Exploring the connections among residential location, self-selection, and driving: Propensity score matching with multiple treatments

Cao, Xinyu; Xu, Zhiyi; Fan, Yingling

doi:10.1016/j.tra.2010.07.010

Cited by 70 publications

(68 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results obtained so far could be classified as mixed. Whilst the first studies mostly have concluded that residential self-selection was more important than land-use patterns or built environment (e.g., Kitamura et al 1997;Bagley and Mokhtarian 2002;Cao et al 2006), other more recent ones have concluded otherwise (e.g., de Abreu e Silva, Martinez, and Goulias 2012; Schwanen and Mokhtarian 2005;Bhat and Guo 2007;Aditjandra et al 2012;Cao et al 2010). Cao et al (2009) concluded, based on reviewed empirical studies, for the existence of residential self-selection, but also for the existence of non-spurious effects of land-use patterns on travel behavior.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial self-selection in land-use–travel behavior interactions: accounting simultaneously for attitudes and socioeconomic characteristics

Silva¹

2014

JTLU

View full text Add to dashboard Cite

Spatial self-selection can be ascribed to two main factors: socioeconomic characteristics or attitudinal aspects towards travel and location choices. Several studies have investigated the influence of self-selection on the relations between travel behavior and land-use patterns. So far the results could be considered mixed.The model proposed herein uses data collected in 2009 for the Lisbon Metropolitan Area. A structural equations model was built to study the effects of spatial self-selection due to both socioeconomic and attitudinal effects. Three model specifications were considered: one treating attitudes toward travel as exogenous and two others considering them as endogenous. The preferred specification considered attitudes as exogenous. The land-use patterns are described by factors both at the residence and employment zones of each individual. The travel behavior variables included here are multidimensional and include commuting distance, car ownership, the number of trips by mode, and the total amount of time between the first and last trips. On account of the data characteristics and sample size, Bayesian estimation, as implemented in AMOS TM software, was used. The results obtained show that although the attitudinal variables significantly influence travel behavior, they do not annul the effects of land-use patterns in also contributing to shape the same behavior.Copyright 2014 João de Abreu e Silva. Licensed under the Creative Commons Attribution -NonCommercial License 3.0. IntroductionOne of the main theoretical criticisms of the use of land-use policies as a way of reducing the level of car use and changing mobility in the direction of a more intensive use of transit and nonmotorized modes is related to residential self-selection. Residential self-selection can be defined as the tendency of people to opt for residential locations based on their abilities, needs, and preferences (Mokhtarian and Cao 2008; Cao et al. 2009). This concept could be extended beyond residential to other locational choices and to other dimensions of travel behavior like car ownership, car type choice, and modal preferences (van Wee 2009). Not accounting for self-selection could result in biased model results.Residential self-selection is related to the importance and direction of the relations between travel behavior and land-use patterns, and it is connected with the existence of causal relations between them. Here the concept of self-selection is extended to both residential and work location characteristics. Therefore, it will be referred as spatial self-selection, since it encompasses more than residential self-selection. In this paper, the impact of spatial self-selection in several travel behavior dimensions, covering both long-and short-term decisions, is studied. A preliminary analysis of the endogeneity of attitudinal effects vis-à-vis socioeconomic characteristics is made and, proceeding from that, a structural equations model (SEM) is developed. It is based on a previous model, which used the same base...

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Spatial self-selection in land-use–travel behavior interactions: accounting simultaneously for attitudes and socioeconomic characteristics

Silva¹

2014

JTLU

View full text Add to dashboard Cite

show abstract

“…The study found that after self-selection had been controlled, the influence of the BE that remained was 86 percent and 61 percent of the total for strolling frequency and walking-tostore frequency, respectively. 20 JOURNAL OF TRANSPORT AND LAND USE 9.1 Cao, Xu, and Fan (2010) used propensity score matching with multiple treatments to control for RSS with respect to vehicle-miles driven (VMD). The data comprised 3376 households completing a regional travel diary in the Research Triangle metropolitan area of North Carolina-the Greater Triangle Travel Study conducted in 2006.…”

Section: Cao (2010)mentioning

confidence: 99%

Viewpoint: Quantifying residential self-selection effects: A review of methods and findings from applications of propensity score and sample selection approaches

