Representing the Shape and Orientation of Destinations in Spatial Choice Models

This paper illustrates the importance of spatial unit shape and orientation in spatial choice analysis. It also examines the implications of assuming spatial units to be dimensionless points in this context. Through theory and simulation experiments, it is shown how these aspects cannot be ignored and how the ordinary multinomial logit model applied at the spatially aggregate level is particularly vulnerable to such oversights. The aggregated spatial logit model in the end is recommended as a general formulation which addresses many of these fundamental issues of interest to geographers and regional scientists.     

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.     

ON FRONTIER SPECIFICATIONS FOR DISCRETE BINARY CHOICE ANALYSIS

ABSTRACT. In estimating a discrete choice model one is actually estimating the parameters of a conditional indirect utility function. I explore the consequences of recognizing that this function is a maximum-value (frontier) function. I formulate several frontier choice models and, using a pilot empirical study of transportation mode choice, compare the resulting estimates with those of the conventional logit specification. Most strikingly, it appears that the values of time implied by the frontier models are substantially below those of the logit model. This implies that policies designed to improve travel times may be of less value to consumers than is conventionally believed.     

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.     

On the Logit Approach to Competitive Facility Location

The random utility model in competitive facility location is one approach for estimating the market share captured by a retail facility in a competitive environment. However, it requires extensive computational effort for finding the optimal location for a new facility because its objective function is based on a k -dimensional integral. In this paper we show that the random utility model can be approximated by a logit model. The proportion of the buying power at a demand point that is attracted to the new facility can be approximated by a logit function of the distance to it. This approximation demonstrates that using the logit function of the distance for estimating the market share is theoretically founded in the random utility model. A simplified random utility model is defined and approximated by a logit function. An iterative Weiszfeld-type algorithm is designed to find the best location for a new facility using the logit model. Computational experiments show that the logit approximation yields a good location solution to the random utility model.     

Estimating a Destination-Choice Model from a Choice-based Sample with Limited Information

In most applications of multinomial logit and other probabilistic discrete-choice models, the estimation data set is either a simple random sample of the population of interest or an exogenously stratified sample. Often, however, it is cheaper and easier to sample individuals while they are carrying out the chosen activity of concern. This produces a choice-based sample, which presents important problems of estimation and inference. This paper is concerned with estimation of destination-choice models from choice-based samples when neither the aggregate market shares of alternatives nor the probability distribution of explanatory variables in the population is known. The method of Cosslett (1981) for estimating multinomial logit models from such data is summarized, and the limitations on information about choice behavior that can be recovered from the sample are explained. An empirical model of pharmacy choice in the Namur, Belgium, area is presented. It is shown that useful and important information about destination-choice behavior can be obtained from a choice-based sample, even without knowledge of aggregate market shares and the probability distribution of explanatory variables.     

Exogenous Workplace Choice in Residential Location Models: Is the Assumption Valid?

This paper examines the assumption implicit in most models of residential location that the choice of workplace is exogenously determined. Monocentric models have generally made this assumption, but it has come under increasing scrutiny. A nested logit model of workers' choices of workplace, residence, and housing tenure within the Dallas-Fort Worth metropolitan area is developed to provide a test. A unique dataset that includes the workplace and residence census tracts of workers in Dallas-Fort Worth, and their demographic and socioeconomic characteristics, is used to estimate the model. The results confirm that a joint choice specification better represents actual choice behavior in a multinodal metropolis.     

Industrial Location Modeling: Extending the Random Utility Framework*

Abstract. Given sound theoretical underpinnings, the random utility maximization‐based conditional logit model (CLM) serves as the principal method for applied research on industrial location decisions. Studies that implement this methodology, however, confront several problems, notably the disadvantages of the underlying Independence of Irrelevant Alternatives (IIA) assumption. This paper shows that by taking advantage of an equivalent relation between the CLM and Poisson regression likelihood functions one can more effectively control for the potential IIA violation in complex choice scenarios where the decision maker confronts a large number of narrowly defined spatial alternatives. As demonstrated here our approach to the IIA problem is compliant with the random utility (profit) maximization framework.     

