Estimating a model of dynamic activity generation based on one-day observations: Method and results

Theo A. Arentze, Dick Ettema and Harry J.P. Timmermans

Transportation Research Part B: Methodological, 2011, vol. 45, issue 2, 447-460

Abstract: In this paper we develop and explore an approach to estimate dynamic models of activity generation on one-day travel-diary data. Dynamic models predict multi-day activity patterns of individuals taking into account dynamic needs as well as day-varying preferences and time-budgets. We formulate an ordered-logit model of dynamic activity-agenda-formation decisions and show how one-day observation probabilities can be derived from the model as a function of the model's parameters and, with that, how parameters can be estimated using standard loglikelihood estimation. A scale parameter cannot be identified because information on within-person variability is lacking in one-day data. An application of the method to data from a national travel survey illustrates the method. A test on simulated data indicates that, given a pre-set scale, the parameters can be identified and that estimates are robust for a source of heterogeneity not captured in the model. This result indicates that dynamic activity-based models of the kind considered here can be estimated from data that are less costly to collect and that support the large sample sizes typically required for travel-demand modeling. We conclude therefore that the proposed approach opens up a way to develop large-scale dynamic activity-based models of travel demand.

Keywords: Travel-demand; modeling; Activity-based; modeling; Time; use; Dynamic; activity; generation; Estimation (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (8)

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