degree and nondegree holders. With a multinomial logit model, it tests a series of hypotheses about the differential effects of thick labor markets and amenities on the location choice of these groups across metropolitan and nonmetropolitan areas in Canada.     

THE OPTIMAL DISTANCE TO PORT FOR EXPORTING FIRMS*

ABSTRACT Success in international trade depends, among other things, on distance from markets. Most new economic geography models focus on the distance between countries. In contrast, much less theorizing and empirical analysis have focused on how distances within a country—for instance, due to the location behavior of exporting firms—matter to international trade. In this paper, we contribute to the literature on the latter by offering a theoretical model to explain the optimal distance that an export‐oriented firm would locate from a port. We present empirical evidence in support of the model.     

THE JOINT CHOICE OF AN INDIVIDUAL'S OCCUPATION AND DESTINATION*

ABSTRACT This study examines the relationship between an individual's occupation choice and destination choice. It portrays the relationship as an interaction between the supply of occupational skills by individuals and demand by different labor‐market regions. The unusual merger of a multinomial logit model of occupational choice and the conditional logit model of destination choice in a simultaneous equation framework requires derivation of a unique variance–covariance matrix. Results indicate strong association between supply of (migration) and demand for (industry mix) an individual's occupational skills. These effects are especially strong for destinations experiencing slow economic growth, while relatively unimportant for high‐growth locations.