A Novel Procedure for Simplified Nonlinear Numerical Modeling of Structural Units in Masonry Aggregates

ABSTRACT

Historical centers are always composed of masonry building aggregates often designed without respecting seismic design criteria. The current seismic Italian code does not foresee a clear calculation method to predict their static nonlinear behavior. For this reason, in this article the seismic response of structural units into masonry aggregates has been predicted through a simplified modeling approach. The implemented procedure has been calibrated on the results of a numerical model performed by using the Equivalent Frame Method (EFM), implemented within a Finite Element Method (FEM) calculation program, used to investigate a basic building compound representative of the constructive techniques developed in the past decades in the Southern Italy.

First, the whole aggregate has been modeled and analyzed in the nonlinear static field in order to evaluate the seismic behavior of both intermediate and head structural units.

Later on, the seismic response of these structural units, considered as isolated structures, has been assessed by considering in simplified way their position in the aggregate, as well as the influence of other constructions.

Finally, the achieved results on the above single analysis cases have been compared with those deriving from the investigation of the whole building compound, allowing to confirm the effectiveness of the proposed novel analysis procedure.     

Incorporating the effects of spatial structure in discrete choice models of migration

Discrete-choice theory and logit models are evaluated for their usefulness in analyzing migration patterns in a zonal system. The authors "argue that spatial effects and more specifically the relative location of zones are not taken into account in such analyses. We, therefore, introduce a measure of spatial structure and advocate its usage as a predictor of migration in such models. In an example of intrametropolitan migration in Toronto [Canada], we demonstrate that this variable is not only significant but also it improves the performance of all the other variables with the greatest impact on the distance between zones. In addition, inclusion of this variable improves the overall performance of the model in terms of residuals."     

Simultaneous-Equation Systems Involving Binary Choice Variables

Simultaneous-equation systems of continuous variables are well known in the social sciences. Unfortunately, these methods cannot be used when dealing with discrete endogenous variables. Although for discrete types of data a broad range of methods and techniques have been developed, their applicability is restricted to single-equation systems (for example, logit or probit formulations) or to association-type models (log-linear models), mainly because of the lack of suitable estimation methods and computer programs. The basic problem is the multivariate error structure of the endogenous variables. This paper presents a simultaneous-equation system of binary endogenous variables. The model is applied empirically to longitudinal data on mode choice and is compared with the well-known log-linear model.     

Theoretical and Numerical Seismic Analysis of Masonry Building Aggregates: Case Studies in San Pio Delle Camere (L’Aquila,Italy)

Masonry building aggregates are large parts of the Italian building heritage often designed without respecting seismic criteria. The current seismic Italian code does not foresee a clear calculation method to predict their static nonlinear behavior. For this reason, in this article a simple methodology to forecast the masonry aggregate seismic response has been set up. The implemented procedure has been calibrated on the results of two FEM structural analysis programs used to investigate three masonry building compounds. As a result, a design chart used to correctly predict the base shear of aggregate masonry units starting from code provisions has been set up.     

Multiple Contexts as Cross-classified Models: The Labor Vote in the British General Election of 1992

Voters make their decisions in social and geographical contexts that can be seen as different levels in an overall data structure. Increasingly these structures are being analyzed by multilevel models, but this approach has so far been limited to structures that are strictly hierarchical. This paper outlines the approach of cross-classified multilevel models in which units at lower levels in the structure can be nested in more than one higher-level unit simultaneously. An appropriate modeling framework is outlined, models are specified, and particular attention is paid to efficient computation. The approach is illustrated through a cross-classified logit analysis of Labor versus Conservative support for a nationally representative sample of voting behavior for the 1992 British General Election. The data is structured so that individual voters at level 1 are nested within constituencies at level 2 which are cross-classified by geographical and functional regionalizations at level 3. A conclusion discusses the general utility of a cross-classified approach to geographically based contextual research, while two technical appendices provide details on model estimation.     

