Aggregation of Regional Economic Time Series with Different Spatial Correlation Structures. 具有不同空间相关结构的区域经济时间序列集成

In this article, we compare the relative efficiency of different forecasting methods of space‐time series when variables are spatially and temporally correlated. We consider two cases: (1) univariate forecasting (i.e., a space‐time series aggregated into a single time series) and (2) the more general instance of multivariate forecasting (i.e., a space‐time series aggregated into a coarser spatial partition). We extend the results in the literature by including the consideration of larger datasets and the treatment of edge effects and of negative spatial correlation. We first introduce a statistical framework based on the space‐time autoregressive class of random field models, which constitutes the basis of our simulation study, and we present the various alternative forecasting methods considered in the simulation. We then present the results of a Monte Carlo study related to univariate forecasting. In order to allow a comparison with the findings of Giacomini and Granger (2004), we consider the same forecasting strategies and the same combinations of the parameter values used there, but with a larger parametric set. Finally, we extend our analysis to the case of multivariate forecasting. The outcomes obtained provide operational suggestions about how to choose between alternative forecasting methods in empirical circumstances.     

The Impact of Neutral and Nonneutral Productivity Growth on Creative Capital in a Trading Regional Economy. 区域经济贸易中中性和非中性生产力增长对创新资本的影响

We analyze a two‐sector model of a trading creative regional economy (TCRE) of the sort studied by Florida. Our analysis focuses on two cases. The first case concerns the impact of faster neutral, whereas the second case concerns the impact of faster nonneutral, productivity growth in the tradable sector on the employment of creative people in each of a TCRE's two sectors. In both cases, the sign of the percentage change in the steady‐state use of creative capital in the nontradable sector is ambiguous. In other words, the potential departure of creative people from the tradable to the nontradable sector does not depend upon whether the faster productivity growth being studied is neutral or nonneutral. In addition, because the effects of faster productivity growth in the tradable sector are not necessarily innocuous, a potential role exists for activist policy designed to countermand the possibly negative effects of faster productivity growth on either the tradable or the nontradable sector. This finding of possible “uneven development” is consistent with Florida's view that TCREs can give rise to externalities such as uneven regional development.     

Determinants of Variation in Population–Employment Interaction Findings: A Quasi‐Experimental Meta‐Analysis. 人口‐就业相互作用的决定因素研究：一种准实验元分析法

This article reports about a metaregression analysis of empirical results generated using data for the northern Netherlands (1988–2002) in order to investigate the ambiguity in results in the population–employment interaction literature. Specifically, the analysis deals with the issue whether “jobs follow people” or “people follow jobs.” The article starts with introducing the basics of quasi‐experimental meta‐analysis and with identifying some advantages of using quasi‐experimental meta‐analysis as compared with the standard meta‐analysis approach. Two subsequent sections document the selection of the population–employment interaction model and salient characteristics of the data set as well as the setup of the primary analyses. A total of 4,050 quasi‐experimental empirical results for the jobs–people direction of causality are generated using different specifications and estimators for a spatial econometric interaction model. The subsequent metaregression analysis reveals that the empirical results are largely shaped by the spatial, temporal, and employment characteristics of the data sampling. The results also appear much more sensitive to different measurements of the model's key variables when compared with alternative specifications of the spatial weights matrix. The main determinant driving empirical results about jobs–people causality are differences in model specification and estimation, as revealed by an inherent bias in parameter estimates and misguided inferences for some of the commonly used specifications. Finally, suggestions for future research are identified.     

Inferences for Selected Location Quotients with Applications to Health Outcomes. 选择性区位商推断及其在医疗成效中的应用

The location quotient (LQ) is an index frequently used in geography and economics to measure the relative concentration of activities. This quotient is calculated in a variety of ways depending on which group is used as a reference. Here, we focus on a simultaneous inference for the ratios of the individual proportions to the overall proportion based on binomial data. This is a multiple comparison problem and inferences for LQs with adjustments for multiplicity have not been addressed before. The comparisons are negatively correlated. The quotients can be simultaneously tested against unity, and simultaneous confidence intervals can be constructed for the LQs based on existing probability inequalities and by directly using the asymptotic joint distribution of the associated test statistics. The proposed inferences are appropriate for analysis based on sample surveys. Two real data sets are used to demonstrate the application of multiplicity‐adjusted LQs. A simulation study is also carried out to assess the performance of the proposed methods to achieve a nominal coverage probability. For the LQs considered, the coverage of the simple Bonferroni‐adjusted Fieller intervals for LQs is observed to be almost as good as the coverage of the method that directly takes the correlations into account.     

