NETWORK LOADING VERSUS EQUILIBRIUM ESTIMATION OF THE STOCHASTIC ROUTE CHOICE MODEL MAXIMUM LIKELIHOOD AND LEAST SQUARES REVISITED*

Daganzo (1977, 1979), Daganzo and Sheffi (1977), Sheffi (1985), and Sheffi and Daganzo (1980) have used one assumption about traveler behavior in developing estimation techniques for the stochastic route-choice problem and another assumption in predicting flows on networks by using the same model. In estimation, they calculate the congested travel costs of the network links from observed flows on the network, and the network is loaded based on these costs. In prediction, they follow their stochastic user-equilibrium assumption by which travelers evaluate costs using the mean of the observed flows (or equilibrium flows). The travel-cost coefficient obtained from the loading method systematically overestimates the true travel-cost coefficient from which the observed flow data (which must be used in loading) is generated. The estimates of the same coefficient, obtained in this paper, by constraining the estimation results to conform to the equilibrium conditions are unbiased, and only marginally less efficient (have larger standard deviations). The average percentage error and inefficiency of the link flow predictions based on the loading method increases as the level of congestion on the network rises. In contrast, the average percentage error of link flow predictions based on the equilibrium estimation method declines and their efficiency remains very high as the level of congestion on the network rises.     

基于土地利用数据和夜间灯光数据的人口空间化模型对比分析——以黄河三角洲高效生态经济区为例

人口统计数据空间化是解决统计数据与自然要素数据融合分析的有效途径。随着RS和GIS技术的发展,人口空间化方法推陈出新,但不同的方法各有优缺点,方法选择和精度保证是两个重要的问题。本文以黄河三角洲高效生态经济区2010年县(市、区)单元人口统计信息为案例,分别基于土地利用数据和夜间灯光数据建立1km栅格的人口空间化模型,再分别以县(市、区)和乡(镇、街道办)为验证单元,比较两种方法模拟人口分布的优缺点。结果表明,基于土地利用数据的人口空间化模型整体优于基于夜间灯光数据的人口空间化模型,且前者更适合于模拟人口总数居中的县(市、区),后者在人口密度梯度较大的城镇边缘有更好的模拟效果,在人口较少的地区二者的模拟效果均不太理想。本研究能够为获取高精度的区域人口空间化模型提供参考。     

Sequential, Bayesian Geostatistics: A Principled Method for Large Data Sets

The principled statistical application of Gaussian random field models used in geostatistics has historically been limited to data sets of a small size. This limitation is imposed by the requirement to store and invert the covariance matrix of all the samples to obtain a predictive distribution at unsampled locations, or to use likelihood-based covariance estimation. Various ad hoc approaches to solve this problem have been adopted, such as selecting a neighborhood region and/or a small number of observations to use in the kriging process, but these have no sound theoretical basis and it is unclear what information is being lost. In this article, we present a Bayesian method for estimating the posterior mean and covariance structures of a Gaussian random field using a sequential estimation algorithm. By imposing sparsity in a well-defined framework, the algorithm retains a subset of " basis vectors " that best represent the " true " posterior Gaussian random field model in the relative entropy sense. This allows a principled treatment of Gaussian random field models on very large data sets. The method is particularly appropriate when the Gaussian random field model is regarded as a latent variable model, which may be nonlinearly related to the observations. We show the application of the sequential, sparse Bayesian estimation in Gaussian random field models and discuss its merits and drawbacks.     

ANALYZING POLICY IMPACT: SELECTION OF A LINEAR TREND MODEL

Policy analysts, as well as politicians, have shown great interest in assessing both short-term and long-term consequences of public policies in recent years. Recent time-trend studies have attempted to depict the time dimension of policy consequences through extensions of regression techniques. This study examines three linear trend models which have been used to depict policy impact through time-series analyses, and identifies the relative advantages and disadvantages associated with the use of each model. The three models are applied in a quasi-experimental time-series design to time-series of per capita state expenditures for large cities, in eight states, over a twenty-year period. Differences in degrees of multicollinearity and autocorrelation inherent in the three models are discussed, and the model providing the most conservative coefficient estimates is identified.     

苏州市旅游者目的地消费支出空间分布特征研究

基于2003年江苏省国内游客抽样调查资料,选择以苏州为目的地的来自188个地级市的3337份有效游客样本,在综合考虑社会经济要素的基础上,采用相关分析等统计学方法进行研究,结果显示:旅游者在苏州市的目的地消费支出空间分布特征曲线分为两个阶段:递增阶段和停滞阶段。采用同样的方法对江苏省内游客样本进行了研究,结果验证了这种空间分布特征的可靠性。从不同细分消费项目角度的进一步研究发现,住宿、餐饮消费项目对总体消费的空间分布特征贡献最大,娱乐消费项目对总体消费的空间分布特征贡献较大,而其它消费项目贡献不显著。     

Explorations and Syntheses of Linear Programming And Spatial Interaction Models of Residential Location

Various “linear programming” models of residential location are explored in some detail. It is then shown that entropy maximizing “sub-optimal” versions of these can be developed, which may be more realistic at typical levels of resolution used for analysis but can still be given some of the interpretations of the programming models. Further, any programming model can be seen as a limiting case of some entropy maximizing model in which some of the parameters tend to infinity. Some empirical tests of both kinds of models are presented, and the limiting relationships are discussed.     

