Wives,Children … Husbands: Supporting Roles

In 1965, Hugo L. Black asked his wife, Elizabeth, to host a dinner party. The purpose: to help him persuade Carolyn Agger, wife of Washington attorney Abe Fortas, to allow her husband to accept President Lyndon B. Johnson's offer of a seat on the Supreme Court. A tax lawyer at the same firm as Fortas, Agger was displeased that the move would mean a big cut in his salary; she thought he should spend a few more years in his lucrative private practice before becoming a judge. After all, he was only fifty‐five. Elizabeth Black described the tense occasion in a diary entry:     

Adaptive Cell Tower Location Using Geostatistics. 基于地统计学的适应性基站发射塔选址研究

In this article, we address the problem of allocating an additional cell tower (or a set of towers) to an existing cellular network, maximizing the call completion probability. Our approach is derived from the adaptive spatial sampling problem using kriging, capitalizing on spatial correlation between cell phone signal strength data points and accounting for terrain morphology. Cell phone demand is reflected by population counts in the form of weights. The objective function, which is the weighted call completion probability, is highly nonlinear and complex (nondifferentiable and discontinuous). Sequential and simultaneous discrete optimization techniques are presented, and heuristics such as simulated annealing and Nelder–Mead are suggested to solve our problem. The adaptive spatial sampling problem is defined and related to the additional facility location problem. The approach is illustrated using data on cell phone call completion probability in a rural region of Erie County in western New York, and accounts for terrain variation using a line‐of‐sight approach. Finally, the computational results of sequential and simultaneous approaches are compared. Our model is also applicable to other facility location problems that aim to minimize the uncertainty associated with a customer visiting a new facility that has been added to an existing set of facilities.     

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.     

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.     

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.     

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.     

A Theory‐Based Cellular Automata for the Simulation of Land‐Use Change. 基于理论细胞自动机的土地利用变化模拟

This study proposes a theory‐based cellular automata (CA) in which CA rules are constructed on the basis of a theory of urban land‐use change and other local conditions. Rent gap theory that describes urban redevelopment and exogenous conditions that reflect urban development are embedded into a CA to simulate changes of land use. The theoretical framework provides a strong conceptual background for the CA simulation. A case study demonstrates the flexibility of the integrated framework for simulating land‐use changes in complex settings. This research aims to help decision‐makers formulate appropriate development plans.     

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 .”     

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.