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.     

Modeling Strategies for Categorical Data: Examples from Housing and Tenure Choice

Models to investigate categorical data can be divided into preprocessing, limited parameterization, and formal logit models. To illustrate the advantages of preprocessing and limited parameterization models they are applied to a data set of tenure and type of housing choice before the data are examined with hierarchical logit and nested logit models. The preprocessing approaches are useful in selecting optimal subsets of independent variables with respect to the dependent variable. The ease of application and interpretation of a limited parameterization approach extends the clarity of the results from the preprocessing approaches. Because some variables are only relevant at specific levels of other independent variables, nonstandard (nested) logit models are necessary to understand the nested relationships.     

METROPOLITAN OUTMIGRATION PATTERN OF CANADIAN LABOUR FORCE ENTRANTS, 1971–76

This paper analyses the 1971 -76 metropolitan out-migration pattern of Canadian males in the labour force entrance age group. Migration is conceptualized within a three-level choice framework, and statistical inference is based on a multinomial logit model. It was found (1) that the propensity to outmigrate and the destination choice pattern vary substantially among the 23 metropolitan areas; (2) that 83 per cent of the variation in the destination choice probabilities of metropolitanward migrants can be explained by only five variables (log of distance, cultural dissimilarity, temperature, employment growth, and population size); and (3) that housing conditions are essentially the results (rather than the causes) of intermetropolitan migration .     

The information effects of origin on migrants' job search behavior

"Migrants are generally assumed to gather specific information about the destination primarily through physical contact, or through family, friends, and acquaintances. In this paper, I propose an additional source of information: similarities between origin and destination labor markets. Data from the 1983-1987 PSID [Panel Study of Income Dynamics] are used in a two-stage least squares model of postmove search duration in the U.S. Rural-to-urban migrants (except for rural Southerners) exhibit significantly lower search duration than other groups, controlling for productivity-related characteristics and postmove earnings. In addition, employment growth differences between origin and destination are found to be better predictors of search duration than are differences in average earnings."     

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.     

在线信息搜索对旅游者感知形象及决策的影响研究

本文基于目的地形象理论,利用实验、出声思维、访谈等多种方法,结合词频统计、同位素示踪等分析手段解析了在线信息搜索对于旅游者感知形象演化及目的地选择决策的影响。研究发现:潜在旅游者持有的目的地原生形象具有集中性。随着外部信息搜索的进行,来自DMO控制型信息源的信息加强了这种印象并形成引致形象的热门词部分,依此旅游者对意识域中众多可选目的地进行筛选并形成考虑域。这一过程构成"广泛信息搜索路径"。而对非DMO控制型信息源的信息摄取则使引致形象演化出长尾,这些形象的细节性信息促使旅游者做出具体决策,此即为"精细信息搜索路径"。旅游者的目的地选择决策过程即是在不断重复这两条路径,直至做出最终选择。     

Studying Rules Changes in the U.S. House: Evidence from an Alternative Empirical Model

Binder (1996) and Schickler (2000) define the current debate as to why the U.S. House has changed its standing rules regarding the majority rule and the minority rights. I revisit their empirical models—binary logit and ordered logit—and theoretically and statistically test the appropriateness of these models. I find that both of them are actually choosing inappropriate models. Their theoretical claims cannot be properly examined by utilizing their choices of models. In addition, the data do not satisfy the “parallel regression” assumption but do satisfy the “independence of irrelevant alternatives” assumption, which supports using an alternative multinomial logit model. I further extend the model, and find the dynamic nature of rules changes in the U.S. House. It appears there is no symmetry between the rules changes that promote the majority rule and the rules changes that enhance the minority rights.     

Some Extensions to Rushton's Spatial Preference Scaling Model

Rushton's spatial preference scaling model is extended and its computing algorithm modified in order to utilize more fully all the information contained in the input data set, and to make it a better predictor of choice behavior. The preference scale that is produced by the model measures the certainty with which generalizations can be made about choices between classes of objects. The model offers two significant advantages over commonly used spatial interaction models: freedom from a priori selection of the function relating choice to attributes of objects, and applicability to studies where the number of origin and destination zones is large relative to the populations involved.     

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.     

Joint Effects of Personal Factors and Ecological Variables on the Interprovincial Migration Pattern of Young Adults in Canada: A Nested Logit Analysis

This paper applies a nested logit model to the 1981 census micro data to study the joint effects of personal factors (sex, mother tongue, nativity, education, and marital status) and ecological variables on the 1976–1981 interprovincial migration pattern of young adults in Canada. In multivariate contexts, personal factors not only are of paramount importance in explaining the departure process but also have significant interactions with ecological variables in determining the destination choice pattern.     

Disaggregate Migration Behavior and the Volume of Interregional Migration

Nested multinomial logit models are used to investigate migration behavior during the 1971–74 period for a large sample of the population of Ecuador. The nested form of the model makes it possible to test hypotheses about the importance of destination characteristics in conditioning the odds for out-migration. Our empirical results indicate that the odds for migration from each origin are conditioned by the expected utilities of the available set of destinations, as well as characteristics of the origins and the personal characteristics of potential migrants. The association between destination characteristics and the frequency of out-migration allows the total volumes of migration to be adjusted to interregional differences in place-specific utilities.     