A Framework for Exploring Urban Retail Discontinuities. 探索城市零售业不连续性的框架

A key area in the analysis of urban structural evolution is identifying discontinuities. Effective analysis could improve long‐term forecasting and provide a better understanding of how to steer an urban system toward a desirable future state. We use a simple aggregate retail model to demonstrate an algorithm for identifying discontinuities in model parameter space. Explorations of retailing in both Greater London and South Yorkshire in the United Kingdom illustrate how understanding a system's potential for discontinuity can provide insights for both policy makers and retail businesses. The Harris and Wilson model, described in the section so‐named, is used as a simple archetype to illustrate the new framework. This model can be developed in a straightforward way to incorporate further refinement. In “ Executing the model and visualizing the results ,” we describe a single model run and in “ Investigating discontinuities ,” we explain our framework for detecting and analyzing discontinuities. “ Identifying discontinuities in the London retail system ” shows the results of applying this methodology to the Greater London retail system, and in “ Practical applications ,” we explore the policy applications for this technique as related to the decline of town centers in the South Yorkshire retail system. Some concluding comments are offered in “ Conclusions .”     

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.     

A Wavelet‐Based Extension of Generalized Linear Models to Remove the Effect of Spatial Autocorrelation. 基于小波扩展广义线性模型消除空间自相关的影响

Biogeographical studies are often based on a statistical analysis of data sampled in a spatial context. However, in many cases standard analyses such as regression models violate the assumption of independently and identically distributed errors. In this article, we show that the theory of wavelets provides a method to remove autocorrelation in generalized linear models (GLMs). Autocorrelation can be described by smooth wavelet coefficients at small scales. Therefore, data can be decomposed into uncorrelated and correlated parts. Using an appropriate linear transformation, we are able to extend GLMs to autocorrelated data. We illustrate our new method, called the wavelet‐revised model (WRM), by applying it to multiple regression with response variables conforming to various distributions. Results are presented for simulated data and real biogeographical data (species counts of the plant genus Utricularia [bladderworts] in grid cells throughout Germany). The results of our WRM are compared with those of GLMs and models based on generalized estimating equations. We recommend WRMs, especially as a method that allows for spatial nonstationarity. The technique developed for lattice data is applicable without any prior knowledge of the real autocorrelation structure.     

An Empirically Based Implementation and Evaluation of a Hierarchical Model for Commuting Flows. 一种基于经验的层状通勤流模型实现与评估

This article provides an empirical evaluation of a hierarchical approach to modeling commuting flows. As the gravity family of spatial interaction models represents a benchmark for empirical evaluation, we begin by reviewing basic aspects of these models. The hierarchical modeling framework is the same that Thorsen, Ubøe, and Nævdal (1999) used. However, because some modifications are required to construct a more workable model, we undertake a relatively detailed presentation of the model, rather than merely referring to the presentation in Thorsen, Ubøe, and Nævdal (1999) . The model uses a hierarchical specification of a transportation network and the individual search procedure. Journeys to work are determined by the effects of distance deterrence and of intervening opportunities, and by the location of potential destinations relative to alternatives at subsequent levels in a transportation network. The model calibration uses commuting data from a region in western Norway. The estimated parameter values are reasonable, and the explanatory power is very satisfactory when compared with the results of a competing destinations approach.     

The Colocation Quotient: A New Measure of Spatial Association Between Categorical Subsets of Points. 协同区位商：点集分类子集间空间关联性的新度量标准

This article presents a new metric we label the colocation quotient (CLQ), a measurement designed to quantify (potentially asymmetrical) spatial association between categories of a population that may itself exhibit spatial autocorrelation. We begin by explaining why most metrics of categorical spatial association are inadequate for many common situations. Our focus is on where a single categorical data variable is measured at point locations that constitute a population of interest. We then develop our new metric, the CLQ, as a point‐based association metric most similar to the cross‐k‐function and join count statistic. However, it differs from the former in that it is based on distance ranks rather than on raw distances and differs from the latter in that it is asymmetric. After introducing the statistical calculation and underlying rationale, a random labeling technique is described to test for significance. The new metric is applied to economic and ecological point data to demonstrate its broad utility. The method expands upon explanatory powers present in current point‐based colocation statistics.     