Mokhtarian

Herick

2016

JTLU

View full text Add to dashboard Cite

Abstract:The phenomenon whereby individuals self-select into their residential environment based on previously determined preferences for how to travel is known as residential self-selection (RSS). Numerous studies have investigated the influence of RSS on the estimated effect of the built environment on travel behavior. However, surprisingly few have actually quantified its effect in terms of partitioning the total influence of the built environment (BE) on travel behavior into a component attributable to RSS and one attributable to the built environment itself. This paper reviews 10 analyses (found in seven studies) that have quantified the proportion of the total influence of the built environment that is due to the BE itself (which we call the BEP), using either propensity-score or sample-selection approaches to control for RSS. After first outlining the basics of each approach, we then explain the various methods used to compute the BEP, followed by a discussion of the empirical results. The estimated BEPs vary widely, ranging from 34 percent to 98 percent. A number of reasons for these disparities are suggested, but there is considerable divergence in estimates even when many of these factors are held constant. Additional research is called for to better understand the circumstances under which the BEP is higher or lower. Keywords:Residential self-selection, propensity score, sample selection, travel behavior IntroductionThe influence of the built environment (BE) on travel behavior (TB) is of considerable interest to transportation policy and planning, particularly since it is the most obvious limiting factor on whether individuals even have opportunities to make certain decisions with respect to their behavior. Without tracks, there is no rail transportation; without roads, there is no driving; and increased incidence of 10JOURNAL OF TRANSPORT AND LAND USE 9.1 aesthetic walking paths leading to interesting destinations will surely encourage, if not lead to, more walking in an area. It remains an open question, however, how much the built environment itself brings about a certain kind of behavior versus how much one's proclivities for a certain kind of behavior influence one's choice of built environment. To the extent the latter is true, policies that attempt to induce more sustainable travel behavior by shaping the built environment could fall short of expectations if large numbers of people end up living in sustainable built environments (perhaps due to financial incentives or a sizable increase in the supply of such environments) without having the proclivity to travel more sustainably. The phenomenon whereby individuals self-select into their residential environment based on previously determined preferences for how to travel is known as residential self-selection (RSS). In the past two decades, numerous studies have analyzed the influence of the built environment on travel behavior after controlling for self-selection. In the process, a variety of approaches have been employed: direct questioning, ...

show abstract

“…One additional approach to addressing the self-selection issue is by comparing the travel behavior (e.g., distance traveled) of individuals living in their preferred neighborhoods (consonant residents) to that of individuals not living in their preferred neighborhoods (dissonant residents) (Schwanen and Mokhtarian 2005). More recently, Cao et al (2010) proposes to apply the so-called propensity score matching method to quantify the contribution of residential self-selection to the connection between built environment and travel behavior. Whichever modeling approach is adopted, incorporating the travel-related attitudes and preferences into the analysis appears to be the key in addressing the issue.…”

mentioning

confidence: 99%

“…However, built environment variables remain significant even after the effects of residential self-selection are controlled (Mokhtarian and Cao 2008;Cao et al 2009). Several studies quantify the relative contributions of residential self-selection and built environments to travel behavior mostly using the sample selection model (e.g., Zhou and Kockelman 2008;Cao 2009;Bhat and Eluru 2009) or propensity score matching (e.g., Cao 2010;Cao et al 2010).…”

mentioning

confidence: 99%

See 1 more Smart Citation

Residential self-selection, built environment, and travel behavior in the Chinese context

Wang

Lin

2014

JTLU

View full text Add to dashboard Cite

Residential self-selection has been reported to be a factor confounding the observed relationship between built environment and travel behavior. By incorporating residential self-selection, studies have generated much insight into the causalities involved in the relationship between built environment and travel behavior. However, most of these studies were conducted in North American cities, where individuals may have the opportunity to realize their preferences in residential and transport mode choices. There are not many similar studies for other parts of the world, such as China, where residential and transport choices are probably more constrained than in North America. This paper aims to partly fill the gap by discussing the specificities of the residential self-selection issue in urban China and suggesting how to cope with this issue when examining the relationship between built environment and travel behavior in the Chinese context. We argue that studies addressing the residential self-selection issue in China need to consider the housing source, which has implications for residential choice, and acknowledge the importance of some travel-related attitudes such as preferences for short commutes, good accessibility to public transport, and proximity to markets for daily goods shopping.

show abstract

Exploring the connections among residential location, self-selection, and driving: Propensity score matching with multiple treatments

Cited by 70 publications

References 27 publications

Spatial self-selection in land-use–travel behavior interactions: accounting simultaneously for attitudes and socioeconomic characteristics

Spatial self-selection in land-use–travel behavior interactions: accounting simultaneously for attitudes and socioeconomic characteristics

Viewpoint: Quantifying residential self-selection effects: A review of methods and findings from applications of propensity score and sample selection approaches

Residential self-selection, built environment, and travel behavior in the Chinese context

Contact Info

Product

Resources

About