Modeling Micro-Spatial Employment Location Patterns: A Comparison of Count and Choice Approaches

This article studies employment location patterns in the Puget Sound Region of Washington State at a micro level of geography. Traditional discrete choice modeling using multinomial logit (MNL) models may be problematic at a micro level of geography due to the high dimensionality of the set of alternative locations and the likely violations of the independence from irrelevant alternatives (IIA) assumption. Count models are free from the IIA assumption and, unlike logit models, actually benefit from large numbers of alternatives by adding degrees of freedom. This study identifies the best-fitting count model as the zero-inflated negative binomial (ZINB) model, because this model more effectively addresses the large number of cells with no jobs and reflects a dual process that facilitates the identification of threshold clustering effects such as those found in specialized employment centers. The estimation and prediction results of ZINB are compared with those of MNL with a random sampling of alternatives estimated on an equivalent data set. The ZINB and MNL models largely agree on major trends, with the ZINB model providing more insightful details, but with less capacity to predict large count situations.     

信息过载情境下旅游者目的地选择决策研究——热门形象与长尾形象的差异化作用分析

借助网络,旅游者能够获得丰富的目的地属性信息,形成的引致形象更为丰满。本文采用情境实验法,检验了信息过载情境下引致形象发生的结构性变化对旅游者目的地选择决策的影响。研究发现：①属性信息过载主要表现为旅游者对目的地长尾形象信息的选择性记忆,而目的地热门形象仍能被普遍记住;②在旅游者目的地选择决策过程中,目的地的热门形象依旧起着决定性作用,即USP依然是有效的营销策略;③在网络信息环境中新生成的引致形象长尾部分对旅游者决策的影响受到引致形象热门部分的调节,即引致形象长尾只有在特定的条件下才对旅游者决策有所影响。该研究结论有助于深化旅游者目的地选择决策理论、指导DMO目的地营销工作的开展。     

Markovian Models of Movement Within Urban Spatial Structures

Much work has assumed that movement within urban spatial structures is an “adaptive” process. Nonetheless, mathematical models have not yet been specified and tested which formulate both how different individuals “adapt” over time in destination or route selection, and how predictions about aggregate movement can be derived from postulates about different persons. Two adaptive first-order Markov models for heterogeneous individuals are suggested by the literature. When formulated and tested, however, these models are inadequate to describe travel within urban spatial structures. This implies that the use of Markovian processes to model movement may be overrated. More confidence may be placed in other formulations such as linear learning models of route and destination choice.     

WHAT ATTRACTS FOREIGN MULTINATIONAL CORPORATIONS? EVIDENCE FROM BRANCH PLANT LOCATION IN THE UNITED STATES

ABSTRACT. The location decisions of foreign multinational corporations (FMNCs) are analyzed using a conditional logit model with states as the choice set. We consider the establishment of new manufacturing plants and separately analyze the site selection of all MNCs, Japanese MNCs, and European MNCs. The results indicate that access to markets, labor market conditions, state promotional efforts to attract foreign investment, and state and local personal taxes are significant fadors in the location decision. The decision determinants for Japanese and European MNCs are found to be different.     

DISCRETE SPATIAL CHOICE MODELS FOR AGGREGATE DESTINATIONS*

ABSTRACT. In problems of spatial choice, the choice set is typically more aggregated than the one considered by decision-makers, often because choice data are available only at the aggregate level. These aggregate choice units will exhibit heterogeneity in utility and in size. To be consistent with utility maximization, a choice model must estimate choice probabilities on the basis of the maximum utility within heterogeneous aggregates. The ordinary multinomial logit model applied to aggregate choice units fails this criterion as it is estimated on the basis of average utility. In this paper, we derive and discuss a model which utilizes the theory underlying the nested logit model to estimate the appropriate maximum utilities of aggregates. We also demonstrate that the aggregate alternative error terms are asymptotically Gumbel, thereby relaxing the assumption of extreme value distributed error terms. This is accomplished with help from the asymptotic theory of extremes.     

旅游者目的地选择的TPB模型与分析

本文借鉴消费者计划行为理论——Theory of Planned Behavior（TPB）,构建了一个旅游目的地选择的TPB模型,并对各层次构成要素的作用进行分析,试图通过模型研究揭示旅游者目的地选择的心理及行为特征。本文认为,意向、情境、旅游群体是旅游者目的地选择的基本影响要素,而态度、主观规则和主观感知对意向产生重要影响;目的地形象、旅游经历、动机等9个因素是最直接的影响要素。     

The Impact of Migration on Wages: Empirical Evidence from French Youth*

Abstract. This paper deals with the impact of migration on wages. We introduce a spatial dimension into the job search framework, so that the agent faces neither the same job offer distribution nor the same search costs when looking for a job inside his local labor market. This is in comparison to the agent searching outside his local labor market, where migration costs are a factor. We estimate wage equations in which we introduce the decision to migrate as a binary choice, and later as a polychotomic choice (stayer/mover from provinces to Paris/mover from provinces to provinces). We find no selection effect for people with low levels of education, and a positive selection effect for highly educated migrants. When we distinguish the migration destination for highly educated from provinces, we find a hierarchical effect, that is, the selection effect is higher for men who migrate to Paris than for those who migrate to other provinces.     

A Decision-Making and Search Model For Intraurban Migration

Most of the research on the intraurban migration attempting to develop models of the mobility process has presented intuitively appealing statements about the residential decision process, but stopped short of a formal development of these concepts. If it is to be possible to predict the mobility pattern within the city, both the search and selection process must be more clearly specified. In this paper, a preliminary theoretical model containing decision rules similar to those found in optimal search models is developed. The model explicitly incorporates the spatial and temporal aspects of residential choice and has the potential to predict the probability that a prospective migrant will search for a new residence in a given area of the city, the time when the search process will come to a conclusion and, by implication, the expected location of the new residence. The preliminary results from the model suggest a major elaboration of the spatial and temporal aspects of residential choice under conditions of uncertainty in terms of a set of empirically measurable determinants, relating to a household's preferences, beliefs, and degree of risk aversion.     

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。