Gibrat Revisited: An Urban Growth Model Incorporating Spatial Interaction and Innovation Cycles. 再评吉尔布瑞特：顾及空间相互作用和创新周期的城市增长模型

We designed a geographical model for simulating the distribution of urban growth in systems of cities. The model incorporates the hierarchical and spatial diffusion of innovation cycles through gravitational interactions within a set of cities. Using theoretical simulations, we demonstrate that this model is able to reproduce the observed properties of urban systems for the log‐normal distribution of city sizes as well as the observed distribution of growth rates. Our experimentation was performed on a large harmonized historical database that includes a few hundred French urban agglomerations between 1831 and 1999 (Pumain‐INED database). Both spatial interaction and innovation cycles are necessary ingredients to explain the evolution of urban hierarchies. We suggest that Gibrat's generic stochastic growth model based on independent entities should be replaced by a more relevant model of spatially and temporally interdependent geographical entities.     

Weighted Bidimensional Regression. 加权二维回归

Shape analysis is useful for a wide variety of disciplines and has many applications. One of the many approaches to shape analysis focuses on shapes that are represented by predefined landmarks on an object. Some landmarks may be measured with greater precision, exhibit more natural variation, or be more important than others to an analysis. This article introduces a method for including this information when estimating mapping relations or assessing the degree of similarity between two objects that are represented by a set of two‐dimensional landmarks. Weighted bidimensional regression combines aspects of weighted least squares regression and bidimensional regression as a way to weight variables that are represented by a set of two‐dimensional spatial coordinates. One possible weighting scheme is suggested, and the effect of weighting is demonstrated through a face‐matching application. Results indicate that appropriate weighting increases the ability to correctly match two faces and that weighting has the largest effect when used with a projective transformation.     

A Hybrid Framework for Space–Time Modeling of Environmental Data. 环境数据时空建模的混合框架

The space–time autoregressive integrated moving average (STARIMA) model family provides useful tools for modeling space–time processes that exhibit stationarity (or near stationarity) in space and time. However, a more general method for routine use and efficient computation is needed to model the nonlinearities and nonstationarities of environmental space–time series. This article presents a hybrid framework combining machine learning and statistical methods to address this issue. It uses an artificial neural network (ANN) to extract global deterministic (nonlinear) space–time trends and a STARIMA model to extract local stochastic space–time variations in data. A four‐stage procedure is proposed for analyzing and modeling space–time series. The proposed framework and procedures are applied to forecast annual average temperature at 137 national meteorological stations in China. The results demonstrate that the hybrid framework achieves better forecasting accuracy than the STARIMA model alone. This finding suggests that the combination of machine learning and statistical methods provides a very powerful tool for analyzing and modeling space–time series of environmental data that have strong spatial nonlinear and nonstationary components.     

A Fractal Approach to Identifying Urban Boundaries. 城市边界识别的分形方法

Fractal geometry can be used for determining the morphological boundaries of metropolitan areas. A two‐step method is proposed here: (1) Minkowski's dilation is applied to detect any multiscale spatial discontinuity and (2) a distance threshold is located on the dilation curve corresponding to a major change in its behavior. We therefore measure the maximum curvature of the dilation curve. The method is tested on theoretical urban patterns and on several European cities to identify their morphological boundaries and to track boundary changes over space and time. Results obtained show that cities characterized by comparable global densities may exhibit different distance thresholds. The less the distances separating buildings differ between an urban agglomeration and its surrounding built landscape, the greater the distance threshold. The fewer the buildings that are connected across scales, the greater the distance threshold.     

