Economics at your fingertips  

Modeling hurricane evacuation behavior using a dynamic discrete choice framework

Tarun Rambha, Linda K. Nozick and Rachel Davidson

Transportation Research Part B: Methodological, 2021, vol. 150, issue C, 75-100

Abstract: Predicting evacuation-related choices of households during a hurricane is of paramount importance to any emergency management system. Central to this problem is the identification of socio-demographic factors and hurricane characteristics that influence an individual’s decision to stay or evacuate. However, decision makers in such conditions do not make a single choice but constantly evaluate current and anticipated conditions before opting to stay or evacuate. We model this behavior using a finite-horizon dynamic discrete choice framework in which households may choose to evacuate or wait in time periods prior to a hurricane’s landfall. In each period, an individual’s utility depends not only on his/her current choices and the present values of the influential variables, but also involves discounted expected utilities from future choices should one decide to postpone their decision to evacuate. Assuming generalized extreme value (GEV) errors, a nested algorithm involving a dynamic program and a maximum likelihood method is used to estimate model parameters. Panel data on households affected by Hurricane Gustav, which made landfall in Louisiana on 1 September 2008, was fused with the National Hurricane Center’s forecasts on the trajectory and intensity for the case study in the paper.

Keywords: Hurricanes; Evacuation; Demand estimation; Dynamic discrete choice; Maximum-likelihood (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.trb.2021.06.003

Access Statistics for this article

Transportation Research Part B: Methodological is currently edited by Fred Mannering

More articles in Transportation Research Part B: Methodological from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

Page updated 2021-10-16
Handle: RePEc:eee:transb:v:150:y:2021:i:c:p:75-100