THE AGGREGATED SPATIAL CHOICE MODEL VS. THE MULTINOMIAL LOGIT: AN EMPIRICAL COMPARISON USING MIGRATION MICRODATA

Frequently, in spatial interaction analysis, researchers are forced to use destinations that are zonal aggregates of the ‘real’ destinations perceived by the participants in the interaction process. Previous simulation studies demonstrated that, under certain circumstances, the aggregated spatial choice model can outperform the popular ordinary multinomial logit model, both in explanatory power and predictive ability. In this paper, the two models are compared with interprovincial migration microdata for the time period 1990-91, obtained from the 1991 Canadian census. Since this is not meant to be a migration study, the analysis is limited to out-migrants from Ontario. The results indicate that, at least with the data used, the multinomial logit model performed reasonably well. The paper, however, highlights some practical advantages that can accrue from the use of the aggregated model. Dans l'analyse de l'interaction à référence spatiale, il arrive fréquemment que les chercheurs soient contraints de se servir de destinations qui regroupent les?vraies?destinations perçues par les participants dans le processus d'interaction. Les études en simulations antérieures ont démontré que, dans certaines circonstances, le modèle groupé des choix à référence spatiale peut donner de meilleurs résultats que le modèle ordinaire commun du logit multinomial, sur le plan de la capacité d'explication comma sur celui de la valeur de prévision. Dans la présente étude, on fait la comparaison entre les deux modèles en utilisant les microdonnées sur l'émigration interprovinciale en 1990-91 obtenues par le recensement de 1991. L'analyse ne porte que sur les émigrants de l'Ontario puisqu'elle ne vise pas particulièrement l'étude de l'émigration. D'après les résultats, le modèle employant le logit multinomial fonctionne relativement bien, au moins avec les données utilisées. Toutefois, l'étude souligne certains avantages pratiques pouvant inciter à se servir davantage du modèle groupé.     

Exposing Unobserved Spatial Similarity: Evidence from German School Choice Data

In a spatial context, flexible substitution patterns play an important role when modeling individual choice behavior. Issues of correlation may arise if two or more alternatives of a selected choice set share characteristics that cannot be observed by a modeler. Multivariate extreme value (MEV) models provide the possibility to relax the property of constant substitution imposed by the multinomial logit (MNL) model through its independence of irrelevant alternatives (IIA) property. Existing approaches in school network planning often do not account for substitution patterns, nor do they take free school choice into consideration. In this article, we briefly operationalize a closed‐form discrete choice model (generalized nested logit [GNL] model) from utility maximization to account for spatial correlation. Moreover, we show that very simple and restrictive models are usually not adequate in a spatial choice context. In contrast, the GNL is still computationally convenient and obtains a very flexible structure of substitution patterns among choice alternatives. Roughly speaking, this flexibility is achieved by allocating alternatives that are located close to each other into nests. A given alternative may belong to several nests. Therefore, we specify a more general discrete choice model. Furthermore, the data and the model specification for the school choice problem are presented. The analysis of free school choice in the city of Dresden, Germany, confirms the influence of most of the exogenous variables reported in the literature. The estimation results generally indicate the applicability of MEV models in a spatial context and the importance of spatial correlation in school choice modeling. Therefore, we suggest the use of more flexible and complex models than standard logit models in particular. En un contexto espacial, los patrones sustitución flexible juegan un papel importante en el modelamiento del comportamiento de las decisiones individuales. Varios problemas de correlación pueden presentarse si dos o más alternativas de elección comparten características no observables por el modelador. Los modelos de valor extremo (multivariate extreme value‐MEV) ofrecen la posibilidad de relajar la propiedad de sustitución constante (constant substitution) presente en los modelos logit multinomiales (multinomial logit‐MNL), a través de su propiedad de independencia de alternativas irrelevantes (Independence of irrelevant alternatives property ‐IIA). A menudo, los enfoques existentes en la planificación de redes escolares no toman en consideración los patrones de sustitución y de libre elección de escuela. En este artículo, los autores presentan brevemente el funcionamiento de un modelo de elección discreta (discrete choice model) para la maximización de utilidad o modelo logit anidado generalizado (generalized nested logit model‐GNL) para dar cuenta de la autocorrelación espacial. Los autores sostienen que modelos demasiado simples y restrictivos no suelen ser adecuados en un contexto de elección espacial. En contraste el modelo GNL es conveniente en términos de su computación y obtiene una estructura muy flexible de los patrones de sustitución entre las alternativas de elección. En términos generales, esta flexibilidad se logra mediante la asignación (o anidación) de las alternativas cercanas en el espacio (una alternativa puede pertenecer a varios nidos). Por lo tanto, los autores presentan un modelo de elección discreta más general. El estudio presenta además datos y la especificación del modelo para un caso de elección de escuela concreto: el análisis de libre elección de escuela en la ciudad de Dresden, Alemania. El análisis confirma la influencia de la mayoría de las variables exógenas presentes en la literatura. Los resultados de la estimación demuestran en términos generales la aplicabilidad de los modelos MEV en un contexto espacial y la importancia de la autocorrelación espacial en el modelado de elección de escuela. Los autores concluyen sugiriendo el uso de modelos más flexibles y complejos que los modelos utilizados habitualmente, en particular los modelos logit estándar. 从空间视角看,灵活的替代模式在个人行为选择建模中发挥着重要作用。当存在两个或两个以上备选方案集具有共性且无法被建模者观察到时,就可能出现相关性问题。多元极值模型（MEV）通过不相关的替代属性（IIA）实现了对多元logit模型（MNL）中常数限制的松弛替代。现有校园网络规划方法通常无法解释替代模式,而且没有考虑到自由择校因素。本文简要地建立一个封闭离散选择模型（广义嵌套（GNL）模型）,从效用最大化角度来解释空间相关性。此外分析还表明,非常简单的约束模型通常不具有足够的空间选择情境。相比之下,GNL模型计算便捷,且可以在各选择方案中获得非常灵活的替代模式。大致而言,这种灵活性大体是通过与住处位置距离上彼此靠近的替代选择分配而获得,一个给定的选择可能属于不同的住处。因此,我们给出了一个更一般的离散选择模型。此外,还给出了针对择校问题的数据和模型设定。基于德国德累斯顿市自由择校分析,证实了已有研究中多数外生变量的影响。估计结果证实了MEV模型在空间分析中的适用性以及择校模型中空间相关的重要性,并建议使用更加灵活和复杂的模型而不是标准的logit模型。     

