Correcting for endogeneity in behavioral choice models with social influence variables

Walker, Joan L.; Ehlers, Emily; Banerjee, Ipsita; Dugundji, Elenna R.

doi:10.1016/j.tra.2011.01.003

Cited by 57 publications

(42 citation statements)

References 31 publications

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“…Páez and Scott (2007) clarified the social influence on travel behavior within the context of telecommuting. Walker et al (2011) confirmed that an individual's mode choice to work is influenced by the choices made by one's peers, friends, family, and neighbors. 6.…”

mentioning

confidence: 70%

Revisiting residential self-selection issues: A life-oriented approach

Zhang

2014

JTLU

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It has been widely argued that residential self-selection stems from two sources: attitudes and socio-demographic traits. This argument would be true if decisions were made with respect to only residential choice and travel behavior. Because they are just a part of people's life choice, the influence of life choice on self-selection cannot be ignored. In this context, a life-oriented approach becomes relevant, where residential and travel decisions are interdependent not only with each other, but also with other life domains as a part of general life decisions. This paper conceptually argued and empirically confirmed the necessity of developing a life-oriented approach to reexamine residential self-selection issues. I proposed that life choices should be treated as an additional source of the self-selection, and dynamic interdependences between residential choice, travel behavior, and other life choices should be properly modeled. From a policy perspective, the life-oriented approach suggests that successful transport and land use policies should be designed together with policies in other significantly relevant sectors (e.g., health and environment) and such cross-sectoral policies could better contribute to the improvement of people's quality of life.

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confidence: 70%

Revisiting residential self-selection issues: A life-oriented approach

Zhang

2014

JTLU

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“…Idiosyncratic differences in individual choice behavior are captured by the conventional logit error term. We also address unobserved neighborhood effects, by introducing elements of the approach pioneered by Berry et al (1995) along the lines of Walker et al (2011) in their model of social interactions in travel mode choice. Subsequently, we deal with the issue of correct identification of the social interaction effect, and we address the endogeneity of the social interaction effect.…”

Section: The Modelmentioning

confidence: 99%

“…Their approach is used in other fields as well. For instance, Walker et al (2011) apply a model like (2), but without neighborhood variables Z, to study the effect of social interactions on travel mode choice. Berry et al (1995) suggest a two-stage procedure.…”

Section: The Choice Of Whether or Not To Be A Criminalmentioning

confidence: 99%

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Social Interactions and Crime Revisited: An Investigation Using Individual Offender Data in Dutch Neighborhoods

Bernasco

Graaff

Rouwendal

et al. 2017

The Review of Economics and Statistics

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Using data on the age, sex, ethnicity and criminal involvement of 14.3 million residents aged 10-89 residing in 4,007 neighborhoods in the Netherlands, this article tests whether an individual's decision whether or not to be involved in crime is affected by the number of criminals in the neighborhood. Controlling for unobserved neighborhood heterogeneity and endogeneity of this decision, a small positive effect is found on violent crime, but not on property crime. The results suggest that individual characteristics and other neighborhood characteristics play a much greater role in an individual's decision to be involved in crime.

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“…Taking aggregate bicycle modal split as a proxy for the social network effect, they find that this is indeed a significant factor for mode choice for shopping and recreational trips. Walker et al (2011) discuss the problem of endogeneity in the estimation of social network effects (or field effects) in more detail, and suggest a different correction method. With mode choice data from the Netherlands they also find significant field effects for the mode choice for work trips.…”

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confidence: 99%

Dynamic process model of mass effects on travel demand

2013

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Whereas transportation planners commonly predict the negative impacts of mass transportation, there is increasing empirical evidence of the existence of positive mass effects, whereby increased use of a mode by the 'mass' will generally increase its attractiveness for future travellers. In this paper we consider the dynamic impact of such an effect on the problem of travel demand forecasting, with particular regards to social network effects. Our proposed modelling approach is inspired by literature from social physics, evolutionary game theory and marketing. For simplicity of exposition, our model is specified for a scenario in which (a) there is a binary choice between two mobility lifestyles, referred to as car-oriented and transit-oriented, and (b) there are two population groups, where one is the "leading" or "innovative" population group and the other the "following" or "imitating" population group. This latter distinction follows the rather well-known Bass model from the marketing literature (1969). We develop the transition probabilities and transition dynamics. We illustrate with a numerical case study that despite lower intrinsic utility for the transit lifestyle, significant changes towards this lifestyle can be achieved by considering congestion, service improvements and mass effects. We further illustrate that mass effects can be positive or negative. In all cases we explore the sensitivity of our conclusions to the assumed parameter values.

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Correcting for endogeneity in behavioral choice models with social influence variables

Cited by 57 publications

References 31 publications

Revisiting residential self-selection issues: A life-oriented approach

Revisiting residential self-selection issues: A life-oriented approach

Social Interactions and Crime Revisited: An Investigation Using Individual Offender Data in Dutch Neighborhoods

Dynamic process model of mass effects on travel demand

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