The influence of panel effects and inertia on travel cost elasticities for car use and public transport

Lissy La Paix,Karst Geurs,Abu Toasin Oakil,Frank Hofman

doi:10.1007/s11116-021-10201-8

Lissy La Paix, Karst Geurs + Show 2 more

Open Access

https://doi.org/10.1007/s11116-021-10201-8

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Abstract

Studies on the impact of changes in travel costs on car and public transport use are typically based on cross-sectional travel survey data or time series analysis and do not capture intrapersonal variation in travel patterns, which can result in biased cost elasticities. This paper examines the influence of panel effects and inertia in travel behaviour on travel cost sensitiveness, based on four waves of the Mobility Panel for the Netherlands (comprising around 90,000 trips). This paper analyses the monetary costs of travel. Panel effects reflect (within wave) intrapersonal variations in mode choice, based on three-day trip diary data available for each wave. The impact of intrapersonal variation on cost sensitiveness is shown by comparing mode choice models with panel effects (mixed logit mode choice models with error components) and without panel effects (multinomial logit models). Inertia represents variability in mode choice between waves, measured as the effect of mode choice decisions made in a previous wave on the decisions made in the current wave. Additionally, all mode choice models include socio-economic and spatial variables but also mode preferences and life events. The effect of inertia on travel cost elasticities is measured by estimating mixed logit mode choice models with and without inertia effects. The main conclusion is that the inclusion of intrapersonal effects tends to increase cost sensitiveness whereas the inclusion of inertia effects decreases travel cost sensitiveness for car and public transport modes. Car users are identified as inert travellers, whereas public transport users show a lower tendency to maintain their usual mode choice. This paper reveals the inertia effects over four waves of repeated respondent’s data repeated yearly.

Highlights

Our grasp of people’s travel behaviour is still mostly based on cross-sectional surveys in which only one day is surveyed for each respondent, often limited to representative periods with maximal traffic flows
Studies on the impact of changes in travel costs on car and public transport use are typically based on cross-sectional travel survey data or time series analysis and do not capture intrapersonal variation in travel patterns, which can result in biased cost elasticities
We estimated three discrete choice model types: (1) a standard multinomial logit, (b) a standard mixed logit model with error components that capture within wave day-to-day variability in mode choice given by multiple observations of the same individual, (c) a hybrid mixed logit model capturing inertia in mode choice between waves

Summary

Introduction

Our grasp of people’s travel behaviour is still mostly based on cross-sectional surveys in which only one day is surveyed for each respondent, often limited to representative periods with maximal traffic flows (see for an overview Ortúzar 2011). Studies on the impact of changes in travel costs on car and public transport use are typically based on cross-sectional travel survey data or time series analysis and do not capture intrapersonal variation in travel patterns, which can result in biased cost elasticities. Cherchi et al (2013) used hybrid choice models to represent inertia by measuring the tendency to stick with the same alternative (inertia) via lagged variables. Those variables linked the current choice with the previous trip(s) made for the same purpose, during the same time of day, and with the same mode of transport. For an overview of unrepeated versus repeated panel surveys see for example Thomas et al (2019)

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