The contribution of Sir Alan Wilson to spatial interaction and transport modelling

ABSTRACT

In a series of papers in the mid-1960s and early 70s, building on his key 1967 paper, Alan Wilson made a series of fundamental contributions to the specification and application of land-use transport models. In this paper the basis of his entropy-maximizing approach to spatial distribution models is outlined with a demonstration that the methods have applications very much beyond its transport roots. The entropy maximization method laid the foundations for the development of a range of multinomial logit share models. He expanded the core transport ideas to the whole range of comprehensive models, initially building on, and extending, Lowry's iconic Pittsburgh model. The factors that have sustained the longevity of Wilson's models are explored and articulated.     

现代服务业集聚形成机理空间计量分析

在纳入空间效应前提下,构建现代服务业集聚形成机理空间面板计量模型,对我国28个省域相关数据实证研究表明:我国现代服务业集聚在省域之间有较强的空间依赖性和正的空间溢出效应。技术差异在时间维度上对现代服务业集聚促进作用显著,在空间维度上并不显著;交易费用与现代服务业集聚有显著的负相关性;知识溢出、规模经济、政府行为对现代服务业集聚促进作用显著。     

STATISTICAL SEISMIC VULNERABILITY ASSESSMENT OF EXISTING REINFORCED CONCRETE BUILDINGS IN TURKEY ON A REGIONAL SCALE

A statistical procedure, called discriminant analysis, is used to develop a model for the preliminary assessment of the seismic vulnerability of low- to medium-rise (2-7 storey) reinforced concrete buildings. The earthquake damage data compiled in Düzce province after the 12 November 1999 Düzce earthquake formed the damage database. Number of storeys, minimum normalised lateral stiffness index, minimum normalised lateral strength index, normalised redundancy score, soft storey index and overhang ratio are selected as the basic damage inducing variables. Two discriminant functions are derived in terms of these variables considering immediate occupancy and life safety performance levels. In the proposed preliminary seismic vulnerability assessment model, the discri-minant scores obtained from these two discriminant functions are combined in an optimal way and axe used to classify existing buildings as “safe”, “unsafe” and “requires further evaluation”. The optimality criterion imposed into the model is the minimisation of the misclassification rate of damage states causing collapse. The validity of the proposed model is checked by using the seismic damage data associated with recent earthquakes that occurred in Turkey. The consistency between the observed damage distribution and the predictions of the proposed model supports the effectiveness of the proposed model.     

THE BAYESIAN APPROACH TO THE INTERPRETATION OF ARCHAEOLOGICAL DATA

Archaeologists are increasingly becoming aware of an approach to data investigation known as Bayesian statistics. In this paper we outline both the philosophical and statistical background to the approach. We show that it provides a logical and coherent framework in which to make inferences on the basis of both data and a priori expert knowledge. We note that adoption of the Bayesian framework is particularly timely since there have been recent dramatic developments in numerical methods which mean that a number of previous implementation problems have now been solved. As a result, many questions of archaeological interest, which require the use of complex statistical models, are being investigated using this methodology. We use a variety of recently published examples from a range of archaeological areas to illustrate the type of questions that can be answered and the nature of the methodologies used, and we make comparisons with the results obtained using more traditional statistical techniques.     

当代国外城市模型研究的进展与未来

由于城市的复杂性、系统性和不可逆性,对城市问题的诊断与解决也必须运用系统化、模型化的方法。本文综述了1980年代以来,城市模型研究在基础理论、模型方法、技术和研究内容上新的发展。认为当代城市模型研究存在的突出问题是:仍然沿用工业化城市的经济社会规律,研究已经被信息化和全球化所深刻影响的城市;复杂性科学理论的综合性不够;GIS与其它模型的集成度有待提高。未来城市模型的研究应着重关注新的城市变化,综合运用复杂性科学的理论与方法,强化以GIS为平台的计算机技术。     

AN EXAMINATION OF STATE FOREIGN EXPORT PROMOTION AND MANUFACTURING EXPORTS*

ABSTRACT As a means of promoting economic development state governments are increasing their levels of support for export promotion; however, there has been virtually no statistical analysis of the effects of the state export promotion expenditures. The present study specifies and estimates a cross-section model in order to quantify the relationship between state export promotion and exports. The empirical analysis allows for the calculation of the export promotion elasticity of exports on a state basis. Two conclusions are that the rationale supporting export promotion expenditures is supported empirically and that there is much diversity among states for the estimated elasticity.     

