Preferences for Housing, Jobs, and Commuting: A Mixed Logit Analysis

This paper reports stated preferences of Dutch workers for combinations of housing, employment, and commuting. The analysis uses standard logit models as well as mixed logit models. Estimation results offer insights into the relative importance of various aspects of housing, employment, and commuting. Households dislike commuting and the value of commuting time implied by the model is high in comparison to the wage rate. Nevertheless, preferences for some housing attributes are strong enough to make substantially longer commuting acceptable to most workers. Of special interest is the strong preference for living in small-or medium-size cities, especially among two income households. Using a mixed logit model instead of a standard logit model results in a substantial improvement of the loglikelihood, reflecting the importance of heterogeneity among respondents. If no individual characteristics are incorporated into the model, the mixed logit implies substantially lower average monetary evaluations of most attributes. These differences are much smaller if some individual characteristics are incorporated into the model.     

A Conditional Logit Approach to U.S. State-to-State Migration

This paper uses a conditional logit approach to study interstate migration in the United States for each of eleven years, from 1986–1987 to 1996–1997. We test substantive hypotheses regarding migration in the United States and demonstrate the richness of the conditional logit approach in studies of place-to-place migration. We investigate migration responses to relative economic opportunities (unemployment rate, per capita income) and the associated costs of moving (distance between origin and destination and its square). We also investigate how noneconomic factors, such as amenities, affect migration between states through a state fixed effect. Finally, we study the magnitude of unmeasured costs associated with a particular migration. The conditional logit model also allows us to compute various trade-off and other values that are of interest in migration analysis.     

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.     

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.     

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.     

A Spatial Mixture Model of Innovation Diffusion

The diffusion of new product or technical innovation over space is here modeled as an event‐based process in which the likelihood of the next adopter being in region r is influenced by two factors: (i) the potential interactions of individuals in r with current adopters in neighboring regions, and (ii) all other attributes of individuals in r that may influence their adoption propensity. The first factor is characterized by a logit model reflecting the likelihood of adoption due to spatial contacts with previous adopters, and the second by a logit model reflecting the likelihood of adoption due to other intrinsic effects. The resulting spatial diffusion process is then assumed to be driven by a probabilistic mixture of the two. A number of formal properties of this model are analyzed, including its asymptotic behavior. But the main analytical focus is on statistical estimation of parameters. Here it is shown that standard maximum‐likelihood estimates require large sample sizes to achieve reasonable results. Two estimation approaches are developed which yield more sensible results for small sample sizes. These results are applied to a small data set involving the adoption of a new Internet grocery‐shopping service by consumers in the Philadelphia metropolitan area.     

论早期都邑——中国早期文明的关键性标志

The early capital cities are the key symbols of early Chinese civilization. By comparing the Erlitou site, Shang city in Zhengzhou, Shang city in Yanshi with Niuheliang site, Mojiaoshan site, Shijiahe site, Taosi site, and Wangchenggang site, the characteristics of the early capital cities could be drawn: First, it should have palace or palace city in big sizes; Second, the palace or palace city should be surrounded by living quarters for noble families, working areas for melting bronze, and quarters for sacrifice.     

Early capital cities

The early capital cities are the key symbols of early Chinese civilization. By comparing the Erlitou site, Shang city in Zhengzhou, Shang city in Yanshi with Niuheliang site, Mojiaoshan site, Shijiahe site, Taosi site, and Wangchenggang site, the characteristics of the early capital cities could be drawn: First, it should have palace or palace city in big sizes; Second, the palace or palace city should be surrounded by living quarters for noble families, working areas for melting bronze, and quarters for sacrifice. __________ Translated by Chen Bo from Wenwu 文物 (Cultural Relics), 2006, (6): 56–60, 87     

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.     

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.     

A Spatial Logit Association Model for Cluster Detection

In this paper, I propose to set out a logit spatial association model for binary spatial events and develop a scan algorithm to search for spatial associations. I extend the traditional logit model with a spatial autocorrelated component so that the model includes not only known risk factors, but also spatially autocorrelated regions as control or explanatory factors. The case study of West Virginia lung cancer shows that the model effectively captures cool and hot spots in lung cancer mortality.     

Restoring the Shine to a Pearl: Recycling Behaviour in Penang,Malaysia

Despite serious waste management problems in Penang Island, a recycling campaign launched in 2001 has met with little success. This may be because the campaign was not backed up with knowledge about factors that motivate recycling. This article develops a simple economic framework to explain individual recycling behaviour. A logit model that utilizes survey data drawn from a sample of 760 respondents was used to test the insights gained from the framework. As predicted by the framework, recycling was negatively related to factors that increased the private costs of recycling, such as the lack of storage space and low income. Recycling increased among respondents who recognized its benefits: they include the environmentally conscious, those who were aware of the recycling campaign and respondents in the twenty‐five to thirty‐five year age category. Interestingly, neither gender nor distance to recycling centres were reliable predictors of recycling behaviour.     

