There has been an increasing interest in the land use-transportation connection in the past decade, motivated by the possibility that design policies associated with the built environment can be used to control, manage, and shape individual traveler behavior and aggregate travel demand. In this line of research and application pursuit, it is critical to understand whether the empirically observed association between the built environment and travel behavior-related variables is a true reflection of underlying causality or simply a spurious correlation attributable to the intervening relationship between the built environment and the characteristics of people who choose to live in particular built environments. In this research paper, we identify the research designs and methodologies that may be used to test the presence of “true” causality versus residential sorting-based “spurious” associations in the land-use transportation connection. The paper then develops a methodological formulation to control for residential sorting effects in the analysis of the effect of built environment attributes on travel behavior-related choices. The formulation is applied to comprehensively examine the impact of the built environment, transportation network attributes, and demographic characteristics on residential choice and car ownership decisions. The model formulation takes the form of a joint mixed multinomial logit-ordered response structure that (a) accommodates differential sensitivity to the built environment and transportation network variables due to both demographic and unobserved household attributes and (b) controls for the self-selection of individuals into neighborhoods based on car ownership preferences stemming from both demographic characteristics and unobserved household factors. The analysis in the paper represents, to our knowledge, the first instance of the formulation and application of a unified mixed multinomial logit-ordered response structure in the econometric literature. The empirical analysis in the paper is based on the residential choice and car ownership decisions of San Francisco Bay area residents.

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A Comprehensive Analysis of Built Environment Characteristics on Household Residential Choice and Auto Ownership Levels

I never thought that others would take them so much more seriously then I did. —Albert Einstein on his theories “I invoke the first law of geography: everything is related to everything else, but n...

Tobler's First Law and Spatial Analysis

Efficient algorithms for the uncapacitated single allocation p-hub median problem

Haynes and Fotheringham provide an introduction to gravity and spatial interaction models which are extensively applied in forecasting. They trace the different applications of the gravity model to market area analysis, developing real-life examples of the use of these models: planning a new service, defining retail shopping boundaries, forecasting migration and voting patterns, examining university enrollment by area, determining the optimal size of a shopping complex, and locating a facility for best results.

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Gravity and Spatial Interaction Models

Statistical Methods for Social Scientists.

Members of the family of spatial-interaction models commonly referred to as gravity models are shown to be misspecified. One result of this misspecification is the occurrence of an undesirable "spatial-structure effect" in estimated distance-decay parameters and this effect is examined in detail. An alternative set of spatial-interaction models is formulated from which more accurate predictions of interactions and more accurate parameter estimates can be obtained. These new interaction models are termed competing destinations models, and estimated distance-decay parameters obtained in their calibration are shown to have a purely behavioural interpretation. The implications of gravity-model misspecification are discussed. (Author/TRRL)

A new set of spatial-interaction models: the theory of competing destinations.

Aspects of destination choice which concern relationships between destinations are explored in the context of a production-constrained gravity model. It is shown that, if competition exists between destinations or, alternatively, if agglomeration effects are present, the gravity model is misspecified and estimated distance-decay parameters obtained from the model are related to spatial structure.

Some theoretical aspects of destination choice and their relevance to production-constrained gravity models

The misspecification of gravity spatial interaction models has recently been described by the author. The bias in parameter estimates that results from such misspecification appears to produce the ‘map pattern effect’ or ‘spatial structure bias’ in estimated distance-decay parameters. A further aspect of the misspecification bias in gravity parameter estimates is explored here. The severity of the bias is shown to vary in a predictable manner with variations in spatial structure. In particular, the bias is shown to be dependent upon the pattern of accessibility that exists within a spatial system. The relevant aspects of this pattern are discussed for intraurban and interurban (or interregional) flow matrices. It is shown that from an examination of the spatial structure of centres in a spatial system it is possible, a priori, to identify whether significant bias will arise in the calibration of a gravity model. Certain configurations of centres are shown theoretically to produce maximal bias. The author ...

A S Fotheringham

Papers

A new set of spatial-interaction models: the theory of competing destinations.

Some theoretical aspects of destination choice and their relevance to production-constrained gravity models

Spatial Flows and Spatial Patterns