A Selection Bias Approach to Destination Choice

Research on consumer search behavior commonly envisages destination choice as a two-step process: (1) delineate the search set, and (2) evaluate choices therein. However, much of the empirical work in destination choice—including logit and nested logit formulations—models only the latter, and not the set delineation itself. In the presence of correlation between error terms in set delineation and choice selection, statistical estimators are biased, a problem that Heckman and others have called selection bias. In this paper, an alternative two-stage method is proposed to estimate the parameters of models of set delineation and choice selection. Monte Carlo simulation is used to explore the properties of these two-stage estimators, and to show the magnitude of bias inherent in traditional methods of estimation.     

Statistical Network Analysis for Analyzing Policy Networks

To analyze social network data using standard statistical approaches is to risk incorrect inference. The dependencies among observations implied in a network conceptualization undermine standard assumptions of the usual general linear models. One of the most quickly expanding areas of social and policy network methodology is the development of statistical modeling approaches that can accommodate such dependent data. In this article, we review three network statistical methods commonly used in the current literature: quadratic assignment procedures, exponential random graph models (ERGMs), and stochastic actor‐oriented models. We focus most attention on ERGMs by providing an illustrative example of a model for a strategic information network within a local government. We draw inferences about the structural role played by individuals recognized as key innovators and conclude that such an approach has much to offer in analyzing the policy process.     

Exploring Spatial Process Dynamics Using Irregular Cellular Automaton Models

Cellular automaton models have enjoyed popularity in recent years as easily constructed models of many complex spatial processes, particularly in the natural sciences, and more recently in geography also. Most such models adopt a regular lattice (often a grid) as the basis for the spatial relations of adjacency that govern evolution of the model. A number of variations on the cellular automaton formalism have been introduced in geography but the impact of such variations on the likely behavior of the models has not been explored. This paper proposes a method for beginning to explore these issues and suggests that this is a new approach to the investigation of the relationships between spatial structure and dynamics of spatial processes. A framework for this exploration is suggested, and details of the required methods and measures are provided. In particular, a measure of spatial pattern—spatial information—based on entropy concepts is introduced. Initial results from investigation along the proposed lines are reported, which suggest that a distinction can he made between spatially robust and fragile processes. Some implications of this result and the methodology presented are briefly discussed.     

江苏省城市化质量的区域差异时空分析

根据城市化的内涵及推进城市化的目的,从人口城市化、经济城市化、居民生活城市化、景观环境城市化和基础设施城市化等五个方面,构建区域城市化质量的综合评价指标体系,运用熵值法,对2001-2009年江苏县市城市化质量进行综合测度,并以此为变量,运用差异系数,对江苏县市城市化质量差异的演变过程与空间格局进行定量分析。结果发现:2001-2009年江苏区域城市化质量差异总体扩大的基础上呈现先扩大后缩小趋势,且主要表现为经济发展质量差异、基础设施质量差异和居民生活质量差异,人口发展质量差异和景观环境质量差异则相对较小;在空间上,县市城市化质量提升有向环太湖地区不断极化的态势。其中,地级市区以向下收敛为主;苏中和苏北县域以向上收敛为主,而沿海地区县域以向下发散为主;苏南地区的沿江县域以向下收敛为主,环太湖县域则以向上发散为主。     

PROBLEMS OF THE LEVEL OF THE CASPIAN AND THE STABILITY OF ITS SHORELINE

The first of two papers on the problem of forecasting the level of the Caspian Sea evaluates factors widely believed to have been responsible for its lowering during much of the present century (including tectonic movements, climatic cycles, human activity). It concludes that previous forecasts have been inaccurate because of the failure to adequately model the complexity of processes involved, specifically the internal mechanisms of “self-regulation” of water levels. Continuation of the recent slight rise in the Caspian's level is predicted at least into the early 1990s (translated by Andrew R. Bond).     

MEASURES OF DIVERSIFICATION: PREDICTORS OF REGIONAL ECONOMIC INSTABILITY*

This work focuses on determining which measure of regional economic diversification best explains differences in economic instability across regions. One recent article found that a portfolio variance measure had the highest explanatory power. Another researcher found that an entropy measure was best after the model was corrected for heteroscedasticity. Results presented here indicate that, after correction for heteroscedasticity, portfolio variance once again displays the greatest power to explain cross-sectional variation in observed regional instability.     

RESIDENTIAL PATTERNS OF NEW IMMIGRANTS AND LINGUISTIC INTEGRATION

The present study looks at the residential patterns of new immigrants in Montreal and their impact on subsequent language use in the workplace and educational programs. We first explore the themes of language and territory, citing evidence for the neighbourhood of residence as being a site of language contact organized linguistically around models corresponding to the majority language spoken by its population. Secondly, we explore a sample of 1000 new immigrants, situating them in francophone, anglophone, allophone, and heterogeneous neighbourhoods. Three aspects of their residential establishment are examined: their distribution within the neighbourhoods of Montreal, the factors determining the choice of one or another of the four types of linguistic milieux, and the influence of these milieux on subsequent language use. These latter two aspects use Event History Analysis, a statistical model permitting the longitudinal analysis of dated data.