Determinants of Residential Location Choice: How Important Are Local Public Goods in Attracting Homeowners to Central City Locations?*

Abstract. A hybrid conditional logit choice model is estimated using data on the characteristics and destination of homeowners who engaged in intrametropolitan moves among 17 school districts within the Columbus, Ohio area in 1995. The model is used to test the relative influence of local fiscal and public goods versus household‐level characteristics in determining household location choices across central city and suburban school districts. Results provide evidence of both a “natural evolution” of households to the suburbs, due to job location, residential filtering, and household income and lifecycle effects, and “flight from blight,” due to lower school quality, higher crime levels, and lower average income levels in the city. In comparing the magnitudes of these variables, we find that school quality exerts the strongest influence: a 1‐percent increase in the school quality of the city district increases the probability of choosing a city residence by 3.7 percent. In contrast, the effects of household income and other individual characteristics are relatively modest. The findings provide support for a “flight from blight” suburbanization process that is dominated by differences in neighborhood quality between the city and suburbs. An implication is that investments that promote central city development and reduce suburbanization are justified on efficiency grounds if negative externalities are generated by increased concentration of poverty, crime, and low school quality.     

COLLEGE-TO-WORK MIGRATION OF TECHNOLOGY GRADUATES AND HOLDERS OF DOCTORATES WITHIN THE UNITED STATES

ABSTRACT.  This study estimates a series of random parameter logit models of the college-to-work migration decisions of technology graduates and holders of doctorates within the United States. We employ detailed information on the migration-relevant characteristics of individuals, as well as on their actual origins and destinations at the metropolitan scale. In addition to its obvious implications for "brain drain" policies in U.S. metropolitan areas, the study demonstrates the richness of the random parameters technique for behavioral-geographic analysis. We find that science and technology graduates migrate to better educated places, other things equal; that PhD graduates pay greater attention to amenity characteristics than other degree holders; and that foreign students from some immigrant groups migrate to places where those groups are concentrated.     

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.     

THE EXCHANGEABILITY OF HEDONIC PROPERTY PRICE STUDIES*

ABSTRACT. Observations drawn from multiple markets are essential to the construction of indices of housing costs and to measures of demand for housing attributes. It is not evident when multiple markets exist or whether such markets exist for some attributes but not for others. We test for multiple markets by using Bayesian methods to assess the transferability (random exchangeability) of entire hedonic price expressions from one site and time to another, the transferability of hedonic price functions for particular attributes, and the degrees of similarity that hedonic price functions must have in order to be transferable. In our illustrations, price functions for structural housing attributes are generally transferable; prices for neighborhood attributes are not. Therefore, in our illustrations, the desired price indices and demand functions should be estimable for neighborhood attributes, but not for structural ones.     

The Location Choice of Employment‐based Immigrants among U.S. Metro Areas*

Abstract. This paper examines the initial location choice of legal employment‐based immigrants to the United States using Immigration and Naturalization Service data on individual immigrants, as well as economic, demographic, and social data to characterize the 298 metropolitan areas we define as the universal choice set. Focusing on interactions between place characteristics and immigrant characteristics, we provide multinomial logit model estimates for the location choices of about 38,000 employment‐based immigrants to the United States in 1995, focusing on the top 10 source countries. We find that, as groups, immigrants from nearly all countries are attracted to large cities with superior climates, and to cities with relatively well‐educated adults and high wages. We also find evidence that employment‐based immigrants tend to choose cities where there are relatively few immigrants of nationalities other than their own. However, when we introduce interaction terms to account for the sociodemographic characteristics of the individual immigrants, we find that the estimated effects of location destination factors can reverse as one takes account of the age, gender, marital status, and previous occupation of the immigrants.     

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.     

AN EPR AND ISOTOPIC STUDY OF THE MARBLES OF THE TRAJAN's ARCH AT ANCONA: AN EXAMPLE OF ALLEGED HYMETTIAN PROVENANCE*

The provenance of 20 marble samples drawn from the Trajan's arch at Ancona, which is supposed to be made of Greek, Hymettian marble, has been established on the basis of the independent use of EPR and isotopic data. The results of the two methods are in good agreement and unequivocally indicate a Proconnesian provenance. Sixteen samples are assigned to this site, whereas two are classified as untypical Proconnesian samples and the remaining two are assigned an unlikely Parian provenance. No indication exists for a possible Hymettian origin of the marbles. A multi‐method approach, which employs all of the experimental variables simultaneously, demonstrates that the 18 samples identified as Proconnesian belong to several different quarrying areas within the site. This result is taken as an indication that the Proconnesian quarries were run following a highly organized, semi‐industrial production model. The origin of the Hymettian/Proconnesian misunderstanding and the possible misclassification of other Roman monuments in Italy are briefly commented on.     

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。