A Geostatistical Linear Regression Model for Small Area Data. 一种适用于小区域数据的地统计线性回归模型

We present a new linear regression model for use with aggregated, small area data that are spatially autocorrelated. Because these data are aggregates of individual‐level data, we choose to model the spatial autocorrelation using a geostatistical model specified at the scale of the individual. The autocovariance of observed small area data is determined via the natural aggregation over the population. Unlike lattice‐based autoregressive approaches, the geostatistical approach is invariant to the scale of data aggregation. We establish that this geostatistical approach also is a valid autoregressive model; thus, we call this approach the geostatistical autoregressive (GAR) model. An asymptotically consistent and efficient maximum likelihood estimator is derived for the GAR model. Finite sample evidence from simulation experiments demonstrates the relative efficiency properties of the GAR model. Furthermore, while aggregation results in less efficient estimates than disaggregated data, the GAR model provides the most efficient estimates from the data that are available. These results suggest that the GAR model should be considered as part of a spatial analyst's toolbox when aggregated, small area data are analyzed. More important, we believe that the GAR model's attention to the individual‐level scale allows for a more flexible and theory‐informed specification than the existing autoregressive approaches based on an area‐level spatial weights matrix. Because many spatial process models, both in geography and in other disciplines, are specified at the individual level, we hope that the GAR covariance specification will provide a vehicle for a better informed and more interdisciplinary use of spatial regression models with area‐aggregated data.     

RURAL–URBAN SPATIAL INTERACTION IN THE GLOBAL SOUTH: LONG‐DISTANCE MOBILITY CHANGES,DESIRES AND RESTRICTIONS OVER TWO DECADES IN RURAL PHILIPPINES

The spatial interaction between rural and urban areas is intense in the Global South. While research into how this interaction influences livelihood opportunities is extensive, longitudinal identification and analysis of rural people's long‐distance mobility is rudimentary. This is problematic given the possible repercussions of a greater flow of people for transport system management (congestion, emissions, investments, social exclusion, etc.). Based on longitudinal survey data from 1990 to 2008/2009, this article addresses this gap by exploring how the long‐distance mobility behaviour of households and individuals has changed over a period of intensified rural–urban interaction in a rural Philippine area. The article furthermore addresses the individuals' mobility desires and restrictions related to long‐distance travel. The results indicate that both accessibility effects and effects related to information and communication technology (ICT), concentration of activities and opportunities towards major cities, age, labour market, and economic situation. Over time, particularly since improved accessibility conditions have enabled much faster travelling, more people have come to travel more frequently (although a suppressed demand is still present and inequalities are considerable) to more distant destinations, major cities in particular, for mainly social motives. A recent countertrend is evident, partly arising from mobile phones replacing physical movement. The increase in private vehicle ownership has so far been slow, so modal choice is still highly sustainable. Overall, the findings support core ideas derived from the new economic geography, but also notes, with earlier studies in transport geography, that travel time is a prime consideration.     

Minority–Majority Relations in the Schelling Model of Residential Dynamics. 住宅动态迁移Schelling模型中的少数‐多数关系

The Schelling model describing segregation between two groups of residential agents, reflects the most abstract, basic view of noneconomic forces motivating residential migrations: be close to people of “your own” kind. The model assumes that residential agents, located in neighborhoods where the fraction of “friends” is less than a predefined threshold value F, try to relocate to neighborhoods where this fraction is F or higher. For groups of equal size, Schelling's residential pattern converges either to complete integration (random pattern) or segregation, depending on F. We investigate Schelling model pattern dynamics as a function of F in addition to two other parameters—the ratio of groups' numbers, and neighborhood size. We demonstrate that the traditional integration–segregation pattern dichotomy should be extended. In the case of groups of different sizes, a wide interval of F‐values exists that entails a third persistent residential pattern, one in which a portion of the majority population segregates while the rest remains integrated with the minority. We also demonstrate that Schelling model dynamics essentially depend on the formalization of urban agents' residential behavior. To obtain realistic results, the agents should be satisficers, and the fraction of the agents relocating irrespective of the neighborhood's state should be nonzero. We discuss the relationship between our results and real‐world residential dynamics.     

A New Perspective about Moran's Coefficient: Spatial Autocorrelation as a Linear Regression Problem. Moran系数的新视角：空间自相关视为线性回归问题

The computation of Moran's index of spatial autocorrelation requires the definition of a spatial weighting matrix. The eigendecomposition of this doubly centered matrix (i.e., one that forces the sums of all rows and columns to equal zero) has interesting properties that have been exploited in various contexts: distribution properties of the Moran coefficient (MC), spatial filtering in linear models, generalized linear models, and multivariate analysis. In this article, this eigendecomposition is used to propose a new view of MC based on its interpretation in the simple context of linear regression. I use this interpretation to demonstrate the different properties of MC and also the inefficiency of this index in some situations involving simultaneous positive and negative spatial autocorrelation. I propose some new statistics and procedures for testing spatial autocorrelation, and conduct a simulation study to evaluate these new approaches.     