Does Believing Homosexuality Is Innate Increase Support for Gay Rights?

Why are Americans who believe homosexuality is innate more likely to support the rights of lesbians, gay men, and bisexuals (LGBs)? Attribution theory suggests that people are more likely to support LGB rights if they do not blame LGBs for their sexual orientation. Alternatively, moral condemnation of homosexuality may lead both to belief that homosexuality is a choice and opposition to LGB rights, while acceptance of LGB rights may lead to a belief in a biological basis for homosexuality as part of a constellation of tolerant beliefs. Using logit analysis on individual‐level data from 24 national surveys conducted since 1977, I find that the link between belief in a biological basis for homosexuality and support for LGB rights is strong and growing for almost all groups on almost all issues. The reason may have more to do with people shaping their origin beliefs to match their political and religious values, than with origin beliefs affecting support for LGB rights.     

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.     

Travel-Time Constraints on Destination-Choice Sets

The importance of travel-time constraints in spatial choice is widely recognized in the literature of geography and related disciplines, but little work has been done toward developing operational models of spatial choice wherein these constraints and their effects are made explicit. The purpose of the paper is to test the accuracy of predictions produced by a destination choice model that does not take explicit account of travel constraints under the assumption that observed choices are made from choice sets delineated by a constraint of maximum travel time. Observed choices are generated by simulation from a new random utility model consistent with the constrained nature of individual choice sets. Results show that the characteristics of constraints are a decisive factor in the accuracy of the unconstrained choice model. Choice probabilities of the constrained reality are predicted with a reasonably good accuracy in some instances, but predictions are less impressive, and even poor, in many others.     

Impacts of Multiple-Period Lags in Dynamic Logit Models

This paper will provide an introduction to a new field of research, viz. the sensitivity of the solution trajectory of a dynamic logit model (belonging to the class of discrete choice models) in the light of a multiperiod lag structure. It is well known from recent advances in the area of chaos and turbulence theory that the stability of a dynamic system is critically dependent on various factors, such as threshold values of parameters, initial conditions, and also the lag structure. This paper aims to identify the consequences of different lag structures in dynamic logit models (including also dynamic spatial interaction models). Various simulation experiments will be used to show that the onset of instability of the solution trajectory tends to decrease as the number of time lags increases (depending also on the growth rate of the system).     

Heterogeneity of birth-state effects on internal migration

Working in a discrete location choice framework, we develop a model of migration that allows the identification of heterogeneity in state-of-birth effects across states. We employ a novel method for using aggregate data to estimate the role of birth state on migration choices. This approach reveals considerable heterogeneity and some regional clustering in birth-state inertia effects across states, with strong attachments in California, the Southwest, and the upper Midwest. The weakest attachments are in the mountain states and New York.