Economics at your fingertips  

Local Sensitivity Analysis of Forecast Uncertainty in a Random-Utility-Based Multiregional Input-Output Model

Guangmin Wang and Kara M. Kockelman

Journal of the Transportation Research Forum, 2016, vol. 55, issue 2

Abstract: Transportation systems are critical to regional economies and quality of life. The Random-Utility- Based Multiregional Input-Output Model (RUBMRIO) for trade and travel choices is used here to appreciate the distributed nature of commodity flow patterns across the United States’ 3,109 contiguous counties and 12 industry sectors, for rail and truck operations. This paper demonstrates the model’s sensitivity to various inputs using the method of local sensitivity analysis with interactions (LSAI). This work simulates both individual effects as well as interaction effects of model inputs on outputs by providing sensitivity indices of model outputs to variations of inputs under two scenarios. Model outputs include predictions of domestic and export trade flows, value of goods produced, labor expenditures, and household and industry consumption levels across the counties in the United States. The LSAI technique allows transportation system operators to appreciate the roles of any model input and the associated uncertainty of outputs.

Keywords: Public Economics; Research Methods/ Statistical Methods (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) ... om-Utility-Based.pdf (application/pdf) ... d.pdf?subformat=pdfa (application/pdf)

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:

DOI: 10.22004/ag.econ.262661

Access Statistics for this article

More articles in Journal of the Transportation Research Forum from Transportation Research Forum
Bibliographic data for series maintained by AgEcon Search ().

Page updated 2021-01-16
Handle: RePEc:ags:ndjtrf:262661