4. “KEEP THAT WOMAN OUT!” NOTIONS OF SPACE IN TWENTIETH‐CENTURY FLEMISH WITCHCRAFT DISCOURSE

This article considers the importance of a spatial dimension for witchcraft research, which has so far been largely neglected. In twentieth‐century Europe people in certain regions still considered their world in terms of witchcraft; they attributed misfortune to bewitchments and usually blamed their neighbors. Here a part of Flemish‐speaking Belgium is investigated with the help of legend texts collected in the 1960s. The witchcraft discourse that informed these texts did not just contain formulations of space; sometimes it also determined how people negotiated space. In this part of Flanders, witchcraft was embedded in Roman Catholicism; monasteries were the favored destinations of all those who considered themselves or their family members bewitched. In order to find cures for bewitchments people undertook hazardous journeys of considerable distance and found their efforts hindered by the witch they sought to counteract. The measures against evil influences that they were given were meant to consolidate the boundaries between their own (private) space and the (outside) space where witches roamed. Bewitchments were generally blamed on women. In the contemporary patriarchal social order, both public and domestic spaces were nearly always under men's control. This is why bewitchment was caused less by transgressions of male‐defined boundaries than by infringements of bodily spaces such as by eying or touching somebody else's children. This suggests a different approach to female space based on notions of proximity.     

2. CONSTRUCTIONS OF “HOME,”“FRONT,” AND WOMEN'S MILITARY EMPLOYMENT IN FIRST‐WORLD‐WAR BRITAIN: A SPATIAL INTERPRETATION

In First‐World‐War Britain, women's ambition to perform noncombatant duties for the military faced considerable public opposition. Nevertheless, by late 1916 up to 10,000 members of the female volunteer corps were working for the army, laying the foundation for some 90,000 auxiliaries of the official Women's Services, who filled support positions in the armed forces in the second half of the war. This essay focuses on the public debate in which the volunteers overcame their critics to understand how they obtained sufficient popular consent for their martial work. I explain the process in terms of shifting hegemonic understandings of space. As critics' arguments in the debate indicate, the gender attribution of war participation was organized and represented spatially, assigning men to the warlike “front” as warriors and women to the peaceful “home” as civilians. To redefine the meaning of these gendered wartime spaces, women volunteers deployed rival spatial discourses and practices in their campaign for martial employment. The essay explores the progress of these competing definitions through feminist and spatial theories, including gender performativity, discursively constructed and constructive spaces, and heterotopias. I argue that the upheaval caused by the war in gender and spatial norms undermined absolute conceptualizations of space with dichotomous binary areas on which critics drew for their arguments and reinforced more recent, relative spatialities, including the cultural construction of militarized heterotopic sites in between and paralleling both “home” and “front” for soldiers in training or recovery. The volunteers' efforts to gain access to military employment both contributed to and were supported by this shift. Heterotopic sites offered ideal discursive locations for constructing the new gender role of auxiliary soldiering through the performance of martial training and work, and competing spatial definitions provided arguments through which they could justify their activities to both critics and supporters.     

Space–Time Sequential Similarity for Identifying Factors of Activity‐Travel Pattern Segmentation: A Measure of Sequence Alignment and Path Similarity

The article develops a new method that compares activity‐travel patterns in both terms of the sequential order of activities and the shape of activity‐travel trajectory in time and space. The similarity of the list of activities and their order between activity‐travel patterns are computed by a sequence alignment method. The shape of activity‐travel trajectory is compared between the patterns using a path similarity technique that captures the direction and speed of a movement from the current location and the duration of staying at each location. The comparison results, therefore capture how people move around in three‐dimensional space–time choreography that indicates how people conduct which activities in what order. A total of 1,000 individuals are sampled from the data of 2016 Household Travel Survey, South Korea. The data provide the information of individual activity‐travel behavior and personal characteristics. The suggested method computes the pairwise distance matrix, and Ward clustering algorithm segments the pattern groups of similar activity sequences and space–time trajectories. A CHAID analysis then associates personal and household characteristics with the pattern groups to identify important factors for the segmentation. The analysis provides a significant implication in both terms of research and practice in transportation.